Question 1

The importance of the underlying assumption of normality behind a one-sample means test

Accepted Answer

A)  depends on how fussy you are. 
B)  depends on the sample size. 
C)  depends on whether you are solving for t or z . 
D)  doesn't depend on anything. 
A)  depends on how fussy you are. 
B)  depends on the sample size. 
C)  depends on whether you are solving for t or z . 
D)  doesn't depend on anything.

Question 2

A one-sample t test was used to see if a college ski team skied faster than the population of skiers at a popular ski resort. The resulting statistic was t .05(23) = -7.13, p

Accepted Answer

A)  The sample mean of the college skiers was significantly different from the population mean. 
B)  The sample mean of the college skiers was not significantly different from the population mean. 
C)  The null hypothesis was true. 
D)  The sample mean was greater than the population mean. 
A)  The sample mean of the college skiers was significantly different from the population mean. 
B)  The sample mean of the college skiers was not significantly different from the population mean. 
C)  The null hypothesis was true. 
D)  The sample mean was greater than the population mean.

Question 3

Calculate the 95% confidence interval for μ given 
   s = 25, and N = 101.

Accepted Answer

p (95.4 ≤

Question 4

Assuming a two-tailed one sample test is being used, what are the critical values for t given the following sample sizes: 
a. N = 10 
b. N = 15 
c. N = 30

Accepted Answer

a. 2.262

Question 5

The sampling distribution of the mean is

Accepted Answer

A)  the population mean. 
B)  the distribution of the population mean over many populations. 
C)  the distribution of sample means over repeated samples. 
D)  the mean of the distribution of the sample. 
A)  the population mean. 
B)  the distribution of the population mean over many populations. 
C)  the distribution of sample means over repeated samples. 
D)  the mean of the distribution of the sample.

Question 6

If we have calculated a confidence interval and we find that it does NOT include the population mean,

Accepted Answer

A)  we must have done something wrong in collecting data. 
B)  our interval was too wide. 
C)  we made a mistake in calculation. 
D)  this will happen a fixed percentage of the time. 
A)  we must have done something wrong in collecting data. 
B)  our interval was too wide. 
C)  we made a mistake in calculation. 
D)  this will happen a fixed percentage of the time.

Question 7

When we take a single sample mean as an estimate of the value of a population mean, we have

Accepted Answer

A)  a point estimate. 
B)  an interval estimate. 
C)  a population estimate. 
D)  a parameter. 
A)  a point estimate. 
B)  an interval estimate. 
C)  a population estimate. 
D)  a parameter.

Question 8

The two-tailed p value that a statistical program produces refers to

Accepted Answer

A)  the value of t . 
B)  the probability of getting at least that large a value of t if the null hypothesis is false. 
C)  the probability of getting at least that large an absolute value of t if the null hypothesis is true. 
D)  the probability that the null hypothesis is true. 
A)  the value of t . 
B)  the probability of getting at least that large a value of t if the null hypothesis is false. 
C)  the probability of getting at least that large an absolute value of t if the null hypothesis is true. 
D)  the probability that the null hypothesis is true.

Question 9

If we compute 95% confidence limits on the mean as 112.5 - 118.4, we can conclude that

Accepted Answer

A)  the probability is .95 that the sample mean lies between 112.5 and 118.4. 
B)  the probability is .05 that the population mean lies between 112.5 and 118.4. 
C)  an interval computed in this way has a probability of .95 of bracketing the population mean. 
D)  the population mean is not less than 112.5. 
A)  the probability is .95 that the sample mean lies between 112.5 and 118.4. 
B)  the probability is .05 that the population mean lies between 112.5 and 118.4. 
C)  an interval computed in this way has a probability of .95 of bracketing the population mean. 
D)  the population mean is not less than 112.5.

Question 10

Which of the following statements is true?

