Question

We have developed a multiple regression model to predict the number of volunteers for a monthly charity event. One of the independent variables is Rain: a binary variable equal to 1 if it rains on the day of the event, and 0 otherwise. In the regression output, the coefficient for Rain is -22. What does that coefficient mean, precisely, with regard to the model’s predictions?

Answer #1

Given that rain =1,if it rans on the day of event and 0 otherwise

coefficient is -22, negative sign shows that there will be 22 less volunteers when binary variable is set to 1

this means that **"on an average,there are 22 less
number of volunteers for the monthly charity event on rainy day as
compared to normal day,when there is no rain"**

so, coefficient tells us the numbe of volunteers for the monthly charity event based on the day type, either rain or normal

A
multiple linear regression model based on a sample of 24 weeks is
developed to predict standby hours based on the total staff present
and remote hours. The SSR is 31,193.47 and the SSE is 33,923.99.
complete parts a through d.
a. Determine whether there is a significant relationship
between standby hours and the two independent variables at the .05
level of significance.
test statistic
pvalue
state the conclusion
b. Interpret the meaning of the p-value.
c. compute the coefficent...

A multiple linear regression model based on a sample of 17 weeks
is developed to predict standby hours based on the total staff
present and remote hours. The SSR is 20,905.02 and the SSE is
25,434.29. (use 0.05 level of significance)
H0: B1 = B2 = 0
H1: At least one Bj does not equal 0, j = 1, 2
1. Calculate the test statistic.
Fstat= _____
2. Find the p-value.
p-value= _____
3. Compute the coefficient of multiple determination,...

1.A real estate analyst has developed a multiple regression
line, y = 60 + 0.068 x1 – 2.5
x2, to predict y = the market
price of a home (in $1,000s), using two independent variables,
x1 = the total number of square feet of living
space, and x2 = the age of the house in years.
With this regression model, the predicted price of a 10-year old
home with 2,500 square feet of living area is __________.
$205.00
$255,000.00
$200,000.00...

An investigator developed a multiple regression model for
employee salaries at a particular company. In this multiple
regression model, the salaries are in thousands of dollars. For
example, a data entry of 35 for the dependent variable indicates a
salary of $35,000. The indicator variable for gender is coded as if
male and if female. The computer output of this multiple regression
model shows that the coefficient for this variable is -4.2. The t
test showed that was significant at...

The owner of a movie theater company used multiple regression
analysis to predict gross revenue (y)
as a function of television advertising
(x1) and newspaper advertising
(x2). The estimated regression
equation was
ŷ = 82.5 + 2.26x1 +
1.30x2.
The computer solution, based on a sample of eight weeks,
provided SST = 25.3 and SSR = 23.415.
(a)Compute and interpret R2
and Ra2.
(Round your answers to three decimal places.)
The proportion of the variability in the dependent variable that...

A microcomputer manufacturer has developed a regression model
relating his sales (Y in $10,000s) with three independent
variables. The three independent variables are price per unit
(Price in $100s), advertising (ADV in $1,000s) and the number of
product lines (Lines). Part of the regression results is shown
below.
Coefficient
Standard Error
Intercept
1.0211
22.8752
Price (X1)
-.1523
-.1411
ADV (X2)
.8849
.2886
Lines(X3)
-.1463
1.5340
Source
D.F.
S.S.
Regression
3
2708.651
Error
14
2840.51
Total
17
5549.12
(a) What has...

The owner of a movie theater company used multiple regression
analysis to predict gross revenue (y) as a
function of television advertising
(x1) and newspaper
advertising (x2). The
estimated regression equation was
ŷ = 83.8 + 2.26x1 +
1.50x2.
The computer solution, based on a sample of eight weeks,
provided SST = 25.8 and SSR = 23.385.
(a) Compute and
interpret R2 and
Ra2.
(Round your answers to three decimal places.)
The proportion of the variability in the dependent variable that
can be...

A regression analysis was performed and the summary output is
shown below.
Regression Statistics
Multiple R
0.7149844700.714984470
R Square
0.5112027920.511202792
Adjusted R Square
0.4904029110.490402911
Standard Error
8.2079903998.207990399
Observations
5050
ANOVA
dfdf
SSSS
MSMS
FF
Significance FF
Regression
22
3311.5863311.586
1655.7931655.793
24.577224.5772
4.9491E-084.9491E-08
Residual
4747
3166.4423166.442
67.37167.371
Total
4949
6478.0286478.028
Step 1 of 2:
How many independent variables are included in the regression
model?
Step 2 of 2:
Which measure is appropriate for determining the proportion of
variation in the dependent...

Consider the following results of a multiple regression model of
dollar price of unleaded gas (dependent variable) and a set of
independent variables: price of crude oil, value of S&P500,
price U.S. Dollars against Euros, personal disposal income (in
million of dollars) :
Coefficient
t-statistics
Intercept
0.5871
68.90
Crude Oil
0.0651
32.89
S&P 500
-0.0020
18.09
Price of $
-0.0415
14.20
PDI
0.0001
17.32
R-Square = 97%
What will be forecasted price of unleaded gas if the value of
independent...

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...

ADVERTISEMENT

Get Answers For Free

Most questions answered within 1 hours.

ADVERTISEMENT

asked 5 minutes ago

asked 6 minutes ago

asked 10 minutes ago

asked 11 minutes ago

asked 21 minutes ago

asked 29 minutes ago

asked 51 minutes ago

asked 1 hour ago

asked 1 hour ago

asked 1 hour ago

asked 1 hour ago

asked 1 hour ago