Failing to reject the null hypothesis when it is false is a Type II Error. T or F, and why or why not?

Type I: rejecting Ho when it is true

Type II: failure to reject Ho when it is false
answer is false

False. Failing to reject the null hypothesis when it is false is actually associated with Type II Error. Type II Error occurs when you incorrectly fail to reject the null hypothesis, leading to the conclusion that there is no significant difference or relationship between variables, when in reality there is.

To understand why this is the case, it's important to distinguish between Type I and Type II Errors. Type I Error occurs when you reject the null hypothesis even though it is actually true, leading to a false positive conclusion. On the other hand, Type II Error occurs when you fail to reject the null hypothesis even though it is false, resulting in a false negative conclusion.

In the given statement, it is stated correctly that failing to reject the null hypothesis leads to Type II Error, as it indicates the failure to detect a significant relationship or difference that actually exists in the population.