Accepted Answer

A)  Confidence intervals are the boundaries of confidence limits. 
B)  Confidence intervals always enclose the population mean. 
C)  Sample size does not affect the calculation of t . 
D)  Confidence limits are the boundaries of confidence intervals. 
A)  Confidence intervals are the boundaries of confidence limits. 
B)  Confidence intervals always enclose the population mean. 
C)  Sample size does not affect the calculation of t . 
D)  Confidence limits are the boundaries of confidence intervals.

Question 11

Given  m = 100, 
   s = 27, and N = 30: 
a. Calculate t. 
b. Write a sentence interpreting the value of t as a two-tailed test. 
c. Write a sentence interpreting the value of t as a one-tailed test.

Accepted Answer

a. t = -1.25 
b. The sample me

Question 12

If the standard deviation of the population is 15 and we repeatedly draw samples of 25 observations each, the resulting sample means will have a standard error of

Accepted Answer

A)  2 
B)  3 
C)  15 
D)  0.60 
A)  2 
B)  3 
C)  15 
D)  0.60

Question 13

When comparing the mean of a sample of 30 people to the population mean, the degrees of freedom are 31.

Accepted Answer

A) True 
 B)False

Question 14

The mean anxiety score in elementary school children is 14.55. A researcher wants to know if children of anxious parents are more anxious than the average child. Below are the anxiety scores from 10 children of anxious parents. 
13         14         14         15         15         15         16         17         17         18 
  
a. Calculate the t value. 
b. Write a sentence to answer the researcher's question.

Accepted Answer

a. t = 1.18 
b. Based on this

Question 15

A normal distribution is one in which all outcomes are equally likely.

Accepted Answer

A) True 
 B)False

Question 16

A sampling distribution of the mean is typically the mean of one sample.

Accepted Answer

A) True 
 B)False

Question 17

With a one-sample t test, the value of t is

Accepted Answer

A)  always positive. 
B)  positive if the sample mean is too small. 
C)  negative whenever the sample standard deviation is negative. 
D)  positive if the sample mean is larger than the hypothesized population mean. 
A)  always positive. 
B)  positive if the sample mean is too small. 
C)  negative whenever the sample standard deviation is negative. 
D)  positive if the sample mean is larger than the hypothesized population mean.

Question 18

With large samples and a small population variance, the sample means usually

Accepted Answer

A)  will be close to the population mean. 
B)  will slightly underestimate the population mean. 
C)  will slightly overestimate the population mean. 
D)  will equal the population mean. 
A)  will be close to the population mean. 
B)  will slightly underestimate the population mean. 
C)  will slightly overestimate the population mean. 
D)  will equal the population mean.

Question 19

When would you NOT use a standardized measure of effect size?

Accepted Answer

A)  when the difference in means is itself meaningful 
B)  when it is clearer to the reader to talk about a percentage 
C)  when some other measure conveys more useful information 
D)  all of the above 
A)  when the difference in means is itself meaningful 
B)  when it is clearer to the reader to talk about a percentage 
C)  when some other measure conveys more useful information 
D)  all of the above

Question 20

All of the following increase the magnitude of the t statistic and/or the likelihood of rejecting H0 EXCEPT

Accepted Answer

A)  a greater difference between the sample mean and the population mean. 
B)  an increase in sample size. 
C)  a decrease in sample variance. 
D)  a smaller significance level ( a ). 
A)  a greater difference between the sample mean and the population mean. 
B)  an increase in sample size. 
C)  a decrease in sample variance. 
D)  a smaller significance level ( a ).

The importance of the underlying assumption of normality behind a one-sample means test

A one-sample t test was used to see if a college ski team skied faster than the population of skiers at a popular ski resort. The resulting statistic was t _.05(23) = -7.13, p

Calculate the 95% confidence interval for μ given s = 25, and N = 101.

Assuming a two-tailed one sample test is being used, what are the critical values for t given the following sample sizes: a. N = 10 b. N = 15 c. N = 30

The sampling distribution of the mean is

If we have calculated a confidence interval and we find that it does NOT include the population mean,

When we take a single sample mean as an estimate of the value of a population mean, we have

The two-tailed p value that a statistical program produces refers to

If we compute 95% confidence limits on the mean as 112.5 - 118.4, we can conclude that

Which of the following statements is true?

