Statistics Study Materials

Measures of central tendency (mean, median, mode), measures of dispersion (variance, SD, range).

Sample space, events, classical and frequency probability, conditional probability, Bayes' theorem.

Discrete distributions (binomial, Poisson, geometric) and continuous distributions (normal, exponential).

Population, sample, sampling methods, sampling distribution, Central Limit Theorem, and standard error.

Point estimation, interval estimation, confidence intervals, and properties of estimators.

Null/alternative hypothesis, p-value, t-test, z-test, chi-square test, and ANOVA.

Pearson correlation, rank correlation, simple linear regression, and multiple regression.

Trend, seasonal, cyclical, irregular components; moving averages and forecasting.

Price indices (Laspeyres, Paasche, Fisher), CPI, WPI, and uses of index numbers.

Wilcoxon, Mann-Whitney, Kruskal-Wallis, sign test, and run test.

Completely randomised design, randomised block design, factorial design, and ANOVA types.

Using R (ggplot2, tidyverse) and Python (scipy, statsmodels) for statistical analysis.