Question

1. What is the difference between practical significance and statistical significance? Give an example of something that might be statistically significant, but not practically significant.

2. What is a Type I error? Give an example.

3. What is a Type II error? Give an example.

Answer 1

1) The basic diffrence between practcial significance and statistical significance is that practical significance tells us the whether the differnece is large enough to be value in a practical snese i.e.it considers the magnitude of effect where as statistical significane just tells us whether the effect actually exixts or not ( does not give the magnitude of difference ) under the assumption that null hypothesis is true.

Example :

2) Type I error : It is the error when a test result indicates that the condition is true when it was actually false. It occurs when the null hypothesis is true but it is rejected.

3) Type II error : It is the error when a test result indicates that the condition is failed ( false) when it was actually successful ( true ). It occurs when the null hypothesis is false but it is accepted.

Example :

H0: Person has cancer.

Type I error : Doctor tells to the person that he has no cancer. ( when actually he has cancer )

Type II error : Doctor tell to the person that he has cancer. ( when actually he is a healthy person i.e has no disease )