how to write a research design in chapter 3

• 218,859 Views

HOW TO WRITE CHAPTER THREE OF YOUR RESEARCH PROJECT (RESEARCH METHODOLOGY) | ResearchWap Blog

• Posted: Friday, 17 April 2020
• By: ResearchWap Admin

How To Write Chapter Three Of Your Research Project (Research Methodology)

Methodology In Research Paper

Chapter three of the research project or the research methodology is another significant part of the research project writing. In developing the chapter three of the research project, you state the purpose of research, research method you wish to adopt, the instruments to be used, where you will collect your data, types of data collection, and how you collected it.

This chapter explains the different methods to be used in the research project. Here you mention the procedures and strategies you will employ in the study such as research design, study design in research, research area (area of the study), the population of the study, etc.

You also tell the reader your research design methods, why you chose a particular method, method of analysis, how you planned to analyze your data. Your methodology should be written in a simple language such that other researchers can follow the method and arrive at the same conclusion or findings.

You can choose a survey design when you want to survey a particular location or behavior by administering instruments such as structured questionnaires, interviews, or experimental; if you intend manipulating some variables.

The purpose of chapter three (research methodology) is to give an experienced investigator enough information to replicate the study. Some supervisors do not understand this and require students to write what is in effect, a textbook.

A research design is used to structure the research and to show how all of the major parts of the research project, including the sample, measures, and methods of assignment, work together to address the central research questions in the study. The chapter three should begin with a paragraph reiterating the purpose of research.

It is very important that before choosing design methods, try and ask yourself the following questions:

Will I generate enough information that will help me to solve the research problem by adopting this method?

Method vs Methodology

I think the most appropriate in methods versus methodology is to think in terms of their inter-connectedness and relationship between both. You should not beging thinking so much about research methods without thinking of developing a research methodology.

Metodologia or methodology is the consideration of your research objectives and the most effective method  and approach to meet those objectives. That is to say that methodology in research paper is the first step in planning a research project work. 

Design Methodology: Methodological Approach                

Example of methodology in research paper, you are attempting to identify the influence of personality on a road accident, you may wish to look at different personality types, you may also look at accident records from the FRSC, you may also wish to look at the personality of drivers that are accident victims, once you adopt this method, you are already doing a survey, and that becomes your  metodologia or methodology .

Your methodology should aim to provide you with the information to allow you to come to some conclusions about the personalities that are susceptible to a road accident or those personality types that are likely to have a road accident. The following subjects may or may not be in the order required by a particular institution of higher education, but all of the subjects constitute a defensible in metodologia or methodology chapter.

 READ ALSO:  HOW TO WRITE EFFECTIVE RESEARCH PROJECT ABSTRACT

Methodology

A  methodology  is the rationale for the research approach, and the lens through which the analysis occurs. Said another way, a methodology describes the “general research strategy that outlines the way in which research is to be undertaken” The methodology should impact which method(s) for a research endeavor are selected in order to generate the compelling data.

Example Of Methodology In Research Paper :

• Phenomenology: describes the “lived experience” of a particular phenomenon
• Ethnography: explores the social world or culture, shared beliefs and behaviors
• Participatory: views the participants as active researchers
• Ethno methodology: examines how people use dialogue and body language to construct a world view
• Grounding theory*: assumes a blank slate and uses an inductive approach to develop a new theory

A  method  is simply the tool used to answer your research questions — how, in short, you will go about collecting your data.

Methods Section Of Research Paper Example :

• Contextual inquiry
• Usability study
• Diary study

If you are choosing among these, you might say “what method should I use?” and settle on one or more methods to answer your research question.

 READ ALSO:  HOW TO DEVELOP EFFECTIVE AND UNIQUE PROJECT TOPICS

Research Design Definition: WRITING A RESEARCH DESIGN

A qualitative study does not have variables. A scientific study has variables, which are sometimes mentioned in Chapter 1 and defined in more depth in Chapter 3. Spell out the independent and dependent, variables. An unfortunate trend in some institutions is to repeat the research questions and/or hypotheses in both Chapter 1 and Chapter 3. Sometimes an operational statement of the research hypotheses in the null form is given to set the stage for later statistical inferences. In a quantitative study, state the level of significance that will be used to accept or reject the hypotheses.

Pilot Study

In a quantitative study, a survey instrument that the researcher designed needs a pilot study to validate the effectiveness of the instrument, and the value of the questions to elicit the right information to answer the primary research questions in. In a scientific study, a pilot study may precede the main observation to correct any problems with the instrumentation or other elements in the data collection technique. Describe the pilot study as it relates to the research design, development of the instrument, data collection procedures, or characteristics of the sample.

Instruments

In a research study, the instrument used to collect data may be created by the researcher or based on an existing instrument. If the instrument is the researcher created, the process used to select the questions should be described and justified. If an existing instrument is used, the background of the instrument is described including who originated it, and what measures were used to validate it.

If a Likert scale is used, the scale should be described. If the study involves interviews, an interview protocol should be developed that will result in a consistent process of data collection across all interviews. Two types of questions are found in an interview protocol: the primary research questions, which are not asked of the participants, and the interview questions that are based on the primary research questions and are asked of the participants.

In a qualitative study, this is the section where most of the appendices are itemized, starting with letters of permission to conduct the study and letters of invitation to participate with the attached consent forms. Sample: this has to do with the number of your participants or subjects as the case may be. Analysis (how are you planning to analyze the results?)

ALSO READ:  TRENDING PROJECT TOPICS FOR FINAL YEAR STUDENTS AT A GLANCE

EFFECTIVE GUIDE AND METHODOLOGY SAMPLES

This chapter deals effectively with the research methods to be adopted in conducting the research, and it is organized under the following sub-headings:

• Research Design
• Area of Study

The population of the Study

• Sample and Sampling Techniques
• Instruments for Data Collection

The validity of the Instrument

Reliability of the Instrument

• Administration of the instruments
• Scoring the instruments

Method of Data Collection

Method of Data Analysis

Research Design:

This has to do with the structure of the research instrument to be used in collecting data. It could be in sections depending on different variables that form the construct for the entire topic of the research problems. A reliable instrument with a wrong research design will adversely affect the reliability and generalization of the research. The choice of design suitable for each research is determined by many factors among which are: kind of research, research hypothesis, the scope of the research, and the sensitive nature of the research.

Area of Study:

Research Area; this has to do with the geographical environment of the study area where the places are located, the historical background when necessary and commercial activities of that geographical area. For example, the area of the study is Ebonyi State University. At the creation of Ebonyi State in 1996, the Abakaliki campus of the then ESUT was upgraded to Ebonyi State University College by Edict no. 5 of Ebonyi State, 1998 still affiliated to ESUT with Prof. Fidelis Ogah, former ESUT Deputy Vice-Chancellor as the first Rector. In 1997, the Faculty of Applied and Natural Sciences with 8 departments was added to the fledging University, and later in 1998 when the ESUT Pre-Science Programme was relocated to Nsukka, the EBSUC Pre-Degree School commenced lectures in both Science and Arts in replacement of the former. This study focused on the students of the Business Education department in Ebonyi state university.

