To make tests of hypotheses about more than two population means, we use the:

normal distribution

chi-square distribution

analysis of variance distribution

*t* distribution

A continuous random variable *x* has a right-skewed distribution with a mean of 80 and a standard deviation of 12. The sampling distribution of the sample mean for a sample of 50 elements taken from this population is:

not normal

skewed to the left

skewed to the right

approximately normal

The model *y = A + Bx* is a:

probabilistic model

stochastic model

nonlinear model

deterministic model

For a goodness-of-fit test, the frequencies obtained from the performance of an experiment are the:

expected frequencies

observed frequencies

objective frequencies

subjective frequencies

An error that occurs because of chance is called:

probability error

mean error

nonsampling error

sampling error

What is the critical value of *z* for the hypothesis test?

-2.05

-2.17

-2.33

-1.96

The regression model *y = A + Bx + e* is:

a deterministic model

a probabilistic model

an exact relationship

a nonlinear model

A researcher wants to test if elementary school children spend less than 30 minutes per day on homework. The alternative hypothesis for this example will be that the population mean is:

less than or equal to 30 minutes

less than 30 minutes

equal to 30 minutes

not equal to 30 minutes

What is the critical value of *t* for the hypothesis test?

2.738

2.449

2.733

2.441

You randomly select two households and observe whether or not they own a telephone answering machine. Which of the following is a simple event?

At most one of them owns a telephone answering machine.

Exactly one of them owns a telephone answering machine.

At least one of them owns a telephone answering machine.

Neither of the two owns a telephone answering machine.

For small degrees of freedom, the chi-square distribution is:

rectangular

skewed to the left

skewed to the right

symmetric

In a hypothesis test, a Type I error occurs when:

a true null hypothesis is not rejected

a false null hypothesis is not rejected

a false null hypothesis is rejected

a true null hypothesis is rejected

A quantitative variable is the only type of variable that can:

be used to prepare tables

assume numeric values for which arithmetic operations make sense

have no intermediate values

be graphed

The mean of a discrete random variable is its:

box-and-whisker measure

upper hinge

expected value

second quartile

For a one-tailed test, the *p*-value is:

twice the area under the curve between the mean and the observed value of the sample statistic

the area under the curve between the mean and the observed value of the sample statistic

the area under the curve to the same side of the value of the sample statistic as is specified in the alternative hypothesis

twice the area under the curve to the same side of the value of the sample statistic as is specified in the alternative hypothesis

In a one-way ANOVA, we analyze only one:

mean

population

sample

variable

The alternative hypothesis is a claim about a:

parameter, where the claim is assumed to be true if the null hypothesis is declared false

statistic, where the claim is assumed to be true if the null hypothesis is declared false

statistic, where the claim is assumed to be false until it is declared true

parameter, where the claim is assumed to be true until it is declared false

A researcher wants to test if the mean annual salary of all lawyers in a city is different than $110,000. The null hypothesis for this example will be that the population mean is:

greater than to $110,000

not equal to $110,000

less than to $110,000

equal to $110,000

A qualitative variable is the only type of variable that:

cannot be graphed

can assume an uncountable set of values

can assume numerical values

cannot be measured numerically

You toss a coin nine times and observe 3 heads and 6 tails. This event is a:

multiple outcome

multinomial sample point

simple event

compound event

Which of the following pairs of events are mutually exclusive?

Female and male

No and yes

Female and yes

Female and no

The *p*-value is the:

smallest significance level at which the null hypothesis can be rejected

smallest significance level at which the null hypothesis can be rejected

largest significance level at which the null hypothesis can be rejected

largest significance level at which the alternative hypothesis can be rejected

Which of the following assumptions is not required to use ANOVA?

The populations from which the samples are drawn have the same variance.

The populations from which the samples are drawn are (approximately) normally distributed.

The samples drawn from different populations are random and independent.

All samples are of the same size.

