The following table shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance.What is the computed R square of the resulting multiple linear regression and its interpretation? *

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
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Chapter4: Equations Of Linear Functions
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The following table shows the starting salary and profile of a sample of 10 2 p
employees in a certain call center agency. Run a multiple regression
analysis with starting salary as the dependent variable (pesos) and GPA,
years of experience and civil service ratings as the independent variables.
Use .05 level of significance.What is the computed R square of the
resulting multiple linear regression and its interpretation? *
Civil
Years of
Starting salary
GPA
service
experience
ratings
79.5
15000 80.1
15000 81.2
78.0
15500 81.3
79.0
16000 82.4
80.0
16200 83.4
85.0
17500 87.9
89.9
89.1
18000 90.3
16,300 84.2
17000 87.0
17900 88.1
84.1
89.0
89.2
R squared = 0.8053; This means that 80.53% of the total variation in the starting
salary can be explained by its linear relationship with GPA, years of experience and
civil service ratings.
R squared = 0.9651; This means that 96.51% of the total variation in the starting
salary can be explained by its linear relationship with GPA, years of experience and
civil service ratings.
R squared = 0.9907; This means that 99.07% of the total variation in the starting
salary can be explained by its linear relationship with GPA, years of experience and
civil service ratings.
R squared = 0.9651; This means that 96.51% of the total amount of starting salary
can be explained by its linear relationship with GPA, years of experience and civil
service ratings.
1123 345 45
Transcribed Image Text:The following table shows the starting salary and profile of a sample of 10 2 p employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance.What is the computed R square of the resulting multiple linear regression and its interpretation? * Civil Years of Starting salary GPA service experience ratings 79.5 15000 80.1 15000 81.2 78.0 15500 81.3 79.0 16000 82.4 80.0 16200 83.4 85.0 17500 87.9 89.9 89.1 18000 90.3 16,300 84.2 17000 87.0 17900 88.1 84.1 89.0 89.2 R squared = 0.8053; This means that 80.53% of the total variation in the starting salary can be explained by its linear relationship with GPA, years of experience and civil service ratings. R squared = 0.9651; This means that 96.51% of the total variation in the starting salary can be explained by its linear relationship with GPA, years of experience and civil service ratings. R squared = 0.9907; This means that 99.07% of the total variation in the starting salary can be explained by its linear relationship with GPA, years of experience and civil service ratings. R squared = 0.9651; This means that 96.51% of the total amount of starting salary can be explained by its linear relationship with GPA, years of experience and civil service ratings. 1123 345 45
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