In: Statistics and Probability
Demand can be estimated with experimental data, time-series data, or cross-section data. In this case, cross-section data appear in the Excel file. Soft drink consumption in cans per capita per year is related to six-pack price, income per capita, and mean temperature across the 48 contiguous states in the United States.
Given the data, please construct the demand estimation for soft
drink consumption in the United States by
(1) a multiple-linear regression equation, and
(2) a log-linear (exponential) regression equation (show Excel
please)
TABLE 1. SOFT DRINK DEMAND DATA | ||||
State | Cans/Capita/Yr | 6-Pack Price ($) | Income/Capita ($1,000) | Mean Temp. (F) |
Alabama | 200 | 3.19 | 35.1 | 66 |
Arizona | 150 | 2.99 | 45.9 | 62 |
Arkansas | 237 | 2.93 | 29.7 | 63 |
California | 135 | 3.59 | 67.5 | 56 |
Colorado | 121 | 3.29 | 51.3 | 52 |
Connecticut | 118 | 3.49 | 72.9 | 50 |
Delaware | 217 | 2.99 | 75.6 | 52 |
Florida | 242 | 3.29 | 48.6 | 72 |
Georgia | 295 | 2.89 | 37.8 | 64 |
Idaho | 85 | 3.39 | 43.2 | 46 |
Illinois | 114 | 3.35 | 64.8 | 52 |
Indiana | 184 | 3.19 | 54 | 52 |
Iowa | 104 | 3.21 | 43.2 | 50 |
Kansas | 143 | 3.17 | 45.9 | 56 |
(1) a multiple-linear regression equation,
The Excel regression output is:
R² | 0.768 | |||||
Adjusted R² | 0.698 | |||||
R | 0.876 | |||||
Std. Error | 34.313 | |||||
n | 14 | |||||
k | 3 | |||||
Dep. Var. | Cans/Capita/Yr | |||||
ANOVA table | ||||||
Source | SS | df | MS | F | p-value | |
Regression | 38,917.5555 | 3 | 12,972.5185 | 11.02 | .0016 | |
Residual | 11,773.9445 | 10 | 1,177.3944 | |||
Total | 50,691.5000 | 13 | ||||
Regression output | confidence interval | |||||
variables | coefficients | std. error | t (df=10) | p-value | 95% lower | 95% upper |
Intercept | 315.9683 | |||||
6-Pack Price ($) | -160.9033 | 53.7244 | -2.995 | .0135 | -280.6087 | -41.1980 |
Income/Capita ($1,000) | 1.1644 | 0.8234 | 1.414 | .1877 | -0.6703 | 2.9991 |
Mean Temp. (F) | 5.4509 | 1.4716 | 3.704 | .0041 | 2.1718 | 8.7299 |
The estimated regression equation is:
Cans/Capita/Yr = 315.9683 -160.9033*6-Pack Price ($) +
1.1644Income/Capita ($1,000) + 5.4509Mean Temp. (F)
(2) a log-linear (exponential) regression equation
The exponential regression between Cans/Capita/Yr and 6-Pack Price ($) is:
The estimated regression equation is:
y = 3.6085e-7E-04x
The exponential regression between Cans/Capita/Yr and Income/Capita ($1,000) is:
The estimated regression equation is:
y = 64.722e-0.002x
The exponential regression between Cans/Capita/Yr and Mean Temp. (F) is:
The estimated regression equation is:
y = 43.278e0.0016x