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## Module - 1

Introduction to Statistics: Meaning and Definition, Importance, Types, Measures of Central Tendency -Arithmetic mean, Geometric mean, Harmonic mean, Median, Quartiles, Deciles, Percentiles, Mode. Measures of Dispersion -Range, Quartile deviation, Mean deviation, Standard deviation, Variance, Coefficient of Variation. (Theory and Problem).

## Module - 2

Correlation and Regression: Correlation – Significance, Types, and Methods, Scatter diagram, Karl Pearson correlation, Spearman’s Rank correlation, Regression, Significance, Linear Regression Analysis, Types of regression models, Lines of Regression. (Theory and Problem).

## Module - 3

Probability Distribution: Concept of probability, Counting rules for determining number of outcomes – Permutation and Combination, Rules of probability- Addition and Multiplication, Baye’s Theorem. Concept of Probability Distribution, Theoretical Probability Distributions – Binomial, Poisson, Normal (Problems only on Binomial, Poisson and Normal). (Theory and Problem).

## Module - 4

Time Series Analysis: Objectives, Variations in Time Series. Measurement of Trend, Graphic Method, Moving Average Method, Semi-Average Method, Least Square Method. Measurement of Seasonal Variations- Method of Simple Averages, Ratio to Trend Method-Ratio to Moving Average Method, Link Relative Method. (Theory and Problem)

## Module - 5

Hypotheses Testing: Definition, Types, Procedure for testing, Errors in hypotheses testing. Parametric and Non-Parametric Tests -t-test, z-test, f-test, Chi-square test, u-test, K-W Test (problems on all tests).Analysis of Variance (theory only).

## Module - 6

Computer lab for Statistics: SPSS: Overview of SPSS, Creating, saving and editing files, Importing files from other formats. Transforming Variables – Compute, Multiple responses. Organization and Presentation of Information – Measures of Central Tendency and Variability, Frequency Distributions. Charts and Graphs, Hypotheses testing using means and cross-tabulation, Paired t, Independent sample t, Chi- square. Correlation, Regression Analysis, Linear, Logistic, Analysis of Variance- One Way ANOVA, ANOVA in regression.