15 45 25 60 154 116 in ininau 7.5 31 34.5 182 20 34 150 5.5 26 39 180 20 35 172 21 9.5 32.5 150 11 16 50.5 28 90 9.5 4.5 16 40 26 65 .3.5 6.5 28 64 48 356 70 14.5 6.5 26 65 48 316 20 .3.5 5.5 19 0.5 34 148 16 1.5 5.5 17.5 2.5 30 104 10 11 17 49 29 94 10 11.5 17 47 29.5 86 34 13 21 59 35 150 43 13.5 21 64 35 166 34 16.5 5.5 27 14.5 270 14 5.5 24 65 39 202 58 13.5 6.5 21.5 63 40 202 58 15.5 28 70.5 50 365 11 11.5 16.5 18 31 79 UI ON 17 11.5 17 50.5 28 90 23 12 5.5 19 50 38 148 70 5.5 28 76.5 55 446 11 15 46 27 62 14.5 23 1.5 14 236 13.5 3.5 23 3.5 44 212 3.5 3.5 67.5 42 204 26 65 40 224 15.5 48 26 60 15 41 26 64 21 59 34 146 5 .5 20.5 60 35 152 5 .5 29 79 50 400 3. 24.5 62 41 248 14.5 in 26 0.5 41 278 26.5 69 46.5 297 31.5 47 350 11. 17 53 30.5 114 15 52.5 28 76 uurain u uo 13 23 48 19 57 34.5 148 17 58 29 114 17 58 29.5 116 7.5 19 60 34 158 5.5 21 63 35 198Instruction: This is an individual project. You need to work with dataset bears.xlsx. The goal of this project is letting students explore the dataset, analyze the dataset. build regression models, and interpret the modeling results. Regression Case Study A study is conducted on the greatest threat to humanity, bears. Field studies collect data on the following characteristics of bears in the wild: Variable Description Age age of bear Sex sex of bear Head Length distance from tip of nose to back of head Head Width distance from outer edge of left ear to outer edge of right ear Neck Girth circumference of the neck Length distance from foot to top of head Chest Girth circumference of the chest Weight weight of bear The data are collected by tranquilizing the bear and taking the measurements. Weighing an unconscious bear in the field proves to be very difficult. Our task is to predict bear weight based on the other measurements