EBK BUSINESS STATISTICS
7th Edition
ISBN: 9780134462783
Author: STEPHAN
Publisher: PEARSON CUSTOM PUB.(CONSIGNMENT)
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A trucking company considered a multiple regression model for relating the
dependent variable y = total daily travel time for one of its drivers (hours) to
the predictors x, = distance traveled (miles) and x, = the number of
deliveries made. Suppose that the model equation is
Y = -0.800 + 0.060x, + 0.900x2 + €
(a) What is the mean value of travel time when distance traveled is 50
miles and four deliveries are made?
5.8
v hr
(b) How would you interpret ß1
= 0.060, the coefficient of the predictor
X1?
o When the number of deliveries is held fixed, the average change
in travel time associated with a one-mile (i.e. one unit) increase in
distance traveled is 0.060 hours.
O The total daily travel time increases by 0.060 hours when the
distance traveled increases by 1.
O When the number of deliveries is constant, the average change in
travel time associated with a ten-mile (i.e. one unit) increase in
distance traveled is 0.060 hours.
O The average change in travel time associated with a…
A clothing manufacturer wants to estimate the amount of scrap cloth generated each day by its fabric cutting machines. Eight potential
independent variables have been identified. These include the following.
= amount of cloth run through cutting machines (in square feet)
X2
= machine cutting speed (in feet per minute)
age of machine (in years)
The manufacturer selects 6 of the candidate independent variables to use in a multiple regression model for estimating y, the amount of scrap
cloth (in square feet). Using data collected from 24 different cutting machines operating on different days, the model
y = Bo+B1*1
+B,x2+
+ Bax, is fit to the data. Fill in the blanks in the analysis of variance (ANOVA) table associated with this model. Do all
...
calculations to at least three decimal places.
The monthly premium quoted by an insurance company for a critical illness policy was collected from a sample of 6 adult male smokers at different age. The data for the sample are shown:
Age
28
25
50
39
47
31
Premium ($)
75
40
175
125
250
105
Using Age to predict premium, the Linear Regression equation is given by:
ŷ =6.556X−112 and r2=0.813y^=6.556X−112 and r2=0.813
a. Identify the independent and Dependent variables.
Dependent:
Age
Premium
Independent:
Age
Premium
b. Determine the slope.
Slope = Slope =
Round to 3 decimal places
c. Determine |r||r| .
|r|=|r|=
Round to 3 decimal places
d. Interpret rr :
and
e. Determine critical r value at 5% significance level and determine if there is a significant linear correlation exists.
|r| critical=|r| critical=
Round to 3 decimal places
Linear Correlation:Linear Correlation:
Significant
Not Significant
f. Predict the monthly premium for a 40 years old adult male smoker.…
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- A trucking company considered a multiple regression model for relating the dependent variable y = total daily travel time for one of its drivers (hours) to the predictors x₁ = distance traveled (miles) and x₂ = the number of deliveries made. Suppose that the model equation is Y = -0.800+ 0.060x₁ +0.900x₂ + e (a) What is the mean value of travel time when distance traveled is 50 miles and four deliveries are made? hr (b) How would you interpret ₁ = 0.060, the coefficient of the predictor x₁? O When the number of deliveries is constant, the average change in travel time associated with a ten-mile (i.e. one unit) increase in distance traveled is 0.060 hours. O The total daily travel time increases by 0.060 hours when the distance traveled increases by 1. O When the number of deliveries is held fixed, the average change in travel time associated with a one-mile (i.e. one unit) increase in distance traveled is 0.060 hours. O The average change in travel time associated with a one-mile (i.e.…arrow_forwardThere exists a moderate relationship between the variables x and y.if we draw samples of increasing sample size,what can we expect from the sample r value,the regression slope and the p value of the regression or correlation be affected by increasing sample sizearrow_forwardThe individual residual scores from a sample of participants regarding the difference between the predicted Y values from a regression equation and the actual Y from the data are provided here. Y - Ŷ = 3,8,1,2,2. What is the value for the standard error of estimate?arrow_forward
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