Data Set 9-3: N = 8 $\Sigma$X = 48 $\Sigma$XS1U1P12S1S1P0 = 351 -Refer to Data Set 9-3. For H0: µ = 9.00, the effect size index is

A) 2.83 B) 1.00 C) 0.94 D) none of the other alternatives are correct. A) 2.83 B) 1.00 C) 0.94 D) none of the other alternatives are correct.

A) the null hypothesis should be retained B) the difference analyzed by a t test is statistically significant C) both of the descriptive alternatives are correct D) neither of the descriptive alternatives is correct. A) the null hypothesis should be retained B) the difference analyzed by a t test is statistically significant C) both of the descriptive alternatives are correct D) neither of the descriptive alternatives is correct.

Data Set 9-1: Sample scores: 2, 3, 4 -The t value when the scores in Data Set 9-1 are tested against H0: $\mu$ = 4.00 leads to the conclusion that the null hypothesis be

A) rejected at the .05 level for a two-tailed test B) rejected at the .05 and .01 level for a two-tailed test C) rejected at the .05 level for a one-tailed test D) retained. A) rejected at the .05 level for a two-tailed test B) rejected at the .05 and .01 level for a two-tailed test C) rejected at the .05 level for a one-tailed test D) retained.

Data Set 9-2: Scores: 1, 2, 3, 4, 5 -Refer to Data Set 9-2. For H0: $\mu$ = 4.00, the effect size index is

A) 1.41 B) 0.63 C) 0.57 D) none of the other alternatives are correct. A) 1.41 B) 0.63 C) 0.57 D) none of the other alternatives are correct.

Data Set 9-1: Sample scores: 2, 3, 4 -Refer to Data Set 9-1. For H0: $\mu$ = 1.00, the effect size index is

A) 3.47 B) 2.00 C) 1.41 D) none of the other alternatives are correct. A) 3.47 B) 2.00 C) 1.41 D) none of the other alternatives are correct.

Exam 9: Hypothesis Testing and Effect Size: One-Sample Designs

According to your text, the motivation of the agricultural scientists (agronomists) who selected 30:1 as the point separating differences due to chance from those not due to chance, was

(Multiple Choice)

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(42)

Question 101

The issue of the amount of difference between the mean of the population the sample is from and the mean of the null hypothesis population is the issue of

(Multiple Choice)

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(33)

Question 102

Data Set 9-3: N = 8 $\Sigma$ X = 48 $\Sigma$ X² = 351 -Refer to Data Set 9-3. For H₀: µ = 9.00, the effect size index is

(Multiple Choice)

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(41)

Question 103

Probabilities were calculated for both sample means and sample medians in Chapter 9.

(True/False)

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Question 104

Odometers measure distance traveled. How accurate are automobile odometers? As part of a project for a statistics class, two students borrowed several cars and drove them over a 10 mile course. Using the odometer readings that follow, perform a t test, calculate the effect size index, and write a conclusion about odometers.10.1 , 9.9 , 10.1 , 10.3 , 10.0 , 10.2 , 10.1

(Essay)

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Question 105

A correlation coefficient of .72 based on 7 pairs is, for a two-tailed test,

(Multiple Choice)

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Question 106

"p < .05"means that

(Multiple Choice)

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Question 107

Values of d larger than 1.00 are not possible.

(True/False)

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Question 108

Suppose the difference between a sample mean and the null hypothesis mean was in the rejection region of the sampling distribution. This means that the difference is

(Multiple Choice)

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Question 109

Data Set 9-2: Scores: 1, 2, 3, 4, 5 -The value of the standard error of the mean for the scores in Data Set 9-2 is

(Multiple Choice)

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Question 110

The issue of the amount of difference between a population with an unknown mean (which you sample from) and a null hypothesis population (µ₀= 8) is the issue of

(Multiple Choice)

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Question 111

Data Set 9-1: Sample scores: 2, 3, 4 -The t value when the scores in Data Set 9-1 are tested against H₀: $\mu$ = 4.00 leads to the conclusion that the null hypothesis be

(Multiple Choice)

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Question 112

Data Set 9-2: Scores: 1, 2, 3, 4, 5 -Refer to Data Set 9-2. For H₀: $\mu$ = 4.00, the effect size index is

(Multiple Choice)

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Question 113

Data Set 9-1: Sample scores: 2, 3, 4 -Refer to Data Set 9-1. For H₀: $\mu$ = 1.00, the effect size index is

(Multiple Choice)

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Question 114

A t test value that is larger than the tabled value of t

(Multiple Choice)

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Question 115

Which alternative is most closely related to the concept of a two-tailed test of significance?

(Multiple Choice)

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Question 116

In statistics, a significant difference is one that is

(Multiple Choice)

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Question 117

For a one-sample t test, an effect size that is considered small is

(Multiple Choice)

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Question 118

Data were gathered, the results analyzed, and H_l accepted. Based on the logic of hypothesis testing, you can conclude that

(Multiple Choice)

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Question 119

Which of the following is(are) null hypothesis(ses)?

(Multiple Choice)

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Question 120

Showing 101 - 120 of 157

According to your text, the motivation of the agricultural scientists (agronomists) who selected 30:1 as the point separating differences due to chance from those not due to chance, was

The issue of the amount of difference between the mean of the population the sample is from and the mean of the null hypothesis population is the issue of

Data Set 9-3: N = 8 $\Sigma$ X = 48 $\Sigma$ X² = 351 -Refer to Data Set 9-3. For H₀: µ = 9.00, the effect size index is

Probabilities were calculated for both sample means and sample medians in Chapter 9.

