The Variables Age of The Myocardial Infection Patient Exercise
WHAS100id
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
admitdate
3/13/1995
1/14/1995
2/17/1995
4/7/1995
2/9/1995
1/16/1995
1/17/1995
11/15/1994
8/18/1995
7/22/1995
10/11/1995
5/26/1995
5/21/1995
12/14/1995
11/8/1995
10/8/1995
10/17/1995
10/30/1995
12/10/1995
11/23/1995
10/5/1995
11/5/1995
9/9/1995
9/9/1995
12/15/1995
12/3/1995
10/18/1995
3/16/1995
10/25/1995
10/6/1995
9/3/1995
6/30/1995
7/22/1995
9/17/1995
3/21/1997
2/23/1997
1/1/1997
1/18/1997
1/19/1997
3/18/1997
2/3/1997
5/17/1997
3/8/1997
2/23/1997
6/14/1997
7/7/1997
4/27/1997
5/15/1997
7/26/1997
7/17/1997
9/9/1997
foldate
los
3/19/1995
1/23/1996
10/4/2001
7/14/1995
5/29/1998
9/11/2000
10/15/1997
11/24/2000
2/23/1996
12/31/2002
12/31/2002
9/29/1996
3/18/1996
12/31/2002
12/31/2002
12/31/2002
5/12/2000
1/5/2003
12/31/2002
12/31/2002
2/5/1996
12/31/2002
10/22/1997
3/13/2001
12/31/2002
1/19/2001
12/31/2002
6/4/2000
4/15/1997
1/18/1996
9/9/1995
5/1/1999
12/22/2002
1/5/1998
8/16/1997
12/31/2002
12/31/2002
12/31/2002
4/25/1998
12/31/2002
12/31/2002
12/31/2002
12/31/2002
12/31/2002
1/5/2003
12/31/2002
12/31/2002
2/13/1998
12/31/2002
12/31/2002
12/31/2002
lenfol
4
5
5
9
4
7
3
56
5
9
6
11
6
10
7
5
6
9
6
5
6
8
4
14
4
11
2
7
5
4
4
5
8
4
6
12
16
5
8
10
4
5
5
4
18
9
9
7
4
6
7
fstat
6
374
2421
98
1205
2065
1002
2201
189
2719
2638
492
302
2574
2610
2641
1669
2624
2578
2595
123
2613
774
2012
2573
1874
2631
1907
538
104
6
1401
2710
841
148
2137
2190
2173
461
2114
2157
2054
2124
2137
2031
2003
2074
274
1984
1993
1939
Page 1
age
1
1
1
1
1
1
1
1
1
0
0
1
1
0
0
0
1
1
0
0
1
0
1
1
0
1
0
1
1
1
1
1
1
1
1
0
0
0
1
0
0
0
0
0
1
0
0
1
0
0
0
gender
65
88
77
81
78
82
66
81
76
40
73
83
64
58
43
39
66
61
49
53
85
69
54
82
67
89
68
78
56
85
72
50
81
85
84
75
61
48
83
82
62
39
45
65
76
77
68
73
64
80
84
0
1
0
1
0
1
1
1
0
0
1
0
1
0
0
0
0
0
0
1
0
1
0
0
1
1
0
0
0
1
0
0
1
1
1
0
0
0
1
0
0
0
0
0
1
1
0
0
0
0
1
bmi
31.38134
22.6579
27.87892
21.47878
30.70601
26.45294
35.71147
28.27676
27.12082
21.78971
28.43344
24.66175
27.46412
29.83756
22.95776
30.10881
31.99738
30.7142
25.69548
30.12017
18.41038
37.60097
28.97529
19.90095
28.32237
23.43605
26.44693
28.20595
24.11997
36.71647
27.97907
20.363
28.64898
20.17772
23.6187
23.67519
23.4314
33.4511
19.57068
25.82748
30.86625
24.21079
31.66439
26.22085
32.41986
24.56345
21.3055
26.45678
27.97977
36.02333
22.31424
WHAS100
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
6/19/1997
8/20/1997
8/28/1997
9/9/1997
9/1/1997
9/3/1997
9/24/1997
9/19/1997
4/17/1997
10/21/1997
10/2/1997
1/8/1997
11/11/1997
