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Sheet1 Price 436580 378473 398198 439177 468157 376310 442736 382782 439867 469070 439523 437931 373816 379565 369314 407589 440027 392667 354125 370922 372449 430509 434083 468643 351959 395840 351524 460365 354761 421222 375687 426488 448920 430769 363079 468807 408429 450180 423879 446813 431698 405106 443360 419891 411951 355453 380812 408977 470321 369896 Beds 4 4 3 3 4 5 3 5 4 4 4 5 3 5 5 5 5 4 3 5 5 5 4 5 3 4 3 3 4 3 4 3 3 4 4 4 4 5 5 3 5 4 5 3 3 3 3 4 3 5 Baths 3 3 3 2 2 3 2 3 3 3 3 2 2 2 2 2 3 2 2 3 3 3 3 3 2 2 2 3 2 3 2 3 3 2 2 3 2 2 3 2 2 3 3 3 3 3 2 2 2 2 Garage 2 3 3 2 2 2 2 3 2 2 3 2 3 3 3 2 3 3 2 3 3 2 2 2 2 3 2 2 3 2 3 3 3 2 3 2 2 2 2 2 2 2 3 2 3 3 2 3 2 2 Sqft-House 3627 3472 3700 3430 3815 3760 4035 4460 4005 4109 4329 3403 4262 3066 4131 3625 3008 4475 3736 4003 2996 4125 3449 3215 3883 3744 4036 4258 2861 2755 3028 3361 3238 3710 2797 3790 4067 4484 3040 4016 3891 3437 3525 3982 3953 3014 3322 3405 3544 4093 Page 1 Sqft-Land 10332 20899 9699 10931 19614 26632 25955 18553 29099 17930 10850 21566 11666 15942 17419 20517 22074 16578 15530 23737 11899 18117 15692 12446 25017 18068 14237 13883 17170 9826 10079 10911 24417 9642 10278 26978 17224 18663 10899 24922 12853 18516 16216 11548 16875 9943 19063 26309 27724 23464 Kitchen 0 1 0 0 0 1 0 0 1 0 1 0 1 0 0 1 0 0 0 1 1 0 1 1 0 1 1 0 1 0 0 1 1 0 1 0 0 1 1 0 1 1 1 1 0 1 1 1 1 0 Roof 13 14 5 11 15 7 18 18 9 15 10 18 18 9 18 10 9 12 9 7 11 14 5 10 14 14 6 19 11 13 8 10 13 20 9 8 16 5 15 12 17 20 15 10 13 20 20 11 9 20 Sheet1 467262 427673 418719 454392 369320 350376 390951 462146 421040 460383 473670 397687 421711 379734 412161 388369 439529 355306 443480 376658 434795 358285 405046 448711 445448 386113 465272 357283 414120 416034 470892 417992 444660 393902 381656 456351 365948 465241 433714 362050 372481 446311 401155 395510 370965 373189 417494 355344 379654 353383 417495 5 5 4 3 3 5 5 3 3 4 5 3 3 5 4 5 3 4 4 5 3 5 5 3 3 5 4 3 3 3 3 3 4 5 4 4 4 4 4 5 4 4 4 5 4 3 3 4 3 3 4 3 3 2 2 2 2 3 3 3 3 2 2 3 2 3 2 3 3 3 2 3 3 3 2 3 2 2 2 3 2 2 2 2 3 2 2 2 2 2 3 2 3 3 3 2 3 3 3 2 3 3 2 2 2 2 2 2 3 3 2 3 2 2 3 3 3 2 3 3 3 3 3 2 3 3 3 3 3 3 3 3 3 3 2 3 3 3 2 3 3 2 3 2 2 2 2 2 2 2 3 2 2 4114 3585 3945 3104 3830 3625 3495 4211 2785 4345 3083 4125 4275 3813 3600 3672 4373 4107 3266 2818 3350 2875 3982 3041 3365 3049 3847 3550 4075 3589 3059 3016 3950 4050 4202 3382 4386 4117 3552 3038 3318 2771 3983 3265 3190 2868 3131 3118 3875 3744 3489 Page 2 26444 28580 18397 9761 27199 17545 12242 14655 12484 24792 20617 19114 30277 24320 22006 20303 27249 16085 28036 12670 21272 25249 20398 14211 15180 14180 25560 23481 12576 28590 26617 8990 10649 29576 24108 19734 22279 10631 12019 25085 13702 25378 18268 23529 12733 8169 21918 8202 22012 26810 16915 0 1 0 0 1 0 1 1 0 1 1 1 0 0 0 0 1 0 1 1 1 1 0 1 1 1 0 1 1 1 0 0 0 1 0 0 0 0 1 1 1 1 0 0 0 1 0 1 1 0 0 16 7 5 11 11 10 15 12 12 17 6 5 15 16 10 16 10 20 20 16 10 10 7 8 5 5 19 14 5 11 20 17 7 20 8 11 18 12 18 11 16 11 18 13 6 7 14 19 17 16 7 Sheet1 429166 391227 419638 431309 370744 400830 442122 426359 373200 455155 423695 467326 424760 433807 398942 393751 372107 354200 419725 424751 404936 437356 471297 372417 