Which of the following best describes the p-value of a test? $\begin{array}{|l|l|} \hline A&\text {The \( p $-value is the probability of getting our statistical table value of the test statistic if }\\&\text {the null hypothesized value of the population parameter, were really true. }\\ \hline B&\text {The p-value is the probability of getting our cal culated test statistic or more extreme if the }\\&\text { null hypothesized value of the population parameter, were really true.}\\ \hline C&\text { The p-value is the probability of getting our calculated test statistic, or more extreme, if }\\&\text {the null hypothesized value of the population parameter, were really false. }\\ \hline D&\text {None of these choices are correct. }\\ \hline \end{array}\)

The answer of Which of the following best describes the...

In a criminal trial, a Type I error is made when: $\begin{array}{|l|l|} \hline A&\text {a guilty defendant is acquitted. }\\ \hline B&\text {an innocent person is convicted. }\\ \hline C&\text {a guilty defendant is convicted. }\\ \hline D&\text {an innocent person is acquitted. }\\ \hline \end{array}$

The answer of In a criminal trial, a Type I...

If the research question is not an equality statement, then in hypothesis testing it is specified as: $\begin{array}{|l|l|} \hline A.&\text { the null hypothesis.}\\ \hline B.&\text {either the null or the alternative hypothesis. }\\ \hline C.&\text { the alternative hypothesis.}\\ \hline D.&\text { the test statistic.}\\ \hline \end{array}$

The answer of If the research question is not an...

Using the confidence interval when conducting a two-tail test for the population mean $\mu$ we do not reject the null hypothesis if the hypothesised value for $\mu$ : $\begin{array}{|l|l|} \hline A.&\text { is to the left of the lower confidence limit (LCL).}\\ \hline B.&\text {is to the right of the upper confidence limit (UCL). }\\ \hline C.&\text { falls between the LCL and UCL.}\\ \hline D.&\text {falls in the rejection region. }\\ \hline \end{array}$

The answer of Using the confidence interval when conducting a...

Which of the following statements is (are) not true? $\begin{array}{|l|l|} \hline A&\text { The probability of making a Type II error increases as the probability of making a Type I } \\ &\text { error decreases. } \\ \hline B&\text { The probability of making a Type II error and the level of significance are the same. } \\ \hline C&\text { The power of the test decreases as the level of signi ficance decreases. } \\ \hline D&\text { None of the above statements are true. }\\ \hline \end{array}$

The answer of Which of the following statements is (are)...

A Type I error is committed if we make: $\begin{array}{|l|l|} \hline A.&\text { a correct decision when the null hypothesis is false. }\\ \hline B.&\text {correct decision when the null hypothesis is true. }\\ \hline C.&\text { incorrect decision when the null hypothesis is false. }\\ \hline D.&\text { incorrect decision when the null hypothesis is true.}\\ \hline \end{array}$

The answer of A Type I error is committed if...

For a two-tail Z test, the null hypothesis will be rejected at the 0.05 level of significance if the value of the standardised test statistic is: $\begin{array}{|l|l|} \hline \text { A. } & \text { smaller than }-1.645 \\ \hline \text { B. } & \text { greater than } 1.96 . \\ \hline \text { C. } & \text { smaller than }-1.645 \text { or greater than } 1.645 \\ \hline \text { D. } & \text { smaller than }-1.96 \text { or greater than } 1.96 \\ \hline \end{array}$

The answer of For a two-tail Z test, the null...

Exam 13: Hypothesis Testing: Describing a Single Population

Which of the following best describes the p-value of a test? A The p -value is the probability of getting our statistical table value of the test statistic if the null hypothesized value of the population parameter, were really true. B The p-value is the probability of getting our cal culated test statistic or more extreme if the null hypothesized value of the population parameter, were really true. C The p-value is the probability of getting our calculated test statistic, or more extreme, if the null hypothesized value of the population parameter, were really false. D None of these choices are correct.

(Short Answer)

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Question 21

Which of the following statements best describes the level of significance? A The smaller the level of significance, the larger the rejection region, so therefore the tighter the test. B The larger the level of significance, the smaller the rejection region, so therefore the tighter the test. C The smaller the level of significance, the smaller the rejection region, so therefore the tighter the test. D None of these choices are correct

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Question 22

If the p-value for a one tailed test is 0.03, would you have the same conclusion at a significance level of 0.05 and at a significance level of 0.10?

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Question 23

Reducing the probability of a Type I error, increases the probability of a Type II error.

(True/False)

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Question 24

In a criminal trial, a Type I error is made when: A a guilty defendant is acquitted. B an innocent person is convicted. C a guilty defendant is convicted. D an innocent person is acquitted.

(Short Answer)

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Question 25

If the research question is not an equality statement, then in hypothesis testing it is specified as: A. the null hypothesis. B. either the null or the alternative hypothesis. C. the alternative hypothesis. D. the test statistic.

