Use technology to find the quadratic regression curve through the given points. (1, 4), (3, 6), (4, 5), (5, 2) y(x) =
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Q: The volume (in cubic feet) of a black cherry tree can be modeled by the equation y = -50.6+0.4x₁…
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Q: The volume (in cubic feet) of a black cherry tree can be modeled by the equation y = - 51.7 +0.4x,…
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- 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.The table shows the numbers of new-vehicle sales (in thousands) in the United States for Company A and Company B for 10 years. The equation of the regression line is y = 0.991x + 1,222.81. Complete parts (a) and (b) below. D New-vehicle sales (Company A), x New-vehicle sales (Company B), y 4,149 3,923 3,566 3,400 3,266 3,076 2,868 2,485 1,952 2,066 4,912 4,871 4,827 4,721 4,672 4,474 4,684 3,822 2,956 2,754 (a) Find the coefficient of determination and interpret the result. 12²=0 (Round to three decimal places as needed.) 1***PLEASE INCLUDE EXCEL OUTPUT WITH YOUR RESPONSE
- The owner of a movie theater company used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x,) and newspaper advertising (x,). The estimated regression equation was ý = 82.3 + 2.29x, + 1.90x2. The computer solution, based on a sample of eight weeks, provided SST = 25.1 and SSR = 23.415. (a) Compute and interpret R? and R 2. (Round your answers to three decimal places.) The proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation is 653 x . Adjusting for the number of independent variables in the model, the proportion of the variability in the dependent variable that can be explained by the estimated multiple regression equation is (b) When television advertising was the only independent variable, R2 = 0.653 and R,2 = 0.595. Do you prefer the multiple regression results? Explain. Multiple regression analysis (is preferred since both R2 and R.2 show an increased v v…An individual wants to determine how much money a boy scout earns from selling popcorn (Y-variable) based on the length of time (in days) that they went out selling (X-variable). Using the following linear regression equation Ŷ = 5 + 20X: a. State the value of the intercept AND the value of the slope (2 points) b. Based on the given regression equation, what can you determine about the direction of the relationship between X and Y (i.e. is it positive or negative)? (2 points) c. If a boy scout sells popcorn for 4 days, how much money is he predicted to earn? (2 points)The table shows the amounts of crude oil (in thousands of barrels per day) produced by a certain country and the amounts of crude oil (in thousands of barrels per day) imported by the same country for seven years. The equation of the regression line is y = - 1.269x + 16,635.60. Complete parts (a) and (b) below. Produced, x Imported, y 5,718 5,612 5,409 5,228 5,128 5,006 O 9,106 9,631 10,000 10,140 10,133 10,059 5,759 9,318 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.)
- What is the linear equation (y = mx + b form) that best approximates the relationship between advertising dollars spent(x) and sales revenue(y) based on the above 8 months of data? (round to 2 decimals for the slope and the y intercept)The volume (in cubic feet) of a black cherry tree can be modeled by the equation y = - 50.8 + 0.3x, +4.5x,, where x, is the tree's height (in feet) and x, is the tree's diameter (in inches). Use the multiple regression equation to predict the y-values for the values of the independent variables. x, = 70, x, = 8.6 The predicted volume is cubic feet. (Round to one decimal place as needed.)An interaction term in a multiple regression model may be used when the coefficient of determination is small. there is a curvilinear relationship between the dependent and independent variables. neither one of 2 independent variables contribute significantly to the regression model. the relationship between X1 and Ychanges for differing values of X2.
- 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 y= - 0.558x + 216.186. Use the data to answer the following questions. (a) Find the coefficient of determination, r, and interpret the result. (b) Find the standard error of the estimate, s,, and interpret the result. Goals Allowed, x Points, y 218 212 216 220 257 266 274 200 211 206 216 204 264 244 O 111 106 99 90 86 83 45 105 100 101 94 83 67 68 (a) ? =O (Round to three decimal places as needed.)An oceanographer measured the length, in meters, of a deepwater wave and its speed, in meters per second. The results are shown in the following table. (a) Find the equation of a linear regression line for the data where wave length is the independent variable, x, and speed is the dependent variable. (Round your numerical values to two decimal places.) y= ? (b) Using the equation from part (a), estimate the speed (in meters per second) of a wave that is 200 m long. (Round your answer to one decimal place.) ? m/sA weight-loss clinic would like to have an equation to estimate the number of hours a person should exercise per week (Y), given their age (x1) and the number of calories they eat per day (x2). After collecting data, the clinic is able to perform linear regression and discovers that the correct coefficient for the "age" variable is 13, the correct coefficient for the "calories per day" variable is 23, and the "constant" is -16. Given this information, what would the prediction equation look like to allow the clinic to predict the number of hours of exercise given age and calories? Y =-16x1 + 23x2 + 13 OY= 23 - 16x1 + 13x2 OY= -16 + 13x1+ 23x2 OY = -16 +23x1 + 13x2
