QUESTION 17Problem 4d:A forester has a unique ability to estimate the volume (in cubic feet) of trees prior to a timber sale. The timber company wants him to train otheremployees in his technique of estimation. The forrester's assistant estimates the cubic-foot volume of each tree. After the tree has been chopped down,the forresters obtains the actual cubic-foot volume for a total of 26 trees.A regression model was fitted to the data, with the Estimated Volume y fitted against the Actual Volume x of each tree. The results of the regression areshown below:Analysis of VarianceCoefficientsModel SummaryDF Adj SS Adj MS F-Value P-Value1 234.31 234.315- 294.81SourceTermCoef SE Coef T-Value P-ValueR-sq R-sq(adj)Regression0.000Constant 1.8450.8562.150.0410.891520 92.47%92.16%Error24 19.080.795Act vol 0.7830 0.045617.170.000Total25 253.39d) Provide a point estimate of the standard deviation of the error variable g in the linear model v= Bn + B, X + ɛ Use 3 decimals in your answer.

The linear regression model is in the form of y = βo + β1x + ε In the above…

Answered: QUESTION 17 Problem 4d: A forester has…

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 accompanying data are the length (in centimeters) and girths (in centimeters) of 12 harbor seals. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a)x= 140 cm (b)x= 172 cm (c) x = 164 cm (d) x = 158 cm Click the icon to view the table of lengths and girths. The equation of the regression line is y=x+7 (Round to two decimal places as needed.). 4
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Interpolate the Sales for 1990 from the following data. Years : 1988 1989 1990 1991 1992 Sales : 250 290 ? 390 425 Use Parabolic curve method.
Question 8 please
The accompanying data are the length (in centimeters) and girths (in centimeters) of 12 harbor seals. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x= 140 cm E Click the icon to view the table of lengths and girths. (b) x= 172 cm (c) x= 164 cm (d) x= 158 cm - X The equation of the regression line is y =x+ (Round to two decimal places as needed.) Lengths and Girth Construct a scatter plot of the data and draw the regression line. Plot length on the horizontal axis and girth on the vertical axis. Choose the correct graph below. O A. Length, x Girth, y O B. Oc. 137 106 168 130 153 117 144 105 158 125 159 118 180 120 125 102 137 104 (a) Predict the girth for a length of 140 cm, if it is meaningful. Select the correct choice below and, if…
The U.S. online grocery market is estimating sales worth approximately $29.7 billion by 2021. One of the biggest situational factors that influence the amount spent by a customer is the distance that that customer lives from its closest grocery store. Using the OLS method, the simple regression equation was estimated as: y = 40 + 3.5x. Find 1) the predicted amount a customer spends if they live 10 miles from the closest grocery store, as well as 2) the error amount. Note: the observed amount spent by a customer that lives 10 miles away is $85.50. a) $75.00, $10.50 Ob) $75.00, -$10.50 c) $73.00, $12.50 d) $73.00, -$12.50
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…
Hazel has four very short children and wants to predict how tall the kids will be in the future, as they get older she measures their height and finds: Rufus, age 3, 46 cm in height Angus, age 4, 52 cm in height matilda, age 6, 63 cm in height Lao age 8, 85 cm in height Round to the nearest integers, what is the regression equation computed from the data
The following questions are based on the graph below: If the mean of weight is 69.151 kg and the standard deviation is 13.359 kg and the mean of the height is 171.16 cm and the standard deviation is 9.41 cm. The correlation coeffient is 0.716. a) Find the linear regression equation to predict the weight b) Explain the meaning of the slope c) Find the coefficient of determination d) Explain the meaning of the coefficient of determination.
We want to predict the selling price of a house in Newburg Park, Florida, based on the distance the house lies from the beach. Suppose that we're given the data in the table below. These data detail the distance from the beach (x, in miles) and the selling price (y, in thousands of dollars) for each of a sample of sixteen homes sold in Newburg Park in the past year. The data are plotted in the scatter plot in Figure 1. Distance from the beach, x (in miles) 5.1 6.2 9.5 10.3 10.7 5.3 12.6 13.0 19.4 8.2 5.2 3.8 9.0 11.7 11.5 8.3 Send data to calculator V Selling price, y (in thousands of dollars) 263.5 274.6 238.6 223.7 267.1 306.2 202.5 267.7 217.3 224.7 241.0 312.0 284.6 210.9 185.6 294.2 Send data to Excel thousands of dollars) Selling price 350+ 300+ Figure 1 250 200 150. 0 Distance from the beach (in miles) Español F00 ? D 1 As M
xx=02

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