Question

1-

The answers listed below are characteristics of a Type I error EXCEPT for one. Select the characteristic that is not for Type I error

a)upsetting status quo for falsehood

b)reject null hypothesis when null is true

c)a "missed opportunity"

2-

The answers listed below are characteristics of a Type II error EXCEPT for one. Select the characteristic that is not for Type II error

a)do not reject null hypothesis when it is false

b)a "missed opportunity"

c)upsetting status quo for falsehood

3-

If the null hypothesis is not rejected at the 5% level of significance using the critical value approach, it

a)will be rejected using the p value approach

B)may or may not be rejected using the p value approach

c)will also not be rejected using the p value approach

4-

In a two-tailed hypothesis test, the test statistic is determined to be t = -2.5.

What else do we need to know to determine the pvalue?

a)degrees of freedom

b)Z value

c)proportion

Answer 1

1) In statistical hypothesis testing a type I error is the rejection of a true null hypothesis.

In general, the null hypothesis is usually constructed to be that of the status quo; that is, it is the hypothesis requiring no action to be taken. So if we make a type 1 error, we are upsetting the status quo.

Therefore, the characteristic that is not for Type I error is (c) a "missed opportunity"

2)

You make a Type II error when the null hypothesis is false but you fail to reject it because your data couldn’t detect it, just by chance.

This error is sometimes referred to as “missing out on a detection” or a "missed opportunity". The claim really was wrong, but you didn’t get a random sample that would provide enough evidence to reject it with enough statistical significance.

Therefore, the characteristic that is not for Type II error is (c) upsetting status quo for falsehood

3)

The critical value approach and the P-value approach give the same results when testing hypotheses. The P-value approach has the advantage in that you just need to compute one value, the P-value, to do the test. For the critical value approach, you need to compute the test statistic and find the critical value corresponding to the given confidence or significance level.

Therefore, option (c) will also not be rejected using the p value approach.

4) To determine a p value, we need to know the t statistic (calculated t value), degrees of freedom and significance level of the test.