In Exercises 1–4, use the following listed arrival delay times (minutes) for American Airline flights from New York to Los Angeles. Negative values correspond to flights that arrived early. Also shown are the SPSS results for analysis of variance. Assume that we plan to use a 0.05 significance level to test the claim that the different flights have the same mean arrival delay time.

Flight 1

-32

-25

-26

-6

5

-15

-17

-36

Flight 19

-5

-32

-13

-9

-19

49

-30

-23

Flight 21

-23

28

103

-19

-5

-46

13

-3

ANOVA

a. What characteristic of the data above indicates that we should use one-way analysis of variance?

b. If the objective is to test the claim that the three flights have the same mean arrival delay time, why is the method referred to as analysis of variance?

Short Answer

Expert verified
  1. The fact that the factor, arrival delay time, is compared over three different categories (flight numbers) indicates the use of one-way analysis of variance.
  1. As three different mean values for varied categories of a single factor are desired to be compared using the two components of variance, the method is referred to as analysis of variance.

Step by step solution

01

Given information

The arrival delay times for three flights are known.

The significance level is known to be 0.05.

The SPSS output for analysis of variance is known.

02

Condition to use one-way analysis of variance

One-way analysis of variance is used for comparing the mean of the data for one particular factor over different categories.

03

Identify the characteristic

a.

The arrival delay times of three flights areknown.

The independent variable of the study, referred to as the factor, is the arrival delay time. The variable is categorized into three categories; flights 1, 19, and 21. For comparison of the factors across three different categories, a one-way analysis of variance can be used.

04

Explain the method of analysis of variance

b.

The method to compare the mean values of the arrival delay time of three flights is referred to as analysis of variance because the following two components of variance are involvedin testing the claim:

  • Sum of squares between the groups
  • Sum of squares within the groups.

These are further used to compute the test statistic based on F-distribution.

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Most popular questions from this chapter

Lead and Full IQ Scores Example 1 used measured performance IQ scores for three different blood lead levels. If we use the same three categories of blood lead levels with the fullIQ scores, we get the accompanying Excel display. (The data are listed in Data Set 7 “IQ and Lead” in Appendix B.) Using a 0.05 significance level, test the claim that the three categories of blood lead level have the same mean full IQ score. Does it appear that exposure to lead has an effect on full IQ scores?

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

5. Lead and Verbal IQ Scores Example 1 used measured performance IQ scores for three different blood lead levels. If we use the same three categories of blood lead levels with measured verbal IQ scores, we get the accompanying Minitab display. (The data are listed in Data Set 7 “IQ and Lead” in Appendix B.) Using a 0.05 significance level, test the claim that the three categories of blood lead level have the same mean verbal IQ score. Does exposure to lead appear to have an effect on verbal IQ scores?

Interaction

a. What is an interaction between two factors?

b. In general, when using two-way analysis of variance, if we find that there is an interaction effect, how does that affect the procedure?

c. Shown below is an interaction graph constructed from the data in Exercise 1. What does the graph suggest?

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

Rock Sparrows. Rock Sparrows breeding in northern Italy are the subject of a long-term ecology and conservation study due to their wide variety of breeding patterns. Both males and females have a yellow patch on their breasts that is thought to play a significant role in their sexual behavior. A Pilastro et al. concluded an experiment in which they increased or reduced the size of a female's breast patch by dying feathers at the edge of a patch and then observed several characteristics of the behavior of the male. Their results were published in the paper "Male Rock Sparrows Adjust Their Breeding Strategy According to Female Ornamentation: Parental or Mating Investment?" (Animal Behaviour, Vol. 66, Issue 2, pp. 265-271). Eight mating pairs were observed in each of three groups: a reduced-patch-size group, a control group, and an enlarged-patch-size group. The data on the WeissStats site, based on the results reported by the researchers, give the number of minutes per hour that males sang in the vicinity of the nest after the patch size manipulation was done on the females.

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