A correlation coefficient of .72 based on 7 pairs is, for a two-tailed test,

"p < .05"means that

Values of d larger than 1.00 are not possible.

Suppose the difference between a sample mean and the null hypothesis mean was in the rejection region of the sampling distribution. This means that the difference is

Data Set 9-2: Scores: 1, 2, 3, 4, 5 -The value of the standard error of the mean for the scores in Data Set 9-2 is

The issue of the amount of difference between a population with an unknown mean (which you sample from) and a null hypothesis population (µ₀= 8) is the issue of

Data Set 9-1: Sample scores: 2, 3, 4 -The t value when the scores in Data Set 9-1 are tested against H₀: $\mu$ = 4.00 leads to the conclusion that the null hypothesis be

Data Set 9-2: Scores: 1, 2, 3, 4, 5 -Refer to Data Set 9-2. For H₀: $\mu$ = 4.00, the effect size index is

Data Set 9-1: Sample scores: 2, 3, 4 -Refer to Data Set 9-1. For H₀: $\mu$ = 1.00, the effect size index is

A t test value that is larger than the tabled value of t

Which alternative is most closely related to the concept of a two-tailed test of significance?

In statistics, a significant difference is one that is

For a one-sample t test, an effect size that is considered small is

Data were gathered, the results analyzed, and H_l accepted. Based on the logic of hypothesis testing, you can conclude that

Which of the following is(are) null hypothesis(ses)?

Introduction

Exploring Data: Frequency Distributions and Graphs

Exploring Data: Central Tendency

Exploring Data: Variability

Other Descriptive Statistics

Correlation and Regression

Theoretical Distributions Including the Normal Distribution

Samples, Sampling Distributions, and Confidence Intervals

Hypothesis Testing, Effect Size, and and Confidence Intervals: Two-Sample Designs

Analysis of Variance: One-Way Classification

Analysis of Variance: One-Factor Repeated Measures

Analysis of Variance: Factorial Design

Chi Square Tests

More Nonparametric Tests

Appendix: Grouped Frequency Distributions and Central Tendency

Filters

Exam 9: Hypothesis Testing and Effect Size: One-Sample Designs

According to your text, the motivation of the agricultural scientists (agronomists) who selected 30:1 as the point separating differences due to chance from those not due to chance, was

The issue of the amount of difference between the mean of the population the sample is from and the mean of the null hypothesis population is the issue of

Data Set 9-3: N = 8 Σ\SigmaΣ X = 48 Σ\SigmaΣ X2 = 351 -Refer to Data Set 9-3. For H0: µ = 9.00, the effect size index is

Probabilities were calculated for both sample means and sample medians in Chapter 9.

A correlation coefficient of .72 based on 7 pairs is, for a two-tailed test,

"p < .05"means that

Values of d larger than 1.00 are not possible.

Suppose the difference between a sample mean and the null hypothesis mean was in the rejection region of the sampling distribution. This means that the difference is

Data Set 9-2: Scores: 1, 2, 3, 4, 5 -The value of the standard error of the mean for the scores in Data Set 9-2 is

The issue of the amount of difference between a population with an unknown mean (which you sample from) and a null hypothesis population (µ0 = 8) is the issue of

Data Set 9-1: Sample scores: 2, 3, 4 -The t value when the scores in Data Set 9-1 are tested against H0: μ\muμ = 4.00 leads to the conclusion that the null hypothesis be

Data Set 9-2: Scores: 1, 2, 3, 4, 5 -Refer to Data Set 9-2. For H0: μ\muμ = 4.00, the effect size index is

Data Set 9-1: Sample scores: 2, 3, 4 -Refer to Data Set 9-1. For H0: μ\muμ = 1.00, the effect size index is

A t test value that is larger than the tabled value of t

Which alternative is most closely related to the concept of a two-tailed test of significance?

In statistics, a significant difference is one that is

For a one-sample t test, an effect size that is considered small is

Data were gathered, the results analyzed, and Hl accepted. Based on the logic of hypothesis testing, you can conclude that

Which of the following is(are) null hypothesis(ses)?

Introduction

Exploring Data: Frequency Distributions and Graphs

Exploring Data: Central Tendency

Exploring Data: Variability

Other Descriptive Statistics

Correlation and Regression

Theoretical Distributions Including the Normal Distribution

Samples, Sampling Distributions, and Confidence Intervals

Hypothesis Testing, Effect Size, and and Confidence Intervals: Two-Sample Designs

Analysis of Variance: One-Way Classification

Analysis of Variance: One-Factor Repeated Measures

Analysis of Variance: Factorial Design

Chi Square Tests

More Nonparametric Tests

Appendix: Grouped Frequency Distributions and Central Tendency

Filters

Data Set 9-3: N = 8 $\Sigma$ X = 48 $\Sigma$ X² = 351 -Refer to Data Set 9-3. For H₀: µ = 9.00, the effect size index is

The issue of the amount of difference between a population with an unknown mean (which you sample from) and a null hypothesis population (µ₀= 8) is the issue of

Data Set 9-1: Sample scores: 2, 3, 4 -The t value when the scores in Data Set 9-1 are tested against H₀: $\mu$ = 4.00 leads to the conclusion that the null hypothesis be

Data Set 9-2: Scores: 1, 2, 3, 4, 5 -Refer to Data Set 9-2. For H₀: $\mu$ = 4.00, the effect size index is

Data Set 9-1: Sample scores: 2, 3, 4 -Refer to Data Set 9-1. For H₀: $\mu$ = 1.00, the effect size index is

Data were gathered, the results analyzed, and H_l accepted. Based on the logic of hypothesis testing, you can conclude that