Exam 16: Making Inferences From Sample Data I: The Null Hypothesis Significance Testing Approach

When estimating the effect size when calculating power, it is best to use .50, regardless of the content area being researched.

The situation above (problem 7) is an example of:

Directional alternative hypotheses often are used when comparing a treatment to a control condition.

Statistical power can be gained by:

Which of the following is true about statistical power?

What is important about choosing a direction or non-directional hypothesis?

Null and alternative hypotheses refer to differences between sample means.

The significance level or alpha should be determined at the end of the study.

To increase power:

Within-group variability decreases the statistical power of the study.

An increased sample size will increase variability and decrease statistical power.

There are a number of ways to state the alternative hypothesis. Select which applies:

It is more difficult to reject the null hypothesis using a directional hypothesis.

To interpret fully an inferential statistic, it is only necessary to know if p < .05.

When calculating power, how does a researcher know what estimate to use for the effect size?

If the calculated value of an F statistic is relatively large, the probability is small.

Can the null hypothesis be accepted?

Null and alternative hypotheses are stated in terms of population means.

The only proven method for increasing power is to increase the sample size.

Power from a statistical point of view refers to the probability of not rejecting a false null hypothesis.