The population is regarded in research work as the type of people and the group of people under investigation. It has to be specific or specified. For example educational study teachers in Lagos state. Once the population is chosen, the next thing is to choose the samples from the population.

According to Uma (2007), the population is referred to as the totality of items or object which the researcher is interested in. It can also be the total number of people in an area of study. Hence, the population of this study comprised of all the students in the department of Business Education, Ebonyi State University which is made up of year one to four totaling 482. The actual number for the study was ascertained using Yaro-Yamane's formula which stated thus:

n   =        N

N is the Population

1 is constant

e is the error margin

Then, n   =         482

1+482(0.05)2

= 214.35 approximately 214

Sample and sampling technique:

It may not be possible to reach out to the number of people that form the entire population for the study to either interview, observe, or serve them with copies of the questionnaire. To be realistic, the sample should be up to 20% of the total population. Two sampling techniques are popular among all the sampling techniques. These are random and stratified random sampling techniques. (A). in Random Sampling, the writers select any specific number from a place like a school, village, etc. (B). In Stratified Random Sampling, one has to indicate a specific number from a stratum which could be a group of people according to age, qualification, etc. or different groups from different locations and different considerations attached.

Instruments for Data Collection:

This is a device or different devices used in collecting data. Example: interview, questionnaire, checklist, etc. instrument is prepared in sets or subsections, each set should be an entity thus asking questions about a particular variable to be tested after collecting data. The type of instrument used will determine the responses expected. All questions should be well set so as to determine the reliability of the instrument.

This has to do with different measures in order to determine the validity and reliability of the research instrument. For example, presenting the drafted questionnaire to the supervisor for scrutiny. Giving the questionnaire to the supervisor for useful comments and corrections would help to validate the instrument.

The test-retest reliability method is one of the simplest ways of testing the stability and reliability of an instrument over time. The test-retest approach was adopted by the researcher in establishing the reliability of the instrument. In doing this 25 copies of the questionnaire were administered on twenty-five selected respondents. After two weeks another 25 copies of the same questionnaire were re-administered on the same group. Their responses on the two occasions were correlated using Parsons Product Moment Correlation. A co-efficient of 0.81 was gotten and this was high enough to consider the instrument reliable.

Administration of the instruments:

Here, the writer states whether he or she administers the test personally or through an assistant. He also indicates the rate of return of the copies of the questionnaire administered.

Scoring the instruments:

Here items on the questionnaire or any other device used must be assigned numerical values. For example, 4 points to strongly agree, 3 points to agree, 2 points to disagree, and 1 point to strongly disagree.

Table of Analysis

The researcher collected data using the questionnaire. Copies of the questionnaire were administered by the researcher on the respondents. All the respondents were expected to give maximum co-operation, as the information on the questionnaire is all on things that revolve around their study. Hence, enough time was taken to explain how to tick or indicate their opinion on the items stated in the research questionnaire.

In this study, the mean was used to analyze the data collected. A four (4) point Likert scale was used to analyze each of the questionnaire items.

The weighing was as follows:

VGE—————- Very Great Extent (4 points)

GE—————– Great Extent (3 points)

LE—————– Little Extent (2 points)

VLE—————- Very Little Extent (1 point)

SA—————– Strongly Agree (4 points)

A——————- Agree (3 points)

D—————— Disagree (2 points)

SD—————- Strongly Disagree (1 point)

The mean of the scale will then be determined by summing up the points and dividing their number as follows with the formula:

Where; x= mean

f= frequency

X= Nominal value of the option

∑= summation

N= Total Number

Therefore, the mean of the scale is 2.5.

This means that any item statement with a mean of 2.50 and above is considered agreed by the respondents and any item statement below 2.5 is considered disagreed.

EDITORS SOURCE: How To Write Chapter Three Of Your Research Project (Research Methodology)

Tags: Research project, chapter three, methodology, project topics,

Project Categories

• AFRICAN LANGUAGES AND LINGUISTIC
• ACCOUNTING EDUCATION
• ACTUARIAL SCIENCE
• ADULT EDUCATION
• AGRICULTURAL ECONOMICS
• AGRICULTURAL EXTENSION
• ANIMAL SCIENCE
• ARCHITECTURE
• BANKING AND FINANCE
• BIBLICAL AND THEOLOGY
• BIOCHEMISTRY
• BREWING SCIENCE AND TECHNOLOGY
• BUILDING TECHNOLOGY
• BUSINESS ADMINISTRATION
• BUSINESS EDUCATION

SEE MORE PROJECT CATEGORIES

Copyright © 2024. All rights reserved researchwap.com - Project Topics Ideas and Materials for Final Year Students

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base

Methodology

• What Is a Research Design | Types, Guide & Examples

What Is a Research Design | Types, Guide & Examples

Published on June 7, 2021 by Shona McCombes . Revised on November 20, 2023 by Pritha Bhandari.

A research design is a strategy for answering your   research question  using empirical data. Creating a research design means making decisions about:

• Your overall research objectives and approach
• Whether you’ll rely on primary research or secondary research
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research objectives and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, other interesting articles, frequently asked questions about research design.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities—start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed-methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

Here's why students love Scribbr's proofreading services

Discover proofreading & editing

Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types.

• Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships
• Descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analyzing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study—plants, animals, organizations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

• Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalize your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study , your aim is to deeply understand a specific context, not to generalize to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question .

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviors, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews .

Observation methods

Observational studies allow you to collect data unobtrusively, observing characteristics, behaviors or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what kinds of data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected—for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are high in reliability and validity.

Operationalization

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalization means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in—for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced, while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method , you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample—by mail, online, by phone, or in person?

If you’re using a probability sampling method , it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method , how will you avoid research bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organizing and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymize and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well-organized will save time when it comes to analyzing it. It can also help other researchers validate and add to your findings (high replicability ).

On its own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyze the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarize your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarize your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analyzing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

Quantitative research designs can be divided into two main categories:

• Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
• Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

McCombes, S. (2023, November 20). What Is a Research Design | Types, Guide & Examples. Scribbr. Retrieved June 29, 2024, from https://www.scribbr.com/methodology/research-design/

Is this article helpful?

Shona McCombes

Other students also liked, guide to experimental design | overview, steps, & examples, how to write a research proposal | examples & templates, ethical considerations in research | types & examples, what is your plagiarism score.

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

• Knowledge Base
• Methodology

Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

A research design is a strategy for answering your research question  using empirical data. Creating a research design means making decisions about:

• Your overall aims and approach
• The type of research design you’ll use
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

Prevent plagiarism, run a free check.

Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.

Operationalisation

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample – by mail, online, by phone, or in person?

If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organising and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarise your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
• If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

McCombes, S. (2023, March 20). Research Design | Step-by-Step Guide with Examples. Scribbr. Retrieved 24 June 2024, from https://www.scribbr.co.uk/research-methods/research-design/

Is this article helpful?

Shona McCombes

• How it works

How to Write a Research Design – Guide with Examples

Published by Alaxendra Bets at August 14th, 2021 , Revised On June 24, 2024

A research design is a structure that combines different components of research. It involves the use of different data collection and data analysis techniques logically to answer the  research questions .

