Question

Suppose you wanted to understand the relationship between a customer's yearly income (X) and the number of movies (Y) the customer watched in a year. You then gather data on incomes and the number of movies watched in a year. The range of incomes in your data set is $5K to $150K. After fitting a simple linear model and performing all the appropriate diagnostics, the model showed that, on average, for every $10K in income, the customer watched 1.5 movies in the year. So, for example, if a customer earned 60K in a year, he or she would be expected to watch nine movies during the year. Now you want to apply this model to your very wealthy friend who will earn $1 million in the next year. Is this an appropriate application of your model? Why or why not? Provide specific examples to justify your opinion.

Answer #1

Suppose you wanted to understand the relationship between a
customer's yearly income (X) and the number of movies (Y) the
customer watched in a year. You then gather data on incomes and the
number of movies watched in a year. The range of incomes in your
data set is $5K to $150K. After fitting a simple linear model and
performing all the appropriate diagnostics, the model showed that,
on average, for every $10K in income, the customer watched 1.5
movies...

Suppose you wanted to understand the relationship between a
customer's yearly income (X) and the number of movies (Y) the
customer watched in a year. You then gather data on incomes and the
number of movies watched in a year. The range of incomes in your
data set is $5K to $150K. After fitting a simple linear model and
performing all the appropriate diagnostics, the model showed that,
on average, for every $10K in income, the customer watched 1.5
movies...

A study was done to look at the relationship between number of
movies people watch at the theater each year and the number of
books that they read each year. The results of the survey are shown
below.
Movies
5
8
8
8
1
5
5
9
4
Books
6
0
0
0
7
6
3
0
3
Find the correlation coefficient:
r=r= Round to 2 decimal places.
The null and alternative hypotheses for correlation are:
H0:H0: ? r μ ρ ==...

Suppose you had information from customers who shop at a grocery
store, and you wanted to perform cluster analysis to identify
groups of customers who have similar shopping patterns. The data
that you have includes the age, income, and educational level of
the customer, and the yearly amounts each customer purchases of the
following food types: fruits, vegetables, milk, cereal, peanut
butter, and bread. What are some of the data preparation steps that
should be taken before performing cluster analysis?...

In this exercise, you will use this data to investigate the
relationship between the number of completed years of education for
young adults and the distance from each student's high school to
the nearest four-year college. (Proximity lowers the cost of
education, so that students who live closer to a four-year college
should, on average, complete more years of higher education.) The
following table contains data from a random sample of high school
seniors interviewed in 1980 and re-interviewed in...

Please answer the following Case
analysis questions
1-How is New Balance performing compared to its primary rivals?
How will the acquisition of Reebok by Adidas impact the structure
of the athletic shoe industry? Is this likely to be favorable or
unfavorable for New Balance?
2- What issues does New Balance management need to address?
3-What recommendations would you make to New Balance Management?
What does New Balance need to do to continue to be successful?
Should management continue to invest...

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