4. A study to assess the capability of subsurface flow wetland systems to removebiochemical oxygen demand (BOD) and various other chemical constituentsresulted in the accompanying data on z = BOD mass loading (kg/ha/d) and y= BOD mass removal (kg/ha/d) ("Subsurface Flow Wetlands-A PerformanceEvaluation." Water Envir. Res., 1995: 244-247).xY11813 16 2710 11 1614235 38 44 10330907531 3026 21n = 10; Σ | n = 450; Σα" = 37653; Σy = 318; Σ y = 17244; Σ =y = 25344Answer the following questions:(a) Plot an appropriate graph for the data.(b) Obtain the best lincar prediction equation.(c) For every additional unit change in BOD mass loading, by how much doesthe BOD mass removal change, on average?(d) Give the value of the statistic that measures the linear association betweenthe BOD mass loading and BOD mass removal. Comment.(e) What percent of variation in the BOD mass removal is explained by thevariation by the BOD mass loading?(f) Predict the BOD mass removal, given that the BOD mass loading is 180(kg/ha/d). Are you bothered or not by this prediction? Explain.(g) What is your overall judgment about the linear fit? You may name twoappropriate criteria that may help you in answering this question.(h) Is there anything in particular that bothers you about the data set?

Answered: Image /qna-images/answer/4a2b51f8-50ee-491e-a667-03453c51f355.jpg

Answered: 4. A study to assess the capability of…

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 decline of salmon fisheries along the Columbia River in Oregon has caused great concern among commercial and recreational fishermen. The paper 'Feeding of Predaceous Fishes on Out-Migrating Juvenile Salmonids in John Day Reservoir, Columbia River' (Trans. Amer. Fisheries Soc. (1991: 405-420) gave the accompanying data on y = maximum size of salmonids consumed by a northern squaw fish (the most abundant salmonid predator) and x = squawfish length, both in mm. Here is the computer software printout of the summary: Coefficients: Estimate Std. Error t value Pr(> |t|) (Intercept) −89.010 16.720 −5.324 0.000 Length 0.704 0.049 14.333 0.000 Using this information, give the equation of the least squares regression line.
3. Fit a least squares quadratic curve to the following data and estimate Y at X = 2.4 fig. 03 2 3. 4. గోలిగౌజి రర్ Y 1.7 1.8 2.3 2.3 A. The required least squares quadratic curve(parabola) and the estimated value of Y at X=2.4? * 大 O Y= 2- 0.5X + 0.2X^2; Y = 1.952 Y= 2-0.6X+ 0.2X^2; Y = 1.712 O Y= 2.1 - 0.5X + 0.2X^2;Y = 2.052 Y= 2- 0.5X + 0.4X^2; Y = 3.104
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
Fluid inclusions are microscopic volumes of fluid that are trapped in rock during rock formation. The article "Fluid Inclusion Study of Metamorphic Gold-Quartz Veins in Northwestern Nevada, U.S.A.: Characteristics of Tectonically Induced Fluid" (S. Cheong, Geosciences Journal, 2002:103-115) describes the geochemical properties of fluid inclusions in several different veins in northwest Nevada. The following table presents data on the maximum salinity (% NaCi by weight) of inclusions in several rock samples from several areas. Salinity Area Humboldt Range Santa Rosa Range 9.2 10.0 11.2 8.8 5.2 6.1 8.3 Ten Mile 7.9 6.7 9.5 7.3 10.4 7.0 Antelope Range Pine Forest Range 6.7 8.4 9.9 10.5 16.7 17.5 15.3 20.0 Can you conclude that the salinity differs among the areas?
6.1-2 1 help
True or False: In a model with an interaction variable, we can drop the interaction term if its pvalue>.05
