Exam 7: Making Sense of Statistical Significance: Effect Size and Statistical Power

In statistics, we cannot state that the research hypothesis is ever definitely false. However, if one fails to reject the null hypothesis in a study with a high level of power, this allows us to:

One way of decreasing the standard deviation of the distribution of means in a planned study, thereby increasing power, is to have a larger number of participants. Another would be to:

Cohen has proposed some effect-size conventions based on the effects observed in psychology research in general because:

When a study has only a small chance of being significant even if the research hypothesis is true, the study is said to have:

If the results of a study are not statistically significant and the sample size is large, then:

A researcher may not be able to change the effect size of a planned study to increase power. Another aspect of a planned study that the researcher can usually change to increase power is:

Which of the following is not a direct influence on power?

What does it mean to say "A between-groups effect size of .6 was achieved for the treatment group as compared to the no-treatment group"?

In actual practice, the usual reason for determining power before conducting a study is to:

The word significant in statically significant means the researcher can be fairly confident that there is some real effect. It does not, however, mean that the effect is significant in a __________ sense.

One way of understanding __________ is in terms of the degree of separation between populations due to the experimental variable.

If the difference between population means is 10 and the population SD is 5, according to Cohen's conventions, there is a(n)__________ effect size.

For a particular research study, simply knowing about __________ does not provide much information about the size of the effect.

Power is affected by sample size, effect size, whether a one- or two-tailed test is used, __________ , and type of hypothesis-testing procedure used.

Effect size is a standardized measure of difference (lack of overlap)between populations. (True or False)

Knowing the effect size of a study lets you compare results with effect sizes found in other studies, but only when the other studies have equal sample sizes. (True or False)

Sample size affects power because the larger the sample size:

Practical significance is a combination of statistical significance and:

If the research hypothesis is true, but the study has a low level of power:

Effect size is a measure of: