Estimated Demand Function:ln(Q) = -6.758 – 2.116ln(P) + 1.331ln(l) – 0.44ln(A) + 2.99ln(Psub) + 0.908ln(Pop) Suppose we decide to charge a per ounce price of $2, while at the same time our rival charges a price of $2.15. All else equal, what would you ex
Estimated Demand Function:ln(Q) = -6.758 – 2.116ln(P) + 1.331ln(l) – 0.44ln(A) + 2.99ln(Psub) + 0.908ln(Pop) Suppose we decide to charge a per ounce price of $2, while at the same time our rival charges a price of $2.15. All else equal, what would you ex
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Estimated Demand Function:ln(Q) = -6.758 – 2.116ln(P) + 1.331ln(l) – 0.44ln(A) + 2.99ln(Psub) + 0.908ln(Pop)
- Suppose we decide to charge a per ounce price of $2, while at the same time our rival charges a price of $2.15. All else equal, what would you expect sales to be? How confident are you in your forecast?

Transcribed Image Text:### Descriptive Statistics of Various Variables
The table below presents descriptive statistics for six different variables labeled as \(Q\), \(P\), \(I\), \(A\), \(P_{\text{sub}}\), and \(Pop\).
#### Summary Statistics:
- **Mean:**
- \(Q\): 34.822
- \(P\): 1.990
- \(I\): 29.040
- \(A\): 4.631
- \(P_{\text{sub}}\): 2.113
- \(Pop\): 123.395
- **Standard Error:**
- \(Q\): 1.353
- \(P\): 0.016
- \(I\): 0.444
- \(A\): 0.187
- \(P_{\text{sub}}\): 0.022
- \(Pop\): 3.205
- **Median:**
- \(Q\): 33.695
- \(P\): 1.990
- \(I\): 29.200
- \(A\): 4.410
- \(P_{\text{sub}}\): 2.085
- \(Pop\): 122.800
- **Standard Deviation:**
- \(Q\): 6.050
- \(P\): 0.073
- \(I\): 1.984
- \(A\): 0.835
- \(P_{\text{sub}}\): 0.098
- \(Pop\): 14.335
- **Sample Variance:**
- \(Q\): 36.602
- \(P\): 0.005
- \(I\): 3.935
- \(A\): 0.697
- \(P_{\text{sub}}\): 0.010
- \(Pop\): 205.496
#### Shape Characteristics:
- **Kurtosis:**
- \(Q\): 0.340
- \(P\): -1.323
- \(I\): 1.368
- \(A\): -0.554
- \(P_{\text{sub}}\): 2.041
- \(Pop
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