Balls, Inc. produces two products, Squid Balls (S) and Fish Balls (F), in two departments, the Mixing Department and Deep Frying Department. Production of the two products (combined) during any period cannot exceed 23,700 kilos. Data on the two products follow: Squid Balls (S) Fish Balls (F) Total time available (minutes) Contribution margin per kilo P40 30 TIME REQUIRED (Minutes) Mixing (M) 3.0 1.5 48,000 Which of the following is not a constraint function for this linear programming problem? a. 3S+ 1.5F 48,000 c. S+ F≤ 23,700 b. 2S+ 3.6F ≤ 72,000 d. CM = 40S + 30F Deep Frying (D) 2.0 3.6 72,000
In "Orthogonal Design for Process Optimization and Its Application to Plasma Etching" (Solid State Technology, May 1987), G. Z. Yin and D. W. Jillie describe an experiment to determine the effect of C,F. flow rate on the uniformity of the etch on a silicon wafer used in integrated circuit manufacturing. Three flow rates are used in the experiment, and the resulting uniformity (in percent) for six replicates is shown below. Observations C2F, Flow (SCCM) 2 3 4 125 2.7 4.6 2.6 3.0 3.2 3.8 160 4.9 4.6 5.0 4.2 3.6 4.2 200 4.6 3.4 2.9 3.5 4.1 5.1 Use Fisher's LSD method with a = 0.05 to analyze the means of the three flow rates. Choose the correct answer. O There are significant differences between levels 125 and 160. O There are significant differences between levels 125 and 200. O There are significant differences between levels 160 and 200. O There are significant differences between levels 125 and 160, 160 and 200. O No significant differences.
Interpret the generated results at 5% level of significance.
The article "Effect of Microstructure and Weathering on the Strength Anisotropy of Porous Rhyolite" (Y. Matsukura, K. Hashizume, and C. Oguchi, Engineering Geology, 2002:39- 17) investigates the relationship between the angle betwween cleavage and flow structure and the strength of porous rhyolite. Strengths (in MPa) were measured for a mumber of specimens cut at various angles. The mean and standard deviation of the strengths for each angle are presented in the following table. Angle Mean 0° 22.9 Sample Size Standard Deviation 2.98 12 15° 22.9 1.16 30° 19.7 3.00 45° 14.9 2.99 60° 13.5 2.33 75° 11.9 2.10 90 14.3 3.95 6. Can you conclude that strength varies with the angle?
The decline of salmon fisheries along the Columbia River in Oregon has caused great concern among commercial and recreational fishermen. The paper 'Feeding of Predaceous Fishes on Out-Migrating Juvenile Salmonids in John Day Reservoir, Columbia River' (Trans. Amer. Fisheries Soc. (1991: 405-420) gave the accompanying data on y = maximum size of salmonids consumed by a northern squaw fish (the most abundant salmonid predator) and x = squawfish length, both in mm. Here is the computer software printout of the summary: Coefficients: Estimate Std. Error t value Pr(> |t|) (Intercept) −89.010 16.703 −5.329 0.000 Length 0.705 0.046 15.293 0.000 Using this information, give the equation of the least squares regression line.
The article "Oxidation State and Activities of Chromium Oxides in Cao-SiO,-CrO, Slag System" (Y. Xiao, L. Holappa, and M. Reuter, Metallurgical and Materials Transactions B, 2002:595-603) presents the amount x (in mole percent) and activity coefficient y of CrO,5 for several specimens. The data, extracted from a larger table, are presented in the following table. х У 2.6 10.20 5.03 19.9 8.84 0.8 6.62 5.3 2.89 20.3 2.31 39.4 7.13 5.8 3.40 29.4 5.57 2.2 7.23 5.5 2.12 33.1 1.67 44.2 5.33 13.1 16.70 0.6 9.75 2.2 2.74 16.9 2.58 35.5 1.50 48.0 Compute the least-squares line for predicting y from x. b. Plot the residuals versus the fitted values. Compute the least-squares line for predicting y from 1/x. d. Plot the residuals versus the fitted values. C. Using the better fitting line, find a 95% confidence interval for the mean value of y when x= 5.0.

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