Statistical Hypothesis Testing: Errors, Power, and Inference
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Statistical Hypothesis Testing
1. Statistical Hypothesis
A statistical hypothesis is an assertion about a characteristic or parameter of a population. It's used to perform analysis and can be either rejected or accepted based on the provided information. There are two types of hypotheses:
- Null Hypothesis (H0): Represents the status quo or the default assumption.
- Alternative Hypothesis (H1): Represents the claim or the hypothesis we want to test.
Both H0 and H1 can be simple (if the parameter has only one value) or compound (if the parameter can take multiple values).
2. Significance Level (α)
The significance level is the probability of making a Type I error (rejecting H0 when it's actually true). It represents the level of risk we're willing to... Continue reading "Statistical Hypothesis Testing: Errors, Power, and Inference" »