STA301 Final Term Important Lectures and Topics by Masters

LECTURE 20, 21, LECTURE 22, LECTURE 23, LECTURE 24

•  Independent and Dependent Events Multiplication Theorem of Probability for Independent Events

 Discrete Random Variable

Discrete Probability Distribution

•  Mean, Standard Deviation and Coefficient of Variation of a Discrete Probability Distribution Distribution Function of a Discrete Random Variable
•  Mathematical Expectation (lecture 23 ) Mean, Variance and Moments of a Discrete Probability Distribution

Properties of Expected Values

•  Concept of Continuous Probability Distribution Mathematical Expectation, Variance & Moments of a Continuous Probability Distribution

Mathematical Expectation, Variance & Moments of a Continuous Probability Distribution BIVARIATE Probability Distribution (LECTURE 25) BIVARIATE Probability Distributions (Discrete and Continuous) (LECTURE 26) Covariance & Correlation (LECTURE 27) Discrete Uniform Distribution LECTURE 27

Binomial Distribution (LECTURE 28)

Hyper geometric Distribution (LECTURE 29)

Normal Distribution PAGE 221 TO 224 THE PROCESS OF STANDARDIZATION PAGE 226

LECTURE NO. 30, 31, 32 imp

Sampling Distribution of all cases

Point Estimation Desirable Qualities of a Good Point Estimator

Methods of Point Estimation Interval Estimation

LECTURE NO. 35 imp

Confidence Interval for  Confidence Interval for 1-2 Large Sample Confidence Intervals for p and p1-p2 Determination of Sample Size (with reference to Interval Estimation) Hypothesis-Testing (An Introduction)

Lecture 37 to 39 most important

Hypothesis-Testing all concepts

Lecture 40 to 45

•  T-distribution
•  F-distribution
•  Chi-Square Test of Independence
•  Randomized Complete Block Design
•  The Least Significant Difference (LSD) Test
•  Chi-Square Test of Goodness of Fit