Question 1

A Type I error occurs when the researcher
A)rejects Ho, but Ho is true
B)rejects Ho, but Ho is false
C)fails to reject Ho, but Ho is true
D)fails to reject Ho, but Ho is false

Accepted Answer

A Type I error occurs when the null hypothesis (Ho) is rejected when it is actually true.

Question 2

A Type II error occurs when the researcher
A)rejects Ho, but Ho is true
B)rejects Ho, but Ho is false
C)fails to reject Ho, but Ho is true
D)fails to reject Ho, but Ho is false

Accepted Answer

A Type II error occurs when the researcher fails to reject the null hypothesis (Ho) when it is actually false.

Question 3

Null hypothesis significance testing answers the question ________, while an effect size analysis answers the question ________.
A)how much of an effect did one factor have on another?; is the difference significant?
B)is the difference significant?; how much of an effect did one factor have on another?
C)can we reject Ho; is the sample large enough?
D)have we made a Type I error?; have we made a Type II error?

Accepted Answer

Null hypothesis significance testing determines if the observed difference is statistically significant, while effect size analysis measures the magnitude of the effect.

Question 4

In a maze learning study, a researcher compares the performance of laboratory-bred rats and wild rats, hoping to find that the wild rats are better. Which of the following is true?
A)the null hypothesis is that wild rats will learn faster than lab rats
B)a Type II error would be to find a difference in the study when no true difference exists
C)a Type I error would be to find no difference in the study when a true difference exists
D)if wild rats really are better, but the researcher fails to reject the null hypothesis, then a Type II error has occurred

Accepted Answer

A Type II error occurs when the null hypothesis is not rejected despite there being a true effect or difference.

Question 5

Which of the following is true about Type I errors?
A)the probability of one occurring is equal to the alpha level
B)they cannot occur if the statistical test is powerful enough
C)they occur when a true effect exists, but we fail to discover it in our study
D)if one occurs, there is no chance that your study will be published

Accepted Answer

Type I errors occur when we incorrectly reject a true null hypothesis, and the probability of making a Type I error is equal to the alpha level, which is the threshold for statistical significance.

Question 6

In a study examining gender differences in verbal fluency in children, the null hypothesis is that
A)girls and boys perform equally
B)girls will most likely outperform boys
C)boys will most likely outperform girls
D)could be either alternative b. or c., depending on the researcher's prediction

Accepted Answer

The null hypothesis typically states that there is no difference or effect, so it would posit that girls and boys perform equally in verbal fluency.

Question 7

What is accomplished by a meta-analysis?
A)this analysis determines the probability of making both type I and type II errors
B)this is the statistical technique used to measure power
C)this is the term used to describe the complete statistical analysis of data-both the descriptive and the inferential analyses
D)this is a statistical procedure that combines effect sizes of several studies

Accepted Answer

A meta-analysis is a statistical procedure that combines the effect sizes of several studies to provide a more comprehensive understanding of the research topic.

Question 8

Researchers often report effect sizes to demonstrate
A)the relationship between systematic variance and error variance.
B)confidence intervals.
C)the size or magnitude of the effect.
D)statistical power.

Accepted Answer

Effect sizes are used to quantify the size or magnitude of the effect in a study, providing a measure of the strength of the relationship or the impact of an intervention.

Question 9

Suppose there are 100 studies that failed to demonstrate an effect of gender on false memories, but 8 studies that showed a gender difference. One may conclude from reading the published studies there is a gender difference, but one may be incorrect due to
A)incomplete confidence intervals.
B)error variance.
C)systematic variance.
D)a phenomenon called a file drawer effect.

Accepted Answer

The file drawer effect refers to the bias introduced when studies with non-significant results are less likely to be published, leading to a skewed perception of the evidence. In this case, the 100 studies that failed to show a gender difference might not be published, while the 8 that did show a difference are published, creating a misleading impression of the evidence.

