"Type I" and "Type II" errors, names first given by Jerzy Neyman and Egon Pearson to describe rejecting a null hypothesis when it's true and accepting one when it's not, are too vague for stat newc...

pin 596
heart 63

This lesson will give the definition of a null hypothesis, as well as an alternative hypothesis. Examples will be given to clearly illustrate the...

pin 1
heart 1

If all else fails, use "significant at a p>0.05 level" and hope no one notices. // This concept totally went over my head in my research stats class.

pin 1k
heart 149
speech 1

Videos from Dr. John Kruschke on the need for Bayesian Analysis. Rejecting the null hypothesis is not enough because a good p-value can be present with a huge confidence interval. Why some journals no longer want researchers to report p-values. Bayesian analysis is an improvement.

pin 1
Pinterest • The world’s catalog of ideas
Search