NAME: fishcatch TYPE: Sample SIZE: 159 observations, 8 variables DESCRIPTIVE ABSTRACT: 159 fishes of 7 species are caught and measured. Altogether there are 8 variables. All the fishes are caught from the same lake (Laengelmavesi) near Tampere in Finland. SOURCES: Brofeldt, Pekka: Bidrag till kaennedom on fiskbestondet i vaera sjoear. Laengelmaevesi. T.H.Jaervi: Finlands Fiskeriet Band 4, Meddelanden utgivna av fiskerifoereningen i Finland. Helsingfors 1917 VARIABLE DESCRIPTIONS: 1 Obs Observation number ranges from 1 to 159 2 Species (Numeric) Code Finnish Swedish English Latin 1 Lahna Braxen Bream Abramis brama 2 Siika Iiden Whitewish Leusiscus idus 3 Saerki Moerten Roach Leuciscus rutilus 4 Parkki Bjoerknan ? Abramis bjrkna 5 Norssi Norssen Smelt Osmerus eperlanus 6 Hauki Jaedda Pike Esox lucius 7 Ahven Abborre Perch Perca fluviatilis 3 Weight Weight of the fish (in grams) 4 Length1 Length from the nose to the beginning of the tail (in cm) 5 Length2 Length from the nose to the notch of the tail (in cm) 6 Length3 Length from the nose to the end of the tail (in cm) 7 Height% Maximal height as % of Length3 8 Width% Maximal width as % of Length3 9 Sex 1 = male 0 = female ___/////___ _ / \ ___ | /\ \_ / / H < ) __) \ | \/_\\_________/ \__\ _ |------- L1 -------| |------- L2 ----------| |------- L3 ------------| Values are aligned and delimited by blanks. Missing values are denoted with NA. There is one data line for each case. SPECIAL NOTES: I have usually calculated Height = Height%*Length3/100 Widht = Widht%*Length3/100 PEDAGOGICAL NOTES: I have mainly used only Species=7 (Perch) and here is some of the models and test, we have used Weight=a+b*(Length3*Height*Width)+epsilon Ho: a=0; Heteroscedastic case. Question: What is proper weighting, if you use Length3 as a weighting variable. Log(Weight)=a+b1*Length3+epsilon Weight^(1/3)=a+b1*Length3+epsilon (Given by Box-Cox-transformation) Ho: a=0; Log(Weight)=a+b1*Length3+b2*Height+b3*Width+epsilon Ho: b1+b2+b3=3; i.e. dimension of the fish = 3 Weight^(1/3)=a+b1*Length3+b2*Height+b3*Width+epsilon (Given by Box-Cox-transformation) Ho: a=0; Weight=a*Length3^b1*Height^b2*Width^b3+epsilon Nonlinear, heteroscedastic case. What is proper weighting? Is obs 143 143 7 840.0 32.5 35.0 37.3 30.8 20.9 0 an outlier? It had in its stomach 6 roach. REFERENCES: Brofeldt, Pekka: Bidrag till kaennedom on fiskbestondet i vaara sjoear. Laengelmaevesi. T.H.Jaervi: Finlands Fiskeriet Band 4, Meddelanden utgivna av fiskerifoereningen i Finland. Helsingfors 1917 SUBMITTED BY: Juha Puranen Departement of statistics PL33 (Aleksanterinkatu 7) 000014 University of Helsinki Finland e-mail: jpuranen@noppa.helsinki.fi Obs,Species,Weight,Length 1,Length 2,Length 