357687 468719 410042 363944 458759 433295 427581 454011 462023 372052 406193 350211 355660 380284 409062 412971 457197 390160 442018 435320 435330 387720 384185 379904 362518 3 5 4 5 3 5 5 3 4 4 4 4 3 4 4 3 5 4 5 5 5 5 5 5 5 4 4 4 5 5 5 5 4 4 5 5 3 5 5 4 5 5 3 5 4 4 4 4 5 3 2 2 2 3 2 3 2 2 2 2 2 3 3 2 3 3 3 2 3 3 2 3 3 2 2 3 3 3 3 3 3 2 3 2 3 2 2 2 3 2 3 2 3 3 2 3 2 2 3 3 3 3 2 3 2 3 2 3 2 2 3 3 2 3 3 3 2 3 2 2 3 2 2 3 2 2 2 2 3 3 3 3 3 3 2 2 2 2 2 2 3 3 2 3 3 3 3 3428 4279 2977 4496 3889 3735 3497 3425 3357 4342 4096 4161 4089 3476 3025 3278 3684 3504 2932 3891 3092 4140 4305 4149 3955 4102 3796 4268 4496 3092 2962 3376 4426 3247 3462 3333 3505 3783 4235 3090 3150 4265 2774 2885 3583 3814 4473 3376 3819 Page 3 15177 20390 16911 18786 26389 18062 21544 12398 24497 27165 18959 22076 20344 12856 12783 10915 22087 27957 20191 25073 11886 16661 21326 20759 20343 25253 18604 18301 24759 20637 17463 18026 11206 12958 21856 12884 11089 10690 25208 10015 22701 24738 26406 14447 15983 15303 22887 10188 24262 0 1 0 1 1 0 1 1 1 1 1 0 1 1 1 1 0 0 0 0 0 1 1 1 0 0 1 1 0 0 1 0 1 0 0 1 0 1 1 0 0 1 1 1 0 1 1 1 0 20 10 11 13 18 7 18 16 10 15 13 15 8 10 10 18 8 17 10 7 14 20 7 8 8 9 5 11 5 17 5 20 14 14 19 14 14 9 6 20 20 17 6 15 13 12 8 6 14 Sheet1 Age 28 41 42 21 20 36 22 39 22 42 35 31 15 32 18 24 50 39 48 30 47 19 26 34 23 38 38 12 44 45 35 29 39 35 24 22 32 29 31 47 21 19 34 47 30 32 30 24 32 22 Page 4 Sheet1 17 41 54 48 29 39 28 33 18 31 37 41 36 31 32 15 29 26 27 29 45 40 39 50 39 32 21 33 26 25 18 15 31 11 48 37 40 26 32 46 25 30 38 23 27 45 38 19 18 19 37 Page 5 Sheet1 18 20 31 35 33 36 38 14 49 26 32 17 50 36 37 18 51 43 34 32 26 23 24 30 51 32 46 30 35 32 45 26 20 28 17 44 25 48 49 40 23 38 38 28 17 19 45 32 19 Page 6 FRED Graph Observations Federal Reserve Economic Data Link: https://fred.stlouisfed.org Help: https://fred.stlouisfed.org/help-faq Economic Research Division Federal Reserve Bank of St. Louis ENPLANED Enplanements for U.S. Air Carrier International, Scheduled Passenger Flights, Thousands, Monthly, S Frequency: Monthly observation_date ENPLANED 2000-01-01 2000-02-01 2000-03-01 2000-04-01 2000-05-01 2000-06-01 2000-07-01 2000-08-01 2000-09-01 2000-10-01 2000-11-01 2000-12-01 2001-01-01 2001-02-01 2001-03-01 2001-04-01 2001-05-01 2001-06-01 2001-07-01 2001-08-01 2001-09-01 2001-10-01 2001-11-01 2001-12-01 2002-01-01 2002-02-01 2002-03-01 2002-04-01 2002-05-01 2002-06-01 2002-07-01 2002-08-01 2002-09-01 2002-10-01 2002-11-01 2002-12-01 2003-01-01 2003-02-01 2003-03-01 2003-04-01 2003-05-01 t 5082 5419 5622 5719 5950 5940 6003 6014 6208 6053 5920 5554 5792 5789 5880 5968 5957 6039 5967 6025 4445 4290 4559 4797 5010 5260 5245 5357 5385 5351 5352 5396 5484 5572 5509 5434 5532 5391 5086 4719 4800 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 2003-06-01 2003-07-01 2003-08-01 2003-09-01 2003-10-01 2003-11-01 2003-12-01 2004-01-01 2004-02-01 2004-03-01 2004-04-01 2004-05-01 2004-06-01 2004-07-01 2004-08-01 2004-09-01 2004-10-01 2004-11-01 2004-12-01 2005-01-01 2005-02-01 2005-03-01 2005-04-01 2005-05-01 2005-06-01 2005-07-01 2005-08-01 2005-09-01 2005-10-01 2005-11-01 2005-12-01 2006-01-01 2006-02-01 2006-03-01 2006-04-01 2006-05-01 2006-06-01 