PART IV: Now, we will return to the complete data set and divide into two new groups: male and female. Consider only the female subjects. 1. For these subjects only, construct a stemplot for the variable “age”. (We will be making this into a back-to-back stemplot later, so leave room on the left side.) 2. Discuss the shape of your stemplot. Is it symmetric? Positively skewed? Negatively skewed? None of these? Are there any outliers? 3. How would you describe the center and the spread of this distribution? 4. Find the five-number summary. 5. Construct a box plot. PART V: Now, consider only the male subjects. Repeat #1 - #5 from Part IV above for these subjects. For #1, make your stemplot back-to-back with the previous stemplot. For #5, make your boxplots side-by- side.

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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PART IV: Now, we will return to the complete data set and divide into two new groups: male and female. Consider only the female subjects.
1. For these subjects only, construct a stemplot for the variable “age”. (We will be making this into a back-to-back stemplot later, so leave room on the left side.)
2. Discuss the shape of your stemplot. Is it symmetric? Positively skewed? Negatively skewed? None of these? Are there any outliers?
3. How would you describe the center and the spread of this distribution?
4. Find the five-number summary.
5. Construct a box plot.

PART V: Now, consider only the male subjects. Repeat #1 - #5 from Part IV above for these subjects. For #1, make your stemplot back-to-back with the previous stemplot. For #5, make your boxplots side-by- side.

Systolic
Blood
Previous
Нeart
Admission to
ID Code
Vital Status
Age
Sex
Cancer Infection
Pressure
Rate
ICU
12
Lived
59
Male
No
No
112
80
Yes
38
Lived
69
Male
No
Yes
110
132
No
42
Lived
35
Male
No
Yes
90
140
No
75
Lived
52
Male
No
No
150
100
No
96
Lived
72
Male
No
No
110
144
No
137
Lived
74
Female
No
No
169
73
No
145
Died
67
Female
No
No
128
96
No
165
Died
92
Male
No
No
100
88
No
180
Lived
64
Female
No
No
170
115
Yes
190
Lived
53
Male
No
No
150
85
No
207
Lived
68
Male
No
Yes
110
118
No
208
Died
70
Male
No
No
148
95
Yes
211
Lived
66
Female
No
No
80
81
No
219
Lived
64
Male
No
No
130
140
No
238
Died
41
Male
No
No
136
80
No
292
Lived
61
Male
No
Yes
150
71
Yes
295
Lived
64
Male
Yes
No
190
114
No
299
Died
75
Male
No
Yes
141
140
No
310
Lived
18
Male
Yes
Yes
128
90
Yes
335
Lived
72
Female
No
No
140
76
No
376
Lived
23
Male
No
Yes
144
88
No
412
Died
51
Female
No
No
154
74
No
439
Lived
23
Female
No
No
104
111
No
Male
Female
44
455
468
Lived
67
No
No
162
No
Died
50
Yes
Yes
130
55
No
495
Lived
65
Male
No
No
132
68
No
502
Lived
55
Male
No
No
190
136
No
508
Lived
55
Female
No
Yes
170
95
Yes
518
Died
71
Female
No
No
100
105
No
525
546
Lived
41
Female
No
No
146
112
No
Lived
88
Female
No
No
160
80
Yes
563
Lived
83
Female
No
No
170
92
No
573
Lived
23
Male
No
No
190
88
No
598
Lived
48
Female
No
Yes
190
125
No
611
Died
85
Female
No
Yes
126
96
No
639
Lived
46
Male
Yes
Yes
134
100
Yes
655
Lived
58
Male
No
No
154
98
No
669
Lived
41
Female
No
No
70
112
No
713
Lived
47
Male
No
Yes
130
131
No
732
Lived
71
Male
No
Yes
78
143
135
No
740
Died
72
Female
No
No
131
No
746
Lived
70
Female
No
No
120
120
No
765
Lived
53
Male
No
No
204
52
No
784
Lived
60
Female
No
Yes
104
150
No
837
Lived
17
Female
No
No
130
52
No
875
Lived
Lived
Lived
69
Male
No
No
100
140
No
880
20
Male
No
No
160
60
No
912
71
120
Male
Female
No
Yes
108
No
924
Lived
73
No
No
138
103
No
929
Lived
42
Male
No
No
140
90
No
2222222222222222 232222222222222223225
Transcribed Image Text:Systolic Blood Previous Нeart Admission to ID Code Vital Status Age Sex Cancer Infection Pressure Rate ICU 12 Lived 59 Male No No 112 80 Yes 38 Lived 69 Male No Yes 110 132 No 42 Lived 35 Male No Yes 90 140 No 75 Lived 52 Male No No 150 100 No 96 Lived 72 Male No No 110 144 No 137 Lived 74 Female No No 169 73 No 145 Died 67 Female No No 128 96 No 165 Died 92 Male No No 100 88 No 180 Lived 64 Female No No 170 115 Yes 190 Lived 53 Male No No 150 85 No 207 Lived 68 Male No Yes 110 118 No 208 Died 70 Male No No 148 95 Yes 211 Lived 66 Female No No 80 81 No 219 Lived 64 Male No No 130 140 No 238 Died 41 Male No No 136 80 No 292 Lived 61 Male No Yes 150 71 Yes 295 Lived 64 Male Yes No 190 114 No 299 Died 75 Male No Yes 141 140 No 310 Lived 18 Male Yes Yes 128 90 Yes 335 Lived 72 Female No No 140 76 No 376 Lived 23 Male No Yes 144 88 No 412 Died 51 Female No No 154 74 No 439 Lived 23 Female No No 104 111 No Male Female 44 455 468 Lived 67 No No 162 No Died 50 Yes Yes 130 55 No 495 Lived 65 Male No No 132 68 No 502 Lived 55 Male No No 190 136 No 508 Lived 55 Female No Yes 170 95 Yes 518 Died 71 Female No No 100 105 No 525 546 Lived 41 Female No No 146 112 No Lived 88 Female No No 160 80 Yes 563 Lived 83 Female No No 170 92 No 573 Lived 23 Male No No 190 88 No 598 Lived 48 Female No Yes 190 125 No 611 Died 85 Female No Yes 126 96 No 639 Lived 46 Male Yes Yes 134 100 Yes 655 Lived 58 Male No No 154 98 No 669 Lived 41 Female No No 70 112 No 713 Lived 47 Male No Yes 130 131 No 732 Lived 71 Male No Yes 78 143 135 No 740 Died 72 Female No No 131 No 746 Lived 70 Female No No 120 120 No 765 Lived 53 Male No No 204 52 No 784 Lived 60 Female No Yes 104 150 No 837 Lived 17 Female No No 130 52 No 875 Lived Lived Lived 69 Male No No 100 140 No 880 20 Male No No 160 60 No 912 71 120 Male Female No Yes 108 No 924 Lived 73 No No 138 103 No 929 Lived 42 Male No No 140 90 No 2222222222222222 232222222222222223225
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