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TABLE 17-12
The marketing manager for a nationally franchised lawn service company would like to
study the characteristics that differentiate home owners who do and do not have a lawn
service. A random sample of 30 home owners located in a suburban area near a large
city was selected; 15 did not have a lawn service (code 0) and 15 had a lawn service
(code 1). Additional information available concerning these 30 home owners includes
family income (Income, in thousands of dollars), lawn size (Lawn Size, in thousands of
square feet), attitude toward outdoor recreational activities (Attitude 0 = unfavorable, 1
= favorable), number of teenagers in the household (Teenager), and age of the head of
the household (Age).
The Minitab output is given below:
Referring to Table 17-12, what should be the decision ('reject' or 'do not reject') on the
null hypothesis when testing whether Age makes a significant contribution to the model
in the presence of the other independent variables at a 0.05 level of significance?
TABLE 3-7
In a recent academic year, many public universities in the United States raised tuition
and fees due to a decrease in state subsidies. The change in the cost of tuition, a shared
dormitory room, and the most popular meal plan from the previous academic year for a
sample of 10 public universities were as follows: $1,589, $593, $1,223, $869, $423,
$1,720, $708, $1,425, $922 and $308.
Referring to Table 3-7, what is the standard deviation of the change in the cost?
The number of 911 calls in Butte, Montana, has a Poisson distribution with a mean of
10.0 calls a day. The standard deviation of the number of 911 calls in a day is
________.
TABLE 17-10
Given below are results from the regression analysis where the dependent variable is
the number of weeks a worker is unemployed due to a layoff (Unemploy) and the
independent variables are the age of the worker (Age), the number of years of education
received (Edu), the number of years at the previous job (Job Yr), a dummy variable for
marital status (Married: 1 = married, 0 = otherwise), a dummy variable for head of
household (Head: 1 = yes, 0 = no) and a dummy variable for management position
(Manager: 1 = yes, 0 = no). We shall call this Model 1. The coefficient of partial
determination ( ) of each of the 6 predictors are, respectively,
0.2807, 0.0386, 0.0317, 0.0141, 0.0958, and 0.1201.
Model 2 is the regression analysis where the dependent variable is Unemploy and the
independent variables are Age and Manager. The results of the regression analysis are
given below:
Referring to Table 17-10 and using both Model 1 and Model 2, what are the degrees of
freedom of the test statistic for testing whether the independent variables that are not
significant individually are also not significant as a group in explaining the variation in
the dependent variable at a 5% level of significance?
TABLE 17-3
A financial analyst wanted to examine the relationship between salary (in $1,000) and 4
variables: age (X1 = Age), experience in the field (X2 = Exper), number of degrees (X3 =
Degrees), and number of previous jobs in the field (X4 = Prevjobs). He took a sample of
20 employees and obtained the following Microsoft Excel output:
SUMMARY OUTPUT
Regression Statistics
ANOVA
Referring to Table 17-3, the net regression coefficient of X2 is ________.
Referring to Table 14-18, what is the estimated probability that a
school with a mean SAT score of 1100 and a TOEFL criterion that is
not at least 90?
TABLE 14-18
A logistic regression model was estimated in order to predict the
probability that a randomly chosen university or college would be a
private university using information on mean total Scholastic Aptitude
Test score (SAT) at the university or college and whether the TOEFL
criterion is at least 90 (Toe90 = 1 if yes, 0 otherwise). The
dependent variable, Y, is school type (Type = 1 if private and 0
otherwise).
The PHStat output is given below:
TABLE 17-10
Given below are results from the regression analysis where the dependent variable is
the number of weeks a worker is unemployed due to a layoff (Unemploy) and the
independent variables are the age of the worker (Age), the number of years of education
received (Edu), the number of years at the previous job (Job Yr), a dummy variable for
marital status (Married: 1 = married, 0 = otherwise), a dummy variable for head of
household (Head: 1 = yes, 0 = no) and a dummy variable for management position
(Manager: 1 = yes, 0 = no). We shall call this Model 1. The coefficient of partial
determination ( ) of each of the 6 predictors are, respectively,
0.2807, 0.0386, 0.0317, 0.0141, 0.0958, and 0.1201.
Model 2 is the regression analysis where the dependent variable is Unemploy and the
independent variables are Age and Manager. The results of the regression analysis are
given below:
Referring to Table 17-10 and using both Model 1 and Model 2, what is the critical value
of the test statistic for testing whether the independent variables that are not significant
individually are also not significant as a group in explaining the variation in the
dependent variable at a 5% level of significance?
