Question

In: Statistics and Probability

Endurance Times for nine well-trained cyclists, on each of 3 doses of caffeine (0,5,13 mg) cyclists were given dose of caffeine and one hour later cycled till exhausted

 

Description: Endurance Times for nine well-trained cyclists, on each

of 3 doses of caffeine (0,5,13 mg)

cyclists were given dose of caffeine and one hour later cycled till exhausted

Variables/Columns

 

Subject id   1-15

Dose       0, 5, 13

endurance time  /* minutes until exhaustion at 80% Wmax on cycle  */

Data:

Cyclist id

0mg

mg5

mg13

 

1

43.44

42.47

37.55

 

2

33.67

85.15

61.53

 

3

64.25

63.20

71.28

 

4

46.15

52.10

54.76

 

5

59.71

66.20

68.35

 

6

48.75

73.25

69.47

 

7

42.43

44.50

46.48

 

8

55.32

57.17

62.35

 

9

33.26

35.05

36.20

 

10

41.44

44.47

44.35

 

11

44.15

48.52

53.46

 

12

54.34

58.70

64.21

 

13

58.75

65.25

71.62

 

14

34.35

47.37

58.03

 

15

47.87

77.27

65.35

 

Statistic

Group 1-
0mg

Group 2-
5mg

Group 3-
13mg

 
 

Mean

       

Median

       

Standard deviation

       

Variance

       

Range

       

95% confidence interval of mean

       

Count

       
         

Create and insert at least 2 charts that portray your data, for example bar chart showing the difference between the groups, or line graph showing the relationship between two variables.

What is your null hypothesis about the data?

What is your alternative hypothesis?

Choose the appropriate test to run (one-sample z, t-test, ANOVA, linear regression, or chi-square). What test did you choose and why is it appropriate for the dataset?

Run the relevant statistical test. Insert your results from the chosen test.

Is this test statistically significant? How did you make this determination?

What is your statistical conclusion (i.e. are you rejecting or failing to reject the null hypothesis)?

What is your experimental conclusion (i.e. what are you concluding about your original hypothesis based on the test that you have conducted)?

Solutions

Expert Solution

The appropriate test for the dataset to run is One Way ANOVA.

It is appropriate for the dataset, because, the one-way ANOVA is used to determine whether there are any statistically significant differences between the means of three independents (unrelated) doses of caffeine (0,5,13 mg).


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