Question

In: Statistics and Probability

What is the percentage of the variance of the Avg. Total Score variable explained by this...

  1. What is the percentage of the variance of the Avg. Total Score variable explained by this linear relationship with per pupil spending? Briefly explain your answer.
  2. Interpret the slope of the regression line for this model.
State PPS T/S Ratio Avg. Salary %Takers Avg. Tot. Score
"Alabama"        4.405 17.2 31.144 10 1035
"Alaska"         8.963 17.6 47.951 48 939
"Arizona"        4.778 19.3 32.175 28 950
"Arkansas"       4.459 17.1 28.934 7 1010
"California"     4.992 24 41.078 46 908
"Colorado"       5.443 18.4 34.571 31 985
"Connecticut"    8.817 14.4 50.045 82 914
"Delaware"       7.03 16.6 39.076 70 902
"Florida"        5.718 19.1 32.588 50 895
"Georgia"        5.193 16.3 32.291 66 859
"Hawaii"         6.078 17.9 38.518 58 895
"Idaho"          4.21 19.1 29.783 16 984
"Illinois"       6.136 17.3 39.431 14 1054
"Indiana"        5.826 17.5 36.785 59 887
"Iowa"           5.483 15.8 31.511 7 1105
"Kansas"         5.817 15.1 34.652 11 1066
"Kentucky"       5.217 17 32.257 12 1005
"Louisiana"      4.761 16.8 26.461 10 1027
"Maine"          6.428 13.8 31.972 70 902
"Maryland"       7.245 17 40.661 65 915
"Massachusetts" 7.287 14.8 40.795 81 913
"Michigan"       6.994 20.1 41.895 13 1038
"Minnesota"      6 17.5 35.948 10 1091
"Mississippi"    4.08 17.5 26.818 5 1041
"Missouri"       5.383 15.5 31.189 10 1051
"Montana"        5.692 16.3 28.785 23 1014
"Nebraska"       5.935 14.5 30.922 10 1056
"Nevada"         5.16 18.7 34.836 31 922
"New Hampshire" 5.859 15.6 34.72 70 941
"New Jersey"     9.774 13.8 46.087 72 904
"New Mexico"     4.586 17.2 28.493 12 1021
"New York"       9.623 15.2 47.612 76 898
"North Carolina" 5.077 16.2 30.793 62 871
"North Dakota"   4.775 15.3 26.327 7 1113
"Ohio"           6.162 16.6 36.802 25 981
"Oklahoma"       4.845 15.5 28.172 11 1032
"Oregon"         6.436 19.9 38.555 53 953
"Pennsylvania"   7.109 17.1 44.51 72 885
"Rhode Island"   7.469 14.7 40.729 70 894
"South Carolina" 4.797 16.4 30.279 60 849
South Dakota"   4.775 14.4 25.994 6 1074
"Tennessee"      4.388 18.6 32.477 14 1045
"Texas"          5.222 15.7 31.223 50 899
"Utah"           3.656 24.3 29.082 6 1082
"Vermont"        6.75 13.8 35.406 70 907
"Virginia"       5.327 14.6 33.987 66 902
"Washington"     5.906 20.2 36.151 50 943
"West Virginia" 6.107 14.8 31.944 19 937
"Wisconsin"      6.93 15.9 37.746 10 1079
"Wyoming"        6.16 14.9 31.285 12 1006

Solutions

Expert Solution

We will be applying the Linear regression model here, it can be done by using the function LINEST(y_value, x_value, TRUE, TRUE) where y_values contain values of Sales here and x_values have Advertising values.

Select 5 rows and 2 columns and then write the formula in the first cell and after that, press Shift + Ctrl + Enter.    

The equation comes out to be -

avg tot score = 1053.703 + 5.616*PPS -3.37*T/S Ratio + 1.382*Avg Salary - 2.90 * %Taker s                  

The slopes for the regression line will be 5.616, -3.37, 1.38 and -2.90 for PPS, T/S Ration, Avg Salary and %Taker s respectively.

Interpretation of slopes

When PPS is increased by a unit, the avg total will increase by 5.616 units.

When T/S Ratio is increased by a unit, the avg total will decrease by 3.37 units.

When Avg Salary is increased by a unit, the avg total will increase by 1.382 units.

When %Taker s is increased by a unit, the avg total will decrease by 2.9 units.

The coefficient of determination(R**2) comes out to be 0.824190568, it means 82.4% of the avg total score variable can be explained by all the independent variables.



  


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