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Course Detail

Course Name Research Methods for Policy Studies – I
Course Code 24SDS504
Program M.Sc. in Social Data Science & Policy
Semester I
Credits 4
Campus Faridabad


Unit I

Unit I – Introduction to policy and research design – Elements of research design. Selection of a research approach. Theories, research questions and hypotheses. Measurement, validity, and reliability. Research ethics.

Unit II

Unit II – Foundations of qualitative research – Data collection, organization, and representation. Interviews and focus groups. Conducting observations. Survey research and questionnaire design. Practices of interpretation. Writing as interpretation.

Unit III

Unit III – Foundations of exploratory data analysis. Descriptive statistics. Frequency distributions. Mean, variance, standard deviation, skewness, and kurtosis. Measures of position. Correlation coefficient. Visualizing relationships between variables.

Unit IV

Unit IV – Statistical inference. Probability useful for statistics. A survey of probability concepts. Random variables and functions of random variables. Discrete and continuous probability distributions. Sampling methods and the Central Limit Theorem. Estimation and confidence intervals. Choosing an appropriate sample size. Hypothesis testing.

Unit V

Unit V – Regression analysis. Simple linear regression. Linear model assumptions. Properties of the least squares estimator. Gauss-Markov Theorem. Testing and confidence intervals. Multiple linear regression. Inferences in multiple linear regression. Omitted variable bias. Multicollinearity. Heteroskedasticity. Dummy variables. Interaction Terms. Polynomials and logarithms. Advanced regression topics. Robust regression. Semi-parametric and non-parametric regression. Nonlinear regression: logit and probit models.


This course introduces students to the key issues of the research process in social sciences, including measurement, reliability and validity, internal research design validity, and generalizability. This course is focused on quantitative (as well as the basics of qualitative) research methods and includes a brief introduction to the stages of research design in the policy context, followed by the exploratory data analysis, basics of probability theory, statistical inference, as well as a simple and multiple linear regression as part of a broader strategy of causal analysis. The course equips students with the skills and knowledge necessary to prepare a policy-relevant research project using rigorous empirical research methods.

Course Objectives:

  1. Develop skills and methods to engage in independent empirical research, including the ability to design a study, collect data, and analyze materials and formulate policy recommendations.
  2. Learn the key concepts of social science research and understand how to execute different research approaches in practice.
  3. Become familiar with how to read, interpret, write, and present quantitative research.
  4. Better understand the limits of formal, numerical, quantitative, or analytical reasoning and discuss the potential for the abuse of numerical arguments.
  5. Apply different approaches to estimating relationships between measured constructs, including simple and multiple linear models, non-linear models, and correctly interpret significance tests for estimated coefficients.

Course Outcomes:

CO1: Students will develop the ability to critically evaluate quantitative information, identify appropriate statistical techniques for various research questions, and make informed decisions and policy recommendations based on quantitative data analysis.
CO2: Students will demonstrate proficiency in using statistical methods to analyze data, including descriptive statistics, inferential statistics, and multivariate analysis techniques.
CO3: Students will gain a solid understanding of probability theory, including concepts such as probability distributions, random variables, and probability models, to analyze uncertain outcomes and make probabilistic predictions.
CO4: Students will learn regression analysis techniques and develop the ability to build, interpret, and evaluate regression models to analyze relationships between variables and make predictions.
CO5: Students will understand the basics of qualitative data collection techniques, such as interviews, focus groups, participant observation, and understand the strengths and limitations of each method.


  • Critical thinking and interpretation of results: students will develop critical thinking skills to evaluate the validity and reliability of quantitative research findings, interpret statistical results accurately, and communicate findings effectively to diverse audiences.
  • Problem-solving and adaptability: students will develop strong problem-solving skills and adaptability by confronting and addressing challenges inherent in quantitative and qualitative research.

-Program outcome PO – Course Outcomes CO Mapping


Program Specific Outcomes PSO – Course Objectives – Mapping


Textbooks and Papers

  1. Gujarati, D. N. (2021). Essentials of econometrics. Sage Publications.
  2. Wooldridge, J. (2008) Introductory Econometrics. New York: South-Western. 4th edition.
  3. Creswell, John W. (2002) Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. 2nd ed. Thousand Oaks, CA: Sage.

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