Mechele Neal Statistics Assignment 4dProblems 14.15, 14.28, 14.30, 14.35, 14.44 and XXXXXXXXXXWhat is the SStotal? The sum of squares total, SStotal, represents the worst-case scenario, the total...

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Mechele Neal Statistics Assignment 4dProblems 14.15, 14.28, 14.30, 14.35, 14.44 and 14.5014.15 What is the SStotal? The sum of squares total, SStotal, represents the worst-case scenario, the total error we would have in our predictions if there was no regression equation and we had to predict the mean for everybody.14.28 Write the equation for the line of prediction using the following output from a multiple regression analysis:ModelUnstandardized CoefficientsStandardizedCoefficientst3.3334.313-1.704Sig0.0010.0000.093BStd ErrorBeta1 (Constant) Variable 1 Variable 23.977.414-0.0191.1930.0960.


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Mechele Neal Statistics Assignment 4d Problems 14.15, 14.28, 14.30, 14.35, 14.44 and 14.50 14.15 What is the SStotal? The sum of squares total, SStotal, represents the worst-case scenario, the total error we would have in our predictions if there was no regression equation and we had to predict the mean for everybody. 14.28 Write the equation for the line of prediction using the following output from a multiple regression analysis: ModelUnstandardized CoefficientsStandardized Coefficients t 3.333 4.313 -1.704 Sig 0.001 0.000 0.093BStd ErrorBeta 1 (Constant) Variable 1 Variable 2 3.977 .414 -0.019 1.193 0.096 0.011 0.458 -.181Dependant variable : Outcome (Y) 14.30 Use the equation for the line you created in Exercise 1 4.28 to make predictions for each of the following: a. Variable 1 = 6, variable 2 = 60 b. Variable 1 = 9, variable 2 = 54.3 c. Variable 1 = 1 3, variable 2 = 44.8 1 4.35 Running a football stadium for an NFL team involves innumerable predictions. For example, when stocking up on food and beverages for sale at the game, it helps to have an idea of how much will be sold. In the football stadiums in colder climates, stadium managers use expected outdoor temperature to predict sales of hot chocolate. a. What is the independent variable in this example? Outdoor temperature b. What is the dependent variable? How many hot chocolates expected to be sold c. As the value of the independent variable increases, what can we predict would happen to the value of the dependent variable? Increase in outdoor temperature will decrease hot chocolates sold. d. What other variables might predict this dependent variable? Name at least three. How many people came to the game, how many people like hot chocolate, how much money people have to spend at the game. 1 4.44 Exercises 1 4.39, 1 4.41 , and 14.43 used the example from How It Works 1 3.2 on whether age can predict how much people study. Here are the data once again. Number...



Answered Same DayDec 20, 2021

Answer To: Mechele Neal Statistics Assignment 4dProblems 14.15, 14.28, 14.30, 14.35, 14.44 and XXXXXXXXXXWhat...

David answered on Dec 20 2021
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Mechele Neal Statistics Assignment 4d
Problems 14.15, 14.28, 14.30, 14.35, 14.44 and 14.50
14.15 What is the SStotal? The sum of squares total, SStotal, represen
ts the worst-case scenario, the
total error we would have in our predictions if there was no regression equation and we had to predict
the mean for everybody.
14.28 Write the equation for the line of prediction using the following output from a multiple regression
analysis:
Model
Unstandardized
Coefficients
Standardized
Coefficients
t
3.333
4.313
-1.704
Sig
0.001
0.000
0.093
B Std Error Beta
1 (Constant)
Variable 1
Variable 2
3.977
.414
-0.019
1.193
0.096
0.011
0.458
-.181
a. Dependant variable : Outcome (Y)
Answer:
Y = 3.977 + 0.414*Variable1 – 0.019*Variable2
14.30 Use the equation for the line you created in Exercise 1 4.28 to make predictions for each of the
following:
a. Variable 1 = 6, variable 2 = 60
b. Variable 1 = 9, variable 2 = 54.3
c. Variable 1 = 1 3, variable 2 = 44.8
Answer: a. Predicted Y = 3.977 + 0.414*6 – 0.019*60 = 5.321
b. Predicted Y = 3.977 + 0.414*9 – 0.019*54.3 = 6.6713
c. Predicted Y = 3.977 + 0.414*13 – 0.019*44.8 = 8.5078
14.35 Running a football stadium for an NFL team involves innumerable predictions. For example, when
stocking up on food and beverages for sale at the game, it helps to have an idea of how much will be
sold. In the football stadiums in colder climates, stadium managers use expected outdoor temperature
to predict sales of hot chocolate.
a. What is the independent variable in this example? Outdoor temperature
b. What is the dependent...
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