Hypotheses are statements made about a population parameter that can be tested using statistical methods. They include a null hypothesis (H0) and an alternative hypothesis (H1 or Ha).
5 Must Know Facts For Your Next Test
The null hypothesis (H0) typically states that there is no effect or no difference, and it serves as the default assumption.
The alternative hypothesis (H1 or Ha) suggests that there is an effect or a difference, opposing the null hypothesis.
Hypothesis testing involves determining whether to reject the null hypothesis based on sample data.
A p-value is used in hypothesis testing to measure the strength of the evidence against the null hypothesis.
Common significance levels (alpha) for testing hypotheses are 0.05, 0.01, and 0.10.
Review Questions
What is the primary purpose of formulating a null hypothesis in statistical testing?
How do you interpret a p-value in the context of hypothesis testing?
Why is it important to set a significance level before conducting a hypothesis test?
Related terms
Null Hypothesis: A statement asserting that there is no effect or no difference; it serves as the starting point for statistical testing.
Alternative Hypothesis: A statement suggesting that there is an effect or difference, opposing the null hypothesis.
p-value: \(\text{A measure used in statistical tests to determine the strength of the evidence against the null hypothesis.}\)