Suppose the Kalamazoo Brewing Company (KBC) currently sells its microbrews in a seven-state area: Illinois, Indiana, Michigan, Minnesota, Mississippi, Ohio, and Wisconsin. The company’s marketing department has collected data from its distributors in each state. This data consists of the quantity and price (per case) of microbrews sold in each state, as well as the average income (in thousands of dollars) of consumers living in various regions of each state. The data for each state are available via the link below--please note there are multiple tabs at the bottom of the spreadsheet, each refers to one of the seven states selling the Kalamazoo Brewing Company’s microbrews.
Assuming that the underlying demand relation is a linear function of price and income, use your spreadsheet program to obtain least squares estimates of Mississippi’s demand for KBC microbrews.
Instruction: If the estimate is negative, enter a
negative number (-) in the equation. Enter your responses rounded
to two decimal places.
Q = + Price + Income
Quantity | Price | Income |
575 | 31.26 | 33.95 |
674 | 30.69 | 35.51 |
616 | 31.54 | 28.78 |
183 | 27.41 | 30.44 |
501 | 29.75 | 31.28 |
578 | 29.48 | 33.77 |
590 | 28.94 | 38.31 |
445 | 28.17 | 34.01 |
603 | 28.58 | 32.53 |
713 | 28.57 | 31.69 |
337 | 30.06 | 32.26 |
230 | 29.36 | 31.57 |
403 | 28.81 | 32.75 |
383 | 32.52 | 29.48 |
568 | 32.02 | 35.91 |
698 | 32.91 | 34.85 |
826 | 28.45 | 34.06 |
789 | 26.85 | 38.92 |
645 | 30.49 | 35.94 |
601 | 31.72 | 38.05 |
467 | 31.23 | 36.48 |
429 | 31.28 | 37.61 |
552 | 28.89 | 38.29 |
553 | 31.13 | 36.9 |
562 | 27.52 | 39.22 |
352 | 30.02 | 34.21 |
611 | 31.38 | 33.97 |
346 | 29.08 | 38.53 |
354 | 28.8 | 34.4 |
401 | 27.64 | 34.01 |
253 | 30.47 | 34.24 |
524 | 30.97 | 38.29 |
211 | 32.85 | 34.66 |
666 | 30.11 | 41.38 |
468 | 29.48 | 32.14 |
585 | 28.41 | 29.16 |
578 | 29.96 | 35.05 |
656 | 30.46 | 37.11 |
571 | 32.86 | 32.94 |
454 | 28.49 | 32.7 |
510 | 30.67 | 33.14 |
672 | 31.92 | 33.73 |
499 | 28.44 | 41.92 |
560 | 27.94 | 35.06 |
848 | 29.74 | 32.71 |
617 | 29.54 | 37.96 |
530 | 31.34 | 37.38 |
649 | 30.08 | 35.55 |
824 | 29.13 | 42.89 |
626 | 31.72 | 37.17 |
Excel regression summary output:
SUMMARY OUTPUT | ||||||
Regression Statistics | ||||||
Multiple R | 0.29259565 | |||||
R Square | 0.08561221 | |||||
Adjusted R Square | 0.04670209 | |||||
Standard Error | 151.154081 | |||||
Observations | 50 | |||||
ANOVA | ||||||
df | SS | MS | F | Significance F | ||
Regression | 2 | 100540.9347 | 50270.47 | 2.200256 | 0.12205759 | |
Residual | 47 | 1073835.145 | 22847.56 | |||
Total | 49 | 1174376.08 | ||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | |
Intercept | -42.65 | 496.56 | -0.09 | 0.93 | -1041.60 | 956.29 |
Price | 2.62 | 13.99 | 0.19 | 0.85 | -25.53 | 30.76 |
Income | 14.32 | 6.83 | 2.10 | 0.04 | 0.58 | 28.05 |
Regression equation: Q = - 42.65 + 2.62 x Price + 14.32 x Income
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