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Questions and Answers
What is the main difference between a population and a sample in hypothesis testing?
What is the main difference between a population and a sample in hypothesis testing?
A population includes all members of a defined group, while a sample is a subset of the population used to represent it.
List the steps involved in hypothesis testing.
List the steps involved in hypothesis testing.
The steps include formulating hypotheses, selecting a significance level, collecting data, performing the test, and making a decision.
What are the common types of tests used in hypothesis testing and when should each be used?
What are the common types of tests used in hypothesis testing and when should each be used?
Common types include the Z test for large samples and the T test for small samples or unknown population variance.
What is the purpose of the Chi-Square test for independence?
What is the purpose of the Chi-Square test for independence?
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How do you compute the Chi-Square statistic from a contingency table?
How do you compute the Chi-Square statistic from a contingency table?
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Study Notes
Chapter 3: Validating a Statement/Hypothesis Testing (Univariate Analysis)
- Introduction to Hypothesis Testing
- Definition and Types
- Key Concepts in Hypothesis Testing
- Population vs Sample
- Understanding the need for sampling
- Common Types of Hypothesis Tests
- Using z-tables and t-tables
- Z Test, T test and their critical value tables
- Steps in Hypothesis Testing
- Errors in Hypothesis Testing
- Practical Applications of Hypothesis Testing
Chapter 4: Chi-Square Test: Testing for Independence (Two Categorical Variables)
- Introduction to the Chi-Square Test
- Key Concepts in the Chi-Square Test for Independence
- Categorical Variables, Contingency Tables and Expected Frequencies
- Steps in Conducting a Chi-Square Test for Independence
- Formulating Hypotheses
- Collecting Data and Creating a Contingency Table
- Calculating Expected Frequencies
- Computing the Chi-Square Statistic
- Determining Degrees of Freedom (df)
- Comparing the Chi-Square Statistic to the Critical Value
- Making a Decision and Interpreting the Results
- Chi-Square vs T-Test or Z-Test
- Practical Applications of the Chi-Square Test for Independence
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Description
Explore the foundations of Hypothesis Testing in Chapter 3, focusing on univariate analysis, key concepts, and practical applications. Chapter 4 delves into the Chi-Square test, essential for analyzing independence between two categorical variables through contingency tables and expected frequencies.
