What is the relationship between and Type I Error What decis

What is the relationship between and Type I Error?

What decision is reached when the p-value is greater than ?

PLEASE EXPLAIN. THANK YOU

Solution

Sol)

Type I error: Rejecting Null hypothesis when null hypothesis is true.

Level of significance: P(Type I error) is level of significance(alpha)

When you are doing a statistical test, the significance level is set at the desired type I error level (alpha). So the concepts you are asking about are basically the same thing - both are fixed by design to the same value. The p-value is calculated from the data and is different from the alpha value, and may be why you are getting confused.

When doing a power calculation, typically the type I error value is fixed, as is either the available sample size, or the desired type II error level (beta). Given an expected effect size (or in the case of your graph, it appears to specify an expected proportion) the non-specified value is calculated (either necessary sample size, or available type II error level - used to get power = 1-beta)

2) if p> alpha , we accept the null hypothesis.