2006-07-01 2006-08-01 2006-09-01 2006-10-01 2006-11-01 2006-12-01 2007-01-01 2007-02-01 2007-03-01 2007-04-01 2007-05-01 2007-06-01 2007-07-01 2007-08-01 2007-09-01 5135 5375 5487 5612 5668 5756 5763 5803 5878 5958 5984 6027 6201 6197 6269 6237 6319 6417 6510 6651 6761 6804 6843 6841 6833 6803 6776 6783 6674 6811 6897 6960 7034 7175 7285 7313 7254 7273 7180 7086 7155 7335 7367 7445 7410 7446 7449 7434 7490 7548 7618 7524 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 2007-10-01 2007-11-01 2007-12-01 2008-01-01 2008-02-01 2008-03-01 2008-04-01 2008-05-01 2008-06-01 2008-07-01 2008-08-01 2008-09-01 2008-10-01 2008-11-01 2008-12-01 2009-01-01 2009-02-01 2009-03-01 2009-04-01 2009-05-01 2009-06-01 2009-07-01 2009-08-01 2009-09-01 2009-10-01 2009-11-01 2009-12-01 2010-01-01 2010-02-01 2010-03-01 2010-04-01 2010-05-01 2010-06-01 2010-07-01 2010-08-01 2010-09-01 2010-10-01 2010-11-01 2010-12-01 2011-01-01 2011-02-01 2011-03-01 2011-04-01 2011-05-01 2011-06-01 2011-07-01 2011-08-01 2011-09-01 2011-10-01 2011-11-01 2011-12-01 2012-01-01 7672 7739 7744 7805 7820 7856 7830 7791 7683 7671 7664 7290 7351 7336 7369 7331 7340 7056 7332 6576 6975 7137 7250 7206 7103 7211 7337 7367 7458 7516 7157 7423 7603 7652 7678 7761 7864 7779 7713 7718 7682 7644 7684 7707 7669 7869 7725 7743 7699 7713 7717 7739 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 2012-02-01 2012-03-01 2012-04-01 2012-05-01 2012-06-01 2012-07-01 2012-08-01 2012-09-01 2012-10-01 2012-11-01 2012-12-01 2013-01-01 2013-02-01 2013-03-01 2013-04-01 2013-05-01 2013-06-01 2013-07-01 2013-08-01 2013-09-01 2013-10-01 2013-11-01 2013-12-01 2014-01-01 2014-02-01 2014-03-01 2014-04-01 2014-05-01 2014-06-01 2014-07-01 2014-08-01 2014-09-01 2014-10-01 2014-11-01 2014-12-01 2015-01-01 2015-02-01 2015-03-01 2015-04-01 2015-05-01 2015-06-01 2015-07-01 2015-08-01 2015-09-01 2015-10-01 2015-11-01 2015-12-01 2016-01-01 2016-02-01 2016-03-01 2016-04-01 2016-05-01 7828 7882 7855 7811 7800 7778 7823 7946 7928 7929 7899 7942 8104 8032 8012 8062 8114 8189 8203 8166 8245 8238 8267 8333 8324 8368 8414 8390 8343 8302 8306 8286 8221 8321 8384 8423 8439 8401 8369 8411 8449 8551 8630 8641 8639 8638 8668 8652 8664 8583 8599 8557 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 2016-06-01 2016-07-01 2016-08-01 2016-09-01 2016-10-01 2016-11-01 2016-12-01 2017-01-01 2017-02-01 2017-03-01 2017-04-01 2017-05-01 2017-06-01 2017-07-01 2017-08-01 2017-09-01 2017-10-01 2017-11-01 2017-12-01 2018-01-01 2018-02-01 2018-03-01 2018-04-01 2018-05-01 2018-06-01 2018-07-01 2018-08-01 2018-09-01 2018-10-01 2018-11-01 2018-12-01 2019-01-01 2019-02-01 2019-03-01 2019-04-01 2019-05-01 2019-06-01 2019-07-01 2019-08-01 2019-09-01 2019-10-01 2019-11-01 2019-12-01 8645 8638 8614 8686 8678 8657 8890 8895 8834 8745 9197 9077 9027 9103 9073 8655 8986 9053 9081 9089 9195 9197 9222 9237 9305 9298 9264 9141 9407 9379 9420 9458 9470 9580 9589 9715 9701 9619 9617 9583 9638 9667 9703 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 enger Flights, Thousands, Monthly, Seasonally Adjusted ECON 3050 (Quantitative Methods) - Spring 2020 Final Comprehensive Examination Due Date & Time: April 30, 2020, 10:00 PM, CT Dr. Achintya Ray Professor of Economics Department of Economics & Finance College of Business, Tennessee State University, Nashville, TN, USA April 20, 2020 Contents 1 How to submit this assignment? 