R coding The data for this assignment represent a sample from a company that beg
ID: 3066205 • Letter: R
Question
R coding
The data for this assignment represent a sample from a company that began an exercise program for their employees. Use this data to answer the following question. The variables in this dataset are: age – Age (in years) of employee; male – Whether the employee is male (1) or female (0); coffee – Number of cups of coffee the employee drinks on a weekday; activity – General daily activity level (0–10 scale, higher numbers are more activity); preStress – Stress level before the exercise program began (0–100 scale); heart – Whether the employee has developed heart disease (e.g., high blood pressure); stress – Stress level one year after the exercise program began (0–100 scale)
Download the file “employeeExercise.dat” and import it into R using the following syntax:dat <- read.table("employeeExercise.dat", header = TRUE) Or, if you have trouble with the working directory, use this syntax: dat <- read.table(file.choose(), header = TRUE)
1. Fit a simple regression in which stress (after the exercise program) is explained by activity levels. The part that I really need help with --> Substantively interpret the 99% confidence interval for the intercept. Use the 99% CI for the slope to test the null hypothesis that the effect of activity on stress is 0, and provide a substantive interpretation of the 99% CI for the slope
The data set:
age male coffee activity preStress heart stress
25 0 3 9 69 0 53
32 1 3 5 66 1 61
35 1 3 3 71 0 55
27 0 1 6 61 0 50
21 1 3 4 61 0 41
53 0 2 4 54 1 85
53 0 4 8 76 1 94
49 0 4 3 68 1 80
35 1 2 5 58 0 56
34 1 5 8 77 1 82
48 1 1 8 64 0 67
31 1 1 10 66 1 47
29 1 1 8 66 0 43
28 1 6 4 74 1 54
49 1 4 6 65 0 76
35 1 4 2 74 1 55
42 1 2 0 66 1 72
21 1 2 2 72 1 47
28 1 5 10 80 0 73
44 1 2 9 73 0 71
41 1 2 10 65 0 70
46 1 1 8 69 0 64
23 1 3 6 70 1 54
47 0 3 6 61 0 76
48 1 3 10 72 0 79
32 1 4 1 71 1 49
34 1 7 7 78 1 80
37 1 5 0 70 1 42
49 0 1 4 64 0 71
27 1 3 2 72 1 49
49 0 2 4 70 1 78
33 1 1 9 71 0 44
41 1 1 4 71 0 61
50 1 2 7 71 1 79
47 1 5 0 75 1 58
50 1 4 6 73 1 86
41 1 2 7 63 0 64
37 0 0 0 63 0 74
33 0 0 9 53 0 43
55 1 4 3 71 1 81
45 0 1 4 64 0 69
51 0 1 9 61 0 67
33 1 7 5 76 0 60
46 1 4 3 73 1 67
54 1 3 4 67 1 83
40 1 3 9 74 0 70
33 0 0 3 58 0 59
52 0 0 3 70 0 79
25 1 2 4 73 1 45
46 1 6 8 79 0 94
46 1 2 6 64 0 75
49 1 2 10 62 0 74
24 1 3 9 69 0 50
27 1 3 4 69 1 53
37 1 4 4 75 1 62
21 0 1 0 65 1 54
35 0 0 1 52 0 73
