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Quantitative Data Analysis
To develop an understanding of various statistical techniques in terms of their assumptions, applications and limitations
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Course |
Course Outcomes |
Learning and teaching strategies |
Assessment Strategies |
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Course Code |
Course Title |
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24CPSY611 |
Quantitative Data Analysis (Theory) |
CO121: Understanding the nature of measurement and its various levels. CO122: Developing skills to use quantitative techniques such as measures of central tendency, variability, and correlation. CO123: Knowing how to use the normal probability curve as a model in scientific theory CO124: Grasping concepts related to hypothesis testing and developing related computational skills CO125: Learning basic techniques of descriptive and inferential statistics. CO126: Contribute effectively in course-specific interaction |
Approach in teaching: Interactive Lectures, Discussion, Reading assignments, Team teaching Learning activities for the students: Self-learning assignments, Effective questions, Simulation, Seminar presentation, Giving tasks, Field practical |
Class test, Semester end examinations, Quiz, Solving problems in tutorials, Assignments, Presentation, Individual and group projects
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Introduction to Statistics; Descriptive and Inferential Statistics;
Measures of central tendency and variability:Characteristics and computation of mean, median and mode; Characteristics and computation of standard deviation & variance
Null and the Alternative Hypotheses; One-Tailed and Two-Tailed Tests; Concept of confidence interval and df; Computation and Interpretation of t values
Purpose and Assumptions; one-way and two-way Analysis of Variance
Correlation: Meaning, types and computation; Regression and Prediction: Regression equations, linear regression
Introduction and assumptions; Comparison with Parametric Tests; Mann Whitney U Test, Chi-square test.
1. Garrett, H.E. (2005). Statistics in Psychology and Education. New Delhi: Paragon International Publishers.
2. Mangal, S.K. (2002). Statistics in Psychology and Education. New Delhi: Prentice Hall India.
3. Minium, E.W., King B.M. & Bear, G. (1995). Statistical Reasoning in Psychology and Education. New York: John Wiley & Sons.
4. Seigel S. (1988). Nonparametric Statistics in Behavioural Sciences. New York: McGraw Hill.
Suggested Readings:
1. Freund, R. J., & Wilson, W. J. (2003). Statistical methods. Elsevier.
2. Ott, R. L., & Longnecker, M. T. (2015). An introduction to statistical methods and data analysis. Cengage Learning.
3. Singh, A.K. (2017). Tests, Measurements and Research Methods in Behavioural Science. Patna : Bharti Bhavan.
4. Welkowitz, J., Ewen, R.B. &Chocen J. (1982). Introduction to Statistics for Behavioural Sciences. New York: Academic Press.
E Resources:
1. Quantitative research. A course offered on Coursera. Access via: https://www.coursera.org/learn/quantitative-research
Psychological research specialization. A course offered on Coursera. Access via https://www.coursera.org/specializations/psychological-research
