In: Statistics and Probability
Price_($) | Length_(inch) | Width_(mm) |
56.58 | 16 | 1.1 |
100 | 16 | 1.5 |
136.53 | 16 | 1.8 |
197.08 | 18 | 2.2 |
63.63 | 18 | 1.2 |
112.51 | 16 | 1.5 |
152.87 | 18 | 1.8 |
221.37 | 18 | 2.3 |
366.14 | 18 | 3.1 |
616.47 | 20 | 3.9 |
70.71 | 18 | 1.1 |
125 | 20 | 1.4 |
170.19 | 20 | 1.9 |
245.66 | 20 | 2.4 |
407.24 | 20 | 3.2 |
685.59 | 20 | 3.9 |
270.86 | 20 | 2.2 |
448.35 | 22 | 3.1 |
753.78 | 22 | 3.9 |
79.82 | 24 | 1.2 |
149.04 | 24 | 1.4 |
198.02 | 24 | 1.9 |
295.16 | 24 | 2.4 |
448.51 | 24 | 3.2 |
882.91 | 24 | 3.9 |
181.21 | 30 | 1.5 |
247.51 | 30 | 1.9 |
368.96 | 30 | 2.3 |
Fit the multiple regression of price on length and width
What is the fit has R^2 and Se(standard error)?
Show me how to work at the excel.
I did try to make the regression in excel that put y to price and put x to length and width but I did not get right answer that is R^2 = 0.92 Se = 64.15 (round to two decimal places)