Question 1

If we have run a t test with 35 observations and have found a t of 3.60, which is significant at the .05 level, we would write

Accepted Answer

A)  t (35) = 3.60, p .05. 
C)  t (34) = 3.60, p .05 
A)  t (35) = 3.60, p .05. 
C)  t (34) = 3.60, p .05

Question 2

A confidence interval computed for the mean of a single sample

Accepted Answer

A)  defines clearly where the population mean falls. 
B)  is not as good as a test of some hypothesis. 
C)  does not help us decide if there is a significant effect. 
D)  is associated with a probability statement about the location of a population mean. 
A)  defines clearly where the population mean falls. 
B)  is not as good as a test of some hypothesis. 
C)  does not help us decide if there is a significant effect. 
D)  is associated with a probability statement about the location of a population mean.

Question 3

When we are using a two-tailed hypothesis test, the null hypothesis is of the form

Accepted Answer

A)  H 1 : µ ≠  50. 
B)  H 1 : µ 
C)  H 1 : µ > 50. 
D)  H 0 : µ = 50. 
A)  H 1 : µ ≠  50. 
B)  H 1 : µ 
C)  H 1 : µ > 50. 
D)  H 0 : µ = 50.

Question 4

The point of calculating effect size measures is to

Accepted Answer

A)  decide if something is statistically significant. 
B)  convey useful information to the reader about what you found. 
C)  reject the null hypothesis. 
D)  prove causality. 
A)  decide if something is statistically significant. 
B)  convey useful information to the reader about what you found. 
C)  reject the null hypothesis. 
D)  prove causality.

Question 5

Many textbooks (though not this one) advocate testing the mean of a sample against a hypothesized population mean by using z even if the population standard deviation is not known, so long as the sample size exceeds 30. Those books recommend this because

Accepted Answer

A)  they don't know any better. 
B)  there are not tables for t for more than 30 degrees of freedom. 
C)  the difference between t and z is small for that many cases. 
D)  t and z are exactly the same for that many cases. 
A)  they don't know any better. 
B)  there are not tables for t for more than 30 degrees of freedom. 
C)  the difference between t and z is small for that many cases. 
D)  t and z are exactly the same for that many cases.

Question 6

As the sample variability increases, the magnitude of t increases.

Accepted Answer

A) True 
 B)False

Question 7

If we knew the population mean and variance, we would expect

Accepted Answer

A)  the sample mean would closely approximate the population mean. 
B)  the sample mean would differ from the population mean by no less than 1.96 standard deviations only 5% of the time. 
C)  the sample mean would differ from the population mean by no more than 1.64 standard deviations only 5% of the time. 
D)  the sample mean would differ from the population mean by more than 1.96 standard errors only 5% of the time. 
A)  the sample mean would closely approximate the population mean. 
B)  the sample mean would differ from the population mean by no less than 1.96 standard deviations only 5% of the time. 
C)  the sample mean would differ from the population mean by no more than 1.64 standard deviations only 5% of the time. 
D)  the sample mean would differ from the population mean by more than 1.96 standard errors only 5% of the time.

Question 8

The reason why we need to solve for t instead of z in some situations relates to

Accepted Answer

A)  the sampling distribution of the mean. 
B)  the sampling distribution of the sample size. 
C)  the sampling distribution of the variance. 
D)  the size of our sample mean. 
A)  the sampling distribution of the mean. 
B)  the sampling distribution of the sample size. 
C)  the sampling distribution of the variance. 
D)  the size of our sample mean.

Question 9

The following 10 numbers were drawn from a population. 
            5           7           7           10         10         10         11         12         12         13 
a. Calculate the 95% confidence interval for the population mean. 
b. Is it likely that these numbers came from a population with a mean of 13? Explain.

Accepted Answer

a. p (7.44 ≤  μ ≤ 11.96) = .95 
b. No. S

Question 10

Student's t distribution essentially accounts for the fact that t is often larger than the corresponding z because it is based on estimated variance, which is biased.

