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The height of bedridden patients is often estimated from the length of the patient's ulna, the distance between the point on the elbow and the prominent bone on the wrist. Eight men over the age of 65 had both their height (in centimeters) and the length of their ulna (in centimeters) measured. The data are given in the table below. Ulna length (cm) 20 23 24 26 27 29 30 31 Height (cm) 160 163 166 168 171 178 182 186 Let x denote a patient's ulna length (in cm) and y denote the patient's height (in cm). Assume that the population distributions for both ulna length and height are approximately normal. The following summary measures were obtained from the data. X = 26.25, y = 171.75, SSxx = 99.5, SSyy= 609.5, SSxy= 238.5 We wish to find the least squares regression line for the data in this table using ulna length as an independent variable and height as a dependent variable. Use the information to estimate the slope of the least squares regression line. Enter your answer using three decimal places. i

The height of bedridden patients is often estimated from the length of the patient's ulna, the distance between the point on the elbow and the prominent bone on the wrist. Eight men over the age of 65 had both their height (in centimeters) and the length of their ulna (in centimeters) measured. The data are given in the table below. Ulna length (cm) 20 23 24 26 27 29 30 31 Height (cm) 160 163 166 168 171 178 182 186 Let x denote a patient's ulna length (in cm) and y denote the patient's height (in cm). Assume that the population distributions for both ulna length and height are approximately normal. The following summary measures were obtained from the data. X = 26.25, y = 171.75, SSxx = 99.5, SSyy= 609.5, SSxy= 238.5 We wish to find the least squares regression line for the data in this table using ulna length as an independent variable and height as a dependent variable. Use the information to estimate the slope of the least squares regression line. Enter your answer using three decimal places. i

MATLAB: An Introduction with Applications
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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The height of bedridden patients is often estimated from the length of the patient's ulna, the distance between the point on the elbow and the prominent bone on the wrist. Eight men over the age of 65 had both their height (in centimeters) and the length of their ulna (in centimeters) measured. The data are given in the table below. Ulna length (cm) 20 23 24 26 27 29 30 31 Height (cm) 160 163 166 168 171 178 182 186 Let x denote a patient's ulna length (in cm) and y denote the patient's height (in cm). Assume that the population distributions for both ulna length and height are approximately normal. The following summary measures were obtained from the data. X = 26.25, ỹ = 171.75, SSxx = 99.5, SSyy= 609.5, SSxy= 238.5 ху We wish to find the least squares regression line for the data in this table using ulna length as an independent variable and height as a dependent variable. Use the information to estimate the slope of the least squares regression line. Enter your answer using three decimal places.
Transcribed Image Text:The height of bedridden patients is often estimated from the length of the patient's ulna, the distance between the point on the elbow and the prominent bone on the wrist. Eight men over the age of 65 had both their height (in centimeters) and the length of their ulna (in centimeters) measured. The data are given in the table below. Ulna length (cm) 20 23 24 26 27 29 30 31 Height (cm) 160 163 166 168 171 178 182 186 Let x denote a patient's ulna length (in cm) and y denote the patient's height (in cm). Assume that the population distributions for both ulna length and height are approximately normal. The following summary measures were obtained from the data. X = 26.25, ỹ = 171.75, SSxx = 99.5, SSyy= 609.5, SSxy= 238.5 ху We wish to find the least squares regression line for the data in this table using ulna length as an independent variable and height as a dependent variable. Use the information to estimate the slope of the least squares regression line. Enter your answer using three decimal places.
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