statistics for june 2014
Effect size is a measure of:


Which of the following is NOT a correct statement about effect size of a study finding:


According to Cohenâ€™s conventions, for research that compares means, a large effect size in which only about 53% of the populations of individuals overlap would be:


Some IQ tests have a standard deviation of 16 points. If an experimental procedure produced an increase of 3.2 IQ points, the effect size would represent a __________ effect size.


A standard verbal memory test is known to have a standard deviation of 10 points. If an experimental procedure produced an increase of 8 points, the effect size would represent a __________ effect size.


In what way is effect size most comparable to a Z score?


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


The effect size conventions proposed by Cohen are useful to researchers for:


A statistical method for combining effect sizes from different studies is known as:


Reviews of a collection of studies on a particular topic that use metaanalyses represent an alternative to traditional __________ articles. These traditional articles describe and evaluate each study and then attempt to draw some overall conclusion.


It is useful to understand statistical power for which of the following reasons?


If statistical power for a given research study is .40, one can say that: â€œAssuming the researcherâ€™s prediction is correct, the researcher has a __________ chance of attaining statistically significant results.â€


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


Standard power tables are useful for:


Effect size is one of the two major factors that contribute to power. Another factor is:


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:


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


What effect will using a onetailed test over a twotailed test have on power (presuming the true population difference is in the expected direction)?


Using a twotailed test makes it __________ to get significance on any one tail. Thus, keeping everything else the same, power __________ with a twotailed test than with a onetailed test.


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


Practical significance is a combination of statistical significance and:


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:


What is the most likely explanation for why a study with a very small effect size came out significant?


When judging a studyâ€™s results, there are two important questions. They are:


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