Hypothesis TestingThe hypothesis that there is an effect or a difference. It is what researchers hope to support. - A statistical method used to make decisions or inferences about population parameters based on sample data., Null Hypothesis (H₀) - The hypothesis that there is no effect or no difference. It is the hypothesis that researchers aim to test against., Alternative Hypothesis (H₁ or Ha) - The hypothesis that there is an effect or a difference. It is what researchers hope to support., Type I Error (α) - Type I error occurs when the null hypothesis is rejected when it is actually true. It is also known as a "false positive.", Type II error - A Type II error occurs when the null hypothesis is not rejected when it is actually false. It is also known as a "false negative.", Power of a test - The power of a test is the probability that it correctly rejects the null hypothesis when the alternative hypothesis is true. It is denoted as 1 - β., One-tailed test - A one-tailed test is a hypothesis test in which the alternative hypothesis specifies a direction of the effect or difference (e.g., greater than or less than a certain value)., Critical value - A critical value is the value that a test statistic must exceed for the null hypothesis to be rejected at a given significance level.,

Hypothesis Testing

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