The electric power consumed each month by a chemical plant is thought to be related to the average ambient temperature x₁, the number of days in the month x2, the average product purity as a percent X3, and the tons of product produced x4. The past year's historical data are available and are presented in the accompanying table. Complete parts (a) and (b) below. Click the icon to view the historical data. (a) Fit a multiple linear regression model using the data set. ŷ-(+)ׂ+() %₂+ ( ) %s + ( ) xx (Round the constant to two decimal places as needed. Round all other values to four decimal places as needed.) (b) Predict power consumption for a month in which x₁ = 76°F, x2 = 26 days, x3 = 92%, and x4 = 89 tons. The predicted power consumption is (Round to one decimal place as needed.) Historical data y x1 251 25 225 30 274 45 292 61 302 64 222222 X3 x4 23 92 101 20 90 94 25 87 109 26 87 89 26 92 95 307 71 26 93 100 293 79 25 86 97 286 85 286 75 289 60 281 50 264 39 22222 24 85 96 24 89 109 25 91 105 25 90 100 24 89 98