Corporate headquarters wants to create a simple linear regression model to predict a dealership's sales using the median salary of people living in the vicinity of their dealerships. The simple linear regression model for these variables has a slope of 1495.20. Interpret the slope is this context.

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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A popular U.S. automobile manufacturer has 10,000 dealerships
located throughout the country. The automobile manufacturer
has multiple brands within its portfolio: a value brand that caters
to younger clientele, a moderate brand that caters to middle
class customers and finally, a premium brand which is marketed
to wealthy clientele. The company's leadership, located at
corporate headquarters, is very interested in the relationship
between the median salary of potential customers and the
company's revenue. Specifically, the company is concerned that
if potential customers' salaries continue to not increase in the
future, the company's revenue will remain stagnant, which will in
turn steer away potential investors and shareholders. The
company's research department recently collected data for
analysis in order to support leadership's upcoming discussion
with shareholders and investors about the company's future
revenue forecast. Sales figures from a random sample of 1000
dealerships were collected. The research division also
conducted statistical analysis, using data provided by the Bureau
of Labor and Statistics, to calculate the median salary of people
living in the vicinity of these 1,000 dealerships. The Dealership
Number, State, Median Salary, Annual Sales, Number of
Vehicles Sold, Square Footage and Quality Award Winner data
were collected for these 1000 dealerships.
StatCrunch Data Set
Corporate headquarters wants to create a simple linear
regression model to predict a dealership's sales using the
median salary of people living in the vicinity of their dealerships.
The simple linear regression model for these variables has a
slope of 1495.20.
Interpret the slope is this context.
==
X₂
BI
Insert Formula
S Tx
!!!
E
IM
Transcribed Image Text:A popular U.S. automobile manufacturer has 10,000 dealerships located throughout the country. The automobile manufacturer has multiple brands within its portfolio: a value brand that caters to younger clientele, a moderate brand that caters to middle class customers and finally, a premium brand which is marketed to wealthy clientele. The company's leadership, located at corporate headquarters, is very interested in the relationship between the median salary of potential customers and the company's revenue. Specifically, the company is concerned that if potential customers' salaries continue to not increase in the future, the company's revenue will remain stagnant, which will in turn steer away potential investors and shareholders. The company's research department recently collected data for analysis in order to support leadership's upcoming discussion with shareholders and investors about the company's future revenue forecast. Sales figures from a random sample of 1000 dealerships were collected. The research division also conducted statistical analysis, using data provided by the Bureau of Labor and Statistics, to calculate the median salary of people living in the vicinity of these 1,000 dealerships. The Dealership Number, State, Median Salary, Annual Sales, Number of Vehicles Sold, Square Footage and Quality Award Winner data were collected for these 1000 dealerships. StatCrunch Data Set Corporate headquarters wants to create a simple linear regression model to predict a dealership's sales using the median salary of people living in the vicinity of their dealerships. The simple linear regression model for these variables has a slope of 1495.20. Interpret the slope is this context. == X₂ BI Insert Formula S Tx !!! E IM
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