It would be best to make some decisions about addressing the research questions adequately before starting the research process, which is achieved with the help of the research design.

Below are the key aspects of the decision-making process:

• Data type required for research
• Research resources
• Participants required for research
• Hypothesis based upon research question(s)
• Data analysis  methodologies
• Variables (Independent, dependent, and confounding)
• The location and timescale for conducting the data
• The time period required for research

The research design provides the strategy of investigation for your project. Furthermore, it defines the parameters and criteria to compile the data to evaluate results and conclude.

Your project’s validity depends on the data collection and  interpretation techniques.  A strong research design reflects a strong  dissertation , scientific paper, or research proposal .

Step 1: Establish Priorities for Research Design

Before conducting any research study, you must address an important question: “how to create a research design.”

The research design depends on the researcher’s priorities and choices because every research has different priorities. For a complex research study involving multiple methods, you may choose to have more than one research design.

Multimethodology or multimethod research includes using more than one data collection method or research in a research study or set of related studies.

If one research design is weak in one area, then another research design can cover that weakness. For instance, a  dissertation analyzing different situations or cases will have more than one research design.

For example:

• Experimental research involves experimental investigation and laboratory experience, but it does not accurately investigate the real world.
• Quantitative research is good for the  statistical part of the project, but it may not provide an in-depth understanding of the  topic .
• Also, correlational research will not provide experimental results because it is a technique that assesses the statistical relationship between two variables.

While scientific considerations are a fundamental aspect of the research design, It is equally important that the researcher think practically before deciding on its structure. Here are some questions that you should think of;

• Do you have enough time to gather data and complete the write-up?
• Will you be able to collect the necessary data by interviewing a specific person or visiting a specific location?
• Do you have in-depth knowledge about the  different statistical analysis and data collection techniques to address the research questions  or test the  hypothesis ?

If you think that the chosen research design cannot answer the research questions properly, you can refine your research questions to gain better insight.

Step 2: Data Type you Need for Research

Decide on the type of data you need for your research. The type of data you need to collect depends on your research questions or research hypothesis. Two types of research data can be used to answer the research questions:

Primary Data Vs. Secondary Data

Qualitative Vs. Quantitative Data

Also, see; Research methods, design, and analysis .

Need help with a thesis chapter?

• Hire an expert from ResearchProspect today!
• Statistical analysis, research methodology, discussion of the results or conclusion – our experts can help you no matter how complex the requirements are.

Step 3: Data Collection Techniques

Once you have selected the type of research to answer your research question, you need to decide where and how to collect the data.

It is time to determine your research method to address the  research problem . Research methods involve procedures, techniques, materials, and tools used for the study.

For instance, a dissertation research design includes the different resources and data collection techniques and helps establish your  dissertation’s structure .

The following table shows the characteristics of the most popularly employed research methods.

Research Methods

Step 4: Procedure of Data Analysis

Use of the  correct data and statistical analysis technique is necessary for the validity of your research. Therefore, you need to be certain about the data type that would best address the research problem. Choosing an appropriate analysis method is the final step for the research design. It can be split into two main categories;

Quantitative Data Analysis

The quantitative data analysis technique involves analyzing the numerical data with the help of different applications such as; SPSS, STATA, Excel, origin lab, etc.

This data analysis strategy tests different variables such as spectrum, frequencies, averages, and more. The research question and the hypothesis must be established to identify the variables for testing.

Qualitative Data Analysis

Qualitative data analysis of figures, themes, and words allows for flexibility and the researcher’s subjective opinions. This means that the researcher’s primary focus will be interpreting patterns, tendencies, and accounts and understanding the implications and social framework.

You should be clear about your research objectives before starting to analyze the data. For example, you should ask yourself whether you need to explain respondents’ experiences and insights or do you also need to evaluate their responses with reference to a certain social framework.

Step 5: Write your Research Proposal

The research design is an important component of a research proposal because it plans the project’s execution. You can share it with the supervisor, who would evaluate the feasibility and capacity of the results  and  conclusion .

Read our guidelines to write a research proposal  if you have already formulated your research design. The research proposal is written in the future tense because you are writing your proposal before conducting research.

The  research methodology  or research design, on the other hand, is generally written in the past tense.

How to Write a Research Design – Conclusion

A research design is the plan, structure, strategy of investigation conceived to answer the research question and test the hypothesis. The dissertation research design can be classified based on the type of data and the type of analysis.

Above mentioned five steps are the answer to how to write a research design. So, follow these steps to  formulate the perfect research design for your dissertation .

ResearchProspect writers have years of experience creating research designs that align with the dissertation’s aim and objectives. If you are struggling with your dissertation methodology chapter, you might want to look at our dissertation part-writing service.

Our dissertation writers can also help you with the full dissertation paper . No matter how urgent or complex your need may be, ResearchProspect can help. We also offer PhD level research paper writing services.

Frequently Asked Questions

What is research design.

Research design is a systematic plan that guides the research process, outlining the methodology and procedures for collecting and analysing data. It determines the structure of the study, ensuring the research question is answered effectively, reliably, and validly. It serves as the blueprint for the entire research project.

How to write a research design?

To write a research design, define your research question, identify the research method (qualitative, quantitative, or mixed), choose data collection techniques (e.g., surveys, interviews), determine the sample size and sampling method, outline data analysis procedures, and highlight potential limitations and ethical considerations for the study.

How to write the design section of a research paper?

In the design section of a research paper, describe the research methodology chosen and justify its selection. Outline the data collection methods, participants or samples, instruments used, and procedures followed. Detail any experimental controls, if applicable. Ensure clarity and precision to enable replication of the study by other researchers.

How to write a research design in methodology?

To write a research design in methodology, clearly outline the research strategy (e.g., experimental, survey, case study). Describe the sampling technique, participants, and data collection methods. Detail the procedures for data collection and analysis. Justify choices by linking them to research objectives, addressing reliability and validity.

You May Also Like

How to write a hypothesis for dissertation,? A hypothesis is a statement that can be tested with the help of experimental or theoretical research.

This article is a step-by-step guide to how to write statement of a problem in research. The research problem will be half-solved by defining it correctly.

To help students organise their dissertation proposal paper correctly, we have put together detailed guidelines on how to structure a dissertation proposal.

USEFUL LINKS

LEARNING RESOURCES

COMPANY DETAILS

• How It Works

Methods Section: Chapter Three

The methods section , or chapter three, of the dissertation or thesis is often the most challenging for graduate students.  The methodology section, chapter three should reiterate the research questions and hypotheses, present the research design, discuss the participants, the instruments to be used, the procedure, the data analysis plan , and the sample size justification.

Research Questions and Null Hypotheses

Chapter three should begin with a portion that discusses the research questions and null hypotheses.  In the research questions and null hypotheses portion of the methodology chapter, the research questions should be restated in statistical language.  For example, “Is there a difference in GPA by gender?” is a t-test type of question, whereas “Is there a relationship between GPA and income level?” is a correlation type of question.  The important thing to remember is to use the language that foreshadows the data analysis plan .  The null hypotheses are just the research questions stated in the null; for example, “There is no difference in GPA by gender,” or “There is no relationship between GPA and income level.”

