Unit Five - Discussion

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Feb 20, 2024

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ANOVA is different from t-test because it compares three or more groups instead of the two groups the t-test can compare. (Kenton, 2023) One would use ANOVA instead of running many sets of t-tests due to the many advantages. Advantages are both from practical and statistical stand points. Such as efficiency because ANOVA requires less statistical tests compared to the t-test. This allows for time and resources to be saved, when multiple groups are to be dealt with. However, there are times were running multiple t-tests are preferred, such as specific hypothesis testing. This occurs when there are research questions that involve specific testing of exact differences between groups, instead of the overall differences in those groups. So, deciding which one to use really depends on the questions that are being asked and other factors such as sample size. References Anaesth, A. C. (2019). Application of Student's t-test, Analysis of Variance, and Covariance. National Library of Medicine , 407-4011. Difference Between T-test and ANOVA . (n.d.). Retrieved from www.keydifferences.com: https://keydifferences.com/difference-between-t-test-and-anova.html Kenton, W. (2023, June 12th). Analysis of Variance (ANOVA) Explanation, Formula, and Applications . Retrieved from www.Investopedia.com: https://www.investopedia.com/terms/a/anova.asp Lind, M. D. (2020). Statistical Techniques in Business Economics. New York: The McGraw-Hill.
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