A paper gives data on x = change in Body Mass Index (BMI, in kilograms/meter2) 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 datagiven in the paper and are approximate values read from a scatterplot in the paper.BMI Change (kg/m²)0.5 -0.5 00.1 0.7 0.811.51.210.4 0.4Depression Score Change -1944581314 17 181214The accompanying computer output is from Minitab.Fitted Line PlotDepression score change = 6.512 + 5.472 BMI change20S5.26270R-Sq27.16%R-Sq (adj) 19.88%15-:10--0.5 0.01.5ⓇS5.26270CoefficientsTermCoefVIFSE Coef2.26T-Value2.88P-Value0.0164Constant6.512BMI change5.4722.831.930.0823 1.00Regression EquationDepression score change = 6.512 + 5.472 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.)%(b) Give a point estimate of o. (Round your answer to five decimal places.)S =Interpret this estimate.s is the typical amount by which the depression score change value differs fromwhat 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.)Depression score change品と0.5BMI changeR-sq27.16 %1.0

From given output, the regression equation is given by Depression score change = 6.512 + 5.472 BMI…

Answered: a) what percentage of observed…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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An online retailer is trying to determine how positive reviews of items affect sales. The plot below shows the relationship between the number of positive reviews and the number of items sold. The linear regression output is shown below. 1500 Regression Statistics Multiple R R Square Adjusted R Square 0.935042 1000 0.968133 0.937282 500 Standard Error 30.00616 Observations 30 110 120 130 140 Number of positive reviews R= Ex: 0.654321 What is the correlation between number of positive reviews and number of items sold? Pick v correlation Number of items sold
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