QUESTION 15Problem 4b: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:CoefficientsAnalysis of VarianceModel SummaryDF Adj SS Adj MS F-Value P-Value1 234.31 234315 294.81SourceTermCoef SE Coef T-Value P-ValueR-sq R-sq(adj)92.16%Regression0.000Constant 1.8450.8562.150.0410.891520 92.47%Error24 19.080.795Act vol 0.7830 0.045617.170.000Total25 253.39b) If the assistant is producing an accurate estimate of the volume, it is reasonable to expect that the slope 8, = 1. In a test of B =1 against its%3Dalternative, report the value of the test statisticUse two decimalas in your answertob

From the given information, The coefficient of the variable 'Act_vol' is 0.7830 and the…

Answered: Problem 4b: A forester has a unique…

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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Wolf packs tend to be large extended family groups that have a well-defined hunting territory. Wolves not in the pack are driven out of the territory or killed. In ecologically similar regions, is the size of an extended wolf pack related to size of hunting region? Using radio collars on wolves, the size of the hunting region can be estimated for a given pack of wolves. Let x represent the number of wolves in an extended pack and y represent the size of the hunting region in km2/1000. The following data are representative of one of the national parks. x wolves 29 37 22 61 94 y km2/1000 7.35 12.18 8.15 15.39 16.81 (a) Verify that Σx = 243, Σy = 59.88, Σx2 = 15,251, Σy2 = 788.2256, Σxy = 3362.04, and r ≈ 0.9135. Σx Σy Σx2 Σy2 Σxy r (b) Use a 1% level of significance to test the claim ρ > 0. (Use 2 decimal places.) t critical t (c) Verify that Se ≈ 1.9804, a ≈ 5.5942, and b ≈ 0.13131. Se a b
The local coffee shop keeps track of how much coffee they sell versus the temperature on that day, here are their figures: Sales in Php 1651 1757 1437 1525 1349 1231 Temp in Celsius 21.6 22.6 25 27.3 29.8 30.1 Suppose you want to create a regression equation that will predict the total sales in Php using the temperature of the day in Celcius, what is the total sales for the day in Php if the temperature is 31.5? Round your answers to the nearest hundredths.
QUESTION 18 Problem 4e: 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 other employees 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 are shown below: Analysis of Variance Coefficients Model Summary DF Adj SS Adj MS F-Value P-Value 1 234.31 234315 294.81 Source Term Coef SE Coef T-Value P-Value 0.000 R-sq R-sq(adj) 92.16% Regression Constant 1.845 0.856 2.15 0.041 0.891520 92.47% Error 24 19.08 0.795 Act vol 0.7830 0.0456 17.17 0.000 Total 25 253.39 e) A prediction of y for x-15 was performed based on the fitted regression, with the following results: Settings Prediction…
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
In a random sample of males, it was found that 27 write with their left hands and 210 do not. In a random sample of females, it was found that 55 write with their left hands and 454 do not. Use a 0.05 significance level to test the claim that the rate of left-handedness among males is less than that among females. Complete parts (a) through (c) below. Question content area bottom Part 1 a. Test the claim using a hypothesis test. Consider the first sample to be the sample of males and the second sample to be the sample of females. What are the null and alternative hypotheses for the hypothesis test? A. H0: p1=p2 H1: p1>p2 B. H0: p1≥p2 H1: p1≠p2 C. H0: p1≠p2 H1: p1=p2 D. H0: p1=p2 H1: p1≠p2 E. H0: p1=p2 H1: p1<p2 F. H0: p1≤p2 H1: p1≠p2 Part 2 Identify the test statistic. z=enter your response here (Round to two decimal places as needed.) Part 3 Identify the P-value.…
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 City of Bellmore’s police chief believes that maintenance costs on high-mileage police vehicles are much higher than those costs for low-mileage vehicles. If high-mileage vehicles are costing too much, it may be more economical to purchase more vehicles. An analyst in the department regresses yearly maintenance costs (Y) for a sample of 200 police vehicles on each vehicle’s total mileage for the year (X). The regression equation finds: Y = $50 + .030X with a r2 of .90 What is the IV? What is the DV? If the mileage increases by one mile, what is the predicted increase in maintenance costs? If a vehicle’s mileage for the year is 50,000, what is its predicted maintenance costs? What does an r2 of .90 tell us? Is this a strong or weak correlation? How can you tell?
A math professor selects 8 students at random from her calculus class and asks them to record their study times. After two weeks, she gives an exam. the number of hours, x, of study time and the test score, y, yield the following sample data summary: Ex = 117 Ey = 660 8 %3| n 3= Ea2 = 1869 54638 9519 The professor is a bit surprised. a) Find the equation of the regression line. b) Use the regression line to predict the score of a student who studies for 20 hours over the two weeks.
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 Length, x Girth, y138 106168 130153 116144 105159 126158 119124 103137 103154 121148 111147 106145 110 The equation of the regression line is y=____x + ___
The table lists the average monthly cost to workers for family health insurance for various years. Year, x Average Monthly Cost to Workers for Family Health Insurance $298 a) Use a graphing calculator to fit a regression line to the data. b) Predict the average monthly cost to workers for family health insurance in 2020, and compare the value with $493.3, which is obtained using the points (1,340) and (4,386). c) Find the correlation coefficient for the regression line, and determine whether the line fits the data closely. 2009, 0 2010, 1 2011, 2 340 348 2012, 3 367 2013, 4 2014, 5 386 406 a) The linear equation of the regression line that best models the data is y =x+. (Round to the nearest hundredth as needed.) b) The average monthly cost to workers for family health insurance in 2020 is predicted to be $ (Round to the nearest cent as needed.) Compare the above obtained value with $493.3 This value is $ $493.3 c) The correlation coefficient is (Round to the nearest thousandth as…
Define both x and y in all problems. x is the cause, and y is the effect. This is the most important step when doing linear regression, otherwise, all the remanding parts will be wrong.

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