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Question 26

In testing the hypotheses: $H _ { 0 } : \mu = 25$ $H _ { 1 } : \mu \neq 25$ , a random sample of 36 observations drawn from a normal population whose standard deviation is 10 produced a mean of 22.8. Compute the p-value.

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Question 27

Using the confidence interval when conducting a two-tail test for the population mean $\mu$ we do not reject the null hypothesis if the hypothesised value for $\mu$ : A. is to the left of the lower confidence limit (LCL). B. is to the right of the upper confidence limit (UCL). C. falls between the LCL and UCL. D. falls in the rejection region.

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Question 28

Consider the hypotheses $H _ { 0 } : \mu = 950$ $H _ { 1 } : \mu \neq 950$ . Assume that $\mu = 1000 ,$ $\alpha = 0.10$ $\sigma = 200$ , and n = 25 and $\beta$ = 0.6535 Recalculate $\beta$ if n is increased from 25 to 40.

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Question 29

An alternative or research hypothesis is an assertion that holds if the null hypothesis is false.

(True/False)

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Question 30

In testing the hypotheses $H _ { 0 } : \mu = 20$ . $H _ { 1 } : \mu < 20$ . the following information was given: $\sigma = 8.1 , \quad n = 100 , \quad \bar { x } = 18.1 , \quad \alpha = 0.025$ . a. Calculate the value of the test statistic. b. Set up the rejection region. c. Determine the p-value. d. Interpret the result.

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Question 31

The manager of a sports store is considering trading on Public holidays. She believes that a majority of consumers would consider visiting the sports store on a Public holiday. She takes a random sample of 50 customers and finds that 29 would visit the sports store on a Public holiday. Is there significant evidence to support the manager's claim? Test at the 5% level of significance.

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Question 32

Which of the following statements is (are) not true? A The probability of making a Type II error increases as the probability of making a Type I error decreases. B The probability of making a Type II error and the level of significance are the same. C The power of the test decreases as the level of signi ficance decreases. D None of the above statements are true.

(Short Answer)

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Question 33

If we reject the null hypothesis, we conclude that there is enough statistical evidence to infer that the alternative hypothesis is true.

(True/False)

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Question 34

A social scientist claims that the average adult watches less than 26 hours of television per week. He collects data on 25 individuals' television viewing habits, and finds that the mean number of hours that the 25 people spent watching television was 22.4 hours. If the population standard deviation is known to be 8 hours, can we conclude at the 1% significance level that he is right?

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Question 35

A Type I error is committed if we make: A. a correct decision when the null hypothesis is false. B. correct decision when the null hypothesis is true. C. incorrect decision when the null hypothesis is false. D. incorrect decision when the null hypothesis is true.

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Question 36

In a two-tail test for the population mean, the null hypothesis will be rejected at the $\alpha$ level of significance if the value of the standardised test statistic z is such that: A. z>. B. z<-. C. -.

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Question 37

For a two-tail Z test, the null hypothesis will be rejected at the 0.05 level of significance if the value of the standardised test statistic is: A. smaller than -1.645 B. greater than 1.96. C. smaller than -1.645 or greater than 1.645 D. smaller than -1.96 or greater than 1.96

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Question 38

If a hypothesis is rejected at the 0.025 level of significance, it: A. must be rejected at any level. B. must be rejected at the 0.01 level. C. must not be rejected at the 0.01 level. D. may be rejected or not rejected at the 0.01 level.

(Short Answer)

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Question 39

A Type II error is represented by $\beta$ and is the probability of failing to reject a false null hypothesis.

(True/False)

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Question 40

If the p-value for a one tailed test is 0.03, would you have the same conclusion at a significance level of 0.05 and at a significance level of 0.10?

Reducing the probability of a Type I error, increases the probability of a Type II error.

In a criminal trial, a Type I error is made when: A a guilty defendant is acquitted. B an innocent person is convicted. C a guilty defendant is convicted. D an innocent person is acquitted.

If the research question is not an equality statement, then in hypothesis testing it is specified as: A. the null hypothesis. B. either the null or the alternative hypothesis. C. the alternative hypothesis. D. the test statistic.

In testing the hypotheses: $H _ { 0 } : \mu = 25$ $H _ { 1 } : \mu \neq 25$ , a random sample of 36 observations drawn from a normal population whose standard deviation is 10 produced a mean of 22.8. Compute the p-value.

Consider the hypotheses $H _ { 0 } : \mu = 950$ $H _ { 1 } : \mu \neq 950$ . Assume that $\mu = 1000 ,$ $\alpha = 0.10$ $\sigma = 200$ , and n = 25 and $\beta$ = 0.6535 Recalculate $\beta$ if n is increased from 25 to 40.

An alternative or research hypothesis is an assertion that holds if the null hypothesis is false.

If we reject the null hypothesis, we conclude that there is enough statistical evidence to infer that the alternative hypothesis is true.

A Type I error is committed if we make: A. a correct decision when the null hypothesis is false. B. correct decision when the null hypothesis is true. C. incorrect decision when the null hypothesis is false. D. incorrect decision when the null hypothesis is true.