3,Height,Width,Sex 1,1,242,23.2,25.4,30,38.4,13.4,NA 2,1,290,24,26.3,31.2,40,13.8,NA 3,1,340,23.9,26.5,31.1,39.8,15.1,NA 4,1,363,26.3,29,33.5,38,13.3,NA 5,1,430,26.5,29,34,36.6,15.1,NA 6,1,450,26.8,29.7,34.7,39.2,14.2,NA 7,1,500,26.8,29.7,34.5,41.1,15.3,NA 8,1,390,27.6,30,35,36.2,13.4,NA 9,1,450,27.6,30,35.1,39.9,13.8,NA 10,1,500,28.5,30.7,36.2,39.3,13.7,NA 11,1,475,28.4,31,36.2,39.4,14.1,NA 12,1,500,28.7,31,36.2,39.7,13.3,NA 13,1,500,29.1,31.5,36.4,37.8,12,NA 14,1,NA,29.5,32,37.3,37.3,13.6,1 15,1,600,29.4,32,37.2,40.2,13.9,1 16,1,600,29.4,32,37.2,41.5,15,NA 17,1,700,30.4,33,38.3,38.8,13.8,1 18,1,700,30.4,33,38.5,38.8,13.5,NA 19,1,610,30.9,33.5,38.6,40.5,13.3,NA 20,1,650,31,33.5,38.7,37.4,14.8,NA 21,1,575,31.3,34,39.5,38.3,14.1,1 22,1,685,31.4,34,39.2,40.8,13.7,NA 23,1,620,31.5,34.5,39.7,39.1,13.3,NA 24,1,680,31.8,35,40.6,38.1,15.1,NA 25,1,700,31.9,35,40.5,40.1,13.8,NA 26,1,725,31.8,35,40.9,40,14.8,1 27,1,720,32,35,40.6,40.3,15,NA 28,1,714,32.7,36,41.5,39.8,14.1,NA 29,1,850,32.8,36,41.6,40.6,14.9,NA 30,1,1000,33.5,37,42.6,44.5,15.5,0 31,1,920,35,38.5,44.1,40.9,14.3,0 32,1,955,35,38.5,44,41.1,14.3,NA 33,1,925,36.2,39.5,45.3,41.4,14.9,1 34,1,975,37.4,41,45.9,40.6,14.7,0 35,1,950,38,41,46.5,37.9,13.7,NA 36,2,270,23.6,26,28.7,29.2,14.8,NA 37,2,270,24.1,26.5,29.3,27.8,14.5,NA 38,2,306,25.6,28,30.8,28.5,15.2,NA 39,2,540,28.5,31,34,31.6,19.3,NA 40,2,800,33.7,36.4,39.6,29.7,16.6,0 41,2,1000,37.3,40,43.5,28.4,15,NA 42,3,40,12.9,14.1,16.2,25.6,14,NA 43,3,69,16.5,18.2,20.3,26.1,13.9,NA 44,3,78,17.5,18.8,21.2,26.3,13.7,NA 45,3,87,18.2,19.8,22.2,25.3,14.3,NA 46,3,120,18.6,20,22.2,28,16.1,NA 47,3,0,19,20.5,22.8,28.4,14.7,NA 48,3,110,19.1,20.8,23.1,26.7,14.7,0 49,3,120,19.4,21,23.7,25.8,13.9,0 50,3,150,20.4,22,24.7,23.5,15.2,0 51,3,145,20.5,22,24.3,27.3,14.6,0 52,3,160,20.5,22.5,25.3,27.8,15.1,0 53,3,140,21,22.5,25,26.2,13.3,NA 54,3,160,21.1,22.5,25,25.6,15.2,0 55,3,169,22,24,27.2,27.7,14.1,NA 56,3,161,22,23.4,26.7,25.9,13.6,NA 57,3,200,22.1,23.5,26.8,27.6,15.4,0 58,3,180,23.6,25.2,27.9,25.4,14,NA 59,3,290,24,26,29.2,30.4,15.4,NA 60,3,272,25,27,30.6,28,15.6,0 61,3,390,29.5,31.7,35,27.1,15.3,NA 62,4,55,13.5,14.7,16.5,41.5,14.1,NA 63,4,60,14.3,15.5,17.4,37.8,13.3,1 64,4,90,16.3,17.7,19.8,37.4,13.5,1 65,4,120,17.5,19,21.3,39.4,13.7,1 66,4,150,18.4,20,22.4,39.7,14.7,NA 67,4,140,19,20.7,23.2,36.8,14.2,NA 68,4,170,19,20.7,23.2,40.5,14.7,0 69,4,145,19.8,21.5,24.1,40.4,13.1,0 70,4,200,21.2,23,25.8,40.1,14.2,NA 71,4,273,23,25,28,39.6,14.8,0 72,4,300,24,26,29,39.2,14.6,0 73,5,6.7,9.3,9.8,10.8,16.1,9.7,1 74,5,7.5,10,10.5,11.6,17,10,0 75,5,7,10.1,10.6,11.6,14.9,9.9,1 76,5,9.7,10.4,11,12,18.3,11.5,0 77,5,9.8,10.7,11.2,12.4,16.8,10.3,1 78,5,8.7,10.8,11.3,12.6,15.7,10.2,1 79,5,10,11.3,11.8,13.1,16.9,9.8,1 