11/7/1997
4/20/1997
6/18/1997
10/29/1997
4/29/1997
11/8/1997
11/17/1997
11/28/1997
5/19/1997
12/11/1997
5/10/1997
10/6/1997
12/21/1997
11/22/1997
10/31/1997
6/28/1997
12/21/1997
10/2/1997
9/14/1997
9/25/1997
12/2/1997
9/26/1997
10/24/1997
11/27/1997
4/12/1997
2/15/1997
10/22/1997
6/27/1997
1/17/1997
12/12/1997
11/4/1997
11/4/1997
12/24/1997
11/26/1997
8/10/1997
3/26/1997
9/3/2000
11/17/1997
1/3/1998
12/31/2002
9/15/1997
6/10/2000
10/30/2001
12/31/2002
12/31/2002
2/5/1998
12/27/1998
12/31/2002
12/31/2002
5/31/2000
4/18/1998
5/1/2000
12/31/2002
12/31/2002
12/31/2002
12/31/2002
12/31/2002
12/31/2002
12/31/2002
12/31/2002
12/31/2002
12/31/2002
3/16/1998
2/4/2002
12/27/2000
12/31/2002
12/31/2002
12/31/2002
12/31/2002
1/15/1998
12/31/2002
7/25/1998
12/31/2002
3/23/2002
12/31/2002
4/22/1998
12/31/2002
12/31/2002
5/24/2002
5/10/1998
12/31/2002
4/19/2002
1/27/1998
12/31/2002
2/13/2000
4
3
7
17
11
5
6
3
1
6
4
3
7
3
5
5
12
5
7
4
5
5
4
7
3
5
7
7
5
3
6
3
10
3
6
5
7
4
6
5
4
5
4
10
4
3
8
16
7
1172
89
128
1939
14
1011
1497
1929
2084
107
451
2183
1876
936
363
1048
1889
2072
1879
1870
1859
2052
1846
2061
1912
1836
114
1557
1278
1836
1916
1934
1923
44
1922
274
1860
1806
2145
182
2013
2174
1624
187
1883
1577
62
1969
1054
Page 2
1
1
1
0
1
1
1
0
0
1
1
0
0
1
1
1
0
0
0
0
0
0
0
0
0
0
1
1
1
0
0
0
0
1
0
1
0
1
0
1
0
0
1
1
0
1
1
0
1
43
87
70
80
64
59
92
51
41
90
83
61
64
82
91
48
63
81
52
65
74
62
60
71
73
43
80
72
57
80
76
53
44
71
64
86
72
73
85
60
63
80
74
79
48
32
86
56
74
1
1
1
0
1
1
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
1
0
0
0
0
0
0
1
0
0
0
0
0
0
1
1
1
0
0
1
0
1
1
1
1
0
0
25.33148
18.77718
18.60004
25.50204
24.41255
29.85998
24.3664
34.77034
27.26234
24.78423
21.80987
27.36909
26.22085
26.88683
27.61844
31.58373
23.33267
28.35006
32.63621
31.95113
25.01782
30.22827
29.28812
32.32407
31.47445
28.59188
33.36074
21.80987
23.57087
28.35006
28.03555
24.21079
32.60387
23.0563
31.75016
21.10959
25.23266
22.86698
26.05501
23.18023
35.48949
20.59809
30.13206
16.78615
32.11709
39.93835
14.91878
29.05295
32.89087
IHP 525 Milestone Four Guidelines and Rubric
Overview: Your task is to help the organization answer their question by critically analyzing the data. You will run descriptive statistics and a statistical test,
create a graph, interpret the results, and present the results and recommendations to non-technical decision makers in the form of a data analysis. Keep in mind
that it is your job to do this from a statistical standpoint. Be sure to justify your conclusions and recommendations with appropriate statistical support.
Prompt: In Milestone Three, you created a table listing the statistics you were going to complete to investigate your health question. In Milestone Four, you will
actually complete these calculations.
Specifically, you must address these critical elements:
I.
Data Analysis
A. Graphs: In this section, you will use graphical displays to examine the data.
1. Create at least one graph that gives a sense of the potential relationship between the two variables that form your chosen health
question. Include the graph and discuss why you selected it as opposed to others.
B. Conduct an appropriate statistical test to answer your health question.
C. Explain why this test is the best choice in this context.
D. Analysis of Biostatistics: Use this section to describe your findings from a statistical standpoint. Be sure to:
1. Present key biostatistics from the graph(s) and statistical test and explain what they mean. Be sure to include a spreadsheet showing
your work or a copy of your StatCrunch output as an appendix.
2. What statistical inferences or conclusions can you draw based on the results of your statistical test, descriptive statistics and graph?
Justify your response.
Rubric
Guidelines for Submission: You will submit screenshots of the graphs, the completed table from Milestone Three, and 2–4 paragraphs explaining and
interpreting these items in a single Microsoft Word document with double spacing, 12-point Times New Roman font, one-inch margins, and using APA format for
any citations.
Critical Elements
Data Analysis: Graphs:
Graph
Proficient (100%)
Creates a graph that gives a sense of the
potential relationship between two
variables that form the chosen health
question and discusses why this graph
was selected over others
Needs Improvement (70%)
Creates a graph that gives a sense of the
potential relationship between two
variables that form the health question
and discusses why this graph was
selected over others, but graph is
inappropriate, reasons are illogical, or
response contains inaccuracies
Not Evident (0%)
Does not create a graph that gives a
sense of the potential relationship
between two variables
Value
20
Critical Elements
Data Analysis: Test
Proficient (100%)
Conducts appropriate statistical test
accurately to answer chosen health
question
Needs Improvement (70%)
Conducts statistical test to answer
chosen health question, but response
contains inaccuracies or test is not
conducted appropriately
Not Evident (0%)
Does not conduct appropriate statistical
test to answer chosen health question
Data Analysis: Best Choice
Explains why test is the best choice in
this context
Explains why test is the best choice in
this context, but explanation is cursory
or contains inaccuracies
Presents graph and statistical test
results, including spreadsheet showing
work or computer output, and explains
what they mean, but response contains
inaccuracies or omits key details
Draws appropriate statistical inferences
based on test results and graph, but
does not justify response, justification is
illogical, or response contains
inaccuracies
Submission has major errors related to
citations, grammar, spelling, syntax, or
organization that negatively impact
readability and articulation of main
ideas
Does not explain why test is the best
choice in this context
15
Does not present graph and statistical
test results, including spreadsheet
showing work or computer output and
does not explain what these
calculations mean
Does not draw appropriate statistical
inferences or conclusions based on test
results and graph
20
Submission has critical errors related to
citations, grammar, spelling, syntax, or
organization that prevent
understanding of ideas
5
Data Analysis: Analysis:
Biostatistics
Data Analysis: Analysis:
Statistical Inferences
Articulation of Response
Presents graph and statistical test
results, including spreadsheet showing
work or computer output, and
accurately explains what chosen
calculations mean
Draws appropriate statistical inferences
based on statistical hypothesis test
results and graph and justifies response
Submission has no major errors related
to citations, grammar, spelling, syntax,
or organization
Total
Value
20
20
100%
1
Data Analysis: Does BMI Affect the Survival (follow-up status) of MI Patients?
Bianco Bernard
Southern New Hampshire University
Biostatistics
Instructor
2
Data Analysis: Does BMI Affect the Survival (follow-up status) of MI Patients?
Research Question
Data analysis: Does BMI affect MI patients’ survival (follow-up status)?
Hypothesis
H0: No interaction model is fit
Ha: Interaction model is fit
Method
The study includes 100 observations and nine variables to understand factors involved
with trends in an extended period in survival rates and incidences following hospital admission
for MI. The collected data is obtained from MI patients admitted to Worcester, Massachusetts.