Accepted Answer

A) True 
 B)False

Question 11

When you have a single sample and want to compute an effect size measure, the most appropriate denominator is

Accepted Answer

A)  the variance of the sample. 
B)  the standard deviation of the sample. 
C)  the sample size. 
D)  none of the above 
A)  the variance of the sample. 
B)  the standard deviation of the sample. 
C)  the sample size. 
D)  none of the above

Question 12

The variance of an individual sample is more likely than not to be

Accepted Answer

A)  larger than the corresponding population variance. 
B)  smaller than the corresponding population variance. 
C)  the same as the population variance. 
D)  less than the population mean. 
A)  larger than the corresponding population variance. 
B)  smaller than the corresponding population variance. 
C)  the same as the population variance. 
D)  less than the population mean.

Question 13

A 95% confidence interval is going to be _______ a 99% confidence interval.

Accepted Answer

A)  narrower than 
B)  wider than 
C)  the same width as 
D)  more accurate than 
A)  narrower than 
B)  wider than 
C)  the same width as 
D)  more accurate than

Question 14

Given a sample size of 30, and one sample t = -2.5, what would you conclude about the sample from which the mean was drawn?

Accepted Answer

The sample mean is s

Question 15

Explain the following statement: p (100 ≤ μ ≤ 110) = .90.

Accepted Answer

The probability is .90 that wh

Question 16

Briefly describe two factors that affect the magnitude of t .

Accepted Answer

The three answers include: 
a. the bigge

Question 17

It makes a difference whether or not we know the population variance because

Accepted Answer

A)  we cannot deal with situations in which the population variance is not known. 
B)  we have to call the result t if the population variance is used. 
C)  we have to call the result z if the population variance is not used. 
D)  we have to call the result t if the sample variance is used. 
A)  we cannot deal with situations in which the population variance is not known. 
B)  we have to call the result t if the population variance is used. 
C)  we have to call the result z if the population variance is not used. 
D)  we have to call the result t if the sample variance is used.

Question 18

The larger the difference between the sample mean and the population mean, the larger the t value.

Accepted Answer

A) True 
 B)False

Question 19

An assumption behind the use of a one-sample t test is that

Accepted Answer

A)  the population is normally distributed. 
B)  the sample is normally distributed. 
C)  the population variance is normally distributed. 
D)  the population variance is known. 
A)  the population is normally distributed. 
B)  the sample is normally distributed. 
C)  the population variance is normally distributed. 
D)  the population variance is known.

Question 20

In one-sample tests of means we

Accepted Answer

A)  compare one sample mean with another. 
B)  compare one sample mean against a population mean. 
C)  compare two sample means with each other. 
D)  compare a set of population means. 
A)  compare one sample mean with another. 
B)  compare one sample mean against a population mean. 
C)  compare two sample means with each other. 
D)  compare a set of population means.

Exam 12: Hypothesis Tests Applied to Means: One Sample

If we have run a t test with 35 observations and have found a t of 3.60, which is significant at the .05 level, we would write

A confidence interval computed for the mean of a single sample

When we are using a two-tailed hypothesis test, the null hypothesis is of the form

The point of calculating effect size measures is to

Many textbooks (though not this one) advocate testing the mean of a sample against a hypothesized population mean by using z even if the population standard deviation is not known, so long as the sample size exceeds 30. Those books recommend this because

As the sample variability increases, the magnitude of t increases.

If we knew the population mean and variance, we would expect

The reason why we need to solve for t instead of z in some situations relates to

The following 10 numbers were drawn from a population. 5 7 7 10 10 10 11 12 12 13 a. Calculate the 95% confidence interval for the population mean. b. Is it likely that these numbers came from a population with a mean of 13? Explain.

Student's t distribution essentially accounts for the fact that t is often larger than the corresponding z because it is based on estimated variance, which is biased.

When you have a single sample and want to compute an effect size measure, the most appropriate denominator is

The variance of an individual sample is more likely than not to be

A 95% confidence interval is going to be _______ a 99% confidence interval.

Given a sample size of 30, and one sample t = -2.5, what would you conclude about the sample from which the mean was drawn?

Explain the following statement: p (100 ≤ μ ≤ 110) = .90.

Briefly describe two factors that affect the magnitude of t .

It makes a difference whether or not we know the population variance because

The larger the difference between the sample mean and the population mean, the larger the t value.

An assumption behind the use of a one-sample t test is that

In one-sample tests of means we

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