Two paired or matched samples would imply that:

two data values are collected from the same source (elements) for two dependent samples

two data values are collected from the same source (elements) for two independent samples

data are collected on two variables from the elements of two independent samples

data are collected on one variable from the elements of two independent samples

We can use the analysis of variance procedure to test hypotheses about:

the proportion of one population

the mean of one population

two or more population proportions

two or more population means

The graph of a cumulative frequency distribution is a(n):

frequency histogram

line graph

stem-and-leaf display

ogive

In a hypothesis test, a Type II error occurs when:

a false null hypothesis is rejected

a false null hypothesis is not rejected

a true null hypothesis is not rejected

a true null hypothesis is rejected

The mean of a discrete random variable is the mean of its:

percentage distribution

frequency distribution

probability distribution

second and third quartiles

If you divide the number of elements in a sample with a specific characteristic by the total number of elements in the sample, the dividend is the:

sample distribution

sample proportion

sampling distribution

sample mean

A linear regression:

gives a relationship between two variables that can be described by a line

gives a relationship between two variables that cannot be described by a line

gives a relationship between three variables that can be described by a line

contains only two variables

We can use the analysis of variance procedure to test hypotheses about:

the proportion of one population

two or more population means

the mean of one population

two or more population proportions

For small degrees of freedom, the chi-square distribution is:

Rectangular

skewed to the left

symmetric

skewed to the right

The alternative hypothesis is a claim about a:

statistic, where the claim is assumed to be false until it is declared true

statistic, where the claim is assumed to be true if the null hypothesis is declared false

population parameter, where the claim is assumed to be true until it is declared false

population parameter, where the claim is assumed to be true if the null hypothesis is declared false

In a hypothesis test, a Type II error occurs when:

a false null hypothesis is rejected

a true null hypothesis is rejected

a true null hypothesis is not rejected

a false null hypothesis is not rejected

In a one-way ANOVA, we analyze only one:

population

mean

variable

sample

To make tests of hypotheses about more than two population means, we use the:

normal distribution

chi-square distribution

analysis of variance distribution

*t* distribution

A continuous random variable *x* has a right-skewed distribution with a mean of 80 and a standard deviation of 12. The sampling distribution of the sample mean for a sample of 50 elements taken from this population is:

not normal

skewed to the left

skewed to the right

approximately normal

The model *y = A + Bx* is a:

probabilistic model

stochastic model

nonlinear model

deterministic model

For a goodness-of-fit test, the frequencies obtained from the performance of an experiment are the:

expected frequencies

observed frequencies

objective frequencies

subjective frequencies

An error that occurs because of chance is called:

probability error

mean error

nonsampling error

sampling error

What is the critical value of *z* for the hypothesis test?

-2.05

-2.17

-2.33

-1.96

The regression model *y = A + Bx + e* is:

a deterministic model

a probabilistic model

an exact relationship

a nonlinear model

A researcher wants to test if elementary school children spend less than 30 minutes per day on homework. The alternative hypothesis for this example will be that the population mean is:

less than or equal to 30 minutes

less than 30 minutes

equal to 30 minutes

not equal to 30 minutes

What is the critical value of *t* for the hypothesis test?

2.738

2.449

2.733

2.441

You randomly select two households and observe whether or not they own a telephone answering machine. Which of the following is a simple event?

At most one of them owns a telephone answering machine.

Exactly one of them owns a telephone answering machine.

At least one of them owns a telephone answering machine.

Neither of the two owns a telephone answering machine.

For small degrees of freedom, the chi-square distribution is:

rectangular

skewed to the left

skewed to the right

symmetric

In a hypothesis test, a Type I error occurs when:

a true null hypothesis is not rejected

a false null hypothesis is not rejected

a false null hypothesis is rejected

a true null hypothesis is rejected

A quantitative variable is the only type of variable that can:

be used to prepare tables

assume numeric values for which arithmetic operations make sense

have no intermediate values

be graphed

The mean of a discrete random variable is its:

box-and-whisker measure

upper hinge

expected value

second quartile

For a one-tailed test, the *p*-value is:

twice the area under the curve between the mean and the observed value of the sample statistic

the area under the curve between the mean and the observed value of the sample statistic

the area under the curve to the same side of the value of the sample statistic as is specified in the alternative hypothesis

twice the area under the curve to the same side of the value of the sample statistic as is specified in the alternative hypothesis