The significant difference can only be identified following a correlation of p0.05).
Conclusion/Statistical Inferences
This study utilized relative survival analysis to evaluate temporal trends on patient (MI
affected) outcomes within a 6-month period. The study stratified groups based on age and sex to
decipher consistency among patient cohorts. A significance p-value>0.05 is obtained, indicating
the lack of a present interaction model. Thus, no interaction model is fit.
7
Reference
Alabas, O., Allan, V., McLenachan, J., Feltbower, R., & Gale, C. (2013). Age-dependent
improvements in survival after hospitalisation with acute myocardial infarction: an
analysis of the Myocardial Ischemia National Audit Project (MINAP). Age And
Ageing, 43(6), 779-785. https://doi.org/10.1093/ageing/aft201
8
Appendix 1
WHAS100
id
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
admitdate
3/13/1995
1/14/1995
2/17/1995
4/7/1995
2/9/1995
1/16/1995
1/17/1995
11/15/1994
8/18/1995
7/22/1995
10/11/1995
5/26/1995
5/21/1995
12/14/1995
11/8/1995
10/8/1995
10/17/1995
10/30/1995
12/10/1995
11/23/1995
10/5/1995
11/5/1995
9/9/1995
9/9/1995
12/15/1995
12/3/1995
10/18/1995
3/16/1995
10/25/1995
10/6/1995
9/3/1995
6/30/1995
7/22/1995
9/17/1995
3/21/1997
2/23/1997
1/1/1997
1/18/1997
1/19/1997
3/18/1997
2/3/1997
5/17/1997
3/8/1997
2/23/1997
6/14/1997
7/7/1997
4/27/1997
5/15/1997
7/26/1997
7/17/1997
9/9/1997
foldate
los
3/19/1995
1/23/1996
10/4/2001
7/14/1995
5/29/1998
9/11/2000
10/15/1997
11/24/2000
2/23/1996
12/31/2002
12/31/2002
9/29/1996
3/18/1996
12/31/2002
12/31/2002
12/31/2002
5/12/2000
1/5/2003
12/31/2002
12/31/2002
2/5/1996
12/31/2002
10/22/1997
3/13/2001
12/31/2002
1/19/2001
12/31/2002
6/4/2000
4/15/1997
1/18/1996
9/9/1995
5/1/1999
12/22/2002
1/5/1998
8/16/1997
12/31/2002
12/31/2002
12/31/2002
4/25/1998
12/31/2002
12/31/2002
12/31/2002
12/31/2002
12/31/2002
1/5/2003
12/31/2002
12/31/2002
2/13/1998
12/31/2002
12/31/2002
12/31/2002
lenfol
4
5
5
9
4
7
3
56
5
9
6
11
6
10
7
5
6
9
6
5
6
8
4
14
4
11
2
7
5
4
4
5
8
4
6
12
16
5
8
10
4
5
5
4
18
9
9
7
4
6
7
fstat
6
374
2421
98
1205
2065
1002
2201
189
2719
2638
492
302
2574
2610
2641
1669
2624
2578
2595
123
2613
774
2012
2573
1874
2631
1907
538
104
6
1401
2710
841
148
2137
2190
2173
461
2114
2157
2054
2124
2137
2031
2003
2074
274
1984
1993
1939
Page 1
age
1
1
1
1
1
1
1
1
1
0
0
1
1
0
0
0
1
1
0
0
1
0
1
1
0
1
0
1
1
1
1
1
1
1
1
0
0
0
1
0
0
0
0
0
1
0
0
1
0
0
0
gender
65
88
77
81
78
82
66
81
76
40
73
83
64
58
43
39
66
61
49
53
85
69
54
82
67
89
68
78
56
85
72
50
81
85
84
75
61
48
83
82
62
39
45
65
76
77
68
73
64
80
84
0
1
0
1
0
1
1
1
0
0
1
0
1
0
0
0
0
0
0
1
0
1
0
0
1
1
0
0
0
1
0
0
1
1
1
0
0
0
1
0
0
0
0
0
1
1
0
0
0
0
1
bmi
31.38134
22.6579
27.87892
21.47878
30.70601
26.45294
35.71147
28.27676
27.12082
21.78971
28.43344
24.66175
27.46412
29.83756
22.95776
30.10881
31.99738
30.7142
25.69548
30.12017
18.41038
37.60097
28.97529
19.90095
28.32237
23.43605
26.44693
28.20595
24.11997
36.71647
27.97907
20.363
28.64898
20.17772
23.6187
23.67519
23.4314
33.4511
19.57068
25.82748
30.86625
24.21079
31.66439
26.22085
32.41986
24.56345
21.3055
26.45678
27.97977
36.02333
22.31424
WHAS100
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
6/19/1997
8/20/1997
8/28/1997
9/9/1997
9/1/1997
9/3/1997
9/24/1997
9/19/1997
4/17/1997
10/21/1997
10/2/1997
1/8/1997
11/11/1997
11/7/1997
4/20/1997
6/18/1997
10/29/1997
4/29/1997