Question 10

The power of a statistical analysis refers to
A)the chances of rejecting the false null hypothesis
B)the chances of rejecting a true null hypothesis
C)the chances of rejecting any null hypothesis
D)whether the analysis involves descriptive or inferential statistics (inferential are more powerful)

Accepted Answer

The power of a statistical analysis is the probability of correctly rejecting a false null hypothesis, which is what choice A describes.

Question 11

Researchers are happy whenever
A)systematic variance is large
B)error variance is small
C)both alternatives a. and b.
D)none of the above

Accepted Answer

Researchers prefer large systematic variance to detect true effects and small error variance to minimize noise and improve the reliability of results.

Question 12

A set of data has a mean of 12 and a 95% confidence interval of 10-14. What does this mean?
A)the standard deviation will be 14-10, or 4
B)you can be 95% sure that 12 is the population mean
C)in order for the mean to be significantly different fro some other mean, the scores producing the other mean cannot be between 10 and 14
D)you can be quite sure that the population mean falls somewhere between 10 and 14

Accepted Answer

A 95% confidence interval of 10-14 means that we can be 95% confident that the true population mean lies within this interval.

Question 13

The tendency for studies with statistically significant results to be published more so than studies with nonsignificant results is called ________.
A)a publication bias
B)an effect size
C)a meta-analysis
D)power

Accepted Answer

Publication bias refers to the phenomenon where studies with statistically significant results are more likely to be published than those with nonsignificant results, leading to a skewed representation of research findings.

Question 14

Which of the following is true about Type II errors?
A)the probability of one occurring is equal to the alpha level
B)they cannot occur if the statistical test is powerful enough
C)they occur when a true effect exists, but we fail to discover it in our study
D)they occur when we reject the null hypothesis, when we really should not do so

Accepted Answer

Type II errors occur when a true effect exists, but the study fails to detect it, leading to a false negative result.

Question 15

In a maze learning study, a researcher compares the performance of laboratory-bred rats and wild rats, hoping to find that the wild rats are better. Which of the following would be a Type II error?
A)the null hypothesis is rejected when it is in fact true
B)the wild rats outperform the lab rats in the study
C)no difference is found in the study, but wild rats are in truth better maze learners
D)lab rats learn faster in the study, but in truth there is no difference

Accepted Answer

A Type II error occurs when the null hypothesis is not rejected when it is actually false. In this case, it means failing to find a difference in the study when, in reality, wild rats are better maze learners.

Question 16

In a "Gee whiz" graph,
A)the differences are so obvious that an inferential analysis is not needed
B)the hoped-for differences fail to materialize
C)apparent differences are exaggerated by failing to label the Y-axis appropriately
D)there are too many lines, making it impossible to interpret

Accepted Answer

A "Gee whiz" graph exaggerates apparent differences by manipulating the Y-axis, often by not labeling it appropriately, to make the data appear more significant than it is.

Quiz 4: Sampling, Measurement, and Hypothesis Testing

A Type I error occurs when the researcher

A Type II error occurs when the researcher

Null hypothesis significance testing answers the question , while an effect size analysis answers the question .

In a maze learning study, a researcher compares the performance of laboratory-bred rats and wild rats, hoping to find that the wild rats are better. Which of the following is true?

Which of the following is true about Type I errors?

In a study examining gender differences in verbal fluency in children, the null hypothesis is that

What is accomplished by a meta-analysis?

Researchers often report effect sizes to demonstrate

Suppose there are 100 studies that failed to demonstrate an effect of gender on false memories, but 8 studies that showed a gender difference. One may conclude from reading the published studies there is a gender difference, but one may be incorrect due to

The power of a statistical analysis refers to

Researchers are happy whenever

A set of data has a mean of 12 and a 95% confidence interval of 10-14. What does this mean?

The tendency for studies with statistically significant results to be published more so than studies with nonsignificant results is called ________.

Which of the following is true about Type II errors?

In a maze learning study, a researcher compares the performance of laboratory-bred rats and wild rats, hoping to find that the wild rats are better. Which of the following would be a Type II error?

In a "Gee whiz" graph,