In a one-way ANOVA, we analyze only one:

mean

population

sample

variable

The alternative hypothesis is a claim about a:

parameter, where the claim is assumed to be true if the null hypothesis is declared false

statistic, where the claim is assumed to be true if the null hypothesis is declared false

statistic, where the claim is assumed to be false until it is declared true

parameter, where the claim is assumed to be true until it is declared false

A researcher wants to test if the mean annual salary of all lawyers in a city is different than $110,000. The null hypothesis for this example will be that the population mean is:

greater than to $110,000

not equal to $110,000

less than to $110,000

equal to $110,000

A qualitative variable is the only type of variable that:

cannot be graphed

can assume an uncountable set of values

can assume numerical values

cannot be measured numerically

You toss a coin nine times and observe 3 heads and 6 tails. This event is a:

multiple outcome

multinomial sample point

simple event

compound event

Which of the following pairs of events are mutually exclusive?

Female and male

No and yes

Female and yes

Female and no

The *p*-value is the:

smallest significance level at which the null hypothesis can be rejected

smallest significance level at which the null hypothesis can be rejected

largest significance level at which the null hypothesis can be rejected

largest significance level at which the alternative hypothesis can be rejected

Which of the following assumptions is not required to use ANOVA?

The populations from which the samples are drawn have the same variance.

The populations from which the samples are drawn are (approximately) normally distributed.

The samples drawn from different populations are random and independent.

All samples are of the same size.

Two paired or matched samples would imply that:

two data values are collected from the same source (elements) for two dependent samples

two data values are collected from the same source (elements) for two independent samples

data are collected on two variables from the elements of two independent samples

data are collected on one variable from the elements of two independent samples

We can use the analysis of variance procedure to test hypotheses about:

the proportion of one population

the mean of one population

two or more population proportions

two or more population means

The graph of a cumulative frequency distribution is a(n):

frequency histogram

line graph

stem-and-leaf display

ogive

In a hypothesis test, a Type II error occurs when:

a false null hypothesis is rejected

a false null hypothesis is not rejected

a true null hypothesis is not rejected

a true null hypothesis is rejected

The mean of a discrete random variable is the mean of its:

percentage distribution

frequency distribution

probability distribution

second and third quartiles

If you divide the number of elements in a sample with a specific characteristic by the total number of elements in the sample, the dividend is the:

sample distribution

sample proportion

sampling distribution

sample mean

A linear regression:

gives a relationship between two variables that can be described by a line

gives a relationship between two variables that cannot be described by a line

gives a relationship between three variables that can be described by a line

contains only two variables

We can use the analysis of variance procedure to test hypotheses about:

the proportion of one population

two or more population means

the mean of one population

two or more population proportions

For small degrees of freedom, the chi-square distribution is:

Rectangular

skewed to the left

symmetric

skewed to the right

The alternative hypothesis is a claim about a:

statistic, where the claim is assumed to be false until it is declared true

statistic, where the claim is assumed to be true if the null hypothesis is declared false

population parameter, where the claim is assumed to be true until it is declared false

population parameter, where the claim is assumed to be true if the null hypothesis is declared false

In a hypothesis test, a Type II error occurs when:

a false null hypothesis is rejected

a true null hypothesis is rejected

a true null hypothesis is not rejected

a false null hypothesis is not rejected

In a one-way ANOVA, we analyze only one:

population

mean

variable

sample

To make tests of hypotheses about more than two population means, we use the:

normal distribution

chi-square distribution

analysis of variance distribution

*t* distribution

A continuous random variable *x* has a right-skewed distribution with a mean of 80 and a standard deviation of 12. The sampling distribution of the sample mean for a sample of 50 elements taken from this population is:

not normal

skewed to the left

skewed to the right

approximately normal

The model *y = A + Bx* is a:

probabilistic model

stochastic model

nonlinear model

deterministic model

For a goodness-of-fit test, the frequencies obtained from the performance of an experiment are the:

expected frequencies

observed frequencies

objective frequencies

subjective frequencies

An error that occurs because of chance is called:

probability error

mean error

nonsampling error

sampling error

What is the critical value of *z* for the hypothesis test?

