An SRS of apartment listings in a large northeastern city comparing monthly rent ($) versus size (〖ft〗^2) yields following computer output: An SRS of apartmentlistings in a largenortheastern citycomparing monthlyrent ($) versus size(ft²) yields thefollowing computeroutput:(a) Is a linear modelappropriate for thesedata? Explain.Rent1,8001,500-1,200-900-600..1,000 1,250 1,500 1,750 2,000SizeVariableConstantSizes = 102.4Coef-311.3411.07707R-squ = 94.7%1. Is a linear model appropriate for these data? Explain2. Interpret the slope of the regression line. [^]3. Interpret r^2 in context.(b) Interpret the slope of the regression line.(c) Interpret ² in context.Residuals150-75-0--75-s.e. Coef117.69000.09047t-2.6511.91,200 1,500 2,000Predicted RentР0.02940.0001R-squ (adj) = 94.08O

The response variable is Rent($) and the predictor variable is Size(ft2). The fitted model is : Rent…

An SRS of apartment listings in a large northeastern city comparing monthly rent ($) versus size (ft²) yields the following computer output: (a) Is a linear model appropriate for these data? Explain. Rent 1,800 1,500- 1,200 900 600.. 1,000 1,250 1,500 1,750 2,000 Size Variable Coef Constant Size s = 102.4 -311.341 1.07707 R-squ = 94.7% Residuals (b) Interpret the slope of the regression line. (c) Interpret ² in context. 150 75 0- s.e. Coef 117.6 0.09047 -75- 900 1,200 1,500 2,000 Predicted Rent t Р -2.65 0.0294 11.9 0.0001 R-squ (adj) = 94.08

An SRS of apartment listings in a large northeastern city comparing monthly rent ($) versus size (ft²) yields the following computer output: (a) Is a linear model appropriate for these data? Explain. Rent 1,800 1,500- 1,200 900 600.. 1,000 1,250 1,500 1,750 2,000 Size Variable Coef Constant Size s = 102.4 -311.341 1.07707 R-squ = 94.7% Residuals (b) Interpret the slope of the regression line. (c) Interpret ² in context. 150 75 0- s.e. Coef 117.6 0.09047 -75- 900 1,200 1,500 2,000 Predicted Rent t Р -2.65 0.0294 11.9 0.0001 R-squ (adj) = 94.08

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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An SRS of apartment listings in a large northeastern city comparing monthly rent ($) versus size (〖ft〗^2) yields following computer output:

An SRS of apartment
listings in a large
northeastern city
comparing monthly
rent ($) versus size
(ft²) yields the
following computer
output:
(a) Is a linear model
appropriate for these
data? Explain.
Rent
1,800
1,500-
1,200-
900-
600..
1,000 1,250 1,500 1,750 2,000
Size
Variable
Constant
Size
s = 102.4
Coef
-311.341
1.07707
R-squ = 94.7%
1. Is a linear model appropriate for these data? Explain
2. Interpret the slope of the regression line. [^]
3. Interpret r^2 in context.
(b) Interpret the slope of the regression line.
(c) Interpret ² in context.
Residuals
150-
75-
0-
-75-
s.e. Coef
117.6
900
0.09047
t
-2.65
11.9
1,200 1,500 2,000
Predicted Rent
Р
0.0294
0.0001
R-squ (adj) = 94.08
O

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