Question 1

An effect size of .40 indicates that

Accepted Answer

A) the size of the difference between two means is .40 of a standard deviation. 
B) the odds of a response in one condition is .40 of the odds in another condition. 
C) 40% of the variability in the dependent variable is due to the independent variable. 
D) the answer depends on which effect size indicator is being used.

Question 2

Why do we say that we "fail to reject" the null hypothesis rather than "accept" it?

Accepted Answer

The answer of Why do we say that we "fail...

Question 3

The probability that a researcher is willing to make a Type I error is

Accepted Answer

A) the alpha-level. 
B) beta. 
C) power. 
D) the confidence interval.

Question 4

Power refers to the degree to which a study is likely to

Accepted Answer

A) discover large effects. 
B) detect effects of the independent variable. 
C) be replicated. 
D) produce Type I errors.

Question 5

Why is p-hacking a questionable research practice?

Accepted Answer

A) It increases Type I errors. 
B) It results in excessive null findings. 
C) It requires discarding data. 
D) It reduces the power of a study.

Question 6

What is power? Do researchers want power to be low or high, and why?

Accepted Answer

The answer of What is power? Do researchers want power...

Question 7

Researchers reject the null hypothesis when

Accepted Answer

A) statistical analyses showed that the p-value is large. 
B) the difference between condition means is larger than would be expected on the basis of error variance alone. 
C) the effect size is smaller than .05. 
D) they want to avoid a Type I error.

Question 8

The power of an experiment was .87. This indicates that

Accepted Answer

A) there is an 87% chance of making a Type I error. 
B) 87% of the participants in one condition will score higher than the average participant in the other condition. 
C) beta is .87. 
D) the experiment has an 87% chance of detecting any effect of the independent variable that might occur.

Question 9

If statistical analyses show that the difference between condition means is larger than would be expected on the basis of error variance alone, a researcher will

Accepted Answer

A) accept the null hypothesis. 
B) reject the null hypothesis. 
C) fail to reject the null hypothesis. 
D) reject the experimental hypothesis.

Question 10

The proportion of the variance in one variable that can be accounted for by another variable is the

Accepted Answer

A) power. 
B) statistical significance. 
C) beta. 
D) effect size.

Question 11

The confidence interval for a mean tells us

Accepted Answer

A) how likely it is that a result can be replicated. 
B) how confident we can be that a significant effect is not a Type I error. 
C) the range of likely values for the population mean. 
D) how many participants we need in order to be confident of the value of the mean we obtained.

Question 12

Researchers use null hypothesis significance testing to

Accepted Answer

A) understand why null findings were obtained. 
B) test whether confounding has occurred. 
C) test whether condition means differ more than they would if the difference were due to error variance. 
D) separate the effects of the independent from the effects of participant variables.

Question 13

Why is it possible for condition means to differ at the end of an experiment even if the independent variable had no effect?

Accepted Answer

A) A Type II error has occurred. 
B) Error variance has created differences between conditions. 
C) A null finding was obtained. 
D) The power of the study was low.

Exam 11: Analyzing Experimental Data: Basic Concepts