Quantitative Research Methods

Semester and Year Offered: semesterIII

Course Coordinator and Team: Dr.Nivdita Sarkar

Email of course coordinator: niveditasarkar@aud.ac.in

Pre-requisites: Students must have taken all the courses of Semester 1 and Semester 2 in M.A. (Education) and M.A. Education (Early Childhood Care and Education)

Course Description:

The course on Quantitative Research Methods is designed to provide students with a well- rounded understanding of research methods (quantitative, qualitative and mixed-methods)and familiarize students with quantitative research methods in particular. This will help them to understand the application of various quantitative techniques in diverse research settings.Emphasis will be given on achieving an understanding of quantitative methods, nature and logic of statistical tests and associated statistical techniques and provide hands-on experience in computer applications for data analysis. This will also help the students to think critically about the suitable procedures for research design, collection and analysis of data, and the usefulness of basic statistics for empirical data analysis.

Course Objectives:

1. To understand the philosophical and epistemological difference between quantitative and qualitative research methods
2. To recognize various concepts of descriptive and inferential statistics
3. To familiarize students with data sets available in the area of education
4. To understands the methods of central tendency and dispersion.
5. To interpret the results drawn on elementary statistics.
6. To introduce students to correlation and regression analysis.
7. To graphically represent a group of empirical data.
8. To familiarize students with Exceland SPSSand increase their ability to navigate these software packages on their own for empirical analysis.

Course Outcomes: One completion of this course

1. The students will be able to comprehend and interpret graphs and summary statistics presented in academic papers, reports and studies.
2. The students will be able to identify which estimates of central tendency (mean, median, mode) would be applied to solve a particular empirical problem.
3. The students will be able to recognize the various measures of dispersion and their applicability to solve different empirical problems.
4. The students will be able to distinguish between the concepts of correlation and regression and their application in various research settings.
5. The students will be able to navigate the software packages like Excel and SPSS for their own for empirical analysis.
6. The students will be able use statistical tools to conduct empirical research in the area education.

Brief description of the units:

Unit 1: Quantitative research methods

The course will begin with a brief discussion on the epistemological and ontological underpinnings of quantitative, qualitative and mixed methods, reasons as to why one should choose quantitative or qualitative approach and typical scenarios where the two approaches are combined, so as to give students a rounded understanding of research methods.

1. Comparative study of quantitative, qualitative and mixed methods approach
2. Sampling
3. Longitudinal, cross- sectional and trend studies
4. Experimental/ quasi- experimental methods
5. Designing a survey questionnaire

Unit 2: Introduction to statistics

This unit discusses descriptive statistics viz. types of variables, frequency distribution, and graphical representation of data, measures of central tendency and measures of dispersion. Students will be introduced to both Excel and SPSS in this unit and these sessions will continue throughout the course. The unit concludes with introducing students to data sets that are available in India for education research.

1. Basic descriptive statistics
2. Charts and graphs
3. Measures of central tendency
4. Measures of dispersion
5. Introduction to various education related data sets and handling data

Unit 3: Probability Distributions

This unit introduces normal probability distributions, which is the most important distribution in statistics and is the foundational base for inferential statistics, z- score problems, sampling distributions and the central limit theorem.

1. Probability distribution for discrete and continuous variables
2. The normal probability distribution
3. Sampling distribution
4. Sampling distribution of sample means

Unit 4: Statistical inference and ANOVA

This unit discusses how to use sample data to estimate population parameters. The topics of discussion are point versus interval estimate and significance tests for means and proportions and decisions and types of errors that typically arise in hypotheses tests.

