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About this document
- Pages
- 41 pages
- Price
- $41 one-time, yours to keep
- Membership
- Included in every plan
- Format
- Subject
- Statistics
- Module
- Chapter 10
This document contains multiple choice questions on hypothesis testing. It covers key concepts such as null and alternative hypotheses, types of errors, significance levels, and various statistical tests. It is useful for students studying Chapter 10.
What's inside
- Null and alternative hypotheses
- Types of errors in hypothesis testing
- Significance levels and p-values
- Statistical tests: chi-square, ANOVA, t-test
- One-tailed and two-tailed tests
Who it is for: Students studying hypothesis testing in statistics. (Undergraduate)
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Summary
Hypothesis testing is a method used to make decisions about population parameters. Students get practice with multiple-choice questions on hypothesis testing concepts.
Basic hypothesis testing concepts
The null and alternative hypotheses are explained. One-tailed and two-tailed tests are described. The significance level is defined.
Types of errors in hypothesis testing
Type I and Type II errors are explained. The seriousness of each type of error is discussed.
Hypothesis testing in practice
The chi-square goodness-of-fit test is described. The effect of sample size on p-values is explained.
ANOVA and observational studies
The assumptions of the ANOVA test are listed. Observational studies are defined.
Key terms
- Null hypothesis
- A statement that there is no effect or no difference.
- Alternative hypothesis
- A statement that there is an effect or a difference.
- Type I error
- Rejecting a true null hypothesis.
- Type II error
- Failing to reject a false null hypothesis.
- Chi-square goodness-of-fit test
- A test used to determine if a sample matches an expected distribution.
- Observational study
- A study where groups are observed without controlling for other factors.
Questions this document helps with
- What are the null and alternative hypotheses?
- How do sample size and p-values relate?
- What is the difference between a Type I and Type II error?
Summary written with AI from the document's text.
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