H0

Definition

H0, or the null hypothesis, is a statistical hypothesis that represents the default or status quo position that there is no significant difference or relationship between the variables being studied. It is the hypothesis that is assumed to be true until the evidence strongly suggests otherwise.

5 Must Know Facts For Your Next Test

1. The null hypothesis (H0) is the starting point for statistical hypothesis testing, and it is assumed to be true unless the evidence strongly suggests otherwise.
2. The goal of hypothesis testing is to determine whether the null hypothesis (H0) should be rejected in favor of the alternative hypothesis (H1).
3. The significance level, denoted as α, is the maximum probability of rejecting the null hypothesis (H0) when it is actually true (a Type I error).
4. If the p-value is less than the significance level (α), the null hypothesis (H0) is rejected, and the alternative hypothesis (H1) is supported.
5. The null hypothesis (H0) is often formulated as a statement of no difference or no relationship between the variables being studied.

Review Questions

• Explain the purpose of the null hypothesis (H0) in the context of hypothesis testing.
  • The null hypothesis (H0) represents the default or status quo position that there is no significant difference or relationship between the variables being studied. It serves as the starting point for hypothesis testing, and the goal is to determine whether the evidence is strong enough to reject the null hypothesis in favor of the alternative hypothesis (H1). The null hypothesis is assumed to be true until the statistical analysis provides sufficient evidence to the contrary.
• Describe the relationship between the null hypothesis (H0) and the alternative hypothesis (H1) in the context of hypothesis testing.
  • The null hypothesis (H0) and the alternative hypothesis (H1) are complementary in hypothesis testing. The null hypothesis represents the claim that there is no significant difference or relationship between the variables, while the alternative hypothesis represents the research hypothesis that there is a significant difference or relationship. The goal of the statistical analysis is to determine whether the evidence is strong enough to reject the null hypothesis (H0) in favor of the alternative hypothesis (H1).
• Analyze the role of the p-value in the decision to reject or fail to reject the null hypothesis (H0).
  • The p-value is a critical component in the decision to reject or fail to reject the null hypothesis (H0). The p-value represents the probability of obtaining the observed results or more extreme results if the null hypothesis is true. If the p-value is less than the predetermined significance level (α), the null hypothesis (H0) is rejected, and the alternative hypothesis (H1) is supported. Conversely, if the p-value is greater than or equal to the significance level, the null hypothesis (H0) is not rejected, and there is not enough evidence to conclude that the alternative hypothesis (H1) is true.

Related terms

Alternative Hypothesis: The alternative hypothesis, denoted as H1 or Ha, represents the research hypothesis that there is a significant difference or relationship between the variables being studied.

Statistical Significance: Statistical significance refers to the likelihood that the observed difference or relationship between variables occurred by chance. If the results are statistically significant, it means the null hypothesis (H0) is likely false.

p-value: The p-value is the probability of obtaining the observed results or more extreme results if the null hypothesis (H0) is true. It is used to determine the statistical significance of the findings.