Question 1

A Type II error is committed when we incorrectly accept an alternative hypothesis that is false.

Accepted Answer

A) True 
 B)False

Question 2

The idea of the chi-square test for independence is to:

Accepted Answer

A)  compare the quantile-quantile (Q-Q)plot with what would be expected under independence 
B)  compare the actual counts in a contingency table with what would be expected under independence 
C)  compare the cumulative distribution with what would be expected under independence 
D)  None of these options 
A)  compare the quantile-quantile (Q-Q)plot with what would be expected under independence 
B)  compare the actual counts in a contingency table with what would be expected under independence 
C)  compare the cumulative distribution with what would be expected under independence 
D)  None of these options

Question 3

The probability of making a Type I error and the level of significance $\alpha$ 
are the same.

Accepted Answer

A) True 
 B)False

Question 4

Tests in which samples are not independent are referred to as matched pairs or paired samples.

Accepted Answer

A) True 
 B)False

Question 5

When testing the equality of two population variances,the test statistic is the ratio of the population variances;namely $$\sigma _ { 1 } ^ { 2 } / \sigma _ { 2 } ^ { 2 }$$ 
.

Accepted Answer

A) True 
 B)False

Question 6

A test with a 0.05 significance level has a larger rejection region than a test with a 0.01 significance level.

Accepted Answer

A) True 
 B)False

Question 7

A null hypothesis is a statement about the value of a population parameter.It is usually the current thinking,or "status quo".

Accepted Answer

A) True 
 B)False

Question 8

A type I error occurs when the:

Accepted Answer

A)  null hypothesis is incorrectly accepted when it is false 
B)  null hypothesis is incorrectly rejected when it is true 
C)  sample mean differs from the population mean 
D)  test is biased 
A)  null hypothesis is incorrectly accepted when it is false 
B)  null hypothesis is incorrectly rejected when it is true 
C)  sample mean differs from the population mean 
D)  test is biased

Question 9

In statistical analysis,the burden of proof lies traditionally with the:

Accepted Answer

A)  alternative hypothesis 
B)  null hypothesis 
C)  analyst 
D)  facts presented to the statistical analyst 
A)  alternative hypothesis 
B)  null hypothesis 
C)  analyst 
D)  facts presented to the statistical analyst

Question 10

In conducting hypothesis testing for difference between two means when samples are dependent (paired samples),the variable under consideration is $$D$$ 
;the sample mean difference between the pairs.

Accepted Answer

A) True 
 B)False

Question 11

The value set for $a$
Is known as:

Accepted Answer

A)  the rejection level 
B)  the acceptance level 
C)  the significance level 
D)  the error in the hypothesis test 
A)  the rejection level 
B)  the acceptance level 
C)  the significance level 
D)  the error in the hypothesis test

Question 12

Type I errors are usually considered more "costly" although this can lead to conservative decision making.

Accepted Answer

A) True 
 B)False

Question 13

A Type I error probability is represented by $\alpha$ 
;it is the probability of incorrectly rejecting a null hypothesis that is true.

Accepted Answer

A) True 
 B)False

Question 14

Which of the following statements are true of the null and alternative hypotheses?

Accepted Answer

A)  Exactly one hypothesis must be true 
B)  Both hypotheses must be true 
C)  It is possible for both hypotheses to be true 
D)  It is possible for neither hypothesis to be true 
A)  Exactly one hypothesis must be true 
B)  Both hypotheses must be true 
C)  It is possible for both hypotheses to be true 
D)  It is possible for neither hypothesis to be true

Question 15

A two-tailed test is one where:

Accepted Answer

A)  results in only one direction can lead to rejection of the null hypothesis 
B)  negative sample means lead to rejection of the null hypothesis 
C)  results in either of two directions can lead to rejection of the null hypothesis 
D)  no results lead to the rejection of the null hypothesis 
A)  results in only one direction can lead to rejection of the null hypothesis 
B)  negative sample means lead to rejection of the null hypothesis 
C)  results in either of two directions can lead to rejection of the null hypothesis 
D)  no results lead to the rejection of the null hypothesis

Question 16

Sample evidence is statistically significant at the $a$ 
level only if the p-value is larger than $a$ 
.

Accepted Answer

A) True 
 B)False

Question 17

The test statistic for a hypothesis test of a population proportion is the z-value.

Accepted Answer

A) True 
 B)False

Question 18

An informal test for normality that utilizes a scatterplot and looks for clustering around a 45° line is known as a(n):

Accepted Answer

A)  Lilliefors test 
B)  empirical cumulative distribution function 
C)  p-test 
D)  quantile-quantile plot 
A)  Lilliefors test 
B)  empirical cumulative distribution function 
C)  p-test 
D)  quantile-quantile plot

Question 19

Which of the following signs is possible in an alternative hypothesis?

Accepted Answer

A) > B) < C) ≠ D) All of these options A) > B) < C) ≠ D) All of these options

Question 20

A type II error occurs when:

Accepted Answer

A)  the null hypothesis is incorrectly accepted when it is false 
B)  the null hypothesis is incorrectly rejected when it is true 
C)  the sample mean differs from the population mean 
D)  the test is biased 
A)  the null hypothesis is incorrectly accepted when it is false 
B)  the null hypothesis is incorrectly rejected when it is true 
C)  the sample mean differs from the population mean 
D)  the test is biased

A Type II error is committed when we incorrectly accept an alternative hypothesis that is false.