-2.05

-2.17

-2.33

-1.96

The regression model *y = A + Bx + e* is:

a deterministic model

a probabilistic model

an exact relationship

a nonlinear model

A researcher wants to test if elementary school children spend less than 30 minutes per day on homework. The alternative hypothesis for this example will be that the population mean is:

less than or equal to 30 minutes

less than 30 minutes

equal to 30 minutes

not equal to 30 minutes

What is the critical value of *t* for the hypothesis test?

2.738

2.449

2.733

2.441

You randomly select two households and observe whether or not they own a telephone answering machine. Which of the following is a simple event?

At most one of them owns a telephone answering machine.

Exactly one of them owns a telephone answering machine.

At least one of them owns a telephone answering machine.

Neither of the two owns a telephone answering machine.

For small degrees of freedom, the chi-square distribution is:

rectangular

skewed to the left

skewed to the right

symmetric

In a hypothesis test, a Type I error occurs when:

a true null hypothesis is not rejected

a false null hypothesis is not rejected

a false null hypothesis is rejected

a true null hypothesis is rejected

A quantitative variable is the only type of variable that can:

be used to prepare tables

assume numeric values for which arithmetic operations make sense

have no intermediate values

be graphed

The mean of a discrete random variable is its:

box-and-whisker measure

upper hinge

expected value

second quartile

For a one-tailed test, the *p*-value is:

twice the area under the curve between the mean and the observed value of the sample statistic

the area under the curve between the mean and the observed value of the sample statistic

the area under the curve to the same side of the value of the sample statistic as is specified in the alternative hypothesis

twice the area under the curve to the same side of the value of the sample statistic as is specified in the alternative hypothesis

In a one-way ANOVA, we analyze only one:

mean

population

sample

variable

The alternative hypothesis is a claim about a:

parameter, where the claim is assumed to be true if the null hypothesis is declared false

statistic, where the claim is assumed to be true if the null hypothesis is declared false

statistic, where the claim is assumed to be false until it is declared true

parameter, where the claim is assumed to be true until it is declared false

A researcher wants to test if the mean annual salary of all lawyers in a city is different than $110,000. The null hypothesis for this example will be that the population mean is:

greater than to $110,000

not equal to $110,000

less than to $110,000

equal to $110,000

A qualitative variable is the only type of variable that:

cannot be graphed

can assume an uncountable set of values

can assume numerical values

cannot be measured numerically

You toss a coin nine times and observe 3 heads and 6 tails. This event is a:

multiple outcome

multinomial sample point

simple event

compound event

Which of the following pairs of events are mutually exclusive?

Female and male

No and yes

Female and yes

Female and no

The *p*-value is the:

smallest significance level at which the null hypothesis can be rejected

smallest significance level at which the null hypothesis can be rejected

largest significance level at which the null hypothesis can be rejected

largest significance level at which the alternative hypothesis can be rejected

Which of the following assumptions is not required to use ANOVA?

The populations from which the samples are drawn have the same variance.

The populations from which the samples are drawn are (approximately) normally distributed.

The samples drawn from different populations are random and independent.

All samples are of the same size.

