Lecture 1 - Introduction to the course

Lecture 2 - Data representation and plotting

Lecture 3 - Arithmetic mean

Lecture 4 - Geometric mean

Lecture 5 - Measure of Variability, Standard deviation

Lecture 6 - SME, Z-Score, Box plot

Lecture 7 - Moments, Skewness

Lecture 8 - Kurtosis, R programming

Lecture 9 - R programming

Lecture 10 - Correlation

Lecture 11 - Correlation and Regression - Part-I

Lecture 12 - Correlation and Regression - Part-II

Lecture 13 - Interpolation and extrapolation

Lecture 14 - Nonlinear data fitting

Lecture 15 - Concept of Probability: introduction and basics

Lecture 16 - Counting principle, Permutations, and Combinations

Lecture 17 - Conditional probability

Lecture 18 - Conditional probability and Random variables

Lecture 19 - Random variables, Probability mass function, and Probability density function

Lecture 20 - Expectation, Variance and Covariance - Part-I

Lecture 21 - Expectation, Variance and Covariance - Part-II

Lecture 22 - Binomial random variables and Moment generating function

Lecture 23 - Probability distribution: Poisson distribution and Uniform distribution Part-I

Lecture 24 - Uniform distribution Part-II and Normal distribution Part-I

Lecture 25 - Normal distribution Part-II and Exponential distribution

Lecture 26 - Sampling distributions and Central limit theorem - Part-I

Lecture 27 - Sampling distributions and Central limit theorem - Part-II

Lecture 28 - Central limit theorem - Part-III and Sampling distributions of sample mean

Lecture 29 - Central limit theorem - Part-IV and Confidence intervals

Lecture 30 - Confidence intervals Part- II

Lecture 31 - Test of Hypothesis - 1

Lecture 32 - Test of Hypothesis - 2 (1 tailed and 2 tailed Test of Hypothesis, p-value)

Lecture 33 - Test of Hypothesis - 3 (1 tailed and 2 tailed Test of Hypothesis, p-value)

Lecture 34 - Test of Hypothesis - 4 (Type -1 and Type -2 error)

Lecture 35 - T-test

Lecture 36 - 1 tailed and 2 tailed T-distribution, Chi-square test

Lecture 37 - ANOVA - 1

Lecture 38 - ANOVA - 2

Lecture 39 - ANOVA - 3

Lecture 40 - ANOVA for linear regression, Block Design