1. Point estimate
2. Confidence intervals
3. Elements of a significance test
4. Significance test
5. Decisions and types of errors in hypotheses tests
6. Small sample inference for a mean- the t- distribution
7. Chi- squared test of inference for categorical variables
8. ANOVA

Unit 5: Correlation and Regression

Bivariate linear regression model will be discussed in this unit. The discussion will be quite detailed since understanding of bivariate regression is essential to further understand multivariate regression and advanced statistical techniques. We will initiate the discussion with the use of straight line to describe a particular form of relationship between two continuous variables and scatter plots to check if the relationship is approximately linear, followed by the use of least squares method to estimate the best line to describe a relationship, variability of data about the straight line, Pearson’s correlation to measure the strength of linear association between two variables. Finally this unit will introduce the basic concepts of regression analysis.

1. Correlation and covariance
2. Pearson’s and Spearman’s correlation coefficient
3. Linear relationships
4. Least squares prediction equation and method of least squares
5. SPSS for empirical analysis

 Assessment Plan

Readings:

Unit 1

• Creswell, J. W. (2003). Research Design: Qualitative, Quantitative and Mixed Methods Approaches. Second Edition.University of Nebraska (Chapter 1, pp.3- 26).
• Kumar, R. (2015). Research Methodology.Fourth Edition. Sage India (Chapter 12, pp. 231-248)
• Cohen, L., L. Manion and K. Morrison.(2000). Fifth Edition.Research Methods in Education.Routledge Falmer (Chapter 12, pp. 211- 225)
• ASER Centre. (2014). Middle Schools in India: Access and Quality | MacArthur Foundation Grant No. 11-99655-00-INP. (A.2: Baseline survey questionnaires)
• Converse, J. and S. Presser. (1986). Survey Questions: Handcrafting the Standardized Questionnaire, Issue 63.
• National Sample Survey (2014): Social Consumption: Education, Schedule 25.2

Unit 2

• Healey, J. Ninth Edition. Statistics- A Tool for Social Research, WadsworthCengage Learning, Student Copy ISBN-978-1-111-18636-4.(Chapter 2, pp. 22- 62; Chapter 3, pp. 63- 87; Chapter 4, pp. 88- 117).

Unit 3

• Healey, J. Ninth Edition. Statistics- A Tool for Social Research, WadsworthCengage Learning, Student Copy ISBN-978-1-111-18636-4.(Chapter 5, pp. 118- 140).

Unit 4

• Healey, J. Ninth Edition. Statistics- A Tool for Social Research, WadsworthCengage Learning, Student Copy ISBN-978-1-111-18636-4.(Chapter 7 to Chapter 11, pp. 157- 306).

Unit 5

• Healey, J. Ninth Edition. Statistics- A Tool for Social Research, WadsworthCengage Learning, Student Copy ISBN-978-1-111-18636-4. (Chapter 14 to Chapter 16, pp. 368-465)
• Gujarati, D. N. (2003).Basic Econometrics, Fourth edition.McGraw-Hill. New York.(Chapter 9, pp. 297-311)
• Das, N.G. (1997). Statistical Methods, Part I, M. das and Co. (Chapter 9, pp. 309-363)
• [Unit 4 and Unit 5 will focus not so much on formulae (though they will be discussed in class); instead emphasis will be placed on learning the significance of the statistic, its interpretation and appropriate use.]

Additional Readings:

• King, B. M., Rosopa, P. J., &Minium, E. W. (2010).Statistical reasoning in the behavioral sciences.Wiley Global Education.
• King, G. R. O. Keohane& S. Verba (1994) Designing Social Inquiry.Princeton University Press.(Chapter 1, pp. 3- 32).
• Muralidharan, K. and V. Sundaram (2013).The aggregate effect of school choice:Evidence from a two-stage experiment in India. NBER Working paper 19441. Available online at http://www.nber.org/papers/w19441
• Office of Quality Improvement. (2010). Survey fundamentals: A guide to designing and implementing surveys. Pew Research Centre.Questionnaire Design. Available online at
• http://www.pewresearch.org/methodology/u-s-survey-research/questionnaire- design/#measuring-change-over-time
• Tashakkori, A. and T. Charles (1998).Mixed Methodology: Combining Qualitative and Quantitative Approaches. Sage Publications. (Part three: applications, examples and future direction of mixed model research)