Research Design

The next portion of the methods section, chapter three is focused on developing the research design.  The research design has several possibilities. First, you must decide if you are doing quantitative, qualitative, or mixed methods research. In a quantitative study, you are assessing participants’ responses on a measure.  For example, participants can endorse their level of agreement on some scale.  A qualitative design is a typically a semi-structured interview which gets transcribed, and the themes among the participants are derived.  A mixed methods project is a mixture of both a quantitative and qualitative study.

Participants

In the research methodology, the participants are typically a sample of the population you want to study.  You are probably not going to study all school children, but you may sample from the population of school children.  You need to include information about the characteristics of the population in your study (Are you sampling all males? teachers with under five years of experience?).  This represents the participants portion of your methods section, chapter three.

Need help with your methods section?

Schedule a time to speak with an expert using the calendar below.

Instruments

The instruments section is a critical part of the methodology section, chapter three.  The instruments section should include the name of the instruments, the scales or subscales, how the scales are computed, and the reliability and validity of the scales.  The instruments portion should have references to the researchers who created the instruments.

The procedure section of the methods chapter is simply how you are going to administer the instruments that you just described to the participants you are going to select.  You should walk the reader through the procedure in detail so that they can replicate your steps and your study.

Data Analysis Plan

The data analysis plan is just that — how you are going to analyze the data when you get the data from your participants.   It includes the statistical tests you are going to use, the statistical assumptions of these tests, and the justification for the statistical tests.

Sample Size Justification

Another important portion of your methods chapter three, is the sample size justification.  Sample size justification (or power analysis) is selecting how many participants you need to have in your study.  The sample size is based on several criteria:  the power you select (which is typically .80), the alpha level selected (which is typically .05), and the effect size (typically, a large or medium effect size is selected).  Importantly, once these criteria are selected, the sample size is going to be based on the type of statistic: an ANOVA is going to have a different sample size calculation than a multiple regression.

Research Design

• First Online: 13 April 2022

Cite this chapter

• Yanmei Li 3 &
• Sumei Zhang 4  

975 Accesses

This chapter introduces methods to design the research. Research design is the blueprint of how to conduct research from conception to completion. It requires careful crafts to ensure success. The initial step of research design is to theorize key concepts of the research questions, operationalize the variables used to measure the key concepts, and carefully identify the levels of measurements for all the key variables. After theorization of the key concepts, a thorough literature search and synthetization is imperative to explore extant studies related to the research questions. The purpose of literature review is to retrieve ideas, replicate studies, or fill the gap for issues and theories that extant research has (or has not) investigated.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

• Get 10 units per month
• Download Article/Chapter or Ebook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime
• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF
• Compact, lightweight edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info
• Durable hardcover edition

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Borrego, M., Douglas, E. P., & Amelink, C. T. (2009). Quantitative, qualitative, and mixed research methods in engineering education. Journal of Engineering Education, 98 (1), 53–66.

Article   Google Scholar  

Creswell, J. W., Plano Clark, V. L., & Garrett, A. L. (2008). Methodological issues in conducting mixed methods research design. In M. M. Bergman (Ed.), Advances in mixed methods research: Theories and application (pp. 66–83). Sage.

Google Scholar  

Li, Y., & Walter, R. (2013). Single-family housing market segmentation, post-foreclosure resale duration, and neighborhood attributes. Housing Policy Debate, 23 (4), 643–665. https://doi.org/10.1080/10511482.2013.835331

Opoku, A., Ahmed, V., & Akotia, J. (2016). Choosing an appropriate research methodology and method. In V. Ahmed, A. Opoku, & Z. Aziz (Eds.), Research methodology in the built environment: A selection of case studies . Routledge.

Pickering, C., Johnson, M., & Byrne, J. (2021). Using systematic quantitative literature reviews for urban analysis. In S. Baum (Ed.). Methods in Urban Analysis (Cities Research Series) (pp. 29–49) . Singapore: Springer.

Download references

Author information

Authors and affiliations.

Florida Atlantic University, Boca Raton, FL, USA

University of Louisville, Louisville, KY, USA

Sumei Zhang

You can also search for this author in PubMed   Google Scholar

Electronic Supplementary Material

(docx 13 kb), rights and permissions.

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this chapter

Li, Y., Zhang, S. (2022). Research Design. In: Applied Research Methods in Urban and Regional Planning. Springer, Cham. https://doi.org/10.1007/978-3-030-93574-0_3

Download citation

DOI : https://doi.org/10.1007/978-3-030-93574-0_3

Published : 13 April 2022

Publisher Name : Springer, Cham

Print ISBN : 978-3-030-93573-3

Online ISBN : 978-3-030-93574-0

eBook Packages : Mathematics and Statistics Mathematics and Statistics (R0)

Share this chapter

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

How To Write Chapter 3 Of A PhD Thesis Proposal (A Detailed Guide)

The format of a PhD thesis proposal varies from one institution to another. In most cases, however, chapter 3 of the PhD thesis is the research methodology chapter.

This article discusses the main sections of the research methodology chapter and provides tips on how best to write it.

Introduction

Research design, population and sampling, random sampling, non-random sampling, data collection methods and tools, questionnaires, focus group discussions, observation, document review, ethical considerations, data analysis, limitations of the study, final thoughts on how to write chapter 3 of a phd thesis proposal.

The first section is a brief introduction to the chapter, which highlights what the chapter is about.

This section discusses the research design that the study will use. The research design should be guided by the research objectives and research questions the student wants to answer. The research design can be: quantitative, qualitative, or mixed-methods design.

In quantitative research, the study will collect, analyse and present numerical data in the form of statistics. The statistics can be descriptive, inferential, or a mix of both.

In qualitative research, the study collects, analyses and presents data that is in the form of words, opinions, or thoughts of the respondents. Its focus is on the lived-in experiences of the respondents with regard to the problem under investigation.

In mixed-methods research, the study uses a combination of quantitative and qualitative research methods. So some of the research questions render themselves to quantitative research, while others to qualitative research.

Each of these research designs has its pros and cons.

Population of study refers to the entire list of your subjects of interest. If the population is so small, the student can opt to include all the subjects in the study. However, if the population is large, it becomes difficult – both time-wise and resource-wise – to include all the subjects in the study.

A sample is a sub-set of the population of study from which data will be collected to enable the student understand the population.

An example of population vs. sample: Suppose a study aims at investigating the effects of COVID-19 pandemic on micro and small enterprises (MSEs) in Kenya. The population of the study will be all the MSEs in Kenya, which are thousands in number, distributed across the country. It will be impossible for the student to collect data from all those MSEs and therefore a sample will be necessary. The sample size the student decides to use will depend on whether the study is quantitative, qualitative or both. For quantitative studies, a large sample size is necessary, while for qualitative study, the sample size need not be large.

Sampling is the process by which a sample is drawn from a population. There are two categories of sampling techniques, namely: random and non-random sampling. The use of either depends on your research design.

In random sampling, the sample is selected randomly and each subject in the population has an equal chance of being selected for the sample.

The advantage of random sampling is that the results from the sample can be generalised to the population, especially if the sample size is sufficiently large.

Random sampling is used primarily for quantitative studies.

