A multiple regression model is to be constructed to predict the heart rate in beats per minute (bpm) of a person based upon their age, weight and height. Data has been collected on 30 randomly selected individuals: show data 3) Find the multiple regression equation using all three explanatory variables. Assume that X1 is age, X2 is weight and X3 is height. Give your answers to 3 decimal places. G: E + Sage + \\:lweight + Sheight b) At a level of signicance of 0.05, the result of the F test for this model is that the null hypotheSis rejected. For parts c) and d), using the data, separately calculate the correlations between the response variable and each of the three explanatory variables. c) The explanatory variable that is most correlated with heart rate is: 0 age 0 weight 0 height d) The explanatory variable that is least correlated with heart rate is: 0 age 0 weight 0 height e) The value of R2 for this model, to 2 decimal places, is equal to E f) The value of se for this model, to 3 decimal places, is equal to S 9) Construct a new multiple regression model by removing the variable height. Give your answers to 3 decimal places. The new regression model equation is: h) In the new model compared to the previous one, the value of R2 (to 2 decimal places) is: 0 increased 0 decreased 0 unchanged i) In the new model compared to the previous one, the value of se (to 3 decimal places) is: 0 increased 0 decreased 0 unchanged Heart Rate Age Weight Height (bpm) (yrs) (lb) (in) 88 52 166 59 105 58 121 60 88 54 132 60 119 58 219 61 65 28 235 75 71 24 216 69 75 54 155 74 79 44 123 74 56 24 185 66 81 44 199 60 112 46 256 70 78 25 153 71 70 22 107 72 75 35 189 73 89 51 209 70 67 26 123 58 85 32 239 57 72 37 130 71 96 54 140 73 110 56 172 64 81 31 220 59 58 48 122 66 74 50 195 71 89 31 176 59 67 30 162 67 81 26 216 64 81 21 230 59 66 45 171 69 84 53 136 61 107 59 210 59