# Quiz 11: Analyzing Experimental Data: Basic Concepts

Psychology

Q 1Q 1

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

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Multiple Choice

B

Q 2Q 2

Researchers use null hypothesis significance testing to
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.

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Multiple Choice

C

Q 3Q 3

The null hypothesis states that
A)null findings will not be obtained.
B)there is no error variance in the data.
C)differences between conditions will be due only to the independent variable.
D)the independent variable did not have an effect.

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Multiple Choice

D

Q 4Q 4

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

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Multiple Choice

Q 5Q 5

Researchers reject the null hypothesis when
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.

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Multiple Choice

Q 6Q 6

A Type I error can occur only when a researcher
A)accepts the null hypothesis.
B)rejects the null hypothesis.
C)fails to reject the null hypothesis.
D)rejects the experimental hypothesis.

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Multiple Choice

Q 7Q 7

Failing to reject the null hypothesis when it is false is
A)confounding.
B)Type I error.
C)Type II error.
D)alpha.

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Multiple Choice

Q 8Q 8

A Type I error occurs when a researcher
A)rejects a null hypothesis that is false.
B)fails to reject a null hypothesis that is false.
C)accepts a null hypothesis that is true.
D)rejects a null hypothesis that is true.

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Multiple Choice

Q 9Q 9

The probability that a researcher is willing to make a Type I error is
A)the alpha-level.
B)beta.
C)power.
D)the confidence interval.

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Multiple Choice

Q 10Q 10

The alpha-level that researchers generally use is designed to ensure Type I errors occur on less than _____ of statistical decisions.
A))5%.
B)1%.
C)5%.
D)50%.

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Multiple Choice

Q 11Q 11

A difference between means that is statistically significant is
A)due to error variance.
B)likely to be a Type II error.
C)a null finding.
D)unlikely to be due to error variance.

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Multiple Choice

Q 12Q 12

Power refers to the degree to which a study is likely to
A)discover large effects.
B)detect effects of the independent variable.
C)be replicated.
D)produce Type I errors.

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Multiple Choice

Q 13Q 13

Type II errors are more likely when
A)a Type I error occurs.
B)the results are statistically significant.
C)power is low.
D)the effect size is large.

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Multiple Choice

Q 14Q 14

A power analysis is often used to determine
A)the number of participants needed for a study.
B)the likelihood of making a Type I error.
C)the strength of the independent variable.
D)whether to reject the null hypothesis.

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Multiple Choice

Q 15Q 15

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

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Multiple Choice

Q 16Q 16

Null hypothesis significance testing has been criticized because
A)no hypothesis is ever truly false.
B)the conclusion that a result is significant is based on an arbitrary criterion.
C)even when an effect is significant, Type I error is always possible.
D)the lack of significant results causes studies to fail.

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Multiple Choice

Q 17Q 17

Why is p-hacking a questionable research practice?
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.

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Multiple Choice

Q 18Q 18

An effect size of .40 indicates that
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.

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Multiple Choice

Q 19Q 19

The proportion of the variance in one variable that can be accounted for by another variable is the
A)power.
B)statistical significance.
C)beta.
D)effect size.

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Multiple Choice

Q 20Q 20

Cohen's d expresses the size of an effect in terms of
A)correlations.
B)standard deviations.
C)amount of variance accounted for.
D)the odds of a response.

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Multiple Choice

Q 21Q 21

The confidence interval for a mean tells us
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.

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Multiple Choice

Q 22Q 22

A 95% confidence interval (CI)
A)includes 95% of the sample means.
B)is more narrow than a 99% CI.
C)is the same as the 95% margin of error.
D)is symmetrical around the sample mean.

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Multiple Choice

Q 23Q 23

Which of the following 95% confidence intervals for the difference between two means most likely indicates that the two means are truly different from one another in the population?
A)95% CI [-.05, .05]
B)95% CI [-1.2, 17.6]
C)95% CI [-7.2, -3.4]
D)95% CI [.00, 5.6]

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Multiple Choice

Q 24Q 24

Why is it insufficient for a researcher to simply inspect the condition means to determine whether the independent variable affected scores on the dependent variable?

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Q 26Q 26

Based on statistical analyses, a researcher will make one of two decisions regarding the null hypothesis. What are they?

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Q 28Q 28

In deciding whether to reject the null hypothesis, researchers may make one of two errors. Explain.

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Q 33Q 33

From looking at a 95% confidence interval for the difference between two means, how can we tell whether the two means are significantly different?

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