53 1 4 3 71 1 85
47 0 4 3 66 0 72
32 1 2 4 65 0 57
35 1 5 4 69 1 67
50 1 4 5 67 1 83
23 1 4 6 75 0 46
28 1 4 7 62 0 60
27 1 3 9 67 0 60
38 1 3 6 73 0 67
22 1 4 3 56 1 46
30 1 6 1 81 1 40
25 0 1 10 58 0 41
43 1 3 0 63 1 66
23 1 5 10 73 0 68
49 0 1 3 61 0 77
32 1 3 3 65 0 55
30 0 4 6 59 0 57
48 1 3 5 75 0 71
30 1 3 10 71 0 59
40 0 0 0 67 0 73
27 0 0 3 60 0 51
45 0 2 6 66 0 71
22 1 6 6 73 1 59
40 1 3 0 67 1 65
52 1 2 5 65 1 78
36 1 4 10 73 0 76
24 1 4 5 73 0 44
29 1 1 3 70 0 50
41 1 2 1 70 1 68
25 1 6 4 81 1 51
23 1 1 2 67 0 44
48 1 3 6 78 0 72
53 1 3 1 70 1 79
28 0 0 10 52 0 35
33 1 7 1 75 1 41
23 1 1 4 71 0 46
35 0 1 7 56 0 56
55 1 3 5 70 1 91
54 1 4 2 70 1 77
52 1 2 6 69 0 79
52 1 4 3 78 1 83
29 1 1 7 77 0 44
45 0 0 3 65 1 78
41 1 3 6 64 0 63
35 0 1 9 66 0 53
26 0 1 5 61 0 45
41 1 2 10 74 0 61
46 0 3 3 74 1 71
42 1 5 4 81 0 63
49 0 1 8 63 0 70
37 0 1 5 50 0 61
39 1 3 4 68 0 66
35 1 8 4 75 0 53
21 0 4 2 60 1 42
31 1 2 5 69 0 55
51 0 2 0 70 1 86
42 1 5 8 77 1 90
29 0 1 0 63 1 62
39 1 3 1 71 1 60
39 1 0 0 58 1 78
45 0 1 8 60 0 67
36 1 3 2 65 1 62
55 0 1 0 63 0 87
53 1 2 7 71 1 84
28 1 6 0 70 1 33
53 1 7 6 79 1 99
51 1 2 3 67 1 83
44 0 0 1 54 1 87
29 0 4 2 79 0 44
45 1 3 1 71 1 72
28 0 3 6 77 0 47
50 1 3 0 73 1 75
52 1 3 7 66 0 84
52 1 3 6 65 0 79
23 0 3 10 67 0 51
51 1 2 7 66 0 75
51 1 5 10 82 0 100
38 1 2 7 62 0 63
27 0 1 5 62 0 44
47 0 4 2 62 1 72
40 1 1 0 68 1 73
50 1 1 10 75 1 73
22 1 6 7 76 0 52
35 1 4 6 74 1 67
24 0 0 6 61 0 37
48 0 0 1 62 0 83
40 1 2 8 70 0 67
48 0 1 3 64 0 76
28 1 2 1 65 1 58
50 0 0 8 62 0 65
54 1 1 10 62 0 70
47 1 3 4 62 1 81
52 1 2 0 68 0 74
45 1 3 2 78 1 73
29 1 4 2 78 0 41
37 1 7 2 79 1 51
49 1 5 4 69 1 82
37 0 1 6 56 0 58
46 1 3 4 64 0 72
27 1 8 7 77 1 75
34 1 1 1 64 0 60
39 1 1 2 74 1 68
35 0 1 9 64 0 50
28 1 5 6 74 0 60
41 1 4 7 79 1 85
23 1 2 5 62 0 42
35 1 5 3 76 1 48
36 0 2 6 59 0 59
38 1 4 8 67 0 72
24 1 1 10 69 0 39
54 1 2 6 67 0 82
40 1 7 1 74 1 43
37 0 1 7 62 0 56
29 1 3 0 71 1 46
24 1 3 2 68 1 49
21 0 1 10 59 0 35
31 1 2 9 63 0 52
40 0 3 5 58 0 69
52 1 6 8 79 0 100
39 1 2 0 68 1 62
25 1 2 1 77 0 45
Explanation / Answer
r<-read.table("balbichi.txt",header=TRUE)
r
confint(l,"activity",0.95)
Output
2.5 % 97.5 %
activity -0.5593442 0.8859033
This means that,based on the data,95% of the time COnfidence Interval lies between -0.5593442 and 0.8859033 which indicates that you cant be 95% confident whether the slope will be either be positive or negative,because it contains 0.
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