Question
In: Statistics and Probability
8. The following Regression function has been developed to check the relationship between Y-‘Risk of a...
8. The following Regression function has been developed to check the relationship between Y-‘Risk of a stroke’ and some other factors;
X1- Age
X2 –Pressure
X3 –Smoker
X4 -Age
Press Consider the following Minitab output and answer the questions.
Risk = - 123 + 1.51 Age + 0.448 Pressure + 8.87 Smoker - 0.00276 AgePress
Predictor Coef SE Coef T P
Constant -123.16 56.94 -2.16 0.047
Age 1.5130 0.5980 2.53 0.021
Pressure 0.4483 0.1291 3.47 0.004
Smoker 8.866 3.074 2.88 0.011
AgePress -0.002756 0.004807 -0.57 0.575
S = 5.881 R-Sq = 87.6% R-Sq(adj) = 84.3%
Analysis of Variance
Source DF SS MS F P
Regression 4 3672.11 918.03 26.54 0.000
Residual Error 15 518.84 34.59
Total 19 4190.95
a) Write the hypotheses of F-test to check the overall relationship between Y and X1,X2,X3 ,X4.
b) What is your conclusion of part (a) ? (Use α =0.05) You need to justify your answer using appropriate value from the output.
c) Write the hypotheses of the t-tests to test whether X1, X2, X3 and Y have a significant regression relationship.
d)What can you say about the significance of the X2 and X4 to the regression equation based on the corresponding t-tests? (Use α =0.05). Please conduct t-test for X2 and X4 separately. Please use appropriate values related to t-test from the above output. Make sure to show all your steps.
e) What can you say about the above regression equation based on the adjusted r2 (R-Sq(adj)) value from the output?
Solutions
orchestra answered 1 year agoRelated Solutions
The following Regression function has been developed to check the relationship between Y- ‘Sales’ and the...
The following Regression function has been developed to check
the relationship between Y- ‘Sales’ and the following independent
variables;
X1- Time (Length of time employed in months)
X2 –Poten (Market potential)
X3 – AdvExp (Advertising expenditure in the sales territory)
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3 Consider the following Minitab output and answer the
questions. Regression Analysis: Sales versus Time, Poten,
AdvExp,
Accounts Regression Equation Sales = -391 - 0.58 Time + 0.02227
Poten +...
Multiple regression analysis was used to study the relationship between a dependent variable, y, and four...
Multiple regression analysis was used to study the relationship
between a dependent variable, y, and four independent
variables; x1, x2,
x3, and x4. The following
is a partial result of the regression analysis involving 31
observations.
Coefficients
Standard Error
Intercept
18.00
6.00
x1
12.00
8.00
x2
24.00
48.00
x3
-36.00
36.00
x4
16.00
2.00
ANOVA
df
SS
MS
F
Regression
125
Error
Total
760
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Shirley industries is analyzing an average risk project, and the following data has been developed. Annual...
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A hospital administrator developed a regression line, y = 30 + 2x, to predict y =...
A hospital administrator developed a regression line, y
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slope of this regression line suggests this: __________.
for a unit increase in the number of beds, the number of FTEs is
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for a unit increase in the number of beds, the number of FTEs is
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for a unit...
8. Run a regression analysis on the following bivariate set of data with y as the...
8. Run a regression analysis on the following bivariate set of
data with y as the response variable.
x
y
27.2
68.2
28.1
66.7
28.7
64.6
30.2
66.4
33.7
69.5
31.8
68.3
30.4
67.8
28.6
65.5
32.5
69.4
34.8
67.9
33.3
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28
66.1
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r =
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A computer manufacturer has developed a regression model relating his sales (Y in $10,000s) with three...
A computer manufacturer has developed a regression model
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variables. The three independent variables are price per unit
(Price in $100s), advertising (ADV in $1,000s) and the number of
product lines (Lines). Part of the regression results is shown
below.
Coefficient
Standard Error
Intercept
1.0211
22.8752
Price
-0.1524
0.1411
ADV
0.8849
0.2886
Lines
-0.1463
1.5340
Analysis of Variance
Source of
Variation
Degrees
of Freedom
Sum of
Squares
Regression
2708.61
Error (Residuals)
Required:...
A computer manufacturer has developed a regression model relating his sales (Y in $10,000s) with three...
A computer manufacturer has developed a regression model
relating his sales (Y in $10,000s) with three independent
variables. The three independent variables are price per unit
(Price in $100s), advertising (ADV in $1,000s) and the number of
product lines (Lines). Part of the regression results is shown
below.
Coefficient
Standard Error
Intercept
1.0211
22.8752
Price
-0.1524
0.1411
ADV
0.8849
0.2886
Lines
-0.1463
1.5340
Analysis of Variance
Source of
Variation
Degrees
of Freedom
Sum of
Squares
Regression
2708.61
Error (Residuals)
Required:...
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1. scatter plot of x and y
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In Chapter 8, Mayo (2019) discussed the relationship between risk and required return and referenced the...
In Chapter 8, Mayo (2019) discussed the relationship between
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