Given m = 100, s = 27, and N = 30: a. Calculate t. b. Write a sentence interpreting the value of t as a two-tailed test. c. Write a sentence interpreting the value of t as a one-tailed test.

If the standard deviation of the population is 15 and we repeatedly draw samples of 25 observations each, the resulting sample means will have a standard error of

When comparing the mean of a sample of 30 people to the population mean, the degrees of freedom are 31.

A normal distribution is one in which all outcomes are equally likely.

A sampling distribution of the mean is typically the mean of one sample.

With a one-sample t test, the value of t is

With large samples and a small population variance, the sample means usually

When would you NOT use a standardized measure of effect size?

All of the following increase the magnitude of the t statistic and/or the likelihood of rejecting H₀ EXCEPT

Introduction

Basic Concepts

Displaying Data

Measures of Central Tendency

Measures of Variability

The Normal Distribution

Basic Concepts of Probability

Sampling Distributions and Hypothesis Testing

Correlation

Regression

Multiple Regression

Hypothesis Tests Applied to Means: Two Related Samples

Hypothesis Tests Applied to Means: Two Independent Samples

Power

One-Way Analysis of Variance

Factorial Analysis of Variance

Repeated-Measures Analysis of Variance

Chi-Square

Nonparametric and Resampling Statistical Tests

Meta-Analysis

Filters

Exam 12: Hypothesis Tests Applied to Means: One Sample

The importance of the underlying assumption of normality behind a one-sample means test

A one-sample t test was used to see if a college ski team skied faster than the population of skiers at a popular ski resort. The resulting statistic was t .05(23) = -7.13, p

Calculate the 95% confidence interval for μ given s = 25, and N = 101.

Assuming a two-tailed one sample test is being used, what are the critical values for t given the following sample sizes: a. N = 10 b. N = 15 c. N = 30

The sampling distribution of the mean is

If we have calculated a confidence interval and we find that it does NOT include the population mean,

When we take a single sample mean as an estimate of the value of a population mean, we have

The two-tailed p value that a statistical program produces refers to

If we compute 95% confidence limits on the mean as 112.5 - 118.4, we can conclude that

Which of the following statements is true?

Given m = 100, s = 27, and N = 30: a. Calculate t. b. Write a sentence interpreting the value of t as a two-tailed test. c. Write a sentence interpreting the value of t as a one-tailed test.

If the standard deviation of the population is 15 and we repeatedly draw samples of 25 observations each, the resulting sample means will have a standard error of

When comparing the mean of a sample of 30 people to the population mean, the degrees of freedom are 31.

A normal distribution is one in which all outcomes are equally likely.

A sampling distribution of the mean is typically the mean of one sample.

With a one-sample t test, the value of t is

With large samples and a small population variance, the sample means usually

When would you NOT use a standardized measure of effect size?

All of the following increase the magnitude of the t statistic and/or the likelihood of rejecting H0 EXCEPT

Introduction

Basic Concepts

Displaying Data

Measures of Central Tendency

Measures of Variability

The Normal Distribution

Basic Concepts of Probability

Sampling Distributions and Hypothesis Testing

Correlation

Regression

Multiple Regression

Hypothesis Tests Applied to Means: Two Related Samples

Hypothesis Tests Applied to Means: Two Independent Samples

Power

One-Way Analysis of Variance

Factorial Analysis of Variance

Repeated-Measures Analysis of Variance

Chi-Square

Nonparametric and Resampling Statistical Tests

Meta-Analysis

Filters

A one-sample t test was used to see if a college ski team skied faster than the population of skiers at a popular ski resort. The resulting statistic was t _.05(23) = -7.13, p

All of the following increase the magnitude of the t statistic and/or the likelihood of rejecting H₀ EXCEPT