The idea of the chi-square test for independence is to:

The probability of making a Type I error and the level of significance $\alpha$ are the same.

Tests in which samples are not independent are referred to as matched pairs or paired samples.

When testing the equality of two population variances,the test statistic is the ratio of the population variances;namely $\sigma _ { 1 } ^ { 2 } / \sigma _ { 2 } ^ { 2 }$ .

A test with a 0.05 significance level has a larger rejection region than a test with a 0.01 significance level.

A null hypothesis is a statement about the value of a population parameter.It is usually the current thinking,or "status quo".

A type I error occurs when the:

In statistical analysis,the burden of proof lies traditionally with the:

In conducting hypothesis testing for difference between two means when samples are dependent (paired samples),the variable under consideration is $D$ ;the sample mean difference between the pairs.

The value set for $a$ Is known as:

Type I errors are usually considered more "costly" although this can lead to conservative decision making.

A Type I error probability is represented by $\alpha$ ;it is the probability of incorrectly rejecting a null hypothesis that is true.

Which of the following statements are true of the null and alternative hypotheses?

A two-tailed test is one where:

Sample evidence is statistically significant at the $a$ level only if the p-value is larger than $a$ .

The test statistic for a hypothesis test of a population proportion is the z-value.

An informal test for normality that utilizes a scatterplot and looks for clustering around a 45° line is known as a(n):

Which of the following signs is possible in an alternative hypothesis?

A type II error occurs when:

Introduction to Data Analysis and Decision Making

Describing the Distribution of a Single Variable

Finding Relationships Among Variables

Probability and Probability Distributions

Normal, Binomial, Poisson, and Exponential Distributions

Decision Making Under Uncertainty

Sampling and Sampling Distributions

Confidence Interval Estimation

Regression Analysis: Estimating Relationships

Regression Analysis: Statistical Inference

Time Series Analysis and Forecasting

Introduction to Optimization Modeling

Optimization Models

Introduction to Simulation Modeling

Simulation Models

Data Mining

Importing Data Into Excel

Analysis of Variance and Experimental Design

Statistical Process Control

Filters

Exam 9: Hypothesis Testing

A Type II error is committed when we incorrectly accept an alternative hypothesis that is false.

The idea of the chi-square test for independence is to:

The probability of making a Type I error and the level of significance α\alphaα are the same.

Tests in which samples are not independent are referred to as matched pairs or paired samples.

When testing the equality of two population variances,the test statistic is the ratio of the population variances;namely σ12/σ22\sigma _ { 1 } ^ { 2 } / \sigma _ { 2 } ^ { 2 }σ12​/σ22​ .

A test with a 0.05 significance level has a larger rejection region than a test with a 0.01 significance level.

A null hypothesis is a statement about the value of a population parameter.It is usually the current thinking,or "status quo".

A type I error occurs when the:

In statistical analysis,the burden of proof lies traditionally with the:

In conducting hypothesis testing for difference between two means when samples are dependent (paired samples),the variable under consideration is DDD ;the sample mean difference between the pairs.

The value set for aaa Is known as:

Type I errors are usually considered more "costly" although this can lead to conservative decision making.

A Type I error probability is represented by α\alphaα ;it is the probability of incorrectly rejecting a null hypothesis that is true.

Which of the following statements are true of the null and alternative hypotheses?

A two-tailed test is one where:

Sample evidence is statistically significant at the aaa level only if the p-value is larger than aaa .

The test statistic for a hypothesis test of a population proportion is the z-value.

An informal test for normality that utilizes a scatterplot and looks for clustering around a 45° line is known as a(n):

Which of the following signs is possible in an alternative hypothesis?

A type II error occurs when:

Introduction to Data Analysis and Decision Making

Describing the Distribution of a Single Variable

Finding Relationships Among Variables

Probability and Probability Distributions

Normal, Binomial, Poisson, and Exponential Distributions

Decision Making Under Uncertainty

Sampling and Sampling Distributions

Confidence Interval Estimation

Regression Analysis: Estimating Relationships

Regression Analysis: Statistical Inference

Time Series Analysis and Forecasting

Introduction to Optimization Modeling

Optimization Models

Introduction to Simulation Modeling

Simulation Models

Data Mining

Importing Data Into Excel

Analysis of Variance and Experimental Design

Statistical Process Control

Filters

The probability of making a Type I error and the level of significance $\alpha$ are the same.

When testing the equality of two population variances,the test statistic is the ratio of the population variances;namely $\sigma _ { 1 } ^ { 2 } / \sigma _ { 2 } ^ { 2 }$ .

In conducting hypothesis testing for difference between two means when samples are dependent (paired samples),the variable under consideration is $D$ ;the sample mean difference between the pairs.

The value set for $a$ Is known as:

A Type I error probability is represented by $\alpha$ ;it is the probability of incorrectly rejecting a null hypothesis that is true.

Sample evidence is statistically significant at the $a$ level only if the p-value is larger than $a$ .