Exam 8: Introduction to Hypothesis Testing

A sample of n = 16 individuals is selected from a population with μ = 60 and σ = 6 and a treatment is administered to the sample.After treatment, the sample mean is M = 63.What is the value of Cohen's d for this sample?

(Multiple Choice)

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Question 21

Which of the following correctly describes the effect of increasing the alpha level (for example from .01 to .05)?

(Multiple Choice)

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Question 22

Which of the following accurately describes the effect of increasing the alpha level?

(Multiple Choice)

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Question 23

A researcher administers a treatment to a sample from a population with a mean of $\mu$ = 60.If the treatment is expected to increase scores and a one-tailed test is used to evaluate the treatment effect, then the null hypothesis states that $\mu$ $\geq$ 60.

(True/False)

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Question 24

Which of the following is an accurate definition for the power of a statistical test?

(Multiple Choice)

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Question 25

The alpha level determines the risk of a Type I error.

(True/False)

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Question 26

Which of the following accurately describes the effect of increasing the sample size?

(Multiple Choice)

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Question 27

A Type I error occurs when a researcher concludes that a treatment has an effect but, in fact, the treatment has no effect.

(True/False)

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Question 28

A researcher conducts a hypothesis test to evaluate the effect of a treatment that is expected to increase scores.The hypothesis test produces a z-score of z = 2.37.If the researcher is using a one-tailed test, what is the correct statistical decision?

(Multiple Choice)

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Question 29

The value obtained for Cohen's d is independent of the sample size.

(True/False)

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Question 30

You can reduce the risk of a Type I error by using a larger sample.

(True/False)

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Question 31

What is the relationship between the alpha level, the size of the critical region, and the risk of a Type I error?

(Multiple Choice)

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Question 32

What is the consequence of a Type II error?

(Multiple Choice)

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Question 33

A researcher conducts a hypothesis test to evaluate the effect of a treatment.The hypothesis test produces a z-score of z = 2.37.Assuming that the researcher is using a two-tailed test, what decision should be made?

(Multiple Choice)

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Question 34

If other factors are held constant, the larger the size of the treatment effect, the greater the power of the hypothesis test.

(True/False)

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Question 35

A researcher administers a treatment to a sample of participants selected from a population with µ = 80.If a hypothesis test is used to evaluate the effect of the treatment, which combination of factors is most likely to result in rejecting the null hypothesis?

(Multiple Choice)

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Question 36

If the research prediction is that the treatment will decrease scores, then the critical region for a directional test will be in the left?hand tail.

(True/False)

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Question 37

A researcher administers a treatment to a sample of n = 16 selected from a population with $\mu$ = 40 and $\sigma$ = 8.If the sample mean after treatment is M = 42, then Cohen's d = 1.00.

(True/False)

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Question 38

If other factors are held constant, then increasing the sample size will increase the likelihood of rejecting the null hypothesis.

(True/False)

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Question 39

When is there a risk of a Type II error?

(Multiple Choice)

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Question 40

Showing 21 - 40 of 69

A sample of n = 16 individuals is selected from a population with μ = 60 and σ = 6 and a treatment is administered to the sample.After treatment, the sample mean is M = 63.What is the value of Cohen's d for this sample?

Which of the following correctly describes the effect of increasing the alpha level (for example from .01 to .05)?

Which of the following accurately describes the effect of increasing the alpha level?

A researcher administers a treatment to a sample from a population with a mean of $\mu$ = 60.If the treatment is expected to increase scores and a one-tailed test is used to evaluate the treatment effect, then the null hypothesis states that $\mu$ $\geq$ 60.

Which of the following is an accurate definition for the power of a statistical test?

The alpha level determines the risk of a Type I error.

Which of the following accurately describes the effect of increasing the sample size?

A Type I error occurs when a researcher concludes that a treatment has an effect but, in fact, the treatment has no effect.

A researcher conducts a hypothesis test to evaluate the effect of a treatment that is expected to increase scores.The hypothesis test produces a z-score of z = 2.37.If the researcher is using a one-tailed test, what is the correct statistical decision?

The value obtained for Cohen's d is independent of the sample size.

You can reduce the risk of a Type I error by using a larger sample.

What is the relationship between the alpha level, the size of the critical region, and the risk of a Type I error?

What is the consequence of a Type II error?

A researcher conducts a hypothesis test to evaluate the effect of a treatment.The hypothesis test produces a z-score of z = 2.37.Assuming that the researcher is using a two-tailed test, what decision should be made?

