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Estimating Length Using the same results displayed in Exercise 8, does it appear that the length estimates are affected by the sex of the subject?

Short Answer

Expert verified

As the p-value equal to 0.395 is greater than 0.05, it can be concluded that the factor of sex does not significantly affect the visual estimation of the length of the classroom.

Step by step solution

01

Given information

The two-way analysis of variance results is shown through the minitab output for estimating the class length using sex and major for 18 students.

Refer to Exercise 8.

02

Analysis of the two-way analysis of variance

The following three effects are analyzed on the target variable, here, estimates.

  • Effect of the interaction term
  • Effect of factor 1, sex
  • Effect of factor 2, major

The null hypothesis to test the significance of the effect of sex is as follows.


There is no significant effect of sex on the length estimates of the classroom.

The value of the F-statistic for the factor ‘sex’ is equal to 0.78.

The corresponding p-value is equal to 0.395.

As the p-value is greater than 0.05, the null hypothesis is failed to reject.

Thus, there is not enough evidence to conclude that sex has a significant effect on length estimates.

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Most popular questions from this chapter

Cola Weights Identify the value of the test statistic in the display included with Exercise 1. In general, do larger test statistics result in larger P-values, smaller P-values, or P-values that are unrelated to the value of the test statistic

ANOVA The XLSTAT display below results from using the one-way analysis of variance test with the three samples.

a. What is the null hypothesis?

b. Assuming a 0.05 significance level, what conclusion is indicated by the displayed results?

In Exercises 5–16, use analysis of variance for the indicated test.

Triathlon Times Jeff Parent is a statistics instructor who participates in triathlons. Listed below are times (in minutes and seconds) he recorded while riding a bicycle for five stages through each mile of a 3-mile loop. Use a 0.05 significance level to test the claim that it takes the same time to ride each of the miles. Does one of the miles appear to have a hill?

Mile 1

3:15

3:24

3:23

3:22

3:21

Mile 2

3:19

3:22

3:21

3:17

3:19

Mile 3

3:34

3:31

3:29

3:31

3:29

Cola Weights For the four samples described in Exercise 1, the sample of regular Coke has a mean weight of 0.81682 lb, the sample of Diet Coke has a mean weight of 0.78479 lb, the sample of regular Pepsi has a mean weight of 0.82410 lb, and the sample of Diet Pepsi has a mean weight of 0.78386 lb. If we use analysis of variance and reach a conclusion to reject equality of the four sample means, can we then conclude that any of the specific samples have means that are significantly different from the others?

Weights The weights (kg) in the following table are from Data Set 1 “Body Data” in Appendix B. Results from two-way analysis of variance are also shown. Use the displayed results and use a 0.05 significance level. What do you conclude?


Female

Male

18-29

63.4

57.8

52.6

46.9

61.7

61.5

77.2

50.4

97

76.1

71.6

64.9

144.9

96.4

80.7

84.4

63.9

79

99.4

64.1

30-49

110.5

84.6

133.3

90.2

125.7

105.3

115.5

75.3

92.8

57.7

96.2

56.4

107.4

99.5

64.8

94.7

74.2

112.8

72.6

91.4

50-80

103.2

48.3

87.8

101.3

67.8

45.2

79.8

60.1

68.5

43.3

84.8

127.5

89.9

75.3

110.2

72.3

77.2

86.5

71.3

73.1

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