Hypothesis test

Definition

A hypothesis test is a statistical method used to make inferences or draw conclusions about a population based on sample data. It involves comparing observed data with what we expect under the null hypothesis.

5 Must Know Facts For Your Next Test

1. The null hypothesis ($H_0$) states that there is no effect or difference, and it serves as the default assumption.
2. The alternative hypothesis ($H_a$) represents what you aim to support, indicating an effect or difference.
3. A p-value measures the strength of evidence against the null hypothesis; a lower p-value indicates stronger evidence.
4. Common significance levels ($\alpha$) are 0.05, 0.01, and 0.10, determining the threshold for rejecting the null hypothesis.
5. Types of errors include Type I error (rejecting $H_0$ when it is true) and Type II error (failing to reject $H_0$ when it is false).

Review Questions

• What does the p-value indicate in a hypothesis test?
• Explain the difference between Type I and Type II errors.
• How do you determine whether to reject or fail to reject the null hypothesis?

Related terms

Null Hypothesis: $H_0$: A statement that there is no effect or difference, serving as the starting assumption in a hypothesis test.

Alternative Hypothesis:

$H_a$: A statement that indicates an effect or difference, which you aim to support through your hypothesis test.

P-Value: A probability measure that helps determine the strength of evidence against the null hypothesis; lower values suggest stronger evidence.