Question
1: Find the sample correlation coefficient for the following data. Data set A: Sales Area 10.2 41 36.8 150 182.8 755 35.3 125 144.5 488
1: Find the sample correlation coefficient for the following data.
Data set A:
| Sales | Area |
| 10.2 | 41 |
| 36.8 | 150 |
| 182.8 | 755 |
| 35.3 | 125 |
| 144.5 | 488 |
| 63.4 | 282 |
| 16.7 | 62 |
| 35.7 | 123 |
| 37 | 155 |
| 20.7 | 76 |
| 33 | 129 |
| 3 | 10 |
| 3.2 | 10 |
| 9.1 | 32 |
| 65.2 | 266 |
| 59.9 | 270 |
| 17.8 | 63 |
| 5.6 | 24 |
| 1.9 | 8 |
| 127 | 410 |
| 47.9 | 187 |
| 2.8 | 9 |
|
|
|
(Answer here.)
2: Create a scatter plot for Data set A. Is the relationship linear?
(Insert scatter plot here; right click on chart in Excel, then copy. Then right click again to Paste into this Word document.)
Run a simple regression for the following data and produce the output necessary to answer the following questions.
Data set B
| Per Person Average Spend (X) | Average Weekly Sales (Y) |
| 6.8090 | 31,778 |
| 7.5717 | 10,513 |
| 6.8877 | 17,214 |
| 7.1300 | 19,937 |
| 7.0420 | 19,193 |
| 6.9310 | 14,280 |
| 7.1142 | 24,732 |
| 7.1274 | 29,642 |
| 6.5822 | 24,040 |
| 6.7677 | 24,447 |
| 6.6611 | 22,282 |
| 7.0309 | 26,909 |
| 7.0334 | 13,525 |
| 6.9964 | 27,540 |
| 7.3802 | 22,399 |
| 7.1779 | 17,727 |
| 7.3526 | 18,033 |
| 6.9531 | 22,180 |
| 7.0190 | 23,748 |
| 6.8495 | 20,608 |
| 7.1644 | 20,484 |
| 6.9920 | 30,112 |
| 7.2836 | 19,540 |
| 7.0671 | 16,156 |
| 7.0503 | 18,407 |
| 6.5384 | 23,285 |
| 6.7031 | 22,841 |
| 6.9098 | 14,490 |
| 7.5825 | 18,307 |
|
|
|
Insert output here
3: Is the regression model for Data set B significant at the .05 level?
Answer here:
4: What is the coefficient of determination for the simple regression model for Data set B?
Answer here:
5: Extra credit: A researcher wished to predict the price of homes ($1000s) using size (square footage), distance, and whether the home had a garage as independent (explanatory) variables. The results were as follows.
| Price (in thousands of dollars) |
| |
| Size (square feet) |
| |
| Distance (miles from central city) | ||
| Garage: 0 = no garage; 1 = garage | ||
| Regression Statistics | ||||||
| Multiple R | 0.636 | |||||
| R Square | 0.404 | |||||
| Adjusted R Square | 0.386 | |||||
| Standard Error | 36.896 | |||||
| Observations | 105 | |||||
| ANOVA | ||||||
|
| df | SS | MS | F | Significance F | |
| Regression | 3 | 93272.93 | 31090.98 | 22.84 | 0.0000 | |
| Residual | 101 | 137494.66 | 1361.33 | |||
| Total | 104 | 230767.59 |
|
|
| |
|
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% |
| Intercept | 78.71 | 36.69 | 2.15 | 0.0343 | 5.93 | 151.49 |
| Size | 0.06 | 0.01 | 4.09 | 0.0001 | 0.03 | 0.09 |
| Distance | -1.45 | 0.80 | -1.81 | 0.0733 | -3.03 | 0.14 |
| Garage | 44.71 | 8.25 | 5.42 | 0.0000 | 28.34 | 61.08 |
What independent variable is not significant at the .05 significance level?
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Fundamentals of Cost Accounting
Authors: William Lanen, Shannon Anderson, Michael Maher
3rd Edition
978-0077398194
