Psychological Statistics - II

Paper Code: 
PSY 401
Credits: 
3
Contact Hours: 
45.00
Max. Marks: 
100.00
Objective: 

1. To develop an understanding of various statistical techniques in terms of their assumptions, applications and limitations.

2. To acquire elementary knowledge about computer use in Psychology for Statistical analysis.

 

9.00
Unit I: 
Hypothesis testing and making inferences

Sampling , Standard Error : Mean (Small and Large Samples), df

9.00
Unit II: 
Significance of Difference between Means

 Null Hypothesis, computation of ‘t’ values for independent samples; interpretation of ‘t’ values; levels of significance; Type I and Type II errors in inference making.

9.00
Unit III: 
Non Parametric Test

Nature and assumption; Distribution free Statistics - Chi Square (Equal Probability, 2×2 Contingency tables); Rank order correlation

9.00
Unit IV: 
Higher Statistical Analysis

 

Purpose and assumption of ANOVA;  One Way Analysis of Variance (Independent Samples)

9.00
Unit V: 
Familiarization with software and application of computers in Psychology
Essential Readings: 

Ø Garrett, H.E. Statistics in Psychology and Education Vakils, Feffer & Simons Ltd.

Ø Mangal, S.K. Statistics in Psychology and Education McGraw Hill Publication.

Ø Minimum, E.W. King, B.M. & Bear, G (1993). Statistical Reasoning in Psychology and Education, New York, John Wiley.

Ø Siegel, S. (1994). Non Parametric Statistics. New York : McGraw Hill.

 

References: 

Ø Broota, K.D. (1992) : Experimental Design in Behavioral Research.

Ø Fergusen, G.A. (1971). Statistical Analysis in Psychology and Education. 3rd Edition, New Delhi, McGraw Hill.

Ø Guilford, J.P. : Fundamental Statistics in Psychology and Education, New York, McGraw Hill (Asian Student Edition).

Ø Sen, A.K. (1976). Sandlers ‘A’ Test. A Simple Statistics for correlated samples, Journal of Psychological Researches, 20, pp 16 to 20.

Ø Welkowitz, J. Ewen, R.B. and Cohen, J. (1982). Introduction to Statistics for Behavioral Sciences. Academic Press, N.Y.

Ø Winer, B.J. (1971). Statistical Principles in Experimental Designs. McGraw Hill, New York.

 

Academic Year: 
2017-18
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