In non-random sampling, the sample is selected deliberately rather than randomly. As a result, the subjects do not have an equal chance of being selected for the sample.

It is also referred to as purposive sampling, meaning that the sample being selected have a specific purpose.

Non-random sampling is used primarily for qualitative sampling.

In this section, the student is expected to discuss in detail the type of data he will collect, that is, whether primary or secondary data (or both) and how he will go about collecting the data from the sample. The methods and tools used also depend on the research design. They include:

Questionnaires are mostly used to collect quantitative data.

Questionnaires are structured in nature and include closed-ended questions.

There are four main types of closed-ended questions used in questionnaires:

• for example: how many children do you have?
• for example: does your household have a radio? 1. Yes 2. No
• for example: what is your highest level of education? 1. No education 2. Primary education 3. Secondary education 4. Tertiary level
• for example: please rate your level of satisfaction with the water services board. 1. Very dissatisfied 2. Dissatisfied 3. Neutral 4. Satisfied 5. Very satisfied

There are two forms of questionnaaire delivery: facilitated questionnaires and self-administered questionnaires.

For facilitated questionnaires, the researcher administers the questionnaire while in self-administered questionnaires, the respondent fills in the questionnaire without the presence of the researcher.

Self-administered questionnaires can be delivered by hand, or mailed via the post office or through email. Facilitated questionnaires can be done either face-to-face or through telephone. Each of these options has its pros and cons.

Interviews are oral discussions between the researcher and the respondent.

Unlike questionnaires, interviews are semi-structured. The researcher uses an interview guide to guide the discussion. The interview guide has some questions that the researcher asks the respondent. However, subsequent questions and discussions are determined by the responses given by the respondent to previous questions.

The flow of interviews will therefore vary from one respondent to another depending on their personalities and openness to responding to the questions.

Whereas interviews are held with individuals, focus group discussions (FGDs) are held with a group of respondents who are key to the problem under investigation.

The participants for an FGD should be selected carefully to represent diverse subjects of the population under investigation.

In the example of the study on the effects of COVID-19 pandemic on micro and small enterprises in Kenya, the student can create a focus group that has the following members: a female-owned enterprise, a male-owned enterprise, a youth-owned enterprise, a family-run enterprise, a non-family-run enterprise, customers of the enterprises, and an employee of the Micro and Small Enterprises Authority (MSEA). Such a focus group would have rich discussions of the views of the different players in the industry.

Observation is also a method of data collection that is commonly used. There are two types of observation: participant observation and non-participant observation.

In participant observation, the researcher immerses himself into the environment of study. In the MSEs study, for example, the researcher would choose to work in one of the enterprises for a period of time where he would observe how the business performs on a day-to-day basis.

In non-participant observation, the researcher removes himself from the environment of study and instead observes from a distance. In the MSEs study, for example, the researcher would go somewhere close to an enterprise and observe how the business performs e.g. how many clients visit the business on a day-to-day basis.

Each observation type has its own pros and cons.

During observation, the researcher should use an observation checklist that guides him on what needs to be observed and the frequency of observation.

In this data collection methods, the student obtains relevant documents to his study and reviews them in-depth. For instance, in the MSEs, the student can review the MSEs Policy of Kenya, Strategic Plan of the Micro and Small Enterprises Authority etc. Such documents are useful in informing the researcher the current state of affairs of the problem under investigation.

This section highlights the ethical considerations that would be followed during the data collection process. The ethical considerations vary from study to study and include:

Consent: the researcher should seek informed consent from the respondent before the data collection begins. For instance, when administering the questionnaire or conducting interviews, the researcher should start by informing the respondent what the study is about, how the respondent was selected, and the benefits of the study and then seek permission to continue with the study. The consent can be in written or oral form.

Compensation for participation: while participating in the study should be voluntary, some research have allowance for monetary compensation. The respondents should be informed of any plans to compensate them but after they have participated in the study, not before.

Confidentiality: the researcher should assure the respondents that their responses will be kept confidential.

Dissemination of the study findings with the respondents: there should be a plan for the student to disseminate the results of the study with the participants, for instance, through validation workshops or written publications.

Additionally, most academic institutions require their students to obtain ethical clearance for their research from the relevant authorities. Students should check if this requirement applies to them and follow the necessary procedure.

In this section, the student should discuss how the data collected will be analysed. Data analysis methods and techniques vary depending on whether the data is quantitative or qualitative.

For quantitative research, the interest of data analysis is the numbers which can be obtained through descriptive statistics and inferential statistics.

Descriptive statistics is usually the first step in analysing quantitative data. There are three categories of descriptive statistics:

• Measures of frequency: frequency table or cross-tabulation table.
• Measures of central tendency: mean, median and mode.
• Measures of variability: range, standard deviation and variance.

Inferential analysis goes a step further and looks at whether the results from the sample can be generalised to the wider population. For studies that involve interventions, inferential analysis is used to check if the intervention has any impact on the population in which it was implemented.

Some inferential analysis techniques include:

• Checking for differences between groups: t-test, analysis of variance (ANOVA) and Chi-square test.
• Checking for correlation or causation between variables: linear regression, logistic regression (logit, probit, multinomial logit/probit models etc).

The choice of data analysis technique will depend on the type of data the student has. For instance, a dependent variable that is continuous will use a different analysis technique from a dependent variable that is categorical in nature. Additionally, the choice of the data analysis technique should be guided by the research questions. The results from the analysis should be able to provide answers to the research questions posed.

For qualitative research, data analysis involves analysing the content of the interviews and focus group discussions. The content can be in different forms such as interview recordings and hand-written notes.

The recordings should be transcribed first and the notes should be organised well before analysis can take place.

The analysis of qualitative data involves coding the data, indexing the data and framing the data to identify the themes that emerge from the data.

Besides discussing the data analysis techniques, the student should discuss the softwares that will be used for analysis. There are many softwares in the market that are used for quantitative (such as SPSS and STATA) and qualitative data (such as NVivo).

The last section in the research methodology chapter discusses the potential limitations of the study and how the limitations will be mitigated. An example of study limitation is low response rate of questionnaires, which can be mitigated through triangulation.

The limitations of the study will vary from one study to another and depend on the context within which the study is conducted.

This article provided a detailed guide on how to write the research methodology chapter of a PhD thesis proposal. The research methodology chapter is informed by the research problem and research questions specified in chapter 1 of the thesis proposal. Students should therefore think through carefully their research study from the beginning because what is in the introduction chapter informs the content in the remaining chapters of the proposal and final thesis.

Related posts

How To Write Chapter 1 Of A PhD Thesis Proposal (A Practical Guide)

How To Write Chapter 2 Of A PhD Thesis Proposal (A Beginner’s Guide)

Grace Njeri-Otieno

Grace Njeri-Otieno is a Kenyan, a wife, a mom, and currently a PhD student, among many other balls she juggles. She holds a Bachelors' and Masters' degrees in Economics and has more than 7 years' experience with an INGO. She was inspired to start this site so as to share the lessons learned throughout her PhD journey with other PhD students. Her vision for this site is "to become a go-to resource center for PhD students in all their spheres of learning."

