Research design is a systematic blueprint for conducting research that outlines the objectives, methods, and timeline for answering research questions. It includes different types such as quantitative, qualitative, and mixed-methods approaches, and emphasizes the importance of ethical considerations throughout the research process. Key elements also involve sampling techniques and data collection and analysis methods.

1. Introduction to
Research Design
Research design is the framework or blueprint for conducting research. It
outlines the steps and procedures to be followed to answer a research
question.
SS
Dr. Siva Gurunathan S
Assistant Professor,
PG and Research Department of Economics,
Sacred Heart College (Autonomous),
Tirupattur-635601.

2. Defining Research Design
A research design is a systematic plan that guides the collection and
analysis of data to address a research question.
Objectives
Research design clarifies
objectives to be achieved.
Methods
It specifies methods for data
collection and analysis.
Timeline
It outlines a clear timeline and budget for the research.

3. Types of Research Design
Research designs are categorized based on the purpose and methods of the study.
Quantitative
Quantitative research uses numerical
data to measure and analyze
phenomena.
Qualitative
Qualitative research explores
meanings, experiences, and
perspectives using non-numerical
data.
Mixed-Methods
Mixed-methods research combines
both quantitative and qualitative
approaches.

4. Quantitative Research
Design
Quantitative designs emphasize objective measurement and statistical
analysis of data.
1 Experimental
Involves manipulating
variables to establish
cause-and-effect
relationships.
2 Survey
Collects data from a large
sample using
questionnaires or
interviews.
3 Correlational
Examines the relationships between variables without manipulation.

5. Qualitative Research Design
Qualitative designs focus on understanding the meaning and interpretation of data.
Ethnographic
Immersion in a culture or community to understand their perspectives.
Grounded Theory
Developing theories based on patterns emerging from data analysis.
Case Study
In-depth examination of a particular individual, group, or event.

6. Mixed-Methods
Research Design
Mixed-methods designs integrate quantitative and qualitative
approaches to provide a comprehensive understanding.
Triangulation Using multiple methods to
validate findings.
Expansion Qualitative data to enrich
quantitative findings.
Embedded One method nested within
another.

7. Sampling Techniques
Sampling techniques are used to select a representative subset of the
population for the study.
Random Sampling
Every individual has an equal
chance of being selected.
Stratified Sampling
Dividing the population into strata
and randomly selecting from each
stratum.
Convenience Sampling
Selecting participants based on
ease of access.
Snowball Sampling
Participants refer other potential
participants.

8. Data Collection Methods
Data collection methods are the tools used to gather data from participants.
1
Surveys
Using questionnaires or interviews to collect
data from a large sample.
2 Observations
Systematic recording of behaviors or events in
a natural setting.
3
Experiments
Manipulating variables to test hypotheses.
4 Interviews
In-depth conversations with participants to
gather detailed information.
5
Focus Groups
Discussions with a small group of participants
to explore a particular topic.

9. Data Analysis Strategies
Data analysis strategies are used to interpret and draw meaning from collected data.
Quantitative Analysis
Using statistical methods to analyze numerical data.
Qualitative Analysis
Thematic analysis, content analysis, or discourse analysis to
interpret non-numerical data.

10. Ethical
Considerations in
Research Design
Ethical considerations are crucial throughout the research
process to ensure participant safety and data integrity.
1 Informed Consent
Participants must be
fully informed about the
study and provide
consent to participate.
2 Confidentiality
Protecting participant
privacy and ensuring
anonymity of data.
3 Beneficence
Maximizing benefits to
participants while
minimizing risks.
4 Integrity
Maintaining honesty
and transparency in
data collection and
reporting.