The depth of wetting of a soil is the depth to which water content will increase owing toextemal factors. The article "Discussion of Method for Evaluation of Depth of Wetting inResidential Areas" (J. Nelson, K. Chao, and D. Overton, Journal of Geotechnical andGeoenvironmental Engineering, 2011:293-296) discusses the relationship between depth ofwetting beneath a structure and the age of the structure. The article presents measurementsof depth of wetting, in meters, and the ages, in years, of 21 houses, as shown in thefollowing table.AgeDepth7.644.66.19.134.37.35.210.415.55.810.745.56.110.710.44.67.06.11416.8109.18.8Compute the least-squares line for predicting depth of wetting (y) from age (x).b. Identify a point with an unusually large x-value. Compute the least-squares line thatresults from deletion of this point.Identify another point which can be classified as an outlier. Compute the least-squaresline that results from deletion of the outlier, replacing the point with the unusuallylarge x-value.Which of these two points is more influential? Explain.a.C.d.

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Answered: The depth of wetting of a soil is the…

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter4: Eigenvalues And Eigenvectors

Section4.6: Applications And The Perron-frobenius Theorem

Problem 22EQ

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Please use the accompanying Excel data set or accompanying Text file data set when completing the following exercise. An article in Wood Science and Technology, "Creep in Chipboard, Part 3: Initial Assessment of the Influence of Moisture Content and Level of Stressing on Rate of Creep and Time to Failure" (1981, Vol. 15, pp. 125-144) studied the deflection (mm) of particleboard from stress levels of relative humidity. Assume that the two variables are related according to the simple linear regression model. The data are shown below x = Stress level (%) 54 54 61 61 68 68 75 75 75 y = Deflection (mm) 16.473 18.693 14.305 15.121 13.505 11.64 11.168 12.534 11.224 a. Calculate the least square estimates of the intercept (a) and slope (b). What is the estimate of o (c)? b. Find the estimate of the mean deflection if the stress level can be limited to 61% (d). c. Estimate the change in the mean deflection associated with a 7% increment in stress level (e). (a) i (Round your answer to 2…
Please use the accompanying Excel data set or accompanying Text file data set when completing the following exercise. An article in Wood Science and Technology, "Creep in Chipboard, Part 3: Initial Assessment of the Influence of Moisture Content and Level of Stressing on Rate of Creep and Time to Failure" (1981, Vol. 15, pp. 125-144) studied the deflection (mm) of particleboard from stress levels of relative humidity. Assume that the two variables are related according to the simple linear regression model. The data are shown below x = Stress level (%) 54 54 61 61 68 68 75 75 75 y = Deflection (mm) 16.473 18.693 14.305 15.121 13.505 11.64 11.168 12.534 11.224 a. Calculate the least square estimates of the intercept (a) and slope (b). What is the estimate of o² (c)? b. Find the estimate of the mean deflection if the stress level can be limited to 66% (d). c. Estimate the change in the mean deflection associated with a 8% increment in stress level (e). (a) i (Round your answer to 2…
Part b)| List five situations in which numerical analyses of seepage would be especially useful.
What methods could an environment geographer use to investigate the relationship between acidity level and distance from a pollution source?
a) Do these data provide good evidence that increasing the stirring rate causes the yield to increase, within the range of the data? Or might the result be due to confounding? Explain.
Recently there has been increased use of stainless steel claddings in industrial settings. Claddings are used to finish the exterior walls of a building and help weatherproof the structure. To ensure the quality of claddings, it is essential to know how welding parameters impact the cladding process. The authors of “Mathematical Modeling of Weld Bead Geometry, Quality, and Productivity for Stainless Steel Claddings Deposited by FCAW” (J. Mater. Engr. Perform., 2012: 1862–1872) in vestigated how y 5 deposition rate was influenced by x1 = feed rate (Wf , in m/min) and x2 = welding speed (S, in cm/min). The following 22 observations correspond to the experiment condition where applied voltage was less than 30v: y: 2.718 3.881 2.773 3.924 2.740 3.870 x1 : 17.0 10.0 7.0 10.0 7.0 10.0 x 2 : 30 30 50 50 30 30 y: 2.847 3.901 2.204 4.454 3.324 3.319 x1 : 7.0 10.0 5.5 11.5 8.5 8.5 x2 : 50 50 40 40 40 20 The whole data and Question parts are attached
