Correlation Analysis: Karl Pearson, Spearman Rank Correlation Complete Guide

These notes cover detailed exploration of correlation analysis including positive/negative, simple/multiple/partial, and linear/non-linear correlations. Covers scatter diagram interpretation, Karl Pearson’s coefficient calculation methods, and Spearman’s rank correlation techniques. Includes probable error analysis, correlation significance testing, and practical business applications with comprehensive mathematical illustrations and real-world examples.

Regression Analysis: Simple Linear Regression, Least-squares Method Complete Guide

Comprehensive guide to regression analysis covering simple linear regression models using least-squares criterion. Explains dependent and independent variables, regression coefficients, slope interpretation, and point estimates. Covers both regression equations (Y on X, X on Y), their properties, intersection points, and coefficient relationships with detailed mathematical illustrations and business applications.

Statistical Inference: Hypothesis Testing, ANOVA, and Confidence Intervals Guide

Comprehensive study of statistical inference covering point and interval estimation methods with confidence intervals. Detailed hypothesis testing procedures including null and alternative hypotheses, Type I and II errors, significance levels. Explores various statistical tests: z-test, t-test, F-test, chi-square, paired t-test, and one-way/two-way ANOVA applications.

Statistical Distributions: Binomial, Normal, Chi-square – Complete Guide

This covers detailed exploration of statistical distributions covering discrete distributions including binomial, hypergeometric, and Poisson with practical applications. Examines continuous distributions focusing on normal distribution, standard normal tables, and z-score calculations. Introduces sampling distributions including chi-square, t-test, and F-test for statistical inference and hypothesis testing.

Probability Concepts: Complete Guide to Classical, Subjective and Bayes Theorem

Comprehensive coverage of probability concepts including classical, relative frequency, and subjective approaches. Explores probability rules for mutually exclusive and non-mutually exclusive events, addition and multiplication rules. Introduces Bayes theorem for sequential events, fundamental counting principles, permutations, combinations, and practical applications with detailed illustrations.