If other factors are held constant, the larger the size of the treatment effect, the greater the power of the hypothesis test.

A researcher administers a treatment to a sample of participants selected from a population with µ = 80.If a hypothesis test is used to evaluate the effect of the treatment, which combination of factors is most likely to result in rejecting the null hypothesis?

If the research prediction is that the treatment will decrease scores, then the critical region for a directional test will be in the left?hand tail.

A researcher administers a treatment to a sample of n = 16 selected from a population with $\mu$ = 40 and $\sigma$ = 8.If the sample mean after treatment is M = 42, then Cohen's d = 1.00.

If other factors are held constant, then increasing the sample size will increase the likelihood of rejecting the null hypothesis.

When is there a risk of a Type II error?

Introduction to Statistics

Frequency Distributions

Central Tendency

Variability

Z-Scores

Probability

The Distribution of Sample Means

Introduction to the T Statistic

The T Test for Two Independent Samples

The T Test for Two Related Samples

Introduction to Analysis of Variance

Repeated-Measures Anova

Two-Factor Analysis of Variance

Correlation

Introduction to Regression

Chi-Square Tests

The Binomial Test

Choosing the Right Statistics

Filters

Exam 8: Introduction to Hypothesis Testing

A sample of n = 16 individuals is selected from a population with μ = 60 and σ = 6 and a treatment is administered to the sample.After treatment, the sample mean is M = 63.What is the value of Cohen's d for this sample?

Which of the following correctly describes the effect of increasing the alpha level (for example from .01 to .05)?

Which of the following accurately describes the effect of increasing the alpha level?

A researcher administers a treatment to a sample from a population with a mean of μ\muμ = 60.If the treatment is expected to increase scores and a one-tailed test is used to evaluate the treatment effect, then the null hypothesis states that μ\muμ ≥\geq≥ 60.

Which of the following is an accurate definition for the power of a statistical test?

The alpha level determines the risk of a Type I error.

Which of the following accurately describes the effect of increasing the sample size?

A Type I error occurs when a researcher concludes that a treatment has an effect but, in fact, the treatment has no effect.

A researcher conducts a hypothesis test to evaluate the effect of a treatment that is expected to increase scores.The hypothesis test produces a z-score of z = 2.37.If the researcher is using a one-tailed test, what is the correct statistical decision?

The value obtained for Cohen's d is independent of the sample size.

You can reduce the risk of a Type I error by using a larger sample.

What is the relationship between the alpha level, the size of the critical region, and the risk of a Type I error?

What is the consequence of a Type II error?

A researcher conducts a hypothesis test to evaluate the effect of a treatment.The hypothesis test produces a z-score of z = 2.37.Assuming that the researcher is using a two-tailed test, what decision should be made?

If other factors are held constant, the larger the size of the treatment effect, the greater the power of the hypothesis test.

A researcher administers a treatment to a sample of participants selected from a population with µ = 80.If a hypothesis test is used to evaluate the effect of the treatment, which combination of factors is most likely to result in rejecting the null hypothesis?

If the research prediction is that the treatment will decrease scores, then the critical region for a directional test will be in the left?hand tail.

A researcher administers a treatment to a sample of n = 16 selected from a population with μ\muμ = 40 and σ\sigmaσ = 8.If the sample mean after treatment is M = 42, then Cohen's d = 1.00.

If other factors are held constant, then increasing the sample size will increase the likelihood of rejecting the null hypothesis.

When is there a risk of a Type II error?

Introduction to Statistics

Frequency Distributions

Central Tendency

Variability

Z-Scores

Probability

The Distribution of Sample Means

Introduction to the T Statistic

The T Test for Two Independent Samples

The T Test for Two Related Samples

Introduction to Analysis of Variance

Repeated-Measures Anova

Two-Factor Analysis of Variance

Correlation

Introduction to Regression

Chi-Square Tests

The Binomial Test

Choosing the Right Statistics

Filters

A researcher administers a treatment to a sample from a population with a mean of $\mu$ = 60.If the treatment is expected to increase scores and a one-tailed test is used to evaluate the treatment effect, then the null hypothesis states that $\mu$ $\geq$ 60.

A researcher administers a treatment to a sample of n = 16 selected from a population with $\mu$ = 40 and $\sigma$ = 8.If the sample mean after treatment is M = 42, then Cohen's d = 1.00.