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Statistical Methods and Psychological Research
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Learning Outcomes |
Learning and teaching strategies |
Assessment Strategies |
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On completion of this course, the students will be able to: CO16: Calculate the statistics necessary to solve problems including descriptive statistics tests. CO17: Explain the basic properties of normal probability curves. Explain the logic and appropriate applications of statistical analyses for univariate or bivariate research designs, problems, or hypotheses. CO18: Understand the basic principles and need of psychological measurement. CO19: Acquiring knowledge about various parameters of assessment technique. CO20: Develop an understanding of functions of tests as well as test construction and standardization. CO21: Acquiring knowledge to effectively understand the psychometric strengths and weaknesses of tests. |
Approach in teaching: Interactive Lectures, Discussion, Tutorials, Reading assignments, Demonstration, 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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Scales of measurement, graphical representation of data- Histogram, Bar graph, Frequency polygon. Introduction to Parametric and Non-Parametric test;
Data Analysis: Measures of central tendency: Mean, median, mode (properties and computation). Measure of Dispersion: Range, Quartile Deviation, Standard deviation (properties and computation)
Normal Probability Curve:Characteristics
Correlation: Pearson Method and Rank order correlation (Properties and Computation)
Nature, scope and history of Psychological Testing, Reliability, Validity, Norms
Types of tests, Steps in test construction, item analysis (speed test and power test).
Qualitative Methods: Interview, questionnaire, Survey, Observation, Experimental, Ex post facto
Quantitative Methods: Rating Scale, Q-sort, Sociometry, Sematic Differential Scale.
· Minium, E.W., King, B.M., & Bear G. (1993). Statistical Reasoning in Psychology and Education. New York: John Wiley Publication.
· Garrett, H. E. (2004). Statistics in Psychology and Education. New Delhi : Paragon International Publishers.
· Mangal, S.K. (2002). Statistics in Psychology and Education(2nd Edition). Delhi : McGraw Hill Publication.
● Broota, K.D. (1992). Experimental Design in Behavioral Research. New Delhi : Wiley Eastern Publication.
● Siegel, S. (1994). Non-Parametric Statistics. New York : McGraw Hill Publication.
● Guilford, J.P. Fundamental Statistics in Psychology and Education. New York : McGraw Hill Publication.
● Sen, A.K. (1976). Sandlers ‘A’ Test. A Simple Statistics for correlated samples. Journal of Psychological Researches. 20, 16-20.
● Welkowitz, J., Ewen, R.B., and Cohen, J. (1982). Introduction to Statistics for Behavioral Sciences. New York : Academic Press.
● Winer, B.J. (1971). Statistical Principles in Experimental Design. New York : McGraw Hill Publication.
● Fergusen, G.A. (1971). Statistical Analysis in Psychology and Education. 3rdEdition. New Delhi : McGraw Hill Publication.
E Resources :
● World Digital Library.
● World E- Book Library.
● California Digital Library.
● ResearchGate
● JSTOR
● Proquest
● Shodhganga
● Delnet
● Google Scholar
● National Digital Library (NPTEL)
● Academia
● Planet EReadings.
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Journals:
● Journal of Official Statistics. Access from https://sciendo.com/journal/jos
● REVSTAT. Access from https://en.wikipedia.org/wiki/REVSTAT
● Statistics Surveys. Access from https://imstat.org/journals-and-publications/statistics-surveys/
