In the following study the researcher was interested in determining how systolic and diastolic blood pressure


  1. In the following study the researcher was interested in determining how systolic and diastolic blood pressure affected heart recovery rate. Subjects (n = 45) in the experiment exercised on a stationary bike until the reached 65% of their maximum heart rate. Then the time to recovery of their normal heart rate was observed. In addition the age of each subject was recorded.
    The data is tabulated below:
    Case Age Systolic Diastolic Recovery
    1 23 128 81 272
    2 33 124 79 75
    3 24 122 77 219
    4 20 130 89 408
    5 23 128 91 391
    6 30 120 68 49
    7 25 135 68 21
    8 30 133 79 176
    9 23 129 73 135
    10 26 135 77 174
    11 20 120 73 192
    12 30 130 74 86
    13 24 136 71 91
    14 22 142 92 393
    15 28 122 74 117
    16 30 120 73 52
    17 27 115 77 198
    18 23 119 84 264
    19 31 127 76 44
    20 22 126 74 180
    21 23 128 78 229
    22 21 110 68 131
    23 27 122 74 182
    24 22 135 86 346
    25 22 135 89 378
    26 21 134 89 313
    27 27 139 101 475
    28 33 126 76 49
    29 21 125 67 69
    30 30 121 71 12
    31 23 132 75 152
    32 21 130 82 340
    33 19 129 68 133
    34 32 141 87 152
    35 24 116 80 190
    36 23 127 73 144
    37 23 129 66 44
    38 26 125 85 186
    39 32 112 78 101
    40 18 118 73 263
    41 28 136 79 188
    42 33 131 82 156
    43 25 126 69 54
    44 22 114 82 296
    45 20 122 81 289

    Use multiple regression analysis to determine how the heart recovery rate was determined by systolic blood pressure, diastolic blood pressure and age.
  2. In the following example, the researcher was interested in determining if the following index (x) was associated with (y), remission in cancer patients. The index x measures proliferation activity of cells after a patient receives an injection of tritiated thymidine. The response variable y indicates whether the patient achieved remission (1), or did not achieve remission (0).

The data is tabulated below:

case x y
1 15 0
2 9 0
3 37 1
4 31 1
5 31 1
6 40 1
7 11 0
8 2 0
9 27 1
10 30 1
11 40 1
12 25 1
13 4 0
14 24 1
15 38 1
16 20 0
17 26 1
18 34 1
19 22 0
20 35 1
21 24 1
22 25 1
23 8 0
24 20 1
25 4 0
26 27 1
27 23 1
28 23 0
29 15 0
30 1 0
31 39 1
32 14 0
33 10 0
34 22 1
35 12 0
36 1 0
37 1 0
38 11 0
39 7 0
40 38 1
41 16 1
42 1 0
43 24 1
44 40 1
45 33 1
46 11 0
47 30 0
48 8 0
49 39 1
50 17 1
51 31 1
52 15 1
53 25 1
54 0 0
55 11 0
56 33 1
57 36 1
58 29 1
59 40 1
60 28 1
61 19 1
62 22 0
63 28 1
64 21 0
65 5 0
66 22 1
67 38 1
68 12 0
69 32 1
70 37 1
71 34 1
72 33 1
73 28 1
74 4 0
75 12 0
76 28 1
77 33 1
78 5 0
79 37 1
80 9 0
81 26 1
82 15 1
83 23 0
84 1 0
85 22 0
86 18 1
87 34 1
88 6 0
89 28 0
90 11 0
91 8 0
92 15 1
93 5 1
94 3 0
95 8 0
96 29 1
97 15 0
98 39 1
99 32 1
100 10 0

Perform logistic regression to determine in remission (y) depends on the index (x).

Price: $9.94
Solution: The downloadable solution consists of 6 pages, 394 words and 2 charts.
Deliverable: Word Document


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