Question 1

Compared to a z-score,a hypothesis test with a t statistic requires more information from the sample.

Accepted Answer

A) True 
 B)False

Question 2

A sample of n = 4 scores is selected from a population with an unknown mean.The sample has a mean of M = 40 and a variance of s² = 16.Which of the following is the correct 90% confidence interval for μ?

Accepted Answer

A) μ = 40 ± 2.353(4) 
B) μ = 40 ± 1.638(4) 
C) μ = 40 ± 2.353(2) 
D) μ = 40 ± 1.638(2) 
A) μ = 40 ± 2.353(4) 
B) μ = 40 ± 1.638(4) 
C) μ = 40 ± 2.353(2) 
D) μ = 40 ± 1.638(2)

Question 3

Which of the following would have no effect on the width of a confidence interval?

Accepted Answer

A) Increase the sample mean 
B) Increase the size of the sample 
C) Increase the percentage of confidence 
D) Increase the sample variance 
A) Increase the sample mean 
B) Increase the size of the sample 
C) Increase the percentage of confidence 
D) Increase the sample variance

Question 4

If the null hypothesis states that µ = 70 and a researcher obtains a sample with M = 73 and s² = 9,then Cohen's d = 0.33.

Accepted Answer

A) True 
 B)False

Question 5

A researcher selects a sample from a population with μ = 30 and uses the sample to evaluate the effect of a treatment.After treatment,the sample has a mean of M = 32 and a variance of s² = 6.If Cohen's d is used to measure the size of the treatment effect,which of the following would have no effect on the value of Cohen's d?

Accepted Answer

A) Increase the sample size 
B) Increase the sample mean 
C) Increase the sample variance 
D) All of the other options will influence the value of Cohen's d. 
A) Increase the sample size 
B) Increase the sample mean 
C) Increase the sample variance 
D) All of the other options will influence the value of Cohen's d.

Question 6

If other factors are held constant,as the sample variance increases,the estimated standard error also increases.

Accepted Answer

A) True 
 B)False

Question 7

How does sample variance influence the estimated standard error and measures of effect size such as r² and Cohen's d?

Accepted Answer

A) Larger variance increases both the standard error and measures of effect size. 
B) Larger variance increases the standard error but decreases measures of effect size. 
C) Larger variance decreases the standard error but increases measures of effect size. 
D) Larger variance decreases both the standard error and measures of effect size. 
A) Larger variance increases both the standard error and measures of effect size. 
B) Larger variance increases the standard error but decreases measures of effect size. 
C) Larger variance decreases the standard error but increases measures of effect size. 
D) Larger variance decreases both the standard error and measures of effect size.

Question 8

In general,the larger the value of the sample variance,the greater the likelihood of rejecting the null hypothesis.

Accepted Answer

A) True 
 B)False

Question 9

Why are t statistics more variable than z-scores?

Accepted Answer

A) The extra variability is caused by variations in the sample mean. 
B) The extra variability is caused by variations in the sample variance. 
C) The extra variability is caused by variations in the df value. 
D) None of the other options explains the extra variability for t statistics. 
A) The extra variability is caused by variations in the sample mean. 
B) The extra variability is caused by variations in the sample variance. 
C) The extra variability is caused by variations in the df value. 
D) None of the other options explains the extra variability for t statistics.

Question 10

As the sample size is increased,the distribution of t statistics becomes flatter and more spread out.

Accepted Answer

A) True 
 B)False

Question 11

Which of the following is a fundamental difference between the t statistic and a z-score?

Accepted Answer

A) The t statistic uses the sample mean in place of the population mean. 
B) The t statistic uses the sample variance in place of the population variance. 
C) The t statistic computes the standard error by dividing the standard deviation by n - 1 instead of dividing by n. 
D) All of these are differences between t and z. 
A) The t statistic uses the sample mean in place of the population mean. 
B) The t statistic uses the sample variance in place of the population variance. 
C) The t statistic computes the standard error by dividing the standard deviation by n - 1 instead of dividing by n. 
D) All of these are differences between t and z.

Question 12

If other factors are held constant,which set of sample characteristics is most likely to produce a significant t statistic?