Recent Content

SPSS Tutorial #12: Partial Correlation Analysis in SPSS

Partial correlation is almost similar to Pearson product-moment correlation only that it accounts for the influence of another variable, which is thought to be correlated with the two variables of...

SPSS Tutorial #11: Correlation Analysis in SPSS

In this post, I discuss what correlation is, the two most common types of correlation statistics used (Pearson and Spearman), and how to conduct correlation analysis in SPSS. What is correlation...

How To Write The Methodology Chapter

The what, why & how explained simply (with examples).

By: Jenna Crossley (PhD) | Reviewed By: Dr. Eunice Rautenbach | September 2021 (Updated April 2023)

So, you’ve pinned down your research topic and undertaken a review of the literature – now it’s time to write up the methodology section of your dissertation, thesis or research paper . But what exactly is the methodology chapter all about – and how do you go about writing one? In this post, we’ll unpack the topic, step by step .

Overview: The Methodology Chapter

• The purpose  of the methodology chapter
• Why you need to craft this chapter (really) well
• How to write and structure the chapter
• Methodology chapter example
• Essential takeaways

What (exactly) is the methodology chapter?

The methodology chapter is where you outline the philosophical underpinnings of your research and outline the specific methodological choices you’ve made. The point of the methodology chapter is to tell the reader exactly how you designed your study and, just as importantly, why you did it this way.

Importantly, this chapter should comprehensively describe and justify all the methodological choices you made in your study. For example, the approach you took to your research (i.e., qualitative, quantitative or mixed), who  you collected data from (i.e., your sampling strategy), how you collected your data and, of course, how you analysed it. If that sounds a little intimidating, don’t worry – we’ll explain all these methodological choices in this post .

Why is the methodology chapter important?

The methodology chapter plays two important roles in your dissertation or thesis:

Firstly, it demonstrates your understanding of research theory, which is what earns you marks. A flawed research design or methodology would mean flawed results. So, this chapter is vital as it allows you to show the marker that you know what you’re doing and that your results are credible .

Secondly, the methodology chapter is what helps to make your study replicable. In other words, it allows other researchers to undertake your study using the same methodological approach, and compare their findings to yours. This is very important within academic research, as each study builds on previous studies.

The methodology chapter is also important in that it allows you to identify and discuss any methodological issues or problems you encountered (i.e., research limitations ), and to explain how you mitigated the impacts of these. Every research project has its limitations , so it’s important to acknowledge these openly and highlight your study’s value despite its limitations . Doing so demonstrates your understanding of research design, which will earn you marks. We’ll discuss limitations in a bit more detail later in this post, so stay tuned!

Need a helping hand?

How to write up the methodology chapter

First off, it’s worth noting that the exact structure and contents of the methodology chapter will vary depending on the field of research (e.g., humanities, chemistry or engineering) as well as the university . So, be sure to always check the guidelines provided by your institution for clarity and, if possible, review past dissertations from your university. Here we’re going to discuss a generic structure for a methodology chapter typically found in the sciences.

Before you start writing, it’s always a good idea to draw up a rough outline to guide your writing. Don’t just start writing without knowing what you’ll discuss where. If you do, you’ll likely end up with a disjointed, ill-flowing narrative . You’ll then waste a lot of time rewriting in an attempt to try to stitch all the pieces together. Do yourself a favour and start with the end in mind .

Section 1 – Introduction

As with all chapters in your dissertation or thesis, the methodology chapter should have a brief introduction. In this section, you should remind your readers what the focus of your study is, especially the research aims . As we’ve discussed many times on the blog, your methodology needs to align with your research aims, objectives and research questions. Therefore, it’s useful to frontload this component to remind the reader (and yourself!) what you’re trying to achieve.

In this section, you can also briefly mention how you’ll structure the chapter. This will help orient the reader and provide a bit of a roadmap so that they know what to expect. You don’t need a lot of detail here – just a brief outline will do.

Section 2 – The Methodology

The next section of your chapter is where you’ll present the actual methodology. In this section, you need to detail and justify the key methodological choices you’ve made in a logical, intuitive fashion. Importantly, this is the heart of your methodology chapter, so you need to get specific – don’t hold back on the details here. This is not one of those “less is more” situations.

Let’s take a look at the most common components you’ll likely need to cover. 

Methodological Choice #1 – Research Philosophy

Research philosophy refers to the underlying beliefs (i.e., the worldview) regarding how data about a phenomenon should be gathered , analysed and used . The research philosophy will serve as the core of your study and underpin all of the other research design choices, so it’s critically important that you understand which philosophy you’ll adopt and why you made that choice. If you’re not clear on this, take the time to get clarity before you make any further methodological choices.

While several research philosophies exist, two commonly adopted ones are positivism and interpretivism . These two sit roughly on opposite sides of the research philosophy spectrum.

Positivism states that the researcher can observe reality objectively and that there is only one reality, which exists independently of the observer. As a consequence, it is quite commonly the underlying research philosophy in quantitative studies and is oftentimes the assumed philosophy in the physical sciences.

Contrasted with this, interpretivism , which is often the underlying research philosophy in qualitative studies, assumes that the researcher performs a role in observing the world around them and that reality is unique to each observer . In other words, reality is observed subjectively .

These are just two philosophies (there are many more), but they demonstrate significantly different approaches to research and have a significant impact on all the methodological choices. Therefore, it’s vital that you clearly outline and justify your research philosophy at the beginning of your methodology chapter, as it sets the scene for everything that follows.

Methodological Choice #2 – Research Type

The next thing you would typically discuss in your methodology section is the research type. The starting point for this is to indicate whether the research you conducted is inductive or deductive .

Inductive research takes a bottom-up approach , where the researcher begins with specific observations or data and then draws general conclusions or theories from those observations. Therefore these studies tend to be exploratory in terms of approach.

Conversely , d eductive research takes a top-down approach , where the researcher starts with a theory or hypothesis and then tests it using specific observations or data. Therefore these studies tend to be confirmatory in approach.

Related to this, you’ll need to indicate whether your study adopts a qualitative, quantitative or mixed  approach. As we’ve mentioned, there’s a strong link between this choice and your research philosophy, so make sure that your choices are tightly aligned . When you write this section up, remember to clearly justify your choices, as they form the foundation of your study.

Methodological Choice #3 – Research Strategy

Next, you’ll need to discuss your research strategy (also referred to as a research design ). This methodological choice refers to the broader strategy in terms of how you’ll conduct your research, based on the aims of your study.

Several research strategies exist, including experimental , case studies , ethnography , grounded theory, action research , and phenomenology . Let’s take a look at two of these, experimental and ethnographic, to see how they contrast.

Experimental research makes use of the scientific method , where one group is the control group (in which no variables are manipulated ) and another is the experimental group (in which a specific variable is manipulated). This type of research is undertaken under strict conditions in a controlled, artificial environment (e.g., a laboratory). By having firm control over the environment, experimental research typically allows the researcher to establish causation between variables. Therefore, it can be a good choice if you have research aims that involve identifying causal relationships.

