Course Contents

1 Application of Normal Probability Distribution. To determine the percentage of cases in a normal distribution within given limits. 2 To find the limits in any normal distribution which include a given percentage of cases (Practice). 3 Introduction to sampling theory, sampling with replacement 4 Sampling without replacement. Sampling distribution of sample mean. (Practice). 5 Sampling distribution of the difference between two sample means (X1-X2) with & without replacement 6 Estimation: Estimate and Estimator, Point and interval estimation. 7 Confidence Interval for Population mean µ, for case I, II and III 8 Confidence Interval for the difference between the means of two population (µ1- µ2) for case I, II and III quiz and Assignment. 9 Formulation of null and alternative hypothesis, one tail and two tail test, type I and Type II errors, level of significance and Rejection region. Testing the difference between means and within means. 10 Application of Z-test (practice) 11 Application of t-test (Practice) 12 Chi-square test and contingency table (Practice) 13 One-way ANOVA (F-test) 14 Practice of Data Analysis 15 Non-Parametric Tests: Introduction to non-parametric tests, wilcoxan test, Mann whitney test 16 Sign test and kruskal wallis test (Practice) 17 Data Analysis

Course Synopsis

This course is designed to acquaint the students with several of the major quantitative techniques used in psychology and social sciences. It treats quantification as an integral part of social science research, and examines the application of standard statististical methods. The primary goal of this course is to develop critical thinking skills necessary for students to evaluate primary empirical research.

Course Learning Outcomes

1. Understanding about inferential statistics will be developed. 2. Understanding of SPSS for data analysis 3. Critical thinking will be developed to evaluate primary and empirical research.