PLEASE HELP WITH HOW TO DO THIS WITH EXCEL!! THANK YOU!   Repair Time in Hours Months Since Last Service Type of Repair Repairperson 2.9 2 Electrical Donna Newton 2.9 2 Electrical Donna Newton 4.4 4 Electrical Bob Jones 4.5 6 Electrical Donna Newton 4.8 8 Electrical Bob Jones 4.9 7 Electrical Bob Jones 1.8 3 Mechanical Donna Newton 3.0 6 Mechanical Donna Newton 4.2 9 Mechanical Bob Jones 4.8 8 Mechanical Bob Jones SUMMARY OUTPUT                                   Regression Statistics               Multiple R 0.730873795               R Square 0.534176504               Adjusted R Square 0.475948567               Standard Error 0.781022322               Observations 10                                 ANOVA                   df SS MS F Significance F       Regression 1 5.596033058 5.596033058 9.17388683 0.016338159       Residual 8 4.879966942 0.609995868           Total 9 10.476                                 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 2.147272727 0.604977289 3.549344356 0.007516627 0.752192596 3.542352858 0.752192596 3.542352858 X Variable 1 0.304132231 0.100412033 3.02884249 0.016338159 0.072581669 0.535682794 0.072581669 0.535682794   Using the simple linear regression model developed in part (a), calculate the predicted repair time and residual for each of the 10 repairs in the data. Sort the data in ascending order by value of the residual. Do you see any pattern in the residuals for the two types of repair? Do you see any pattern in the residuals for the two repairpersons? Do these results suggest any potential modifications to your simple linear regression model? Now create a scatter chart with months since last service on the x-axis and repair time in hours on the y-axis for which the points representing electrical and mechanical repairs are shown in different shapes and/or colors. Create a similar scatter chart of months since last service and repair time in hours for which the points representing repairs by Bob Jones and Donna Newton are shown in different shapes and/or colors. Do these charts and the results of your residual analysis suggest the same potential modifications to your simple linear regression model?

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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PLEASE HELP WITH HOW TO DO THIS WITH EXCEL!! THANK YOU!

 

Repair Time in Hours Months Since Last Service Type of Repair Repairperson
2.9 2 Electrical Donna Newton
2.9 2 Electrical Donna Newton
4.4 4 Electrical Bob Jones
4.5 6 Electrical Donna Newton
4.8 8 Electrical Bob Jones
4.9 7 Electrical Bob Jones
1.8 3 Mechanical Donna Newton
3.0 6 Mechanical Donna Newton
4.2 9 Mechanical Bob Jones
4.8 8 Mechanical Bob Jones
SUMMARY OUTPUT                
                 
Regression Statistics              
Multiple R 0.730873795              
R Square 0.534176504              
Adjusted R Square 0.475948567              
Standard Error 0.781022322              
Observations 10              
                 
ANOVA                
  df SS MS F Significance F      
Regression 1 5.596033058 5.596033058 9.17388683 0.016338159      
Residual 8 4.879966942 0.609995868          
Total 9 10.476            
                 
  Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 2.147272727 0.604977289 3.549344356 0.007516627 0.752192596 3.542352858 0.752192596 3.542352858
X Variable 1 0.304132231 0.100412033 3.02884249 0.016338159 0.072581669 0.535682794 0.072581669 0.535682794

 

Using the simple linear regression model developed in part (a), calculate the predicted repair time and residual for each of the 10 repairs in the data. Sort the data in ascending order by value of the residual. Do you see any pattern in the residuals for the two types of repair? Do you see any pattern in the residuals for the two repairpersons? Do these results suggest any potential modifications to your simple linear regression model? Now create a scatter chart with months since last service on the x-axis and repair time in hours on the y-axis for which the points representing electrical and mechanical repairs are shown in different shapes and/or colors. Create a similar scatter chart of months since last service and repair time in hours for which the points representing repairs by Bob Jones and Donna Newton are shown in different shapes and/or colors. Do these charts and the results of your residual analysis suggest the same potential modifications to your simple linear regression model?

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