Question

**Question #1**

The sale of handguns is very popular in the Hill Country. A Criminal Justician researcher who has been investigating the prevalence of guns in the State came up with the following regression model to predict sales at one of the gun outlets.

where

*X _{1}* = number of competitors who also sell
guns within one mile

*X _{3}*= {=1 when purchase by drive-up window is
allowed; =0 when purchase by drive-up window is not allowed}

*y* = sales ($ 1000s)

The following estimated regression equation was developed after
20 gun shops were surveyed.

*Y^* = 10.1 - *4.2x _{1}*+

- What is the expected amount of sales attributable to the drive-up window?

- Predict sales for a store with two competitors, a population of
8000 within 1 mile, and

no drive-up window. - Predict sales for a store with one competitor, a population of
3000 within 1 mile, and

a drive-up window - Interpret the coefficient for population within 1 mile
- Interpret the coefficient for the number of competitors who sell guns within one mile

Answer #1

- Predict sales for a store with two competitors, a population of
8000 within 1 mile, and

no drive-up window.

*Y* = 10.1 - *4.2*2*+ *6.8*8000*+
*15.3*0*

*Y =* 54401.7

- Predict sales for a store with one competitor, a population of
3000 within 1 mile, and

a drive-up window

*Y* = 10.1 - *4.2*1*+ *6.8*3000*+
*15.3*1*

*Y =* 20421.2

- Interpret the coefficient for population within 1 mile

For every additional population within 1 mile, sales will increase by 6.8.

- Interpret the coefficient for the number of competitors who sell guns within one mile

For every additional competitor who sells guns within one mile, sales will decrease by 4.2.

1.
Management of a fast-food chain proposed the following
regression model to predict sales at outlets:
y = β0 + β1x1 +
β2x2 + β3x3 + ε,
where
y = sales ($1000s)
x1= number of competitors
within one mile
x2= population (in 1000s)
within one mile
x3is 1 if a drive-up window
is present, 0 otherwise
The following estimated regression equation was developed after
20 outlets were surveyed:
= 12.6 − 3.6x1+
7.0x2+ 14.1x3
Use this equation to predict sales...

Management of a fast-food chain proposed the following
regression model to predict sales at outlets:
y = β0 + β1x1 +
β2x2 + β3x3 + ε,
where
y = sales ($1000s)
x1= number of competitors
within one mile
x2= population (in 1000s)
within one mile
x3is 1 if a drive-up window
is present, 0 otherwise
Multiple regression analysis was performed on a random sample of
data collected from 25 outlets.
Given the following portion of an output of the regression...

The following
regression model has been proposed to predict sales at a computer
store:
y_hat = 50 –
3x1 + 20x2 +
10x3
where
x1
= competitor's previous day's sales (in $1000s)
x2
= population within 1 mile (in 1000s)
x3
= 1 if any radio advertising was used and 0
otherwise.
y_hat= sales (in
$1000s)
Predict the change in
sales (in dollars) when radio advertising was used, all else
constant.
This, is from question one if needed; Predict sales (in...

1. You want to obtain a sample to estimate a population
proportion. At this point in time, you have no reasonable estimate
for the population proportion. Your would like to be 99.9%
confident that you estimate is within 4% of the true population
proportion. How large of a sample size is required? n =
2. A regression analysis was performed to determine if there is
a relationship between hours of TV watched per day (xx) and number
of sit ups...

The general manager of a chain of pharmaceutical stores reported
the results of a regression analysis, designed to predict the
annual sales for all the stores in the chain (Y) – measured in
millions of dollars. One independent variable used to predict
annual sales of stores is the size of the store (X) – measured in
thousands of square feet. Data for 14 pharmaceutical stores were
used to fit a linear model. The results of the simple linear
regression are...

Question One:
The demand curve for product X is given as Qx =
180-150Px +60Py +3A.
Where Px =4, Py $8, and A=20
A). Calculate the price elasticity of demand for x. Will
a decrease in price increases total revenue?
B). Calculate the cross-price elasticity of demand. Are
X and Y are substitute or complementary
goods?
Question Two:
A minor league baseball team is trying to predict ticket
sales for the upcoming season and considering changing ticket
price.
The...

13-19 Describe how Bass Pro Shops became the nation’s leading
outdoor retailer based on the retail marketing mix.
13-20 In terms of the major types of retailers, how would you
classify Bass Pro Shops?
13-21 Why is Bass Pro Shops succeeding while Cabela’s is
floundering?
13-22 Is it a good idea for Bass Pro Shops to acquire Cabela’s?
Explain.
Outdoor-products megaretailer Bass Pro Shops has seemingly been
breaking the rules of retail for more than 40 years, basking in the...

As for the sales forecast for Year 1 through Year 3, these are
some important variables I will go to consider for sales:
Economy: The economic condition of the city, the province and
the country are variables I need to consider for a sales forecast.
If conditions are poor, people will spend less money on
consumption. If economic conditions are great, then more people
will have extra money to spend.
Competition: I need to consider the level of competition I...

1.
Johnson Filtration, Inc., provides maintenance service for
water-filtration systems throughout southern Florida. Customers
contact Johnson with requests for maintenance service on their
water-filtration systems. To estimate the service time and the
service cost, Johnson’s managers want to predict the repair time
necessary for each maintenance request.
Management collected data over the last 10 service calls, and
ran a multiple regression analysis on this sample. As a result,
they developed the following estimated regression
equation to predict y = the...

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 ==...

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