11/8/1997
11/17/1997
11/28/1997
5/19/1997
12/11/1997
5/10/1997
10/6/1997
12/21/1997
11/22/1997
10/31/1997
6/28/1997
12/21/1997
10/2/1997
9/14/1997
9/25/1997
12/2/1997
9/26/1997
10/24/1997
11/27/1997
4/12/1997
2/15/1997
10/22/1997
6/27/1997
1/17/1997
12/12/1997
11/4/1997
11/4/1997
12/24/1997
11/26/1997
8/10/1997
3/26/1997
9/3/2000
11/17/1997
1/3/1998
12/31/2002
9/15/1997
6/10/2000
10/30/2001
12/31/2002
12/31/2002
2/5/1998
12/27/1998
12/31/2002
12/31/2002
5/31/2000
4/18/1998
5/1/2000
12/31/2002
12/31/2002
12/31/2002
12/31/2002
12/31/2002
12/31/2002
12/31/2002
12/31/2002
12/31/2002
12/31/2002
3/16/1998
2/4/2002
12/27/2000
12/31/2002
12/31/2002
12/31/2002
12/31/2002
1/15/1998
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7/25/1998
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3/23/2002
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4/22/1998
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5/24/2002
5/10/1998
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4/19/2002
1/27/1998
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2/13/2000
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3
7
17
11
5
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7
1172
89
128
1939
14
1011
1497
1929
2084
107
451
2183
1876
936
363
1048
1889
2072
1879
1870
1859
2052
1846
2061
1912
1836
114
1557
1278
1836
1916
1934
1923
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1922
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1860
1806
2145
182
2013
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1624
187
1883
1577
62
1969
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25.33148
18.77718
18.60004
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29.85998
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27.26234
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27.36909
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31.58373
23.33267
28.35006
32.63621
31.95113
25.01782
30.22827
29.28812
32.32407
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28.59188
33.36074
21.80987
23.57087
28.35006
28.03555
24.21079
32.60387
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31.75016
21.10959
25.23266
22.86698
26.05501
23.18023
35.48949
20.59809
30.13206
16.78615
32.11709
39.93835
14.91878
29.05295
32.89087
IHP 525 Milestone Three Table
For this milestone, in order to explore your health question you are investigating, you need to plan what descriptive
statistics and statistical test you will need to run, as well as what graph you will need to create.
Step 1: Complete the table below in which you will propose the calculations and graph(s) you will need to perform to
answer the health question you are investigating.
Question:
What is your health (research) question?
What are the corresponding null and alternative
hypotheses?
Answer:
Does age determine the severity of myocardial infection between
male and female patients?
Null hypothesis: age does not determine the serevity of myocardial
infarction.
Alternative hypothesis: age determine severity of myocardial
infarction.
List the descriptive statistics you will compute,
using which variable(s), to help answer your
health question.
What is the name of the statistical test you will
use to test your hypothesis and answer your health
question?
What is the formula for your chosen statistical
test?
Mean, median and standard deviation.
