What percentage of the variation in  can be explained by the corresponding variations in  and  taken together

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What percentage of the variation in  can be explained by the corresponding variations in  and  taken together?

The systolic blood pressure of individuals is thought to be related to both age and weight. Let the systolic
blood pressure, age, and weight be represented by the variables x1, x2, and x3, respectively. Suppose that
Minitab was used to generate the following descriptive statistics, correlations, and regression analysis for a
random sample of 15 individuals.
Descriptive Statistics
Variable
Mean Median
TrMean
StDev
SE Mean
0.997939
0.400725
15
157.77 158.27
157.77
.865
15
55.94
56.34
55.94
1.552
X3
15
177.11 176.41
177.11
4.125
1.065070
Variable
Minimum
Маximum
Q1
Q3
128
171
140.378
167.716
Ix
83
44
47.594
77.730
223.140
123
236
143.057
Correlations (Pearson)
Ix
0.855
0.885
0.681
Ex
Regression Analysis
The regression equation is
x1 = 0.557 + 1.117x2 + 0.808x3
Coef
Predictor
Constant
StDev
IT
P
0.557
0.383
1.45
0.086
x2
1.117
0.753
1.48
0.082
0.808
0.018
2.36
R-sq(adj) = 93.8 %
0.343
S = 0.142
R-sq = 96.6 %
What percentage of the variation in xị can be explained by the corresponding variations in x2 and x3
taken together?
O 88.5 %
O 68.1 %
O 93.8 %
O 96.6%
O 85.5%
Transcribed Image Text:The systolic blood pressure of individuals is thought to be related to both age and weight. Let the systolic blood pressure, age, and weight be represented by the variables x1, x2, and x3, respectively. Suppose that Minitab was used to generate the following descriptive statistics, correlations, and regression analysis for a random sample of 15 individuals. Descriptive Statistics Variable Mean Median TrMean StDev SE Mean 0.997939 0.400725 15 157.77 158.27 157.77 .865 15 55.94 56.34 55.94 1.552 X3 15 177.11 176.41 177.11 4.125 1.065070 Variable Minimum Маximum Q1 Q3 128 171 140.378 167.716 Ix 83 44 47.594 77.730 223.140 123 236 143.057 Correlations (Pearson) Ix 0.855 0.885 0.681 Ex Regression Analysis The regression equation is x1 = 0.557 + 1.117x2 + 0.808x3 Coef Predictor Constant StDev IT P 0.557 0.383 1.45 0.086 x2 1.117 0.753 1.48 0.082 0.808 0.018 2.36 R-sq(adj) = 93.8 % 0.343 S = 0.142 R-sq = 96.6 % What percentage of the variation in xị can be explained by the corresponding variations in x2 and x3 taken together? O 88.5 % O 68.1 % O 93.8 % O 96.6% O 85.5%
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