80,5,9.9,11.3,11.8,13.1,16.9,8.9,0 81,5,9.8,11.4,12,13.2,16.7,8.7,0 82,5,12.2,11.5,12.2,13.4,15.6,10.4,0 83,5,13.4,11.7,12.4,13.5,18,9.4,0 84,5,12.2,12.1,13,13.8,16.5,9.1,0 85,5,19.7,13.2,14.3,15.2,18.9,13.6,0 86,5,19.9,13.8,15,16.2,18.1,11.6,0 87,6,200,30,32.3,34.8,16,9.7,NA 88,6,300,31.7,34,37.8,15.1,11,0 89,6,300,32.7,35,38.8,15.3,11.3,NA 90,6,300,34.8,37.3,39.8,15.8,10.1,NA 91,6,430,35.5,38,40.5,18,11.3,NA 92,6,345,36,38.5,41,15.6,9.7,1 93,6,456,40,42.5,45.5,16,9.5,NA 94,6,510,40,42.5,45.5,15,9.8,NA 95,6,540,40.1,43,45.8,17,11.2,NA 96,6,500,42,45,48,14.5,10.2,NA 97,6,567,43.2,46,48.7,16,10,0 98,6,770,44.8,48,51.2,15,10.5,0 99,6,950,48.3,51.7,55.1,16.2,11.2,NA 100,6,1250,52,56,59.7,17.9,11.7,NA 101,6,1600,56,60,64,15,9.6,NA 102,6,1550,56,60,64,15,9.6,0 103,6,1650,59,63.4,68,15.9,11,0 104,7,5.9,7.5,8.4,8.8,24,16,NA 105,7,32,12.5,13.7,14.7,24,13.6,NA 106,7,40,13.8,15,16,23.9,15.2,NA 107,7,51.5,15,16.2,17.2,26.7,15.3,NA 108,7,70,15.7,17.4,18.5,24.8,15.9,NA 109,7,100,16.2,18,19.2,27.2,17.3,NA 110,7,78,16.8,18.7,19.4,26.8,16.1,NA 111,7,80,17.2,19,20.2,27.9,15.1,NA 112,7,85,17.8,19.6,20.8,24.7,14.6,NA 113,7,85,18.2,20,21,24.2,13.2,NA 114,7,110,19,21,22.5,25.3,15.8,NA 115,7,115,19,21,22.5,26.3,14.7,NA 116,7,125,19,21,22.5,25.3,16.3,1 117,7,130,19.3,21.3,22.8,28,15.5,0 118,7,120,20,22,23.5,26,14.5,0 119,7,120,20,22,23.5,24,15,NA 120,7,130,20,22,23.5,26,15,NA 121,7,135,20,22,23.5,25,15,NA 122,7,110,20,22,23.5,23.5,17,0 123,7,130,20.5,22.5,24,24.4,15.1,0 124,7,150,20.5,22.5,24,28.3,15.1,0 125,7,145,20.7,22.7,24.2,24.6,15,NA 126,7,150,21,23,24.5,21.3,14.8,NA 127,7,170,21.5,23.5,25,25.1,14.9,NA 128,7,225,22,24,25.5,28.6,14.6,NA 129,7,145,22,24,25.5,25,15,NA 130,7,188,22.6,24.6,26.2,25.7,15.9,NA 131,7,180,23,25,26.5,24.3,13.9,0 132,7,197,23.5,25.6,27,24.3,15.7,NA 133,7,218,25,26.5,28,25.6,14.8,NA 134,7,300,25.2,27.3,28.7,29,17.9,0 135,7,260,25.4,27.5,28.9,24.8,15,0 136,7,265,25.4,27.5,28.9,24.4,15,NA 137,7,250,25.4,27.5,28.9,25.2,15.8,0 138,7,250,25.9,28,29.4,26.6,14.3,NA 139,7,300,26.9,28.7,30.1,25.2,15.4,0 140,7,320,27.8,30,31.6,24.1,15.1,0 141,7,514,30.5,32.8,34,29.5,17.7,NA 142,7,556,32,34.5,36.5,28.1,17.5,NA 143,7,840,32.5,35,37.3,30.8,20.9,0 144,7,685,34,36.5,39,27.9,17.6,0 145,7,700,34,36,38.3,27.7,17.6,0 146,7,700,34.5,37,39.4,27.5,15.9,0 147,7,690,34.6,37,39.3,26.9,16.2,0 148,7,900,36.5,39,41.4,26.9,18.1,0 149,7,650,36.5,39,41.4,26.9,14.5,NA 150,7,820,36.6,39,41.3,30.1,17.8,NA 151,7,850,36.9,40,42.3,28.2,16.8,0 152,7,900,37,40,42.5,27.6,17,0 153,7,1015,37,40,42.4,29.2,17.6,0 154,7,820,37.1,40,42.5,26.2,15.6,0 155,7,1100,39,42,44.6,28.7,15.4,0 156,7,1000,39.8,43,45.2,26.4,16.1,0 157,7,1100,40.1,43,45.5,27.5,16.3,0 158,7,1000,40.2,43.5,46,27.4,17.7,1 159,7,1000,41.1,44,46.6,26.8,16.3,0