In: Statistics and Probability
Wendy’s is offering a new Wolfburger as a promotional tie-in for the new sequel in the Twilight motion picture series, and wonders how much they should charge. It test-markets five different prices in the cities listed below, with the listed resultant sales (in thousands of dollars):
| 
 City  | 
 Sales($000s)  | 
 Price($)  | 
 Price2  | 
 Sales2  | 
 Price*Sales  | 
| 
 Rochester  | 
 75  | 
 0.99  | 
 0.98  | 
 5625.00  | 
 74.3  | 
| 
 Ottumwa  | 
 70  | 
 1.29  | 
 1.66  | 
 4900.00  | 
 90.3  | 
| 
 Seattle  | 
 45  | 
 1.49  | 
 2.22  | 
 2025.00  | 
 67.1  | 
| 
 Raleigh  | 
 33  | 
 1.89  | 
 3.57  | 
 1089.00  | 
 62.4  | 
| 
 Denair  | 
 42  | 
 2.19  | 
 4.80  | 
 1764.00  | 
 92.0  | 
| 
 sum  | 
 265  | 
 7.85  | 
 13.23  | 
 15403.00  | 
 386.0  | 
| 
 mean  | 
 53  | 
 1.57  | 
 2.65  | 
 3080.60  | 
 77.2  | 
| 
 st.dev.  | 
 18.4  | 
 0.5  | 
 1.53  | 
 2037.06  | 
 13.4  | 
a.) Compute (numerically) and interpret (in words) the
correlation between sales and price
b. ) Estimate the regression function between sales and price
a. 
X Values
∑ = 601.4
Mean = 75.175
∑(X - Mx)2 = SSx = 43565.315
Y Values
∑ = 17.77
Mean = 2.221
∑(Y - My)2 = SSy = 38.098
X and Y Combined
N = 8
∑(X - Mx)(Y - My) = 1222.75
R Calculation
r = ∑((X - My)(Y - Mx)) /
√((SSx)(SSy))
r = 1222.75 / √((43565.315)(38.098)) = 0.9491
b. 
Sum of X = 601.4
Sum of Y = 17.77
Mean X = 75.175
Mean Y = 2.2213
Sum of squares (SSX) = 43565.315
Sum of products (SP) = 1222.7503
Regression Equation = ŷ = bX + a
b = SP/SSX = 1222.75/43565.32
= 0.0281
a = MY - bMX = 2.22 -
(0.03*75.18) = 0.1113
ŷ = 0.0281X + 0.1113