Ethnographic research , on the other hand, involves observing and capturing the experiences and perceptions of participants in their natural environment (for example, at home or in the office). In other words, in an uncontrolled environment.  Naturally, this means that this research strategy would be far less suitable if your research aims involve identifying causation, but it would be very valuable if you’re looking to explore and examine a group culture, for example.

As you can see, the right research strategy will depend largely on your research aims and research questions – in other words, what you’re trying to figure out. Therefore, as with every other methodological choice, it’s essential to justify why you chose the research strategy you did.

Methodological Choice #4 – Time Horizon

The next thing you’ll need to detail in your methodology chapter is the time horizon. There are two options here: cross-sectional and longitudinal . In other words, whether the data for your study were all collected at one point in time (cross-sectional) or at multiple points in time (longitudinal).

The choice you make here depends again on your research aims, objectives and research questions. If, for example, you aim to assess how a specific group of people’s perspectives regarding a topic change over time , you’d likely adopt a longitudinal time horizon.

Another important factor to consider is simply whether you have the time necessary to adopt a longitudinal approach (which could involve collecting data over multiple months or even years). Oftentimes, the time pressures of your degree program will force your hand into adopting a cross-sectional time horizon, so keep this in mind.

Methodological Choice #5 – Sampling Strategy

Next, you’ll need to discuss your sampling strategy . There are two main categories of sampling, probability and non-probability sampling.

Probability sampling involves a random (and therefore representative) selection of participants from a population, whereas non-probability sampling entails selecting participants in a non-random  (and therefore non-representative) manner. For example, selecting participants based on ease of access (this is called a convenience sample).

The right sampling approach depends largely on what you’re trying to achieve in your study. Specifically, whether you trying to develop findings that are generalisable to a population or not. Practicalities and resource constraints also play a large role here, as it can oftentimes be challenging to gain access to a truly random sample. In the video below, we explore some of the most common sampling strategies.

Methodological Choice #6 – Data Collection Method

Next up, you’ll need to explain how you’ll go about collecting the necessary data for your study. Your data collection method (or methods) will depend on the type of data that you plan to collect – in other words, qualitative or quantitative data.

Typically, quantitative research relies on surveys , data generated by lab equipment, analytics software or existing datasets. Qualitative research, on the other hand, often makes use of collection methods such as interviews , focus groups , participant observations, and ethnography.

So, as you can see, there is a tight link between this section and the design choices you outlined in earlier sections. Strong alignment between these sections, as well as your research aims and questions is therefore very important.

Methodological Choice #7 – Data Analysis Methods/Techniques

The final major methodological choice that you need to address is that of analysis techniques . In other words, how you’ll go about analysing your date once you’ve collected it. Here it’s important to be very specific about your analysis methods and/or techniques – don’t leave any room for interpretation. Also, as with all choices in this chapter, you need to justify each choice you make.

What exactly you discuss here will depend largely on the type of study you’re conducting (i.e., qualitative, quantitative, or mixed methods). For qualitative studies, common analysis methods include content analysis , thematic analysis and discourse analysis . In the video below, we explain each of these in plain language.

For quantitative studies, you’ll almost always make use of descriptive statistics , and in many cases, you’ll also use inferential statistical techniques (e.g., correlation and regression analysis). In the video below, we unpack some of the core concepts involved in descriptive and inferential statistics.

In this section of your methodology chapter, it’s also important to discuss how you prepared your data for analysis, and what software you used (if any). For example, quantitative data will often require some initial preparation such as removing duplicates or incomplete responses . Similarly, qualitative data will often require transcription and perhaps even translation. As always, remember to state both what you did and why you did it.

Section 3 – The Methodological Limitations

With the key methodological choices outlined and justified, the next step is to discuss the limitations of your design. No research methodology is perfect – there will always be trade-offs between the “ideal” methodology and what’s practical and viable, given your constraints. Therefore, this section of your methodology chapter is where you’ll discuss the trade-offs you had to make, and why these were justified given the context.

Methodological limitations can vary greatly from study to study, ranging from common issues such as time and budget constraints to issues of sample or selection bias . For example, you may find that you didn’t manage to draw in enough respondents to achieve the desired sample size (and therefore, statistically significant results), or your sample may be skewed heavily towards a certain demographic, thereby negatively impacting representativeness .

In this section, it’s important to be critical of the shortcomings of your study. There’s no use trying to hide them (your marker will be aware of them regardless). By being critical, you’ll demonstrate to your marker that you have a strong understanding of research theory, so don’t be shy here. At the same time, don’t beat your study to death . State the limitations, why these were justified, how you mitigated their impacts to the best degree possible, and how your study still provides value despite these limitations .

Section 4 – Concluding Summary

Finally, it’s time to wrap up the methodology chapter with a brief concluding summary. In this section, you’ll want to concisely summarise what you’ve presented in the chapter. Here, it can be a good idea to use a figure to summarise the key decisions, especially if your university recommends using a specific model (for example, Saunders’ Research Onion ).

Importantly, this section needs to be brief – a paragraph or two maximum (it’s a summary, after all). Also, make sure that when you write up your concluding summary, you include only what you’ve already discussed in your chapter; don’t add any new information.

Methodology Chapter Example

In the video below, we walk you through an example of a high-quality research methodology chapter from a dissertation. We also unpack our free methodology chapter template so that you can see how best to structure your chapter.

Wrapping Up

And there you have it – the methodology chapter in a nutshell. As we’ve mentioned, the exact contents and structure of this chapter can vary between universities , so be sure to check in with your institution before you start writing. If possible, try to find dissertations or theses from former students of your specific degree program – this will give you a strong indication of the expectations and norms when it comes to the methodology chapter (and all the other chapters!).

Also, remember the golden rule of the methodology chapter – justify every choice ! Make sure that you clearly explain the “why” for every “what”, and reference credible methodology textbooks or academic sources to back up your justifications.

If you need a helping hand with your research methodology (or any other component of your research), be sure to check out our private coaching service , where we hold your hand through every step of the research journey. Until next time, good luck!

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

You Might Also Like:

52 Comments

highly appreciated.

This was very helpful!

This was helpful

Thanks ,it is a very useful idea.

Thanks ,it is very useful idea.

Thank you so much, this information is very useful.

Thank you very much. I must say the information presented was succinct, coherent and invaluable. It is well put together and easy to comprehend. I have a great guide to create the research methodology for my dissertation.

Highly clear and useful.

I understand a bit on the explanation above. I want to have some coach but I’m still student and don’t have any budget to hire one. A lot of question I want to ask.

Thank you so much. This concluded my day plan. Thank you so much.

Thanks it was helpful

Great information. It would be great though if you could show us practical examples.

Thanks so much for this information. God bless and be with you

Thank you so so much. Indeed it was helpful

This is EXCELLENT!

I was totally confused by other explanations. Thank you so much!.

justdoing my research now , thanks for the guidance.

Thank uuuu! These contents are really valued for me!

This is powerful …I really like it

Highly useful and clear, thank you so much.

Highly appreciated. Good guide

That was helpful. Thanks

This is very useful.Thank you

Very helpful information. Thank you

This is exactly what I was looking for. The explanation is so detailed and easy to comprehend. Well done and thank you.

Great job. You just summarised everything in the easiest and most comprehensible way possible. Thanks a lot.

