ANOVA is significant. Now what? Post hoc tests explained. #biostatistics #shorts

Main Video: https://youtu.be/LCneQMG2uEo Why are they needed? Suppose we are overcomplicating three treatment groups and use a significant result, so the finding tells us that a difference exists somewhere among the groups, but it does not answer the question, such as whether group A is different from B, B is different from C, or A is different from C. So post how P provides these answers exactly what is different. Kahana. So common postdoc tests are these to key the honestly significant difference test. It is most commonly used when group sizes are equal or nearly equal, like mine, which were nearly equal. So compares or possible pairs of group meets control the overall type one error rate effectively and is easy to interpret and widely available in its statistical software, so it is quite widely used. Then another one is the Bonferroni Collection. A more conservative method just the significance level according to the number of comparisons that are performed, so it uses the risk of false positive results, particularly useful when only a limited number of planned comparisons are required. Then you have the Aker test, one of the most conservative. Most HO procedures are suitable when multiple complex comparisons are anticipated. Provides strong protection against type one error but has lower statistical power. #anova #PostHocTests #biostatistics #statisticalanalysis #datascience #researchmethods #StatisticsEducation #quantitativeresearch #experimentaldesign #StatisticalSignificance