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Descriptive Statistics : variables,measurement and scales,measures of central tendency and variability,probability theory discrete probability distributions and functions, binomial distribution, continuous probability distributions and functions unit normal distribution
Hypothesis Testing and Inferential Statistics : Z-test; t-test; normal approximation non-parametric statistics chi-square distribution Correlation and Regression: point-biserial biserial tetrachoric rank-biserial regression analysis and equation part and partial correlation multiple regression and correlation 4. Analysis of Variance Techniques : one-way between-subjects ANOVA; factorial between subjects ANOVA mixed between-withinsubjects ANOVA design complexity specific comparisons 5. Analysis of Covariance Techniques 6. Multivariate Analysis of Variance and Covariance Techniques Basic Probability Concepts
Sample space and events, probability axioms, elementary rules of probability, conditional probability, Bayes' Theorem. 8. Random Variables and Probability Distributions Random variables, discrete and continuous, probability distributions, distribution function probability density function mean and variance of a probabilty distribution special discrete distributions binomial, geometric,
negative binomial, Poisson, multinomial; 5. Random Samples and Sampling Distributions Random sampling, estimators sampling distributions Linear Regression and Correlation least squares estimation adequacy of the model correlation regression multiple linear regression
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