2 2 What Topics You Need to Cover for This Assignment? 2 3 What Should You Do Before You Work On This Assignment 2 4 Suggested Videos That You Should Watch 4.1 Disclaimers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Microsoft Excel Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Google Sheets Resources: Free and Online . . . . . . . . . . . . . . . . . . . . . . . . 3 3 3 4 5 The Data You Need For the Assignment 5.1 Housing.xlsx . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Enplanement.xlsx . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 4 4 6 PART 1: Suggested Early Submission Date: April 20, 2020. Accounts for 25% of the Final Grade. 5 7 PART 2: Suggested Early Submission Date: April 25, 2020. Accounts for 25% of the Final Grade. 5 8 PART 3: Suggested Final Submission Date: April 30, 2020. Accounts for 25% of the Final Grade. 6 1 1. How to submit this assignment? 1. Type your answers nicely in a Word document and upload the same in the designated Elearn folder. Any supporting file must be uploaded along with the main submission. All supporting data and calculations must be submitted in an Excel File along with the Word File. You can download a Google Sheet as an Excel File and upload the same in Elearn. 2. If you do not use Word for typing then try to type the answers in a Google Document online using your phone/tablet and download the file as a Word document and then upload that Word document in the designated folder on Elearn. All supporting data and calculations must be submitted in an Excel File along with the Word File. You can download a Google Sheet as an Excel File and upload the same in Elearn. 3. DO NOT VIOLATE the honor code. Your submission MUST BE your OWN WORK. You may earn a failing grade in the assignment if you violate the honor code. 4. No late submission is allowed. Early submission is welcome and strongly encouraged. Make plans to NOT wait until the very last moments to finish and upload your work. You must reserve about 15 − 20 hours to finish the entire work. Actual time may be more or less depending on your level of preparations. 5. No email submission will be accepted. All submissions MUST BE through Elearn. Otherwise, they will not be graded. 2. What Topics You Need to Cover for This Assignment? Watch the videos of ANOVA posted in the Elearn. Read the 10 step ANOVA example. Other topics include: Descriptive Statistics, sampling and confidence interval, t-Test, F-Test, χ2 - Test. χ2 is Pronounced as Chi-Squared, regression analysis, time series and forecasting. All relevant tables are posted in the Elearn. Numerous video resources are referred below to help you master the essential concepts easily. 3. What Should You Do Before You Work On This Assignment 1. Read the whole assignment very very carefully. Make a note of everything that you need to do for this assignment. 2. Read the relevant chapters and the associated lecture slides posted on the Elearn. 3. Consult the additional lecture materials posted on Elearn. 