blood pres pressu randomly males hown in the table below. Assume that the weight and blood pressure are j Subject Weight Systolic BP Subject Weight 1 165 130 14 172 2 167 133 15 159 3 180 150 16 168 4 155 128 17 174 5 212 151 18 183 6 175 146 19 215 7 190 150 20 195 8 210 140 21 180 9 200 148 22 143

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Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
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The weight and systolic blood pressure of 26 randomly selected males in the age group 25 to 30 are
shown in the table below. Assume that the weight and blood pressure are jointly normally distributed
Systolic BP Subject
Weight
Systolic BP
Subject
1
Weight
165
130
14
172
153
2
167
133
15
159
128
3
180
150
16
168
132
4
155
128
17
174
149
5
212
151
18
183
158
6
175
146
19
215
150
7
190
150
20
195
163
8
210
140
21
180
156
9
200
148
22
143
124
10
149
125
23
240
170
11
158
133
24
235
165
12
169
135
25
192
160
13
170
150
26
187
159
a. Find a regression line relating systolic blood pressure to weight
b. Test for significance of regression using a = 0.05
c. Estimate the correlation coefficient
a. y = 69.104 + 0.419x
Regression model is significant
r = 0.77349
b.y = 69.104 + 0.419x
Regression model is not significant
r = 0.5982
O c. y = -25.294 + 1.426x
Regression model is significant
r = 0.77349
d. y = 5.50 +6.73x
Regression model is significant
r = 0.77349
O e. y = 69.104 + 0.419x
Doaroosion model is not significant
Transcribed Image Text:The weight and systolic blood pressure of 26 randomly selected males in the age group 25 to 30 are shown in the table below. Assume that the weight and blood pressure are jointly normally distributed Systolic BP Subject Weight Systolic BP Subject 1 Weight 165 130 14 172 153 2 167 133 15 159 128 3 180 150 16 168 132 4 155 128 17 174 149 5 212 151 18 183 158 6 175 146 19 215 150 7 190 150 20 195 163 8 210 140 21 180 156 9 200 148 22 143 124 10 149 125 23 240 170 11 158 133 24 235 165 12 169 135 25 192 160 13 170 150 26 187 159 a. Find a regression line relating systolic blood pressure to weight b. Test for significance of regression using a = 0.05 c. Estimate the correlation coefficient a. y = 69.104 + 0.419x Regression model is significant r = 0.77349 b.y = 69.104 + 0.419x Regression model is not significant r = 0.5982 O c. y = -25.294 + 1.426x Regression model is significant r = 0.77349 d. y = 5.50 +6.73x Regression model is significant r = 0.77349 O e. y = 69.104 + 0.419x Doaroosion model is not significant
O e.y = 69.104 + 0.419x
Regression model is not significant
r = 0.77349
Transcribed Image Text:O e.y = 69.104 + 0.419x Regression model is not significant r = 0.77349
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