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Chi-Square Test for Goodness Fit - I

Testing for Independence in rxc Contingency Table - II

Applications of N-P-Lemma - I

Testing Equality of Proportions

Testing for Independence in rxc Contingency Table - I

Neyman- Pearson Fundamental Lemma

Examples

Two Types of Errors

Paired t-Test

Testing for Normal Variance

Large Sample Test for Variance and Two Sample Problem

Testing for Normal Mean

Chi-Square Test for Goodness Fit - II

Examples on MLE - I

Examples on MME, MLE

LSE, MME

Introduction to Estimation

Descriptive Statistics - IV

Descriptive Statistics - III

Descriptive Statistics - II

Descriptive Statistics - I

F-Distribution

Chi - Square Distribution (Contd.)., t-Distribution

Chi - Square Distribution

Transformation of Random Variables

Additive Properties of Distributions - II

Additive Properties of Distributions - I

Bivariate Normal Distribution - II

Bivariate Normal Distribution - I

Linearity property of Correlation and Examples

Independence , product moments

Joint Distributions - II

Joint Distributions - I

Function of a random variable - II

Function of a random variable - I

Problems on special distributions - II

Problems on special distributions - I

Problems on normal distribution

Special continuous distributions - IV

Special continuous distributions - III

Special continuous distributions - V

Normal distribution

Special continuous distributions - II

Description:

Explore the fundamentals of probability and statistics through a comprehensive 21-hour course covering a wide range of topics. Delve into descriptive statistics, special continuous distributions, joint distributions, bivariate normal distribution, and transformation of random variables. Learn about chi-square, t, and F distributions, as well as estimation techniques like LSE, MME, and MLE. Master hypothesis testing concepts, including Neyman-Pearson Lemma, paired t-tests, and chi-square tests for goodness of fit and independence. Gain practical skills in analyzing contingency tables, testing for equality of proportions, and handling large sample tests for variance and mean. Apply these concepts through numerous examples and problem-solving exercises throughout the course.

NOC- Probability and Statistics

NIOS

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#Mathematics #Statistics & Probability #Data Science #Data Analysis #Probability #Hypothesis Testing #Descriptive Statistics #Estimation #t-tests

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