a )Do these data provide good evidence that increasing the temperature causes the yield to increase, within the range of the data? Or might the result be due to confounding? Explain.
The article "Polyhedral Distortions in Tourmaline" (A. Eril, J. Hughes, et al., The Canadian Mineralogist, 2002 153-162) presents a model for calculating bond-length distortion in vanadium-bearing tourmaline. To check the accuracy of the model, several calculated values (x) were compared with directly observed values (y) The results (read from a graph) are presented in the following table. Observed Value Calculated Value 0.33 0.36 0.36 0.36 0.54 0.58 0.56 0.66 0.64 0.64 0.66 0.67 0.74 0.58 0.74 0.78 0.79 0.86 0.97 0.97 1.11 1.03 110 1.06 1.13 1.08 114 117 Assume that the observed value y is an unbiased measurement of the true value. Show that if the calculated value x is accurate (ie., equal to the true value), then y = x+ , where e is measurement error. a. b. Compute the least-squares line y= Show that if the calculated value is accurate, then the true coefficients are , = Oand e, Â, + Â,x- C. =1. d. Test the null hypotheses e,-0 and e, = 1. Is it plausible that the calculated value…
cONCLUSION: Leaf Area Index (LAI) was found to be independent on soil nitrogen content
The article "Characteristics and Trends of River Discharge into Hudson, James, and Ungava Bays, 1964-2000" (S. Dery, M. Stieglitz, et al., Journal of Climate, 2005:2540-2557) presents measurements of discharge rate x (in kmlyr) andpeakflow y (in m/s) for 42 rivers that drain into the Hudson, James, and Ungava Bays. The data are shown in the following table: Discharge Peak Flow 94.24 4110.3 66.57 4961.7 59.79 10275.5 48.52 6616.9 40.00 7459.5 32.30 2784.4 31.20 3266.7 30.69 4368.7 26.65 1328.5 22.75 4437.6 21.20 1983.0 20.57 1320.1 19.77 1735.7 18.62 1944.1 17.96 3420.2 17.84 2655.3 16.06 3470.3 1561.6 14.69 11.63 869.8 11.19 936.8 11.08 1315.7 10.92 1727.1 9.94 768.1 7.86 483.3
The toco toucan, the largest member of the toucan family, possesses the largest beak relative to body size of all birds. This exaggerated feature has received various interpretations, such as being a refined adaptation for feeding. However, the large surface area may also be an important mechanism for radiating heat (and hence cooling the bird) as outdoor temperature increases. Here are data for beak heat loss, as a percent of total body heat loss from all sources, at various temperatures in degrees Celsius. [Note: The numerical values in this problem have been modified for testing purposes.] Temperature (oC)(oC) 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Percent heat loss from beak 33 33 34 31 37 46 54 49 41 50 44 56 55 61 64 59 The equation of the least-squares regression line for predicting beak heat loss, as a percent of total body heat loss from all sources, from temperature is: (Use decimal notation. Enter the values of the intercept and slope rounded to two decimal…
The toco toucan, the largest member of the toucan family, possesses the largest beak relative to body size of all birds. This exaggerated feature has received various interpretations, such as being a refined adaptation for feeding. However, the large surface area may also be an important mechanism for radiating heat (and hence cooling the bird) as outdoor temperature increases. Here are data for beak heat loss, as a percent of total body heat loss from all sources, at various temperatures in degrees Celsius. [Note: The numerical values in this problem have been modified for testing purposes.] Temperature (oC)(oC) 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Percent heat loss from beak 33 33 33 31 37 44 56 52 45 54 46 55 59 59 61 63 The equation of the least-squares regression line for predicting beak heat loss, as a percent of total body heat loss from all sources, from temperature is: (Use decimal notation. Enter the values of the intercept and slope rounded to two…

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