4. Watch the suggested videos mentioned below. 5. The assignment is broken down in many parts. Finish them in order and periodically upload your submissions for different parts by the suggested dates mentioned for the individual parts. 2 4. 4.1. Suggested Videos That You Should Watch Disclaimers The resources are provided so that you can perform your analysis on two largely comparable platforms: Microsoft Excel and Google Sheets. You need to choose between Microsoft Excel or Google Sheets as your preferred analytics platform but it will be entirely fine to learn BOTH. The videos are referred as learning materials. No product, opinion, advertisement, etc. is endorsed. YOU ARE STRONGLY ADVISED TO IGNORE ANY COMMERCIAL MATERIAL THAT IS NOT RELETED TO FORMULAS AND CONCEPTS COVERED IN THE COURSE. Please bring to my attention if you notice any inappropriate material. 4.2. Microsoft Excel Resources 1. For Microsoft Windows: How to Install the Data Analysis ToolPak in Microsoft Excel https://www.youtube.com/watch?v= yNxLFagKgw 2. For Mac: How to Install the Data Analysis ToolPak in Microsoft Excel https://www.youtube.com/watch?v=mtmrAXwLcuU 3. Excel - Simple Linear Regression https://www.youtube.com/watch?v=Cltt47Ah3Q4 4. Multiple Regression in Microsoft Excel https://www.youtube.com/watch?v=cXiZ t2NK1k 5. Using Multiple Regression in Excel for Predictive Analysis https://www.youtube.com/watch?v=HgfHefwK7VQ 6. Excel - Time Series Forecasting - Part 1 of 3 https://www.youtube.com/watch?v=gHdYEZA50KE 7. Excel - Time Series Forecasting - Part 2 of 3 https://www.youtube.com/watch?v=5C012eMSeIU 8. Excel - Time Series Forecasting - Part 3 of 3 https://www.youtube.com/watch?v=kcfiu-f88JQ 9. Creating Pivot Tables in Excel https://www.youtube.com/watch?v=BkmxrvIfDGA 10. Excel - One-Way ANOVA Analysis Toolpack https://www.youtube.com/watch?v=nmHFFFpOVZs 11. F Test in Excel https://www.youtube.com/watch?v=2337cSdINF0 12. Moving Average Time Series Forecasting with Excel https://www.youtube.com/watch?v=mC1ARrtkObc 3 4.3. Google Sheets Resources: Free and Online 1. Installing the XLMiner Analysis ToolPak add-on in Google Sheets https://www.youtube.com/watch?v=JHXsKwcRdRw 2. Multiple Regression with Google Sheets XL Miner https://www.youtube.com/watch?v=YhBU92eyNRo 3. Time Series Forecasting with Google Sheets part (1 of 4) https://www.youtube.com/watch?v=FWNlS7hRQOo 4. Time Series Forecasting with Google Sheets part (2 of 4) https://www.youtube.com/watch?v=lL61SGr1lJk 5. Time Series Forecasting with Google Sheets part (3 of 4) https://www.youtube.com/watch?v=I29vxyfIVtw 6. Time Series Forecasting with Google Sheets part (4 of 4) https://www.youtube.com/watch?v=C68u9nuw50Y 7. Google Sheets: Create Pivot Tables and Charts https://www.youtube.com/watch?v=SzrBbBV adM 8. Two Way ANOVA - with Google Sheets XL-miner https://www.youtube.com/watch?v=uCkycwF2HUU 9. Running a t-Test using Google Sheets https://www.youtube.com/watch?v=YeVF2lnhr7o 10. Using Google Sheets to Calculate Differences in Proportions (Z Test) https://www.youtube.com/watch?v=1uGvuaCw6t8 5. The Data You Need For the Assignment Two data sets will be needed to complete this assignment. Both of these data sets are posted in Elearn. 