The data below represent the number of days absent, x, and the final grade, y, for a sample of college students at a large university. Complete parts (a) through (e) belov No. of absences, x 4 5 6 7 0 1 2 3 8 9 89.1 86.2 83.4 81.0 78.1 73.8 64.1 68.9 66.1 63.3 Final grade, y (a) Find the least-squares regression line treating the number of absences, x, as the explanatory variable and the final grade, y, as the response variable. ŷ=[ x + ( (Round to three decimal places as needed.)

Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter4: Eigenvalues And Eigenvectors
Section4.6: Applications And The Perron-frobenius Theorem
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The data below represent the number of days absent, x, and the final grade, y, for a sample of college students at a large university. Complete parts (a) through (e) below.
No. of absences, x
4
5
6
7
8
9
0 1 2 3
89.1 86.2 83.4 81.0 78.1 73.8 64.1 68.9 66.1
Final grade, y
63.3
(a) Find the least-squares regression line treating the number of absences, x, as the explanatory variable and the final grade, y, as the response variable.
y =
0
X +
(Round to three decimal places as needed.)
Transcribed Image Text:The data below represent the number of days absent, x, and the final grade, y, for a sample of college students at a large university. Complete parts (a) through (e) below. No. of absences, x 4 5 6 7 8 9 0 1 2 3 89.1 86.2 83.4 81.0 78.1 73.8 64.1 68.9 66.1 Final grade, y 63.3 (a) Find the least-squares regression line treating the number of absences, x, as the explanatory variable and the final grade, y, as the response variable. y = 0 X + (Round to three decimal places as needed.)
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