I’m working on a Statistics question and need support to help me understand better.

Regression Analysis. Show all work and output to all code. I dont need just output, i need it to show how to use the output.

– You only need to do the LOF test for the reduced model on the project. All kinds of problems arise when you try to do it for the full model.

– In the Fish set data, the weight is measured in grams. Everything else is measured in centimeters

– First, for the lack of fit test, it would seem that a lot of you are running into an issue that I had not, but I am not sure why. If you do the lack of fit test for the full model, I am having a lot of people say that R gives a fatal error. This looks to be due to exceeding memory limitations when everything is broken down into factors. The remedy to this seems to be that we should do the LOF test only for the reduced model, so just do that.

Using the “Fish.txt” data set, specify and completely analyze a multiple linear regression model that relatesweight to length1, length2, length3, height, and width. Carry out a full analysis of the model, including testsfor each coefficient (with the significance level adjusted for multiple tests) and confidence intervals for eachcoefficient. If any are not significant to the model, drop them, fit the reduced model, and repeat the fullanalysis. Do not forget to examine multicollinearity among predictors, and for each model you fit, carry out aformal test for a lack of fit.

Fish.txt :

“Weight” “Length1” “Length2” “Length3” “Height” “Width”
“1” 242 23.2 25.4 30 11.52 4.02
“2” 290 24 26.3 31.2 12.48 4.3056
“3” 340 23.9 26.5 31.1 12.3778 4.6961
“4” 363 26.3 29 33.5 12.73 4.4555
“5” 430 26.5 29 34 12.444 5.134
“6” 450 26.8 29.7 34.7 13.6024 4.9274
“7” 500 26.8 29.7 34.5 14.1795 5.2785
“8” 390 27.6 30 35 12.67 4.69
“9” 450 27.6 30 35.1 14.0049 4.8438
“10” 500 28.5 30.7 36.2 14.2266 4.9594
“11” 475 28.4 31 36.2 14.2628 5.1042
“12” 500 28.7 31 36.2 14.3714 4.8146
“13” 500 29.1 31.5 36.4 13.7592 4.368
“14” 340 29.5 32 37.3 13.9129 5.0728
“15” 600 29.4 32 37.2 14.9544 5.1708
“16” 600 29.4 32 37.2 15.438 5.58
“17” 700 30.4 33 38.3 14.8604 5.2854
“18” 700 30.4 33 38.5 14.938 5.1975
“19” 610 30.9 33.5 38.6 15.633 5.1338
“20” 650 31 33.5 38.7 14.4738 5.7276
“21” 575 31.3 34 39.5 15.1285 5.5695
“22” 685 31.4 34 39.2 15.9936 5.3704
“23” 620 31.5 34.5 39.7 15.5227 5.2801
“24” 680 31.8 35 40.6 15.4686 6.1306
“25” 700 31.9 35 40.5 16.2405 5.589
“26” 725 31.8 35 40.9 16.36 6.0532
“27” 720 32 35 40.6 16.3618 6.09
“28” 714 32.7 36 41.5 16.517 5.8515
“29” 850 32.8 36 41.6 16.8896 6.1984
“30” 1000 33.5 37 42.6 18.957 6.603
“31” 920 35 38.5 44.1 18.0369 6.3063
“32” 955 35 38.5 44 18.084 6.292
“33” 925 36.2 39.5 45.3 18.7542 6.7497
“34” 975 37.4 41 45.9 18.6354 6.7473
“35” 950 38 41 46.5 17.6235 6.3705
“36” 40 12.9 14.1 16.2 4.1472 2.268
“37” 69 16.5 18.2 20.3 5.2983 2.8217
“38” 78 17.5 18.8 21.2 5.5756 2.9044
“39” 87 18.2 19.8 22.2 5.6166 3.1746
“40” 120 18.6 20 22.2 6.216 3.5742
“41” 0 19 20.5 22.8 6.4752 3.3516
“42” 110 19.1 20.8 23.1 6.1677 3.3957
“43” 120 19.4 21 23.7 6.1146 3.2943
“44” 150 20.4 22 24.7 5.8045 3.7544
“45” 145 20.5 22 24.3 6.6339 3.5478
“46” 160 20.5 22.5 25.3 7.0334 3.8203
“47” 140 21 22.5 25 6.55 3.325
“48” 160 21.1 22.5 25 6.4 3.8
“49” 169 22 24 27.2 7.5344 3.8352
“50” 161 22 23.4 26.7 6.9153 3.6312
“51” 200 22.1 23.5 26.8 7.3968 4.1272
“52” 180 23.6 25.2 27.9 7.0866 3.906
“53” 290 24 26 29.2 8.8768 4.4968
“54” 272 25 27 30.6 8.568 4.7736
“55” 390 29.5 31.7 35 9.485 5.355
“56” 270 23.6 26 28.7 8.3804 4.2476
“57” 270 24.1 26.5 29.3 8.1454 4.2485
“58” 306 25.6 28 30.8 8.778 4.6816
