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This guide contains all of the ASC's statistics resources. If you do not see a topic, suggest it through the suggestion box on the Statistics home page.

- Home
- Excel - Tutorials
- ProbabilityToggle Dropdown
- VariablesToggle Dropdown
- Statistics BasicsToggle Dropdown
- Z-Scores and the Standard Normal DistributionToggle Dropdown
- Accessing SPSS
- SPSS-TutorialsToggle Dropdown
- Effect SizeToggle Dropdown
- G*PowerToggle Dropdown
- ANOVAToggle Dropdown
- Chi-Square TestsToggle Dropdown
- CorrelationToggle Dropdown
- Mediation and Moderation
- Regression AnalysisToggle Dropdown
- T-TestToggle Dropdown
- Predictive Analytics
- Quantitative Research Questions
- Hypothesis Testing
- Statistics Group Sessions

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One important part of hypothesis testing is understanding how to determine if there is enough evidence to support your claim. There are two possible outcomes of hypothesis testing:

*Reject the Null Hypothesis*- Determine that there is sufficient evidence to suggest that the alternative hypothesis is true.
- p < α
- test statistic > critical value

*Fail to Reject the Null Hypothesis*- Determine that there is not sufficient evidence to suggest the alternative hypothesis is true.
- p > α
- test statistic is < critical value

Note that when it comes to statistics, nothing is certain. Rejecting the null hypothesis does not “prove” your claim to be true, it simply provides evidence that suggests that it could be. Similarly, failing to reject the null does not “prove” that the null is true, the data simply just did not provide enough evidence to suggest the alternative is true.

- Last Updated: Nov 30, 2022 3:21 PM
- URL: https://library.ncu.edu/statsresources
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