Why is the statistical test you chose appropriate to
answer your health question? Be sure to be clear
on how the two variables you described in
Milestone Two are used to complete this test.
Which graph(s) (histogram, stem and leaf,
boxplot, bar graph, scatterplot) will you use to
visualize the answer to your health question? Be
specific and include which variables will be used
and if the graph will be created for different
subgroups of subjects.
The 2 sample t-test is useful when testing the difference between
two population means. In this case, it is the most appropriate for
making a comparison between sample one data (males patients)
and sample two data (female patients).
Bar graphs and histogram will be appropriate for this data because
they give visual representation of the differences and similiarities
of the variabls.
2 sample t-test
Step 2: Provide a one- to two-paragraph explanation below as to why you chose the calculations outlined in the table
above to explore your health question. Describe what statistics you will compute in order to answer your chosen health
(research) question. Be sure to discuss any graphs that you will compute and what information they will provide to help
you answer your health question.
Age difference may or may not be a determinant of the severity of myocardial infarction (MI). the use of null and
alternative hypothesis can help derive the answer to the question. A true null hypothesis who indicate that age is a
determinant of the sereverity of Myocardial infarction. The alternative hypothesis refutes the claim that age determine the
severity of MI. the use of mean, standard deviation and median will show the association between age variation and
severity of MI.
12:00 4
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Assignments > View Feedback
Feedback for 5-3 Final
Project Data Analysis
Milestone Three: Process
and Calculations
Submission Feedback
Overall Feedback
Evening Bianco,
Great job on your milestone from week 5!
The 5-3 milestone deliverables:
a. State the following:
a. Create a table in which you propose the calculations and
graphs you will need to perform to answer the health
question you are investigating. Then explain why
you chose these calculations to explore your health
question.
You did an excellent job meeting the expectations for the week-
5 deliverable mentioned above. You did a nice job completing
your table, your tests/graphs were appropriate for your
question, and your explanation was thorough. I’d recommend
you change your question to “Does age affect the survival
(follow-up status) of MI patients?” in row 1 in your table as
“severity” isn’t one of the variables and might be misconstrued.
Thus, I’d change your hypotheses to reflect that as well (Ho:
age does not impact survivability and Ha: age does impact
survivability).
Overall, good work though. I appreciate your time and effort.
You were able to “Meet” or “Exceed” expectations on all the
critical elements! Please see the attached rubric for a
breakdown of your grade and my feedback. Please note that I
had to deduct 4.5 points (10%) for tardiness.
Please let me know if you have any questions.
Respectfully,
Dr. Knight
Rubric Name: IHP 525 Milestone Three Rubric
PER Milestone Three Rubric
00
Done
11:54 1
ul
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Assignments > View Feedback
Feedback for 7-2 Final
Project Data Analysis
Milestone Four: Data
Analysis
Submission Feedback
Overall Feedback
Initial Feedback on 23/2022.
Bianco, I think you’re still misunderstanding that you can’t
use data from another study or dataset for your milestones
and your data analysis project. You have to use the data
set from the Worcester study that was provided in the first
module and use STATCrunch to analyze it. I recommend
you work on this and resubmit it again using the correct
dataset. Let me know if you have any
questions/concerns. Thanks.
Dr. Knight
Note for self: Assignment was initially submitted two
days late.
Second Feedback on 3/3/2022:
Evening Bianco,
I still don’t think that you’re understand what’s expected of you
on this assignment. You need to upload the data set that I sent
you (from module 2-1) and perform the Summary Statistics
(descriptive), t-test, and graphs in STATCrunch (as we
discussed in your feedback from your earlier milestones). This
will be the simplest way for you to complete this project. In
addition, I can tell from your SAS code and your first paragraph
on page 4 that you’re not using the data provided to you (as this
data wasn’t provided to you in the dataset). I’m going to ask
again, that you work on this and resubmit it. Please let me
know if you have any questions.
Respectfully,
Dr. Knight
Rubric Name: IHP 525 Milestone Four Rubric
IH
Four Rubric
D
Not scored
Done
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