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About Hypothesis Testing Lecture
Hypothesis testing involves formulating a null hypothesis (H0) and an alternative hypothesis (Ha). There are two types of errors that can occur: 1) Type I error is rejecting the null hypothesis when it is true. 2) Type II error is failing to reject the null hypothesis when it is false. The test statistic is used to assess how compatible the data are with the null hypothesis. If the p-value is less than the significance level α, then the null hypothesis is rejected in favor of the alternative hypothesis. Choosing a smaller α increases the likelihood of a type I error but decreases the likelihood of a type II error. Power is the probability of rejecting a false null hypothesis. Sample size
Detailed Information
| Author: | ['yogibh'] |
|---|---|
| Publication Year: | 2014 |
| Pages: | 28 |
| Language: | English |
| Format: | |
| Price: | FREE |
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