Thank you very much for the ideas you have given this will really help me a lot. Thank you and God Bless.

Such great effort …….very grateful thank you

Please accept my sincere gratitude. I have to say that the information that was delivered was congruent, concise, and quite helpful. It is clear and straightforward, making it simple to understand. I am in possession of an excellent manual that will assist me in developing the research methods for my dissertation.

Thank you for your great explanation. It really helped me construct my methodology paper.

thank you for simplifieng the methodoly, It was realy helpful

Very helpful!

Thank you for your great explanation.

The explanation I have been looking for. So clear Thank you

Thank you very much .this was more enlightening.

helped me create the in depth and thorough methodology for my dissertation

Thank you for the great explaination.please construct one methodology for me

I appreciate you for the explanation of methodology. Please construct one methodology on the topic: The effects influencing students dropout among schools for my thesis

This helped me complete my methods section of my dissertation with ease. I have managed to write a thorough and concise methodology!

its so good in deed

wow …what an easy to follow presentation. very invaluable content shared. utmost important.

Peace be upon you, I am Dr. Ahmed Khedr, a former part-time professor at Al-Azhar University in Cairo, Egypt. I am currently teaching research methods, and I have been dealing with your esteemed site for several years, and I found that despite my long experience with research methods sites, it is one of the smoothest sites for evaluating the material for students, For this reason, I relied on it a lot in teaching and translated most of what was written into Arabic and published it on my own page on Facebook. Thank you all… Everything I posted on my page is provided with the names of the writers of Grad coach, the title of the article, and the site. My best regards.

A remarkably simple and useful guide, thank you kindly.

I real appriciate your short and remarkable chapter summary

Bravo! Very helpful guide.

Only true experts could provide such helpful, fantastic, and inspiring knowledge about Methodology. Thank you very much! God be with you and us all!

highly appreciate your effort.

This is a very well thought out post. Very informative and a great read.

THANKS SO MUCH FOR SHARING YOUR NICE IDEA

I love you Emma, you are simply amazing with clear explanations with complete information. GradCoach really helped me to do my assignment here in Auckland. Mostly, Emma make it so simple and enjoyable

Thank you very much for this informative and synthesised version.

Submit a Comment Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

• Print Friendly

• Welcome to Chapter 3

Chapter 3 Webinars

• Student Experience Feedback Buttons
• Developing the Quantitative Research Design
• Qualitative Descriptive Design
• Qualitative Narrative Inquiry Research
• SAGE Research Methods
• Alignment of Dissertation Components for DIS-9902ABC
• IRB Resources This link opens in a new window
• Research Examples (SAGE) This link opens in a new window
• Dataset Examples (SAGE) This link opens in a new window

Jump to DSE Guide

Need help ask us.

Was this resource helpful?

• Next: Developing the Quantitative Research Design >>
• Last Updated: Nov 2, 2023 10:17 AM
• URL: https://resources.nu.edu/c.php?g=1007179

© Copyright 2024 National University. All Rights Reserved.

Privacy Policy | Consumer Information

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

Chapter 3 Research design and methodology

the purpose of this paper is to know what are the use of methodology in a research paper.

Related Papers

Dhea Savella Segui

Scholarly Communication and the Publish or Perish Pressures of Academia A volume in the Advances in Knowledge Acquisition, Transfer, and Management (AKATM) Book Series

Dr. Naresh A . Babariya , Alka V. Gohel

The most important of research methodology in research study it is necessary for a researcher to design a methodology for the problem chosen and systematically solves the problem. Formulation of the research problem is to decide on a broad subject area on which has thorough knowledge and second important responsibility in research is to compare findings, it is literature review plays an extremely important role. The literature review is part of the research process and makes a valuable contribution to almost every operational step. A good research design provides information concerning with the selection of the sample population treatments and controls to be imposed and research work cannot be undertaken without sampling. Collecting the data and create data structure as organizing the data, analyzing the data help of different statistical method, summarizing the analysis, and using these results for making judgments, decisions and predictions. Keywords: Research Problem, Economical Plan, Developing Ideas, Research Strategy, Sampling Design, Theoretical Procedures, Experimental Studies, Numerical Schemes, Statistical Techniques.

Chisomo Mgunda

Xochitl Ortiz

The authors felt during their several years of teaching experience that students fail to understand the books written on Research Methodology because generally they are written in technical language. Since this course is not taught before the Master’s degree, the students are not familiar with its vocabulary, methodology and course contents. The authors have made an attempt to write it in very non- technical language. It has been attempted that students who try to understand the research methodology through self-learning may also find it easy. The chapters are written with that approach. Even those students who intend to attain high level of knowledge of the research methodology in social sciences will find this book very helpful in understanding the basic concepts before they read any book on research methodology. This book is useful those students who offer the Research Methodology at Post Graduation and M.Phil. Level. This book is also very useful for Ph.D. Course Work examinations.

Mahesh Hemachandra

Roxannie Ibot

https://www.ijrrjournal.com/IJRR_Vol.6_Issue.3_March2019/Abstract_IJRR0011.html

International Journal of Research & Review (IJRR)

Research methodology is a way to systematically solve the research problem. It may be understood as a science of studying how research is done scientifically. In it we study the various steps that are generally adopted by a researcher in studying his research problem along with the logic behind them. It is necessary for the researcher to know not only the research methods/techniques but also the methodology. Researchers not only need to know how to develop certain indices or tests, how to calculate the mean, the mode, the median or the standard deviation or chi-square, how to apply particular research techniques, but they also need to know which of these methods or techniques, are relevant and which are not, and what would they mean and indicate and why. Researchers also need to understand the assumptions underlying various techniques and they need to know the criteria by which they can decide that certain techniques and procedures will be applicable to certain problems and others will not. All this means that it is necessary for the researcher to design his methodology for his problem as the same may differ from problem to problem.

Contributions to Management Science

Paul Hanges

Victor Ramapala

Anil Jharotia

Research is an important activity of any nation and societies for generating the information to its developments. Robust collection of qualitative information helps in the development of the any nations. Research & Development is an important tool for acquiring new knowledge in any field of human survival. Various type of problems and questions need to use research methodology depend on the rationale of researchers. How to use the research for finding answers of any research questions/problems.

Loading Preview

Sorry, preview is currently unavailable. You can download the paper by clicking the button above.

RELATED PAPERS

melaku emayneh

Sarah Baloyi

Razieh Tadayon Nabavi

Vikalpa: The Journal for Decision Makers

Vivek Patkar

LUWAGA ERIC

Research Methodology and Research Method

Sam Goundar

Bostley Asenahabi

stephenson Nkurikiyimana

Scholars Bulletin

Wahied Khawar Balwan

Ngoc Nguyen

Nova Southeastern University

Addisalem Tadesse

Dirisa Mulindwa

Yuanita Damayanti

mubashar yaqoob

Dr. Moses Gweyi

Skyfox Publishing Group

Dr. T. Vel murugan

Ponsian P R O T Ntui

DR FREDRICK ONASANYA

Tutors India

RESEARCH DESIGN

Ludmila Romanovska

Md. M O H A I M I N U L Rahman

Kristoffer Dean

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024