Accepted Answer

A) n = 25 with s2 = 100 
B) n = 25 with s2 = 400 
C) n = 100 with s2 = 100 
D) n = 100 with s2 = 400 
A) n = 25 with s2 = 100 
B) n = 25 with s2 = 400 
C) n = 100 with s2 = 100 
D) n = 100 with s2 = 400

Question 13

Two samples from the same population both have n = 10 scores with M = 45.If the t statistic is computed for each sample,then what is the relationship between the two t values?

Accepted Answer

A) The two t statistics will be identical. 
B) The sample with the larger variance will produce the larger t statistic. 
C) The sample with the smaller variance will produce the larger t statistic. 
D) There is no way to predict the relationship between the two t statistics. 
A) The two t statistics will be identical. 
B) The sample with the larger variance will produce the larger t statistic. 
C) The sample with the smaller variance will produce the larger t statistic. 
D) There is no way to predict the relationship between the two t statistics.

Question 14

A sample of n = 9 scores has a variance of s² = 36.What is the estimated standard error for the sample mean?

Accepted Answer

A) 1 
B) 2 
C) 4 
D) 16 
A) 1 
B) 2 
C) 4 
D) 16

Question 15

With α = .05,what is the critical t value for a one-tailed test with n = 15?

Accepted Answer

A) t = 1.761 
B) t = 1.753 
C) t = 2.145 
D) t = 2.131 
A) t = 1.761 
B) t = 1.753 
C) t = 2.145 
D) t = 2.131

Question 16

A sample of n = 16 scores produces a t statistic of t = 2.00.If the sample is used to measure effect size with r²,what value will be obtained for r²?

Accepted Answer

A) r² = 2/20 
B) r² = 4/20 
C) r² = 2/19 
D) r² = 4/19 
A) r² = 2/20 
B) r² = 4/20 
C) r² = 2/19 
D) r² = 4/19

Question 17

A sample of n = 16 scores with a sample variance of s² = 64 has an estimated standard error of 4 points.

Accepted Answer

A) True 
 B)False

Question 18

A researcher conducts a hypothesis test using a sample from an unknown population.If the t statistic has df = 30,how many individuals were in the sample?

Accepted Answer

A) n = 29 
B) n = 30 
C) n = 31 
D) Cannot be determined from the information given 
A) n = 29 
B) n = 30 
C) n = 31 
D) Cannot be determined from the information given

Question 19

A sample has a mean of M = 39.5 and a standard deviation of s = 4.3,and produces a t statistic of t = 2.14.For a two-tailed hypothesis test with α = .05,what is the correct statistical decision for this sample?

Accepted Answer

A) The researcher can reject the null hypothesis with α = .05 but not with α = .01. 
B) The researcher can reject the null hypothesis with either α = .05 or α = .01. 
C) The researcher must fail to reject the null hypothesis with either α = .05 or α = .01. 
D) It is impossible to make a decision about H0 without more information. 
A) The researcher can reject the null hypothesis with α = .05 but not with α = .01. 
B) The researcher can reject the null hypothesis with either α = .05 or α = .01. 
C) The researcher must fail to reject the null hypothesis with either α = .05 or α = .01. 
D) It is impossible to make a decision about H0 without more information.

Question 20

If other factors are held constant,how does sample size influence the likelihood of rejecting the null hypothesis and measures of effect size such as r² and Cohen's d?

Accepted Answer

A) A larger sample increases both the likelihood and measures of effect size. 
B) A larger sample increases the likelihood but has little influence on measures of effect size. 
C) A larger sample decreases the likelihood but has little influence on measures of effect size. 
D) A larger sample decreases both the likelihood and measures of effect size. 
A) A larger sample increases both the likelihood and measures of effect size. 
B) A larger sample increases the likelihood but has little influence on measures of effect size. 
C) A larger sample decreases the likelihood but has little influence on measures of effect size. 
D) A larger sample decreases both the likelihood and measures of effect size.

Compared to a z-score,a hypothesis test with a t statistic requires more information from the sample.

A sample of n = 4 scores is selected from a population with an unknown mean.The sample has a mean of M = 40 and a variance of s² = 16.Which of the following is the correct 90% confidence interval for μ?

Which of the following would have no effect on the width of a confidence interval?

If the null hypothesis states that µ = 70 and a researcher obtains a sample with M = 73 and s² = 9,then Cohen's d = 0.33.

If other factors are held constant,as the sample variance increases,the estimated standard error also increases.

How does sample variance influence the estimated standard error and measures of effect size such as r² and Cohen's d?

In general,the larger the value of the sample variance,the greater the likelihood of rejecting the null hypothesis.