5.1. Housing.xlsx This data set contains the following data for 150 homes sold recently in a large city. Price: In US Dollars Beds: Number of bedrooms in the house Baths: Number of bathrooms Garage: Number of cars that can be parked in a covered space (like a grage) Sqft-House: Finished Sq-ft for the house Sqft-Land: Sq-ft of the land on which the house sits Kitchen: If the kitchen is updated: 0 means not updated & 1 means updated Roof: Number of years of useful life left for the roof Age: Age of the house 5.2. Enplanement.xlsx Enplanements for U.S. Air Carrier International, Scheduled Passenger Flights, Thousands, Monthly, Seasonally Adjusted. This is a monthly data starting on January 2000 and ending December, 2019. 4 6. PART 1: Suggested Early Submission Date: April 20, 2020. Accounts for 25% of the Final Grade. By using the Housing.xlsx data, answer the following questions. 1. Test the following hypotheses and also state the alternate hypothesis in each case. Write a sentence or two summarizing your conclusion after you have completed each hypothesis testing. Hypothesis 1 Average price per sq-ft of houses with ≤ 3 bedrooms is more than the average price per sq-ft of other houses. (Use the sq-ft of the house only) Hypothesis 2 Average price per sq-ft of houses with updated kirchen is more than the average price per sq-ft of other houses. Hypothesis 3 Average price per sq-ft of houses with ≥ 15, 000 sq-ft of land is more than the average price per sq-ft of other houses. Hypothesis 4 Average price per sq-ft of houses with ≥ 10 years of usable roof life left is more than the average price per sq-ft of other houses. Hypothesis 5 Average price per sq-ft of houses with ≤ 10 years old houses is more than the average price per sq-ft of other houses. Hypothesis 6 Variance of the price per sq-ft of houses with ≤ 10 years old houses is more than the variance of the price per sq-ft of other houses. Hypothesis 7 Average price per sq-ft of 3, 4, or, 5 bedroom houses are basiacally equal to each other. (Hint: Think ANOVA) 2. Run the following regressions and present the results nicely. Also interpret the results carefully: Price per sq-ft of the house = β0 + β1 (Sqf t − House) +  (1) Price per sq-ft of the house = β0 + β1 (Sqf t − Land) +  (2) Price per sq-ft of the house = β0 + β1 (Roof ) +  (3) Price per sq-ft of the house = β0 + β1 (Age) +  (4) Price per sq-ft of the house = β0 + β1 (Beds) +  (5) Price per sq-ft of the house = β0 + β1 (Baths) +  (6) Price per sq-ft of the house = β0 + β1 (Kitchen) +  (7) 3. Write a short essay summarizing your results in the above regressions. Make your presentation in a simple enough format that may be understood by an average home buyer. 7. PART 2: Suggested Early Submission Date: April 25, 2020. Accounts for 25% of the Final Grade. By using the Housing.xlsx data, answer the following questions. 5 1. Run the following regressions and present the results nicely. Also interpret the results carefully: Price = β0 + β1 (Sqf t − House) + β2 (Sqf t − Land) +  (8) Price = β0 + β1 (Sqf t − House) + β2 (Sqf t − Land) + β3 (Beds) + β4 (Baths) +  (9) Price = β ...
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