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If you choose the Bonferroni, Tukey, Dunnett or Dunn (nonparametric) multiple comparisons test, Prism can compute a multiplicity adjusted P value for each ...

https://www.graphpad.com/guides/prism/latest/statistics/

You should only choose a one-tail P value when you have specified the anticipated sign of the correlation coefficient before collecting any data and are willing ...

https://www.graphpad.com/guides/prism/latest/statistics/

Suppose that you've collected data from two samples of animals treated with different drugs. You've measured an enzyme in each animal's plasma, ...

https://www.graphpad.com/guides/prism/latest/statistics/

Comparing slopes. Prism compares slopes first. It calculates a P value (two-tailed) testing the null hypothesis that the slopes are all identical ( ...

https://www.graphpad.com/guides/prism/latest/curve-fitting/

P value The Kruskal-Wallis test is a nonparametric test that compares three or more unmatched groups. To perform this test, Prism first ranks all the values ...

https://www.graphpad.com/guides/prism/latest/statistics/

A two-tailed P value answers this question: Assuming the null hypothesis is true, what is the chance that randomly selected samples would have means as far ...

https://www.graphpad.com/guides/prism/latest/statistics/

When you make one comparison, it is easy to gloss over the difference between reporting a P value and using statistical hypothesis testing to report a ...

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This P value is used to test the null hypothesis that all of the subjects in each of the different groups were sampled from a single population with a single ...

https://www.graphpad.com/guides/prism/latest/statistics/

Each P value you enter must be a decimal fraction. Optionally, enter a column title adjacent to each P value to identify the corresponding comparison. This will ...

https://www.graphpad.com/guides/prism/latest/statistics/

... P value using this GraphPad QuickCalc web calculator, an Excel formula, or a statistical table. The P value answers this question: If all the assumptions ...

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