“59” 540 28.5 31 34 10.744 6.562
“60” 800 33.7 36.4 39.6 11.7612 6.5736
“61” 1000 37.3 40 43.5 12.354 6.525
“62” 55 13.5 14.7 16.5 6.8475 2.3265
“63” 60 14.3 15.5 17.4 6.5772 2.3142
“64” 90 16.3 17.7 19.8 7.4052 2.673
“65” 120 17.5 19 21.3 8.3922 2.9181
“66” 150 18.4 20 22.4 8.8928 3.2928
“67” 140 19 20.7 23.2 8.5376 3.2944
“68” 170 19 20.7 23.2 9.396 3.4104
“69” 145 19.8 21.5 24.1 9.7364 3.1571
“70” 200 21.2 23 25.8 10.3458 3.6636
“71” 273 23 25 28 11.088 4.144
“72” 300 24 26 29 11.368 4.234
“73” 5.9 7.5 8.4 8.8 2.112 1.408
“74” 32 12.5 13.7 14.7 3.528 1.9992
“75” 40 13.8 15 16 3.824 2.432
“76” 51.5 15 16.2 17.2 4.5924 2.6316
“77” 70 15.7 17.4 18.5 4.588 2.9415
“78” 100 16.2 18 19.2 5.2224 3.3216
“79” 78 16.8 18.7 19.4 5.1992 3.1234
“80” 80 17.2 19 20.2 5.6358 3.0502
“81” 85 17.8 19.6 20.8 5.1376 3.0368
“82” 85 18.2 20 21 5.082 2.772
“83” 110 19 21 22.5 5.6925 3.555
“84” 115 19 21 22.5 5.9175 3.3075
“85” 125 19 21 22.5 5.6925 3.6675
“86” 130 19.3 21.3 22.8 6.384 3.534
“87” 120 20 22 23.5 6.11 3.4075
“88” 120 20 22 23.5 5.64 3.525
“89” 130 20 22 23.5 6.11 3.525
“90” 135 20 22 23.5 5.875 3.525
“91” 110 20 22 23.5 5.5225 3.995
“92” 130 20.5 22.5 24 5.856 3.624
“93” 150 20.5 22.5 24 5.856 3.624
“94” 145 20.7 22.7 24.2 5.9532 3.63
“95” 150 21 23 24.5 5.2185 3.626
“96” 170 21.5 23.5 25 6.275 3.725
“97” 225 22 24 25.5 7.293 3.723
“98” 145 22 24 25.5 6.375 3.825
“99” 188 22.6 24.6 26.2 6.7334 4.1658
“100” 180 23 25 26.5 6.4395 3.6835
“101” 197 23.5 25.6 27 6.561 4.239
“102” 218 25 26.5 28 7.168 4.144
“103” 300 25.2 27.3 28.7 8.323 5.1373
“104” 260 25.4 27.5 28.9 7.1672 4.335
“105” 265 25.4 27.5 28.9 7.1672 4.335
“106” 250 25.4 27.5 28.9 7.2828 4.5662
“107” 250 25.9 28 29.4 7.8204 4.2042
“108” 300 26.9 28.7 30.1 7.5852 4.6354
“109” 320 27.8 30 31.6 7.6156 4.7716
“110” 514 30.5 32.8 34 10.03 6.018
“111” 556 32 34.5 36.5 10.2565 6.3875
“112” 840 32.5 35 37.3 11.4884 7.7957
“113” 685 34 36.5 39 10.881 6.864
“114” 700 34 36 38.3 10.6091 6.7408
“115” 700 34.5 37 39.4 10.835 6.2646
“116” 690 34.6 37 39.3 10.5717 6.3666
“117” 900 36.5 39 41.4 11.1366 7.4934
“118” 650 36.5 39 41.4 11.1366 6.003
“119” 820 36.6 39 41.3 12.4313 7.3514
“120” 850 36.9 40 42.3 11.9286 7.1064
“121” 900 37 40 42.5 11.73 7.225
“122” 1015 37 40 42.4 12.3808 7.4624
“123” 820 37.1 40 42.5 11.135 6.63
“124” 1100 39 42 44.6 12.8002 6.8684
“125” 1000 39.8 43 45.2 11.9328 7.2772
“126” 1100 40.1 43 45.5 12.5125 7.4165
“127” 1000 40.2 43.5 46 12.604 8.142
“128” 1000 41.1 44 46.6 12.4888 7.5958
“129” 200 30 32.3 34.8 5.568 3.3756
“130” 300 31.7 34 37.8 5.7078 4.158
“131” 300 32.7 35 38.8 5.9364 4.3844
“132” 300 34.8 37.3 39.8 6.2884 4.0198
“133” 430 35.5 38 40.5 7.29 4.5765
“134” 345 36 38.5 41 6.396 3.977
“135” 456 40 42.5 45.5 7.28 4.3225
“136” 510 40 42.5 45.5 6.825 4.459
“137” 540 40.1 43 45.8 7.786 5.1296
“138” 500 42 45 48 6.96 4.896
“139” 567 43.2 46 48.7 7.792 4.87
“140” 770 44.8 48 51.2 7.68 5.376
“141” 950 48.3 51.7 55.1 8.9262 6.1712
“142” 1250 52 56 59.7 10.6863 6.9849
“143” 1600 56 60 64 9.6 6.144
“144” 1550 56 60 64 9.6 6.144
“145” 1650 59 63.4 68 10.812 7.48
“146” 6.7 9.3 9.8 10.8 1.7388 1.0476
“147” 7.5 10 10.5 11.6 1.972 1.16
“148” 7 10.1 10.6 11.6 1.7284 1.1484
“149” 9.7 10.4 11 12 2.196 1.38
“150” 9.8 10.7 11.2 12.4 2.0832 1.2772
“151” 8.7 10.8 11.3 12.6 1.9782 1.2852
“152” 10 11.3 11.8 13.1 2.2139 1.2838
“153” 9.9 11.3 11.8 13.1 2.2139 1.1659
“154” 9.8 11.4 12 13.2 2.2044 1.1484
“155” 12.2 11.5 12.2 13.4 2.0904 1.3936
“156” 13.4 11.7 12.4 13.5 2.43 1.269
“157” 12.2 12.1 13 13.8 2.277 1.2558
“158” 19.7 13.2 14.3 15.2 2.8728 2.0672
“159” 19.9 13.8 15 16.2 2.9322 1.8792