Reference no: EM13375516
1. Load the Blue Spruce Light Up Data (latest file, through 2013).
Extract and specify a model that predicts Cars through the gate as a function of Price and Average Daily Temperature.
|
Dependent Variable
|
CARS
|
|
N
|
22
|
|
Multiple R
|
0.7912337
|
|
Squared Multiple R
|
0.6260507
|
|
Adjusted Squared Multiple R
|
0.5866876
|
|
Standard Error of Estimate
|
489.8477246
|
|
Regression Coefficients B = (X'X)-1X'Y
|
|
Effect
|
Coefficient
|
Standard Error
|
Std.
Coefficient
|
Tolerance
|
t
|
p-value
|
|
CONSTANT
|
3,256.1687058
|
913.1082505
|
0.0000000
|
.
|
3.5660270
|
0.0020617
|
|
PRICE
|
-289.3428493
|
64.1230827
|
-0.6330709
|
0.9998873
|
-4.5123041
|
0.0002384
|
|
PITTDECT
|
82.8148154
|
24.8288902
|
0.4679557
|
0.9998873
|
3.3354216
|
0.0034764
|
|
Analysis of Variance
|
|
Source
|
SS
|
df
|
Mean Squares
|
F-ratio
|
p-value
|
|
Regression
|
7.6326021E+006
|
2
|
3.8163011E+006
|
15.9045153
|
0.0000874
|
|
Residual
|
4.5590651E+006
|
19
|
2.3995079E+005
|
|
|
|
Durbin-Watson D Statistic
|
0.9936443
|
|
First Order Autocorrelation
|
0.4089696
|
CARS=3256.169 - 289.343(PRICE) + 82.815(TEMP)
Using a hypothetical temperature of 35 degrees and a price of $8, predict the number of cars through the gate.
CARS=3256.169 - 289.343(8) + 82.815(35)
=3256.169 - 2314.744 + 2898.525 = 3839.96
= 3840 CARS
Now using a hypothetical temperature of 35 degrees and a price of $9, predict the number of cars through the gate.
CARS=3256.169 - 289.343(9) + 82.815(35)
=3256.169 - 2604.087 + 2898.525 = 3550.607
=3551 CARS
Now using a hypothetical temperature of 35 degrees and a price of $10, predict the number of cars through the gate.
CARS=3256.169 - 289.343(10) + 82.815(35)
=3256.169 - 2893.43 + 2898.525 = 3261.264
=3261 CARS
Predicted Total Revenue at $8 = 8(3840) = $30,720
Predicted Total Revenue at $9 = 9(3551) = $31,959
Predicted Total Revenue at $10 = 10(3261) = $32,610
Compute the point price elasticity of demand at $8:
At $9:
At $10:
Based on your point elasticity results which is the better price to charge?
Attachment:- Q5 data.xlsx