Question

# Suppose the Kalamazoo Brewing Company (KBC) currently sells its microbrews in a seven-state area: Illinois, Indiana,...

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