Question

April 2018

Explain the influence of a level of significance and sample size has on hypothesis testing. Provide an example of the influence and how it impacts business decisions.

(150-200 words or less please)

Answer 1

The probability of not committing a Type II error is called the power of a hypothesis test.

greater the sample size, the greater the power of the test.

And in case of Significance level (α). The lower the significance level, the lower the power of the test.

Power of Hypothesis testing is tormented by 3 factors.

(1) - Sample size (n).

If other things being equal,and the bigger the sample size, the bigger the power of test.

(2) -Significance level (α).

The lower the level of significance , the lower the power of test .

If we cut back the Level of significance (e.g., from 0.05 to 0.01), the region of acceptance gets larger. As a result, we're less doubtless to reject the null hypothesis. this implies we're less doubtless to reject the null hypothesis once it's false, therefore we're additional doubtless to form a type II error.

In other words we can say that , the power of test decreases if we reduce the significance level.

The "true" value of parameter being tested. The bigger the distinction between the "true" value of parameter and and the value specified in the null hypothesis, the bigger the power of test.

in other words we can say That if the bigger the impact size, the bigger the power of the test

Please like ??

.