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