Examine the computer output for Equation 1 modeling the number of cars admitted to the Blue Spruce
Question:
- Predict the number of cars through the gate when the admission price is set at $6.
- Now predict the number of cars through the gate when the admission price is set at $7.
- Compute the arc price elasticity of demand in the range of prices $6 to $7.
- Is demand elastic or inelastic in the price range $6 to $7.
- Examine the computer output for Equation 2 modeling the number of cars admitted to the Blue Spruce Holiday Light Up Event. Extract and specify Equation 2 which will show Cars as a function of Price and average December Temperature.
7. Predict the number of Cars through the gate if the price is $8 and the average December temperature is 30 degrees.
- Using Equation 1, what price should we charge to get the maximum total revenue?
- Show or explain how you determined the revenue-maximizing price in the previous question? [There are several ways to do this. Think, explore, and try to find a way to figure it out.]
- What percent of the variation in cars through the gate can be accounted for by variation in admission price and average December Temperature?
Dependent Variable | CARS |
N | 15 |
Multiple R | 0.8298604 |
Squared Multiple R | 0.6886683 |
Adjusted Squared Multiple R | 0.6647197 |
Standard Error of Estimate | 478.7469853 |
Regression Coefficients B = (X'X)-1X'Y | ||||||
Effect | Coefficient | Standard Error | Std. Coefficient | Tolerance | t | p-value |
CONSTANT | 7,553.2334688 | 580.7547678 | 0.0000000 | . | 13.0058914 | 0.0000000 |
PRICE | -633.9414634 | 118.2181417 | -0.8298604 | 1.0000000 | -5.3624719 | 0.0001292 |
Dependent Variable | CARS |
N | 15 |
Multiple R | 0.9203313 |
Squared Multiple R | 0.8470097 |
Adjusted Squared Multiple R | 0.8215113 |
Standard Error of Estimate | 349.3071128 |
Regression Coefficients B = (X'X)-1X'Y | ||||||
Effect | Coefficient | Standard Error | Std. Coefficient | Tolerance | t | p-value |
CONSTANT | 5,017.0284102 | 835.1434178 | 0.0000000 | . | 6.0073854 | 0.0000615 |
PRICE | -613.3296817 | 86.4533074 | -0.8028786 | 0.9954233 | -7.0943461 | 0.0000126 |
PITTDECT | 73.4854826 | 20.8519046 | 0.3988350 | 0.9954233 | 3.5241617 | 0.0041912 |
Case | CARS | PRICE | PITTDECT |
1 | 6000 | 3 | 33.9 |
2 | 5966.7 | 3 | 31.7 |
3 | 4697.3 | 4 | 38.2 |
4 | 4436.8 | 4 | 27.7 |
5 | 4760 | 4 | 36.5 |
6 | 5072.8 | 4 | 33.5 |
7 | 5066 | 5 | 37.8 |
8 | 4446 | 5 | 34.6 |
9 | 3455.4 | 5 | 23.1 |
10 | 4781.4 | 5 | 37.5 |
11 | 3865.3 | 6 | 30.7 |
12 | 3447.8 | 6 | 32.6 |
13 | 3711 | 6 | 33.3 |
14 | 3448.2 | 6 | 27.6 |
15 | 4500.2 | 6 | 38.8 |
16 | . | . | . |
Applied Regression Analysis and Other Multivariable Methods
ISBN: 978-1285051086
5th edition
Authors: David G. Kleinbaum, Lawrence L. Kupper, Azhar Nizam, Eli S. Rosenberg