Business Statistics (BUSA 3101)
Homework #4 Chapters 13-14
Dr. Lari Arjomand
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INSTRUCTIONS:
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Answer all of the following seven (7) questions.
You should explain your answers if it is required.
You “must” type your answers.
Due date will be announced in the class.
All the assigned home works are part of your class participations.
Q #1: What are the inputs and the output of linear regression?
Q #2: High school students were interested in a teacher's claim that the length of time (hours)
that a student studies for a test, the higher the test score. The students collected the data and the
teacher did the regression analysis with the following results.
Write the regression equation in terms of the independent and dependent variables.
Q #3: High school students were interested in a teacher's claim that the length of time (hours)
that a student studies for a test, the higher the test score. The students collected the data and the
teacher did the regression analysis with the following results.
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To test the null hypothesis that no relationship exists between study time and score, what are the
F-test statistic and the F-critical value using the 0.05 significance level?
Q #4: An advertising company wanted to study the effect of advertising budget ($ millions) on
the millions of ad impressions of consumers. The following regression analysis shows the results
of the study.
What is the decision regarding the null hypothesis that no relationship exists?
Q #5: A company wants to study the effect of an employee's length of employment on their
number of workdays absent. The company collected the following information on a random
sample of seven employees.
a- What is the dependent variable (Y)?
b- What is the independent variable (X)?
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c- What is the regression equation?
Q #6: The production of automobile tires in any given year is related to the number of
automobiles produced this year and in prior years. Suppose our econometric model resulted in
the following data.
What is the equation for our model?
Q#7: A manager at a local bank analyzed the relationship between monthly salary and three
independent variables: length of service (measured in months), gender (0 = female, 1 = male)
and job type (0 = clerical, 1 = technical). The following ANOVA summarizes the regression
results:
The results for the variable gender show that…..i.e. who makes more money and by how much?
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