Use the data in vapor.csv, obtain the transformed predictor 1/X, and the transformed response log(Y), where "log" refers to the natural logarithm. Denote the new predictor by X*(=1/X) and denote the new response by Y*(=log Y). Fit a least squares model for the new response and the new predictor. It turns out that the estimated intercept is [ PUT ANSWER HERE   ] , and the estimated slope is[ PUT ANSWER HERE ] . The estimated standard error of the estimated slope is [ PUT ANSWER HERE ] , and the value of the F statistic associated with this fitted model is equal to [ PUT ANSWER HERE ].

MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
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Use the data in vapor.csv, obtain the transformed predictor 1/X, and the transformed response log(Y), where "log" refers to the natural logarithm. Denote the new predictor by X*(=1/X) and denote the new response by Y*(=log Y). Fit a least squares model for the new response and the new predictor. It turns out that the estimated intercept is [ PUT ANSWER HERE   ] , and the estimated slope is[ PUT ANSWER HERE ] . The estimated standard error of the estimated slope is [ PUT ANSWER HERE ] , and the value of the F statistic associated with this fitted model is equal to [ PUT ANSWER HERE ].

 

Note: The data in vapor.csv is attached as an image

temp
[pressure
273
4.6
283
9.2
293
17.5
303
31.8
313
55.3
323
92.5
333
149.4
343
233.7
353
355.1
363
525.8
373
760
Transcribed Image Text:temp [pressure 273 4.6 283 9.2 293 17.5 303 31.8 313 55.3 323 92.5 333 149.4 343 233.7 353 355.1 363 525.8 373 760
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