In a two-tail test for the population mean, the null hypothesis will be rejected at the $\alpha$ level of significance if the value of the standardised test statistic z is such that: A. z>. B. z<-. C. -.

For a two-tail Z test, the null hypothesis will be rejected at the 0.05 level of significance if the value of the standardised test statistic is: A. smaller than -1.645 B. greater than 1.96. C. smaller than -1.645 or greater than 1.645 D. smaller than -1.96 or greater than 1.96

If a hypothesis is rejected at the 0.025 level of significance, it: A. must be rejected at any level. B. must be rejected at the 0.01 level. C. must not be rejected at the 0.01 level. D. may be rejected or not rejected at the 0.01 level.

A Type II error is represented by $\beta$ and is the probability of failing to reject a false null hypothesis.

What Is Statistics

Types of Data, Data Collection and Sampling

Graphical Descriptive Methods Nominal Data

Graphical Descriptive Techniques Numerical Data

Numerical Descriptive Measures

Probability

Random Variables and Discrete Probability Distributions

Continuous Probability Distributions

Statistical Inference: Introduction

Sampling Distributions

Estimation: Describing a Single Population

Estimation: Comparing Two Populations

Hypothesis Testing: Comparing Two Populations

Inference About Population Variances

Analysis of Variance

Additional Tests for Nominal Data: Chi-Squared Tests

Simple Linear Regression and Correlation

Multiple Regression

Model Building

Nonparametric Techniques

Statistical Inference: Conclusion

Time-Series Analysis and Forecasting

Index Numbers

Decision Analysis

Filters

Exam 13: Hypothesis Testing: Describing a Single Population

If the p-value for a one tailed test is 0.03, would you have the same conclusion at a significance level of 0.05 and at a significance level of 0.10?

Reducing the probability of a Type I error, increases the probability of a Type II error.

In a criminal trial, a Type I error is made when: A a guilty defendant is acquitted. B an innocent person is convicted. C a guilty defendant is convicted. D an innocent person is acquitted.

If the research question is not an equality statement, then in hypothesis testing it is specified as: A. the null hypothesis. B. either the null or the alternative hypothesis. C. the alternative hypothesis. D. the test statistic.

In testing the hypotheses: H0:μ=25H _ { 0 } : \mu = 25H0​:μ=25 H1:μ≠25H _ { 1 } : \mu \neq 25H1​:μ=25 , a random sample of 36 observations drawn from a normal population whose standard deviation is 10 produced a mean of 22.8. Compute the p-value.

An alternative or research hypothesis is an assertion that holds if the null hypothesis is false.

If we reject the null hypothesis, we conclude that there is enough statistical evidence to infer that the alternative hypothesis is true.

A Type I error is committed if we make: A. a correct decision when the null hypothesis is false. B. correct decision when the null hypothesis is true. C. incorrect decision when the null hypothesis is false. D. incorrect decision when the null hypothesis is true.

In a two-tail test for the population mean, the null hypothesis will be rejected at the α\alphaα level of significance if the value of the standardised test statistic z is such that: A. z>. B. z<-. C. -.

For a two-tail Z test, the null hypothesis will be rejected at the 0.05 level of significance if the value of the standardised test statistic is: A. smaller than -1.645 B. greater than 1.96. C. smaller than -1.645 or greater than 1.645 D. smaller than -1.96 or greater than 1.96

If a hypothesis is rejected at the 0.025 level of significance, it: A. must be rejected at any level. B. must be rejected at the 0.01 level. C. must not be rejected at the 0.01 level. D. may be rejected or not rejected at the 0.01 level.

A Type II error is represented by β\betaβ and is the probability of failing to reject a false null hypothesis.

What Is Statistics

Types of Data, Data Collection and Sampling

Graphical Descriptive Methods Nominal Data

Graphical Descriptive Techniques Numerical Data

Numerical Descriptive Measures

Probability

Random Variables and Discrete Probability Distributions

Continuous Probability Distributions

Statistical Inference: Introduction

Sampling Distributions

Estimation: Describing a Single Population

Estimation: Comparing Two Populations

Hypothesis Testing: Comparing Two Populations

Inference About Population Variances

Analysis of Variance

Additional Tests for Nominal Data: Chi-Squared Tests

Simple Linear Regression and Correlation

Multiple Regression

Model Building

Nonparametric Techniques

Statistical Inference: Conclusion

Time-Series Analysis and Forecasting

Index Numbers

Decision Analysis

Filters

In testing the hypotheses: $H _ { 0 } : \mu = 25$ $H _ { 1 } : \mu \neq 25$ , a random sample of 36 observations drawn from a normal population whose standard deviation is 10 produced a mean of 22.8. Compute the p-value.

In a two-tail test for the population mean, the null hypothesis will be rejected at the $\alpha$ level of significance if the value of the standardised test statistic z is such that: A. z>. B. z<-. C. -.

A Type II error is represented by $\beta$ and is the probability of failing to reject a false null hypothesis.