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hprice1.xls price assess bdrms lotsize sqrft colonial lprice lassess llotsize lsqrft 300 349.1 4 6126 2438 1 5.703783 5.855359 8.720297 7.798934 370 351.5 3 9903

hprice1.xls

price assess bdrms lotsize sqrft colonial lprice lassess llotsize lsqrft
300 349.1 4 6126 2438 1 5.703783 5.855359 8.720297 7.798934
370 351.5 3 9903 2076 1 5.913503 5.86221 9.200593 7.638198
191 217.7 3 5200 1374 0 5.252274 5.383118 8.556414 7.225482
195 231.8 3 4600 1448 1 5.273 5.445875 8.433811 7.277938
373 319.1 4 6095 2514 1 5.921578 5.765504 8.715224 7.82963
466.275 414.5 5 8566 2754 1 6.144775 6.027073 9.055556 7.92081
332.5 367.8 3 9000 2067 1 5.80664 5.907539 9.10498 7.633853
315 300.2 3 6210 1731 1 5.752573 5.704449 8.733916 7.456455
206 236.1 3 6000 1767 0 5.327876 5.464255 8.699514 7.477038
240 256.3 3 2892 1890 0 5.480639 5.546349 7.969704 7.544332
285 314 4 6000 2336 1 5.652489 5.749393 8.699514 7.756196
300 416.5 5 7047 2634 1 5.703783 6.031887 8.860357 7.876259
405 434 3 12237 3375 1 6.003887 6.073044 9.412219 8.12415
212 279.3 3 6460 1899 0 5.356586 5.632287 8.773385 7.549083
265 287.5 3 6519 2312 1 5.57973 5.661223 8.782476 7.745868
227.4 232.9 4 3597 1760 1 5.426711 5.450609 8.187856 7.473069
240 303.8 4 5922 2000 0 5.480639 5.71637 8.68643 7.600903
285 305.6 3 7123 1774 1 5.652489 5.722277 8.871084 7.480992
268 266.7 3 5642 1376 1 5.590987 5.586124 8.637994 7.226936
310 326 4 8602 1835 1 5.736572 5.786897 9.05975 7.5148
266 294.3 3 5494 2048 1 5.583496 5.684599 8.611412 7.624619
270 318.8 3 7800 2124 1 5.598422 5.764564 8.961879 7.661057
225 294.2 3 6003 1768 0 5.416101 5.68426 8.700015 7.477604
150 208 4 5218 1732 0 5.010635 5.337538 8.55987 7.457032
247 239.7 3 9425 1440 1 5.509388 5.479388 9.151121 7.272398
275 294.1 3 6114 1932 0 5.616771 5.68392 8.718336 7.566311
230 267.4 3 6710 1932 0 5.438079 5.588746 8.811355 7.566311
343 359.9 3 8577 2106 1 5.83773 5.885826 9.05684 7.652546
477.5 478.1 7 8400 3529 1 6.168564 6.16982 9.035987 8.16877
350 355.3 4 9773 2051 1 5.857933 5.872962 9.187379 7.626083
230 217.8 4 4806 1573 1 5.438079 5.383577 8.47762 7.36074
335 385 4 15086 2829 0 5.81413 5.953243 9.621523 7.947679
251 224.3 3 5763 1630 1 5.525453 5.412984 8.659213 7.396335
235 251.9 4 6383 1840 1 5.459586 5.529032 8.761394 7.517521
361 354.9 4 9000 2066 1 5.888878 5.871836 9.10498 7.633369
190 212.5 4 3500 1702 0 5.247024 5.358942 8.160519 7.439559
360 452.4 4 10892 2750 1 5.886104 6.114567 9.295784 7.919356
575 518.1 5 15634 3880 1 6.35437 6.250168 9.657204 8.263591
209.001 289.4 4 6400 1854 1 5.342339 5.66781 8.764053 7.525101
225 268.1 2 8880 1421 0 5.416101 5.59136 9.091557 7.259116
246 278.5 3 6314 1662 1 5.505332 5.629418 8.750525 7.415777
713.5 655.4 5 28231 3331 1 6.570182 6.485246 10.24818 8.111028
248 273.3 4 7050 1656 1 5.513429 5.61057 8.860783 7.41216
230 212.1 3 5305 1171 0 5.438079 5.357058 8.576406 7.065613
375 354 5 6637 2293 1 5.926926 5.869297 8.800415 7.737616
265 252.1 3 7834 1764 1 5.57973 5.529826 8.966228 7.475339
313 324 3 1000 2768 0 5.746203 5.780744 6.907755 7.92588
417.5 475.5 4 8112 3733 0 6.034285 6.164367 9.0011 8.224967
253 256.8 3 5850 1536 1 5.53339 5.548297 8.674197 7.336937
315 279.2 4 6660 1638 1 5.752573 5.631928 8.803875 7.401231