Two paired or matched samples would imply that:

two data values are collected from the same source (elements) for two dependent samples

two data values are collected from the same source (elements) for two independent samples

data are collected on two variables from the elements of two independent samples

data are collected on one variable from the elements of two independent samples

We can use the analysis of variance procedure to test hypotheses about:

the proportion of one population

the mean of one population

two or more population proportions

two or more population means

The graph of a cumulative frequency distribution is a(n):

frequency histogram

line graph

stem-and-leaf display

ogive

In a hypothesis test, a Type II error occurs when:

a false null hypothesis is rejected

a false null hypothesis is not rejected

a true null hypothesis is not rejected

a true null hypothesis is rejected

The mean of a discrete random variable is the mean of its:

percentage distribution

frequency distribution

probability distribution

second and third quartiles

If you divide the number of elements in a sample with a specific characteristic by the total number of elements in the sample, the dividend is the:

sample distribution

sample proportion

sampling distribution

sample mean

A linear regression:

gives a relationship between two variables that can be described by a line

gives a relationship between two variables that cannot be described by a line

gives a relationship between three variables that can be described by a line

contains only two variables

We can use the analysis of variance procedure to test hypotheses about:

the proportion of one population

two or more population means

the mean of one population

two or more population proportions

For small degrees of freedom, the chi-square distribution is:

Rectangular

skewed to the left

symmetric

skewed to the right

The alternative hypothesis is a claim about a:

statistic, where the claim is assumed to be false until it is declared true

statistic, where the claim is assumed to be true if the null hypothesis is declared false

population parameter, where the claim is assumed to be true until it is declared false

population parameter, where the claim is assumed to be true if the null hypothesis is declared false

In a hypothesis test, a Type II error occurs when:

a false null hypothesis is rejected

a true null hypothesis is rejected

a true null hypothesis is not rejected

a false null hypothesis is not rejected

In a one-way ANOVA, we analyze only one:

population

mean

variable

sample

To make tests of hypotheses about more than two population means, we use the:

To make tests of hypotheses about more than two population means, we use the:

normal distribution

normal distribution

chi-square distribution

chi-square distribution

analysis of variance distribution

analysis of variance distribution

*t* distribution

*t* distribution*t*t distribution

*x* has a right-skewed distribution with a mean of 80 and a standard deviation of 12. The sampling distribution of the sample mean for a sample of 50 elements taken from this population is:

A continuous random variable *x* has a right-skewed distribution with a mean of 80 and a standard deviation of 12. The sampling distribution of the sample mean for a sample of 50 elements taken from this population is:A continuous random variable *x*x has a right-skewed distribution with a mean of 80 and a standard deviation of 12. The sampling distribution of the sample mean for a sample of 50 elements taken from this population is:

not normal

not normal

skewed to the left

skewed to the left

skewed to the right

skewed to the right

approximately normal

approximately normal

The model *y = A + Bx* is a:

The model *y = A + Bx* is a:The model *y = A + Bx*y = A + Bx is a:

probabilistic model

probabilistic model

stochastic model

stochastic model

nonlinear model

nonlinear model

deterministic model

deterministic model

For a goodness-of-fit test, the frequencies obtained from the performance of an experiment are the:

For a goodness-of-fit test, the frequencies obtained from the performance of an experiment are the:

expected frequencies

expected frequencies

observed frequencies

observed frequencies

objective frequencies

objective frequencies

subjective frequencies

subjective frequencies

An error that occurs because of chance is called:

An error that occurs because of chance is called:

probability error

probability error probability error

mean error

mean error

nonsampling error

nonsampling error

sampling error

sampling error

What is the critical value of *z* for the hypothesis test?

What is the critical value of *z* for the hypothesis test?*z*

-2.05

-2.05

-2.17

-2.17

-2.33

-2.33

-1.96

-1.96

The regression model *y = A + Bx + e* is:

The regression model *y = A + Bx + e* is: *y = A + Bx + e*

a deterministic model

a deterministic model

a probabilistic model

a probabilistic model

an exact relationship

an exact relationship

a nonlinear model

a nonlinear model

less than or equal to 30 minutes

less than or equal to 30 minutes

less than 30 minutes

less than 30 minutes

equal to 30 minutes

equal to 30 minutes

not equal to 30 minutes

not equal to 30 minutes

What is the critical value of *t* for the hypothesis test?

What is the critical value of *t* for the hypothesis test?*t*

2.738

2.738

2.449

2.449

2.733

2.733

2.441

2.441

At most one of them owns a telephone answering machine.

At most one of them owns a telephone answering machine.

Exactly one of them owns a telephone answering machine.

