The equation used to predict annual cauliflower yield (in pounds per acre) is y = 24,677 + 4.556x, - 4.745x2, where x, is the number of acres planted and x, is thenumber of acres harvested. Use the multiple regression equation to predict the y-values for the values of the independent variables.(a) x, = 36,600, x2 = 37,000(b) x, = 38,400, xX2 = 38,600(c) x4 = 39,400, x2 = 39,500(d) x, = 42,600, x2 = 42,700%3D%3D%3D%3D2 (a) The predicted yield is pounds per acre.(Round to one decimal place as needed.)th(b) The predicted yield ispounds per acre.12(Round to one decimal place as needed.)or (c) The predicted yield is pounds per acre.(Round to one decimal place as needed.)(d) The predicted yield isnspounds per acre.(Round to one decimal place as needed.)uestQueQuestEnter your answer in each of the answer boxes.09EGODECtvcBook Pr....

The regression equation is given as,

Answered: The equation used to predict annual…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The equation used to predict annual cauliflower yield (in pounds per acre) is y=24,596+4.423x1−4.772x2, where x1 is the number of acres planted an x2 is the number of acres harvested. Use the multiple regression equation to predict the y-values for the values of the independent variables.
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-1.375 b=26.852 r2=0.395641 r=-0.629 Use this to predict the number of situps a person who watches 14 hours of TV can do (to one decimal place)
The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day) imported by a country, for the last 7 years. Construct and interpret a 98% prediction interval for the amount of oil imported by the country and the amount of oil produced by the country is 5,483 thousand barrels per day. The equation of the regression line is y = -1.194x + 16,234.906
A regression analysis between cost to build a clinic (in dollars) and clinic size (in square foot) resulted in the following equation: y=75+6x. This implies that if the clinic size is 800 square feet, then the cost to build a clinic (in dollars) is?
You run a linear regression to predict BMI (body mass index) from average minutes of physical activity per day. You calculate the slope of the regression to be -.054. Interpret the slope in terms of the independent and dependent variables.
The table shows the number of goals allowed and the total points earned (2 points for a win, and 1 point for an overtime or shootout loss) by 14 ice hockey teams over the course of a season. The equation of the regression line is ŷ= -0.556x+217.766. Use the data to answer the following questions. (a) Find the coefficient of determination, 12, and interpret the result. (b) Find the standard error of the estimate, Se, and interpret the result. 213 213 223 226 259 266 281 202 210 205 226 207 259 239 D Goals Allowed, x Points, y 109 109 102 91 88 80 52 105 107 98 95 85 68 66 (a)² = (Round to three decimal places as needed.) Interpret the coefficient of determination. Select the correct choice below and fill in the answer box to complete your choice. (Round to one decimal place as needed.) OA. About OB. About (b) Se = % of the variation in points earned can be explained by the relationship between number of goals allowed and points earned. The remaining variation is unexplained. % of the…
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (2) and number of sit ups a person can do (y). The results of the regression were: y=ax+b a=-0.666 b=21.511 72=0.543169 r=-0.737 Use this to predict the number of sit ups a person who watches 7 hours of TV can do, and please round your answer to a whole number. Hìnt: Help Question Help: Message instructor Submit Question 围 hp Ce %23 & 3. 4. 6. 8. W e y 61
biologist was recording various temperatures (in degrees Celsius) and predicting the amount of glucose produced by a plant (in milligrams). Suppose the linear equation was the following: ?̂ = 12.7 − 0.223? a) Interpret the slope of the regression line.
The volume (in cubic feet) of a black cherry tree can be modeled by the equation y = - 50.7 + 0.3x, + 5.2x2, where x, is the tree's height (in feet) and x2 is the tree's diameter (in inches). Use the multiple regression equation to predict the y-values for the values of the independent variables. X1 = 70, x, = 8.9 The predicted volume is cubic feet. (Round to one decimal place as needed.)
The equation used to predict annual cauliflower yield (in pounds per acre) is y = 24,121 +4.505x₁ -4.772x₂, where x₁ is the number of acres planted and x2 is the number of acres harvested. Use the multiple regression equation to predict 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.)
The equation used to predict college GPA (range 0-4.0) is y = 0.17 +0.51x, +0.002x,, where x, is high school GPA (range 0-4.0) and x, is college board score (range 200-800). Use the multiple regression equation to predict college GPA for a high school GPA of 3.8 and a college board score of 500. The predicted college GPA for a high school GPA of 3.8 and a college board score of 500 is (Round to the nearest tenth as needed.)
X₁ is the The volume (in cubic feet) of a black cherry tree can be modeled by the equation y = -51.2 +0.4x₁ + 4.8x2, where tree's height (in feet) and x₂ is the tree's diameter (in inches). Use the multiple regression equation to predict the y-values for the values of the independent variables. (a) x₁ = 73, x₂ = 8.8 (b) x₁ = 67, x₂ = 11.5 (c) x₁ = 85, x₂ = 17.6 (d) x₁ = 92, x₂ = 20.8 cubic feet. (a) The predicted volume is (Round to one decimal place as needed.) (b) The predicted volume is cubic feet. (Round to one decimal place as needed.) (c) The predicted volume is cubic feet. (Round to one decimal place as needed.) (d) The predicted volume is cubic feet. (Round to one decimal place as needed.) Next

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