What is the difference between a Type I and Type II error? A Type I error reject

Question

What is the difference between a Type I and Type II error? A Type I error rejects the null hypothesis, when the null is actually true, and a Type II error, accepts the null hypothesis when the null is actually false. There is no difference, they are just degrees of the same thing A Type I error refers the null hypothesis and a Type II error refers to the research hypothesis. We can eliminate the possibility of making a Type I error but we cannot eliminate the possibility of making a Type II error An experimental design was used to assess the effects of an intervention to treat anxiety disorder among youth. The average score on a standardized Liker-scale instrument measuring anxiety symptoms following the intervention was 10 (SD = 0.5) for the treatment or experimental group and 15 (SD = 2.50) for the control group. Compute the effect size. -2 -10 -5 2

Explanation / Answer

Question 8 In statistical hypothesis testing, a typeI error is the incorrect rejection of a true null hypothesis (a "false positive"), while a type II error is incorrectly retainijng a false null hypothesis (a "false negative").

So first option is right. I.e A is answer

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