QUESTION 14Problem 4a: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 SummarySourceDF Adj SS Adj MS F-Value P-ValueTermCoef SE Coef T-Value P-ValueR-sq R-sq(adj)Regression 1 234.31 234.315 294.810.000Constant 1.8450.8562.150.0410.891520 92.47%92.16%Error24 19.080.795Act vol 0.7830 0.045617.170.000Total25 253.39a) In a test of B, =0 against its alternative, report the value of the test statistic t: Use two decimalas in your answer

a) Null Hypothesis: H0:β1=0 Alternative Hypothesis: H1:β1≠0

Answered: A forester has a unique ability to…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

Shortleaf Pines. The ability to estimate the volume of a tree based on a simple measurement, such as the diameter of the tree, is important to the lumber industry, ecologists, and conservationists. Data on volume, in cubic feet, and diameter at breast height, in inches, for 70 shortleaf pines was reported in C. Bruce and F. X. Schumacher’s Forest Mensuration (New York: McGraw-Hill, 1935) and analyzed by A. C. Akinson in the article “Transforming Both Sides of a Tree” (The American Statistician, Vol. 48, pp. 307–312). The data are provided on the WeissStats site. a. obtain and interpret the standard error of the estimate. b. obtain a residual plot and a normal probability plot of the residuals. c. decide whether you can reasonably consider Assumptions 1–3 for regression inferences met by the two variables under consideration.
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 following data are given for a biogas digester suitable for the output of six cows. The volume of digester is 7.5 m3 , the volume of gas holder is 4 m³ and the retention time is 26 days . Find the height of gas holder height of gas holder =- cm
A fire insurance company wants to relate the amount of fire damage in major residential fires to the distance between the residence and the nearest fire station. The study was conducted in a large suburb of a major city; a sample of fifteen recent fires in the suburb was selected. The amount of damage, y (£000), and the distance, r (km), between the fire and the nearest fire station are given in the following table. 3.4 1.8 4.6 2.3 3.1 5.5 0.7 3.0 y 26.2 17.8 31.3 23.1 27.5 36.0 2.1 y 19.6 31.3 24.0 17.3 43.2 36.4 26.1 14.1 22.3 2.6 4.3 1.1 6.1 4.8 3.8 (a) Fit a simple linear regression model to these data. Check if the residual plots give any reason to doubt the usual assumptions of the model. (b) Write a short report giving your conclusions. You do not need to upload the output from R. Include a possible interpretation of the intercept and slope parameters.
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…
An ecologist hypothesizes a relationship between wing span of birds and the width of tree branches they use. The ecologist captured male birds, measured their wing span and other characteristics in millimeters, and then marked and released them. During the ensuing winter, the ecologist repeatedly observed the marked birds as they foraged for food on tree branches. He noted the branch diameter on each occasion, and calculated the average branch diameter for each bird in centimeters. The measurement data are below. What can the ecologist conclude with an a of 0.10? wing span branch diameter 79.3 80.1 80.7 81.5 79.5 80.7 81.1 80.5 80.7 1.02 1.04 1.21 1.15 1.21 1.56 1.39 1.31 1.39 a) What is the appropriate statistic? Select- Compute the statistic selected in a): b) Obtain/compute the appropriate values to make a decision about Ho- Critical Value - ; Test Statistic= Decision: -Select- c) Compute the corresponding effect size(s) and indicate magnitude(s). If not appropriate, input and/or…
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 horsepower (Y, in bhp) of a motor car engine was measured at a chosen set of values of running speed (X, in rpm). The data are given below (the first row is the running speed in rpm and the second row is the horsepower in bhp): rpm 1100 1400 1700 2300 2700 3200 3500 4000 4600 5200 5600 6100 Horsepower (bhp) 50.2 64.29 67.83 98.56 131.09 163.65 161.55 198.62 226.03 254.71 283.63 299.81 The mean and sum of squares of the rpm are 3450.0000 rpm and 173900000.0000 rpm 22 respectively; the mean of the horsepower values is 166.6642 bhp and the sum of the products of the two variables is 8506152.0000 rpm bhp. Given Values: a) Slope: 0.052 b) Intercept: -11.694 c) 95% Confidence Interval when the standard error of the estimate of the slope coefficient was found to be 0.001160: (0.0494, 0.0546) please answer the following: Part e)Without extending beyond the existing range of speed values or changing the number of observations, we would expect that increasing the variance of the…
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.)
Solve for the y-intercept and the slope. Form the equation of the regression line that describes the relationship between the two variables. Predict the profit of the fashion boutique business when the store measures 3,800 square feet. Explain the result.

Recommended textbooks for you

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

Elementary Statistics: Picturing the World (7th E…

Statistics

ISBN:

9780134683416

Author:

Ron Larson, Betsy Farber

Publisher:

PEARSON

The Basic Practice of Statistics

Statistics

ISBN:

9781319042578

Author:

David S. Moore, William I. Notz, Michael A. Fligner

Publisher:

W. H. Freeman

Introduction to the Practice of Statistics

Statistics

ISBN:

9781319013387

Author:

David S. Moore, George P. McCabe, Bruce A. Craig

Publisher:

W. H. Freeman

SEE MORE TEXTBOOKS