The equation used to predict annual cauliflower yield (in pounds per acre) is y = 24,121 +4.505x₁ -4.772x₂, where x₁is the number of acres planted and x2 is the number of acres harvested. Use the multiple regression equation topredict the y-values for the values of the independent variables.(a) x₁ =35,100, x₂ =35,500(b) x₁ = 36,800, X2=37,100(c) x₁ = 37,900, x₂ = 38,000(d) x₁ =41,100, x₂ = 41,200(a) The predicted yield is pounds per acre.(Round to one decimal place as needed.)(b) The predicted yield is pounds per acre.(Round to one decimal place as needed.)(c) The predicted yield is pounds per acre.(Round to one decimal place as needed.)(d) The predicted yield is pounds per acre(Round to one decimal place as needed.)

Y^=24121+4.505x1-4.772x2(a) x1 =35,100, x2 = 35,500(b) x1 = 36,800, x2 = 37,100(c) x1 =37,900, x2…

he equation used to predict annual cauliflower yield (in pounds per acre) is y = 24,121 +4.505x₁ -4.772x2, where x₁ = the number of acres planted and x2 is the number of acres harvested. Use the multiple regression equation to redict the y-values for the values of the independent variables. a) x₁ = 35, 100, x₂=35,500 b) x₁ = 36,800, x₂ = 37,100 c) x₁ = 37,900, x₂ = 38,000 d) x₁ =41,100, x₂ = 41,200 a) The predicted yield is pounds per acre. Round to one decimal place as needed.) b) The predicted yield is pounds per acre. ***

he equation used to predict annual cauliflower yield (in pounds per acre) is y = 24,121 +4.505x₁ -4.772x2, where x₁ = the number of acres planted and x2 is the number of acres harvested. Use the multiple regression equation to redict the y-values for the values of the independent variables. a) x₁ = 35, 100, x₂=35,500 b) x₁ = 36,800, x₂ = 37,100 c) x₁ = 37,900, x₂ = 38,000 d) x₁ =41,100, x₂ = 41,200 a) The predicted yield is pounds per acre. Round to one decimal place as needed.) b) The predicted yield is pounds per acre. ***

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 5PPS

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