In: Statistics and Probability
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.
Excel Data File
Assuming that the underlying demand relation is a linear function
of price and income, use your spreadsheet program to obtain least
squares estimates of Wisconsin’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 | |
You can use the 'Data Analysis' button under the 'Data' tab in excel to choose the 'Regression' option as shown -
Then enter the values of X and Y as shown -
Make sure to mark the 'labels' check as our first row has label for the columns.
Then after you click 'Ok', you will get the following output -
SUMMARY OUTPUT | ||||||
Regression Statistics | ||||||
Multiple R | 0.292595647 | |||||
R Square | 0.085612213 | |||||
Adjusted R Square | 0.046702094 | |||||
Standard Error | 151.1540813 | |||||
Observations | 50 | |||||
ANOVA | ||||||
df | SS | MS | F | Significance F | ||
Regression | 2 | 100540.9347 | 50270.46734 | 2.200255761 | 0.122057592 | |
Residual | 47 | 1073835.145 | 22847.55628 | |||
Total | 49 | 1174376.08 | ||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | |
Intercept | -42.65310543 | 496.5565698 | -0.085897777 | 0.931912569 | -1041.596074 | 956.2898634 |
Price | 2.617411325 | 13.99127624 | 0.187074523 | 0.852407435 | -25.52940592 | 30.76422857 |
Income | 14.31649729 | 6.826898346 | 2.097071988 | 0.041393943 | 0.582549301 | 28.05044527 |
So, we can write the estimated demand as -
Demand = -42.65 + 2.62 (Price) + 14.32 (Income).
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