please help me answer for my data analysis class The data in the accompanying table include the appraised value, land area of the property in acres, and age, in years, for a small sample of 30 single-family homes in a small city. Perform a multiple regression analysis to predict appraised value based onland area of the property (X,) and age, in years, (X2) and determine the VIF for each independent variable in the model. Is there reason to suspect the existence of collinearity?Click the icon to view the data table.Determine the VIF for each independent variable in the model.iTable of DataVIF, =D VIF2 = I(Round to three decimal places as needed.)Appraised Land Area(acres)0.44710.5122AgeValue227.836548.895501.5201.30.5545350.3429840.44580.5188648.834670.474720.40.219991796.30.316153233.30.638668289.60.535635217.10.272950593.20.341149433.10.132428580.30.230641207.40.375967277.70.461714370.90.087959783.40.154151272.50.692948605.30.5545500.25940.4588594.28.636.970462.80.147359761.50.53440.109140363.368789.6435.40.66730.37680.29181486Enter your answer in the edit fields and then click Check Answer.648.375721.60.2024761 partremaining770.50.466210Check Answer

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Description: please help me answer for my data analysis class The data in the accompanying table include the appraised value, land area of the property in acres, and age, in years, for a small sample of 30 single-family homes in a small city. Perform a multiple r

Regression equation for Y, X1 and X2 is constructed below: Excel Procedure for Regression: Enter…

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The data in the accompanying table include the appraised value, land area of the property in acres, and age, in years, for a small sample of 30 single-family homes in a small city. Perform a multiple regression analysis to predict appraised value based on land area of the property (X,) and age, in years, (X,) and determine the VIF for each independent variable in the model. Is there reason to suspect the existence of collinearity? E Click the icon to view the data table. Determine the VIF for each independent variable in the model. Table of Data VIF, =D VIF2 =O (Round to three decimal places as needed.)

The data in the accompanying table include the appraised value, land area of the property in acres, and age, in years, for a small sample of 30 single-family homes in a small city. Perform a multiple regression analysis to predict appraised value based on land area of the property (X,) and age, in years, (X,) and determine the VIF for each independent variable in the model. Is there reason to suspect the existence of collinearity? E Click the icon to view the data table. Determine the VIF for each independent variable in the model. Table of Data VIF, =D VIF2 =O (Round to three decimal places as needed.)

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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Concept explainers

Types of Bias

Statistics is the study of data collection, organization, analysis, interpretation, and presentation. Statistical bias is a characteristic of a statistical technique or its findings in which the expected value deviates from the actual root quantitative parameter being estimated. According to the actual definition of bias, it refers to the tendency of a statistic to overestimate or underestimate a parameter.

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please help me answer for my data analysis class

The data in the accompanying table include the appraised value, land area of the property in acres, and age, in years, for a small sample of 30 single-family homes in a small city. Perform a multiple regression analysis to predict appraised value based on
land area of the property (X,) and age, in years, (X2) and determine the VIF for each independent variable in the model. Is there reason to suspect the existence of collinearity?
Click the icon to view the data table.
Determine the VIF for each independent variable in the model.
i
Table of Data
VIF, =D VIF2 = I
(Round to three decimal places as needed.)
Appraised Land Area
(acres)
0.4471
0.5122
Age
Value
227.8
36
548.8
95
501.5
201.3
0.5545
35
0.3429
84
0.4458
0.5188
648.8
34
670.4
74
720.4
0.2199
91
796.3
0.3161
53
233.3
0.6386
68
289.6
0.5356
35
217.1
0.2729
50
593.2
0.3411
49
433.1
0.1324
28
580.3
0.2306
41
207.4
0.3759
67
277.7
0.4617
14
370.9
0.0879
59
783.4
0.1541
51
272.5
0.6929
48
605.3
0.5545
50
0.2594
0.4588
594.2
8.
636.9
70
462.8
0.1473
59
761.5
0.5344
0.1091
40
363.3
68
789.6
435.4
0.6673
0.3768
0.2918
14
86
Enter your answer in the edit fields and then click Check Answer.
648.3
75
721.6
0.2024
76
1 part
remaining
770.5
0.4662
10
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