Course Contents

1. 1. Recap of Basics of Statistics 1.2. Introduction of statistics 1.3. Presentation of Data 1.4. Measures of Central Tendency 1.5. Measures of Dispersion 1.6. Execution on SPSS 2. Kurtosis and Skewness 2.1 Tailedness & Peaks 2.2 Meso, Platy & Leptokurtic distributions 2.3 Positive & Negative Skew 2.4 Tests of Normality & Homgeniety 3. Hypothesis testing 3.2. Inferential statistics 3.3. Hypothesis formulation (Null and Alternative Hypotheses) 3.4. Level of significance acceptance and rejection regions 3.5. One tailed & two tailed hypotheses tests 3.6. Type – I & type II errors 2. t Distribution 2.1. Testing the hypotheses 2.2. Single Sample t test 2.3. Two Independent Sample t test 2.4. Related sample t test 2.5. Execution of all three types on SPSS 3. F Distribution 3.1. One way ANOVA 3.2 Two way ANOVA 3.4 Post hoc Tests 3.4 MANOVA 3.5 Execution of one way & Two way ANOVA on SPSS 4. Correlation 4.1. Correlation and Hypothesis testing 4.2. Pearson 4.3. Spearman 4.4. Point Bi-Serial Correlation 4.5. Phi Co-efficient 4.6. Execution on SPSS 5. Linear Regression Analysis 5.1. Introduction 5.2. Scatter Diagram 5.3. Simple Linear Regression Model 5.4. Execution on SPSS 6. Non-parametric Statistics 6.1. Chi – Square Distribution 6.2. Mann-Whitney U test 6.3. Wilcoxon Signed-Ranks test 6.4. Kruskal-Wallis test 7. Reliability Analysis

Course Synopsis

The course will provide an understanding of basic statistical and mathematical tools and techniques used to analyze socio-economic data. Development studies deals with both qualitative and quantitative information. This information can only be understood if properly analyzed and quantified. For this purpose the students must have sufficient and sound background of basic analytical tools and techniques. This course covers basic statistical methods, correlation, standard deviation and coefficient of variation, differentiation, linear regression analysis, and functional analysis. Introducing basic concepts of statistics and SPSS, and using it for the purpose of research and data analysis is one of the main objectives of this course.

Course Learning Outcomes

• Hand in experience to compute statistical tests on SPSS • Read and interpret SPSS output • Students will be able to link research and statistics.