264 313.9 3 6637 1972 1 5.575949 5.749074 8.800415 7.586803
255 279.8 2 15267 1478 0 5.541264 5.634075 9.633449 7.298445
210 198.7 3 5146 1408 1 5.347107 5.291796 8.545975 7.249926
180 221.5 3 6017 1812 1 5.192957 5.400423 8.702344 7.502186
250 268.4 3 8410 1722 1 5.521461 5.592478 9.037177 7.451241
250 282.3 4 5625 1780 1 5.521461 5.64297 8.634976 7.484369
209 230.7 4 5600 1674 1 5.342334 5.441118 8.630522 7.422971
258 287 4 6525 1850 1 5.552959 5.659482 8.783396 7.522941
289 298.7 3 6060 1925 1 5.666427 5.69944 8.709465 7.562681
316 314.6 4 5539 2343 0 5.755742 5.751302 8.619569 7.759187
225 291 3 7566 1567 0 5.416101 5.673323 8.931419 7.356918
266 286.4 4 5484 1664 1 5.583496 5.65739 8.60959 7.41698
310 253.6 6 5348 1386 1 5.736572 5.535758 8.584478 7.234177
471.25 482 5 15834 2617 1 6.155389 6.177944 9.669915 7.869784
335 384.3 4 8022 2321 1 5.81413 5.951424 8.989944 7.749753
495 543.6 4 11966 2638 1 6.204558 6.298213 9.389825 7.877776
279.5 336.5 4 8460 1915 1 5.633002 5.818598 9.043104 7.557473
380 515.1 4 15105 2589 1 5.940171 6.244361 9.622781 7.859027
325 437 4 10859 2709 0 5.783825 6.079933 9.292749 7.904335
220 263.4 3 6300 1587 1 5.393628 5.573674 8.748305 7.369601
215 300.4 3 11554 1694 0 5.370638 5.705115 9.354787 7.434848
240 250.7 3 6000 1536 1 5.480639 5.524257 8.699514 7.336937
725 708.6 5 31000 3662 0 6.586172 6.563291 10.34174 8.205765
230 276.3 3 4054 1736 1 5.438079 5.621487 8.307459 7.459339
306 388.6 2 20700 2205 0 5.723585 5.962551 9.937889 7.698483
425 252.5 3 5525 1502 0 6.052089 5.531411 8.617039 7.314553
318 295.2 4 92681 1696 1 5.762052 5.687653 11.43692 7.436028
330 359.5 3 8178 2186 1 5.799093 5.884714 9.009203 7.689829
246 276.2 4 5944 1928 1 5.505332 5.621125 8.690138 7.564239
225 249.8 3 18838 1294 0 5.416101 5.52066 9.843632 7.165493
111 202.4 4 4315 1535 1 4.70953 5.310246 8.369853 7.336286
268.125 254 3 5167 1980 1 5.591453 5.537334 8.550048 7.590852
244 306.8 4 7893 2090 1 5.497168 5.726196 8.973732 7.644919
295 318.3 3 6056 1837 1 5.686975 5.762994 8.708805 7.515889
236 259.4 3 5828 1715 0 5.463832 5.558371 8.670429 7.447168
202.5 258.1 3 6341 1574 0 5.31074 5.553347 8.754792 7.361375
219 232 2 6362 1185 0 5.389072 5.446737 8.758098 7.077498
242 252 4 4950 1774 1 5.488938 5.529429 8.507143 7.480992

Use the data set hprice1 to estimate the model = 0 + 1 + 2+ where price is measured in thousands of dollars. a. Write out the results as an equation b. What is the estimated increase in price for a house with one more bedroom, holding square footage constant? c. What is the estimated increase in price for a house with an additional bedroom that is 140 square feet in size? Compare this to your answer in part (b). d. What percentage of the variation in price is explained by square footgae and number of bedrooms? e. The first house in the sample has sqrft = 2,438 and bdrms = 4. Find the predicted selling price for this house from the OLS regression Line. f. The actual selling price of the first house in the sample was $300,000 (so price = 300). Find the residual for this house. Does it suggest that the buyer underpaid of overpaid for the house?

Please use R-code to answer these questions!

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