Why are t statistics more variable than z-scores?

As the sample size is increased,the distribution of t statistics becomes flatter and more spread out.

Which of the following is a fundamental difference between the t statistic and a z-score?

If other factors are held constant,which set of sample characteristics is most likely to produce a significant t statistic?

Two samples from the same population both have n = 10 scores with M = 45.If the t statistic is computed for each sample,then what is the relationship between the two t values?

A sample of n = 9 scores has a variance of s² = 36.What is the estimated standard error for the sample mean?

With α = .05,what is the critical t value for a one-tailed test with n = 15?

A sample of n = 16 scores produces a t statistic of t = 2.00.If the sample is used to measure effect size with r²,what value will be obtained for r²?

A sample of n = 16 scores with a sample variance of s² = 64 has an estimated standard error of 4 points.

A researcher conducts a hypothesis test using a sample from an unknown population.If the t statistic has df = 30,how many individuals were in the sample?

A sample has a mean of M = 39.5 and a standard deviation of s = 4.3,and produces a t statistic of t = 2.14.For a two-tailed hypothesis test with α = .05,what is the correct statistical decision for this sample?

If other factors are held constant,how does sample size influence the likelihood of rejecting the null hypothesis and measures of effect size such as r² and Cohen's d?

Introduction to Statistics.

Frequency Distributions.

Central Tendency.

Variability.

z-Scores: Location of Scores and Standardized Distributions.

Probability.

Probability and Samples: The Distribution of Sample Means.

Introduction to Hypothesis Testing.

The t Test for Two Independent Samples

The t Test for Two Related Samples

Introduction to Analysis of Variance

Repeated-Measures and Two-Factor Analysis of Variance

Correlation and Regression.

The Chi-Square Statistic: Tests for Goodness of Fit and Independence

Filters

Exam 9: Introduction to the t Statistic

Compared to a z-score,a hypothesis test with a t statistic requires more information from the sample.

A sample of n = 4 scores is selected from a population with an unknown mean.The sample has a mean of M = 40 and a variance of s² = 16.Which of the following is the correct 90% confidence interval for μ?

Which of the following would have no effect on the width of a confidence interval?

If the null hypothesis states that µ = 70 and a researcher obtains a sample with M = 73 and s² = 9,then Cohen's d = 0.33.

If other factors are held constant,as the sample variance increases,the estimated standard error also increases.

How does sample variance influence the estimated standard error and measures of effect size such as r² and Cohen's d?

In general,the larger the value of the sample variance,the greater the likelihood of rejecting the null hypothesis.

Why are t statistics more variable than z-scores?

As the sample size is increased,the distribution of t statistics becomes flatter and more spread out.

Which of the following is a fundamental difference between the t statistic and a z-score?

If other factors are held constant,which set of sample characteristics is most likely to produce a significant t statistic?

Two samples from the same population both have n = 10 scores with M = 45.If the t statistic is computed for each sample,then what is the relationship between the two t values?

A sample of n = 9 scores has a variance of s² = 36.What is the estimated standard error for the sample mean?

With α = .05,what is the critical t value for a one-tailed test with n = 15?

A sample of n = 16 scores produces a t statistic of t = 2.00.If the sample is used to measure effect size with r²,what value will be obtained for r²?

A sample of n = 16 scores with a sample variance of s² = 64 has an estimated standard error of 4 points.

A researcher conducts a hypothesis test using a sample from an unknown population.If the t statistic has df = 30,how many individuals were in the sample?

A sample has a mean of M = 39.5 and a standard deviation of s = 4.3,and produces a t statistic of t = 2.14.For a two-tailed hypothesis test with α = .05,what is the correct statistical decision for this sample?

If other factors are held constant,how does sample size influence the likelihood of rejecting the null hypothesis and measures of effect size such as r² and Cohen's d?

Introduction to Statistics.

Frequency Distributions.

Central Tendency.

Variability.

z-Scores: Location of Scores and Standardized Distributions.

Probability.

Probability and Samples: The Distribution of Sample Means.

Introduction to Hypothesis Testing.

The t Test for Two Independent Samples

The t Test for Two Related Samples

Introduction to Analysis of Variance

Repeated-Measures and Two-Factor Analysis of Variance

Correlation and Regression.

The Chi-Square Statistic: Tests for Goodness of Fit and Independence

Filters