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Hypothesis Testing

In this course, you will learn about hypothesis testing, used for validating dataset hypotheses, along with techniques to test a hypothesis.

Hypothesis testing
One-tailed and two-tailed tests of hypothesis
Type I and type II errors
Decision rule, power of test and confidence intervals
Using z-value and p-value
Tests concerning population mean
Tests concerning equality of population mean
Tests concerning the mean difference of populations
Tests concerning variance of population
Non-parametric tests

Lessons

01

What is Hypothesis Testing

02

Test Statistic, Type I and type II Errors, and Significance Level

03

Decision Rule in Hypothesis Testing

04

p-Value in Hypothesis Testing

05

Selecting the Appropriate Test Statistic

06

Hypothesis Testing with t-statistic

07

Hypothesis Testing with z-statistic

08

Tests Concerning Differences in Means

09

Paired Comparision Tests - Mean Differences When Populations are Not Independent

10

Hypothesis Tests Concerning Variances

11

Chi-square Test – Test for value of a single population variance

12

F-test - Test for the Differences Between Two Population Variances

13

Non-parametric Tests

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1

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