Question

In: Economics

San Francisco Bread Company Demand (Q) Price (P) Competitor Price (Px) Advertising (Ad) Income (I)             ...

San Francisco Bread Company
Demand (Q) Price (P) Competitor Price (Px) Advertising (Ad) Income (I)
             599,201 $6.66 $5.96 $206,647.00 $52,955.00
             572,258 $8.01 $5.30 $207,025.00 $54,391.00
             558,142 $7.53 $6.16 $207,422.00 $48,491.00
             627,973 $6.51 $7.56 $216,224.00 $51,219.00
             593,024 $6.20 $7.15 $217,954.00 $48,685.00
             565,004 $7.28 $6.97 $220,139.00 $47,219.00
             596,254 $5.95 $5.52 $220,215.00 $49,775.00
             652,880 $6.42 $6.27 $220,728.00 $54,932.00
             596,784 $5.94 $5.66 $226,603.00 $48,092.00
             657,468 $6.47 $7.68 $228,620.00 $54,929.00
             519,866 $6.99 $5.10 $230,241.00 $46,057.00
             612,941 $7.72 $5.38 $232,777.00 $55,239.00
             621,707 $6.46 $6.20 $237,300.00 $53,976.00
             597,215 $7.31 $7.43 $238,765.00 $49,576.00
             617,427 $7.36 $5.28 $241,957.00 $55,454.00
             572,320 $6.19 $6.12 $251,317.00 $48,480.00
             602,400 $7.95 $6.38 $254,393.00 $53,249.00
             575,004 $6.34 $5.67 $255,699.00 $49,696.00
             667,581 $5.54 $7.08 $262,270.00 $52,600.00
             569,880 $7.89 $5.10 $275,588.00 $50,472.00
             644,684 $6.76 $7.22 $277,667.00 $53,409.00
             605,468 $6.39 $5.21 $277,816.00 $52,660.00
             599,213 $6.42 $6.00 $279,031.00 $50,464.00
             610,735 $6.82 $6.97 $279,934.00 $49,525.00
             603,830 $7.10 $5.30 $287,921.00 $49,489.00
             617,803 $7.77 $6.96 $289,358.00 $49,375.00
             529,009 $8.07 $5.76 $294,787.00 $48,254.00
             573,211 $6.91 $5.96 $296,246.00 $46,017.00
  1. Create a descriptive statistics table for our variables in word for submission (simply export from excel and cleaning it up a bit)

  2. Create a table showing the variable names, coefficients, and p-values, indicating which variables are statistically significant for submission (export from excel and clean up a bit)

  3. Write out the regression equation for sales here based on excel output:

  4. Interpret the coefficient on our own price here:

  5. If a manager increases our price by $2 then what is the predicted impact on sales?

Solutions

Expert Solution

a.

Variable

Obs

Mean

Std

Min

Max

Demand (Q)

28.00

598545.79

35021.89

519866.00

667581.00

Price (P)

28.00

6.89

0.70

5.54

8.07

Competitor Price (Px)

28.00

6.19

0.82

5.10

7.68

Advertising (Ad)

28.00

247665.86

29503.52

206647.00

296246.00

Income (I)

28.00

50881.43

2849.10

46017.00

55454.00

b.

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.9308

R Square

0.8664

Adjusted R Square

0.8432

Standard Error

13868.2389

Observations

28

ANOVA

df

SS

MS

F

Significance F

Regression

4.000

28692838225.528

7173209556.382

37.297

0.000

Residual

23.000

4423545125.186

192328048.921

Total

27.000

33116383350.714

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

93833.8877

66959.6608

1.4013

0.1745

-44682.7242

232350.4995

Price (P)

-19432.5811

3931.9650

-4.9422

0.0001

-27566.4704

-11298.6919

Competitor Price (Px)

17711.9806

3359.2803

5.2726

0.0000

10762.7798

24661.1814

Advertising (Ad)

0.2869

0.0940

3.0510

0.0057

0.0924

0.4815

Income (I)

8.9996

0.9625

9.3505

0.0000

7.0086

10.9906

All of the variables are significant as the P-value is less than 0.05

c. Q= 93833.89-19432.58P+17711.98*Px+0.2869*Ad+8.99*I

D. Own price is negatively related with Qd . With one unit increase in price, the Qd decreases by 19433 units

E. For $2 increase in the predicted impact on sales Qd would decrease by -19432.58*2 = 38865 units


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