The volume (in cubic feet) of a black cherry tree can be modeled by the equation y = -50.6+0.4x₁ +4.7x2, where x₁is the tree's height (in feet) and x, is the tree's diameter (in inches). Use the multiple regression equation to predictthe y-values for the values of the independent variables.(a) x₁ = 73, x₂ = 8.6(b) x₁ = 65, x₂ = 10.4(c) x₁ = 83, x₂ = 16.9(d) x₁ = 87, x₂ = 20.3(a) The predicted volume is cubic feet.(Round to one decimal place as needed.)

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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 = 24,121 +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.)
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
The equation used to predict annual cauliflower yield (in pounds per acre) is y =24,231 + 4.417x, - 4.677x,, where x, is the number of acres planted and x, is the number of acres harvested. Use the multiple regression equation to predict the y-values for the values of the independent variables. (a) x, = 36,100, X2 = 36,500 (b) x, = 37,800, X2 = 38,100 (c) X4 = 38,800, X2 = 39,000 (d) x, = 42,100, X2 = 42,200 %3D %3D (a) The predicted yield is pounds per acre. (Round to one decimal place as needed.)
A sports-equipment researcher was interested in the relationship between the speed of a golf club (in feet per second) and the distance a golf ball travels (in yards). Information was collected on several golfers and was used to obtain the regression equation ŷ = 2x - 106, where x represents the club speed and ŷ is the predicted distance. Which statement best describes the meaning of the slope of the regression line? For each increase in distance by 1 yard, the predicted club speed increases by 2 ft/sec. For each increase in distance by 1 yard, the predicted club speed decreases by 106 ft/sec. For each increase in club speed by 1 ft/sec, the predicted distance increases by 2 yards. For each increase in club speed by 1 ft/sec, the predicted distance decreases by 106 yards.
Use the linear regression model yˆ=−24.8x+564.38 to predict the y-value for x=63.
The volume (in cubic feet) of a black cherry tree can be modeled by the equation y=−50.8+0.3x1+5.1x2, where x1 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.
The volume (in cubic feet) of a black cherry tree can be modeled by the equation y=−51.9+0.3x1+4.9x2, where x1 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.
There is a linear relationship between the number of chirps made by the stiped ground cricket and the air temperature. It was determined that the linear regression model is: y = 25.2 + 3.3x where x is the number of chirps per minute and y is the estimated temperature in degrees Fahrenheit. What is the predicted number of chirps made when the temperature is 60 degrees Fahrenheit? Round to the nearest integer. Do not include units.
While collecting data on shoe sizes (y) compared to heights in inches (x) of male students in the class a student found that the shoe sizes ranged from size 7 to size 11 and the heights of the students ranged from 60 to 72 inches. The student ran a linear regression to get the function = 1 -x- 3 13 where y is the shoe size and is the height of the person in inches. What would be the shoe size for a student who was 73 inches tall? Shoe sizes only show up in incriments of 0.5 (ie. 7, 7.5, 8, 8.5, 9, 9.5, ....) so round to the nearest 1/2 shoe size. Show all your work.
A business analyst found a linear relationship between the predicted profit (in thousands of dollars) with the amount of employees hired (think of the units as per person). The resulting regression equation and coefficient of determination were found to be: ŷ = 10 + 4.5x R² = 72% a) Interpret the slope and y-intercept using the guidelines learned in class. b) Find the predicted profit when the you hire 5 employees. c) Suppose that the true profit when 5 employees are hired is $42 thousand dollars. Find the residual. d) What is the correlation coefficient? Round to three decimal places. e) What is the strength of the correlation coefficient?
Using the weights (Ib) and highway fuel consumption amounts (mi/gal) of the 48 cars listed in the accompanying data set, one gets this regression equation: y = 58 9-0.00749x, where x represents weight Complete parts (a) through (d). Click the icon to view the car data. 東 b. What are the specific values of the slope and y-intercept of the regression line? O A. The slope is 58.9 and the y-intercept is 0.007499. B. The slope is -0.00749 and the y-intercept is 58.9. O C. The slope is 58.9 and the y-intercept is -0.00749. O D. The slope is 0.00749 and the y-intercept is 58.9. c. What is the predictor variable? O A. The predictor variable is highway fuel consumption, which is represented by x. B. The predictor variable is weight, which is represented by x. O C. The predictor variable is weight, which is represented by y O D. The predictor variable is highway fuel consumption, which is represented by y. d. Assuming that there is a significant linear correlation between weight and highway fuel…
nd fill in the coefficients for the regression equation: Y= _+ X1+ X2

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