100102540557085Created by Gary H. McClelland, Professor Emeritus I University of Colorado Boulder© Cengage Learning. All Rights Reserved.1. Find the point with the highest leverage value on the graph. When that point is omitted what value does the r-squared assume from its default of 0.799?a. 0.544b. 0.817c. 0.864d. 0.777-Select-2. When the highest leverage point is omitted does the model remain significant at a = 0.05?%3Da. Yesb. No-Select- v The leverage or h statistic indicates how much influence an observation has on the estimation of the model parameters.Observations with x-values far from the others have larger influence. Move the mouse over each data point to see its leveragevalue. If all observations fit the regression model well, then omitting one observation should not change the analysis very much.Moving the mouse over the data point not only reveals its leverage value but also shows the regression line with that data pointomitted. Examine how omitting certain points affects the regression model.y = 127.47 + (-0.43) x, r-sq = 0.799, t(5) = -4.46, p = 0.0066%3D130120110 -100102540557085

1 Ao the correct ans is BÂ Â 0.817

Answered: ysi | bartleby

Business

Economics

ysi

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

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Question

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Created by Gary H. McClelland, Professor Emeritus I University of Colorado Boulder
© Cengage Learning. All Rights Reserved.
1. Find the point with the highest leverage value on the graph. When that point is omitted what value does the r-squared assume from its default of 0.799?
a. 0.544
b. 0.817
c. 0.864
d. 0.777
-Select-
2. When the highest leverage point is omitted does the model remain significant at a = 0.05?
%3D
a. Yes
b. No
-Select- v

The leverage or h statistic indicates how much influence an observation has on the estimation of the model parameters.
Observations with x-values far from the others have larger influence. Move the mouse over each data point to see its leverage
value. If all observations fit the regression model well, then omitting one observation should not change the analysis very much.
Moving the mouse over the data point not only reveals its leverage value but also shows the regression line with that data point
omitted. Examine how omitting certain points affects the regression model.
y = 127.47 + (-0.43) x, r-sq = 0.799, t(5) = -4.46, p = 0.0066
%3D
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100
10
25
40
55
70
85

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