Exactly one of them owns a telephone answering machine.

At least one of them owns a telephone answering machine.

At least one of them owns a telephone answering machine.

Neither of the two owns a telephone answering machine.

Neither of the two owns a telephone answering machine.

For small degrees of freedom, the chi-square distribution is:

For small degrees of freedom, the chi-square distribution is:

rectangular

rectangular

skewed to the left

skewed to the left

skewed to the right

skewed to the right skewed to the right

symmetric

symmetric

In a hypothesis test, a Type I error occurs when:

In a hypothesis test, a Type I error occurs when:

a true null hypothesis is not rejected

a true null hypothesis is not rejected

a false null hypothesis is not rejected

a false null hypothesis is not rejected

a false null hypothesis is rejected

a false null hypothesis is rejected

a true null hypothesis is rejected

a true null hypothesis is rejected

A quantitative variable is the only type of variable that can:

A quantitative variable is the only type of variable that can:

be used to prepare tables

be used to prepare tables

assume numeric values for which arithmetic operations make sense

assume numeric values for which arithmetic operations make sense

have no intermediate values

have no intermediate values

be graphed

be graphed

The mean of a discrete random variable is its:

The mean of a discrete random variable is its:

box-and-whisker measure

box-and-whisker measure

upper hinge

upper hinge

expected value

expected value

second quartile

second quartile

For a one-tailed test, the *p*-value is:

For a one-tailed test, the *p*-value is:For a one-tailed test, the *p*p-value is:

twice the area under the curve between the mean and the observed value of the sample statistic

twice the area under the curve between the mean and the observed value of the sample statistic

the area under the curve between the mean and the observed value of the sample statistic

the area under the curve between the mean and the observed value of the sample statistic

In a one-way ANOVA, we analyze only one:

In a one-way ANOVA, we analyze only one:

mean

mean

population

population

sample

sample

variable

variable

The alternative hypothesis is a claim about a:

The alternative hypothesis is a claim about a:

parameter, where the claim is assumed to be true if the null hypothesis is declared false

parameter, where the claim is assumed to be true if the null hypothesis is declared false

statistic, where the claim is assumed to be true if the null hypothesis is declared false

statistic, where the claim is assumed to be true if the null hypothesis is declared false

statistic, where the claim is assumed to be false until it is declared true

statistic, where the claim is assumed to be false until it is declared true

parameter, where the claim is assumed to be true until it is declared false

parameter, where the claim is assumed to be true until it is declared false

greater than to $110,000

greater than to $110,000

not equal to $110,000

not equal to $110,000

less than to $110,000

less than to $110,000

equal to $110,000

equal to $110,000

A qualitative variable is the only type of variable that:

A qualitative variable is the only type of variable that:

cannot be graphed

cannot be graphed

can assume an uncountable set of values

can assume an uncountable set of values

can assume numerical values

can assume numerical values

cannot be measured numerically

cannot be measured numerically

You toss a coin nine times and observe 3 heads and 6 tails. This event is a:

You toss a coin nine times and observe 3 heads and 6 tails. This event is a:

multiple outcome

multiple outcome

multinomial sample point

multinomial sample point

simple event

simple event

compound event

compound event

Which of the following pairs of events are mutually exclusive?

Which of the following pairs of events are mutually exclusive?

Female and male

Female and male

No and yes

No and yes

Female and yes

Female and yes

Female and no

Female and no

The *p*-value is the:

The *p*-value is the:The *p*p-value is the:

smallest significance level at which the null hypothesis can be rejected

smallest significance level at which the null hypothesis can be rejected

smallest significance level at which the null hypothesis can be rejected

smallest significance level at which the null hypothesis can be rejected

largest significance level at which the null hypothesis can be rejected

largest significance level at which the null hypothesis can be rejected

largest significance level at which the alternative hypothesis can be rejected

largest significance level at which the alternative hypothesis can be rejected

Which of the following assumptions is not required to use ANOVA?

Which of the following assumptions is not required to use ANOVA?

The populations from which the samples are drawn have the same variance.

