In: Statistics and Probability
Wendy's wonders how to price its new chili salad. It test-markets five different prices in the cities listed below, with the listed resultant sales (in thousands of dollars). Calculate correlation, and the regression model.
City | Sales($000s) | Price($) | Price^2 | Sales^2 | 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 |
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
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