In a research report, the notation p < .05 indicates that the probability of a Type I error is less than .05.

Question

TRUE OR FALSE ? 

Answer 1

I take it that the "p" in the notation p < 0.05 is the "p-value". The p-value is the probability, calculated assuming the null hypothesis to be true, of obtaining a value of the test statistic at least as extreme (causing rejection of the null hypothesis) as the one that is actually observed. Hence the statement is TRUE.

Answer 2

Hello, thank you for taking the time to post your question!

The statement you posted should be FALSE … when it’s saying that p < 0.05 that means that the p-value is less than 0.05. so the probability of observing a result as extreme as the one observed is very low, assuming the null hypothesis is true.

The Type I error though is based on the “alpha” significance level that is determined before the study begins … so it won’t be affected by the observed p-value.

I hope that helps get you moving in the right direction! Feel free to reach out if you have any additional questions beyond that :)