A paper gives data on x= change in Body Mass Index (BMI, in kilograms/meter) and y= change in a measure of depression for patients suffering from depression who participated in a pulmonary rehabilitation program. The table below contains a subset of the data given in the paper and are approximate values read from a scatterplot in the paper. BMI Change (kg/m²) Depression Score Change -1 %20- 20 15- The accompanying computer output is from Minitab. Fitted Line Plot Depression score change 6.640-3.475 BMI change 10- 5- 0- -0.5 8 5.21216 0.5 -0.50 0.1 0.7 0.8 1 1.5 1.1 1 6 0.0 0.5 Coefficients R-aq 26.919 BMI change 1.0 44 1.5 0.4 0.4 8 13 14 17 18 12 14 @ Term Cont SE Cont Constant 6.640 2.24 2.85 BMI change 6.476 Regression Equation Depression score change 6.640 +8.476 BMI change Interpret this estimate. s is the typical amount by which the-Select- S R-Sq 26.91% R-Sq (adj) 19.60% 5.21215 7-Value P-Value 2.96 0.0143 1.92 0.0840 1.00 VIF (a) What percentage of observed variation in depression score change can be explained by the simple linear regression model? (Round your answer to two decimal places.) % (b) Give a point estimate of a. (Round your answer to five decimal places.) S- value-Select what is predicted using the least squares regression line. (c) Give an estimate of the average change in depression score change associated with a 1 kg/m² increase in BMI change. (Round your answer to three decimal places.) (d) Calculate a point estimate of the mean depression score change for a patient whose BMI change was 1.2 kg/m². (Round your answer to three decimal places.) ý=
A paper gives data on x= change in Body Mass Index (BMI, in kilograms/meter) and y= change in a measure of depression for patients suffering from depression who participated in a pulmonary rehabilitation program. The table below contains a subset of the data given in the paper and are approximate values read from a scatterplot in the paper. BMI Change (kg/m²) Depression Score Change -1 %20- 20 15- The accompanying computer output is from Minitab. Fitted Line Plot Depression score change 6.640-3.475 BMI change 10- 5- 0- -0.5 8 5.21216 0.5 -0.50 0.1 0.7 0.8 1 1.5 1.1 1 6 0.0 0.5 Coefficients R-aq 26.919 BMI change 1.0 44 1.5 0.4 0.4 8 13 14 17 18 12 14 @ Term Cont SE Cont Constant 6.640 2.24 2.85 BMI change 6.476 Regression Equation Depression score change 6.640 +8.476 BMI change Interpret this estimate. s is the typical amount by which the-Select- S R-Sq 26.91% R-Sq (adj) 19.60% 5.21215 7-Value P-Value 2.96 0.0143 1.92 0.0840 1.00 VIF (a) What percentage of observed variation in depression score change can be explained by the simple linear regression model? (Round your answer to two decimal places.) % (b) Give a point estimate of a. (Round your answer to five decimal places.) S- value-Select what is predicted using the least squares regression line. (c) Give an estimate of the average change in depression score change associated with a 1 kg/m² increase in BMI change. (Round your answer to three decimal places.) (d) Calculate a point estimate of the mean depression score change for a patient whose BMI change was 1.2 kg/m². (Round your answer to three decimal places.) ý=
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:A paper gives data on x = change in Body Mass Index (BMI, in kilograms/meter) and y = change in a measure of depression for patients suffering from depression who participated in a pulmonary rehabilitation program. The table below contains a subset of the data given in the paper and are approximate values read from a
scatterplot in the paper.
BMI Change (kg/m2) 0.5 -0.50 0.1 0.7 0.81 1.5 1.1
Depression Score Change
17 18
The accompanying computer output is from Minitab.
Fitted Line Plot
Depression score change 6.640 +5.475 BMI change
20-
15-
10-
04
-0.5
0.0
8
5.21215 26.914
Coefficients
.
0.5 1.0 1.5
BMI change
Term Cont SE Cont
Constant 6.640
EMI change 5.475
4
2.95
7-Value
6
↑
8
S
R-Sq
26.91%
R-Sq (adj) 19.60%
5.21215
P-Value VIF
2.96 0.0143
1.92 0.0840 1.00
13 14
(b) Give a point estimate of a. (Round your answer to five decimal places.)
s-
10.4 0.4
12 14
Regression Equation
Depression score change 6.640+ 6.475 BMI change
(a) What percentage of observed variation in depression score change can be explained by the simple linear regression model? (Round your answer to two decimal places.)
18 12
value --Select-
Interpret this estimate.
s is the typical amount by which the-Select-
what is predicted using the least squares regression line.
(c) Give an estimate of the average change in depression score change associated with a 1 kg/m² increase in BMI change. (Round your answer to three decimal places.)
(d) Calculate a point estimate of the mean depression score change for a patient whose BMI change was 1.2 kg/m². (Round your answer to three decimal places.)
ý=
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