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Primary and Secondary data collection techniques Statistics: Meaning, Importance, Limitations, Classifications and Tabulation of data, discrete and continuous variables. Frequency Distributions and Cumulative frequency distribution, Diagrammatic and Graphical presentation of data Measure of Central Tendency: Mean, Median and Mode Measure of Dispersion Range, Quartile Deviation, Mean Deviation and standard deviation, coefficient of variation. Correlation and Regression analysis |
Scaling Techniques: Purpose of Scaling Techniques, Types of scales: Nominal, Ordinal, Interval and Ratio Scales. Parametric tests: Sampling Distribution and Standard Error. Element of Testing a Statistical Hypothesis- Formulation of the problem, Types of errors. Level of significance, large sample test for proportions, single mean and difference in two means. Small sample test- Application of Student’s t- test for small sample for single mean, difference in two means (independent and paired-t). ANOVA Non-parametric analysis: Chi-square test for population variance, Krukal Wallis H Test, Mann Whitney U – test. |
SAS, AMOS, SPSS, etc. Basics of SPSS Reading Data, Using Data Editor, Examining summary statistics for individual variables, creating and editing charts, working with output, sorting and selecting data. Presentation and Report writing:
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