Liam D. answered • 09/18/23
Math Tutor and Student at Columbia University
The p-value is the probability of obtaining as or more extreme test results than the test results that were observed in null hypothesis testing.
For example, if p = 0.606, that means that there is a 60.6% chance of obtaining as or more extreme test results than the test results that were observed in null hypothesis testing.
It helps us calculate the statistical significance of research findings and determine how much confidence we should have in our hypothesis. That being said, it does not allow you to definitively say that a hypothesis is true or false, but that either you have enough or not enough confidence to reject the null hypothesis. Typically p-values < 0.05 are statistically significant.
Hope this helped :)
Katie N.
I really like Liam's answer. If I were to say exactly what Liam said just using different language, I would say: any p-value at or less than 0.05 (assuming you set alpha to 0.05), is a significant result. Anything greater is not significant. In other words, a p-value of 0.05 means it is unlikely that your results are due to just random chance and significantly likely that your results are due to whatever manipulation you performed. With this in mind, a p-value of 0.606 and 0.448 are not significant results. This means that whatever results you got are not likely significantly affected by whatever manipulation you performed. Example conclusion: The drugs/doses of drug did not significantly improve memory.09/21/23
Kim S.
How do I write p = 0.606 as p >/09/18/23