The populations from which the samples are drawn have the same variance.

The populations from which the samples are drawn are (approximately) normally distributed.

The populations from which the samples are drawn are (approximately) normally distributed.

The samples drawn from different populations are random and independent.

The samples drawn from different populations are random and independent.

All samples are of the same size.

All samples are of the same size.

Two paired or matched samples would imply that:

Two paired or matched samples would imply that:

two data values are collected from the same source (elements) for two dependent samples

two data values are collected from the same source (elements) for two dependent samples

two data values are collected from the same source (elements) for two independent samples

two data values are collected from the same source (elements) for two independent samples

data are collected on two variables from the elements of two independent samples

data are collected on two variables from the elements of two independent samples

data are collected on one variable from the elements of two independent samples

data are collected on one variable from the elements of two independent samples

We can use the analysis of variance procedure to test hypotheses about:

We can use the analysis of variance procedure to test hypotheses about:

the proportion of one population

the proportion of one population

the mean of one population

the mean of one population

two or more population proportions

two or more population proportions

two or more population means

two or more population means

The graph of a cumulative frequency distribution is a(n):

The graph of a cumulative frequency distribution is a(n):

frequency histogram

frequency histogram

line graph

line graph

stem-and-leaf display

stem-and-leaf display

ogive

ogive

In a hypothesis test, a Type II error occurs when:

In a hypothesis test, a Type II error occurs when:

a false null hypothesis is rejected

a false null hypothesis is rejected

a false null hypothesis is not rejected

a false null hypothesis is not rejected

a true null hypothesis is not rejected

a true null hypothesis is not rejected

a true null hypothesis is rejected

a true null hypothesis is rejected

The mean of a discrete random variable is the mean of its:

The mean of a discrete random variable is the mean of its:

percentage distribution

percentage distribution

frequency distribution

frequency distribution

probability distribution

probability distribution

second and third quartiles

second and third quartiles

sample distribution

sample distribution

sample proportion

sample proportion sample proportion

sampling distribution

sampling distribution

sample mean

sample mean

A linear regression:

A linear regression:

gives a relationship between two variables that can be described by a line

gives a relationship between two variables that can be described by a line

gives a relationship between two variables that cannot be described by a line

gives a relationship between two variables that cannot be described by a line

gives a relationship between three variables that can be described by a line

gives a relationship between three variables that can be described by a line

contains only two variables

contains only two variables

We can use the analysis of variance procedure to test hypotheses about:

We can use the analysis of variance procedure to test hypotheses about:

the proportion of one population

the proportion of one population

two or more population means

two or more population means

the mean of one population

the mean of one population

two or more population proportions

two or more population proportions

For small degrees of freedom, the chi-square distribution is:

For small degrees of freedom, the chi-square distribution is:

Rectangular

Rectangular

skewed to the left

skewed to the left

symmetric

symmetric

skewed to the right

skewed to the right

The alternative hypothesis is a claim about a:

The alternative hypothesis is a claim about a:

statistic, where the claim is assumed to be false until it is declared true

statistic, where the claim is assumed to be false until it is declared true

statistic, where the claim is assumed to be true if the null hypothesis is declared false

statistic, where the claim is assumed to be true if the null hypothesis is declared false

population parameter, where the claim is assumed to be true until it is declared false

population parameter, where the claim is assumed to be true until it is declared false

population parameter, where the claim is assumed to be true if the null hypothesis is declared false

population parameter, where the claim is assumed to be true if the null hypothesis is declared false

In a hypothesis test, a Type II error occurs when:

In a hypothesis test, a Type II error occurs when:

a false null hypothesis is rejected

a false null hypothesis is rejected

a true null hypothesis is rejected

a true null hypothesis is rejected

a true null hypothesis is not rejected

a true null hypothesis is not rejected

a false null hypothesis is not rejected

a false null hypothesis is not rejected

In a one-way ANOVA, we analyze only one:

In a one-way ANOVA, we analyze only one:

population

population

mean

mean

variable

variable

sample

sample