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Load the dataset called ec122a.csv and decide the appropriate regression to run. Write down what transformations, corrections, etc... you make and why.

y1 x1
5.347878758 -0.930542578
-69.44110024 -14.33608768
17.66476989 1.817414208
98.65114667 16.87694699
14.79659009 1.441478611
-34.53026553 -8.00737845
93.08997094 15.96019814
9.216932058 0.677367144
82.60075111 13.94035248
115.7981139 21.2544523
210.3870497 38.24079287
25.53810654 2.87106608
103.8321406 18.12872197
69.98871025 11.98941729
115.531925 20.80167988
121.344292 22.01890192
92.73418126 15.95082451
141.3368312 25.38389681
43.96760847 6.627838431
170.3124982 30.6056891
100.141723 18.07441566
135.1275265 25.15574273
35.49106156 5.340678409
49.08861624 7.666301802
183.2330588 33.67478881
133.8996698 31.04847768
119.4723866 19.67743214
158.3820123 38.79481249
158.2657512 32.34495308
143.8934387 31.31839907
209.5541526 39.04705927
269.6967412 47.02609084
214.2778353 39.46210377
137.4487281 32.19515025
207.1423319 30.4353134
195.5302794 37.88951197
260.6133658 47.57776489
193.3585644 32.54438767
214.3550323 35.39687386
236.2462954 46.85739498
179.510295 40.16597219
212.2029972 42.96600845
207.2630019 38.35632342
189.5370809 36.9994191
293.7752011 52.18388283
275.8168686 46.9729304
213.7777301 51.62341054
234.5157107 54.77135643
305.7551645 58.22817991
247.5740289 48.26121356
216.4872019 44.48057022
298.939399 59.5098241
294.087516 59.73239921
242.4707109 56.24233872
314.2166642 52.09946329
198.6418357 45.55247034
451.5017391 71.73712791
334.6397647 56.30033876
325.5397116 61.37532021
334.3609993 65.65095955
375.5016921 69.0188963
279.9239427 50.82003332
391.7471591 84.43876551
256.7554261 61.84252079
335.3483647 78.29722914
326.8626545 67.27018638
409.1990617 67.02263944
315.2786023 62.6960929
389.1157991 67.39885464
324.5584983 74.46138195
277.8602629 51.11520206
348.2209528 73.43184999
394.1015917 69.68283875
378.574745 70.33903001
345.1292913 65.14434869
431.3883837 86.53858814
461.2463404 80.77782163
393.1285873 79.48754349
457.4136172 93.35355915
490.030081 86.14697907
445.0136118 88.28584593
502.4332269 90.18402149
531.9194021 84.58453379
459.430686 101.5844764
524.5345881 93.72181224
384.8318203 88.39970312
369.2556461 64.05937079
460.0115502 94.61728256
581.8494484 100.291462
487.2384874 86.27712908
554.3895438 106.0543582
476.1382136 77.22185093
360.4342344 84.29536632
497.0642852 98.56921723
559.6200173 104.3948843
570.2747244 113.8670233
526.0063913 110.5503116
668.8532939 118.103935
567.238946 105.3303107
551.5252361 104.2587505

Business Economics, Economics

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  • Reference No.:- M93098146
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