The vulnerability of inshore environments to contamination due to urban and industrial expansion in Mombasa is discussed in the paper “Metals, Petroleum Hydrocarbons and Organo- chlorines in Inshore Sediments and Waters on Mombasa, Kenya” [Marine Pollution Bulletin (1997) 34:570–577]. A geochemical and oceanographic survey of the inshore waters of Mombasa, Kenya, was undertaken during the period from September 1995 to January 1996. In the survey, suspended particulate matter and sediment were collected from 48 stations within Mombasa’s estuarine creeks. The concentrations of major oxides and 13 trace elements were determined for a varying number of cores at each of the stations. In particular, the lead concentrations in sus-pended particulate matter (mg kg21 dry weight) were determined at 37 stations. The researchers were interested in determining whether the average lead concentration was greater than 30 mg kg21 dry weight. The data are given in the following table along with summary statistics and a normal
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- 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 attachedarrow_forwardFluid 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?arrow_forwardAn article contained the following observations on degree of polymerization for paper specimens for which viscosity times concentration fell in a certain middle range: 415 420 422 423 426 429 432 435 436 439 446 447 448 452 459 463 464 (a) Construct a boxplot of the data. 420 430 440 450 460 420 430 440 450 460 420 430 440 450 460 420 430 440 450 460 Comment on any interesting features. (Select all that apply.) There are no outliers. There is little or no skew. There is one outlien The data is strongly skewed. The data appears to be centered near 439. The data appears to be centered near 429. (b) Is it plausible that the given sample observations were selected from a normal distribution? O Yes ○ No (c) Calculate a two-sided 95% confidence interval for true average degree of polymerization. (Round your answers to two decimal places.) Does the interval suggest that 445 is a plausible value for true average degree of polymerization? O Yes ○ No Does the interval suggest that 451 is a…arrow_forward
- A) Compute the corresponding effect size(s) and indicate magnitude(s). d= / Magnitude = r2 = / Magnitude = B) Compute the appropriate test statistic(s) to make a decision about H0. critical value = test statistic= d= / Magnitude = r2 = / Magnitude = C) Compute the appropriate test statistic(s) to make a decision about H0 critical value = test statistic= d= / Magnitude = r2 = / Magnitude =arrow_forwardThe vulnerability of inshore environments to contamination due to urban and industrial expansion in Mombasa is discussed in the paper €œMetals, Petroleum Hydrocarbons and Organo-chlorines in Inshore Sediments and Waters on Mombasa, Kenya€ [Marine Pollution Bulletin (1997) 34: 570€“ 577]. A geochemical and oceanographic survey of the inshore waters of Mombasa, Kenya, was undertaken during the period from September 1995 to January 1996. In the survey, suspended particulate matter and sediment were collected from 48 stations within Mombasa€™s estuarine creeks. The concentrations of major oxides and 13 trace elements were determined for a varying number of cores at each of the stations. In particular, the lead concentrations in suspended particulate matter (mg kg-1 dry weight) were determined at 37 stations. The researchers were interested in determining whether the average lead concentration was greater than 30 mg kg-1 dry weight. The data are given in the following table along with…arrow_forwardThe 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?arrow_forward
- 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.arrow_forwardAn article contained the following observations on degree of polymerization for paper specimens for which viscosity times concentration fell in a certain middle range: 415 420 421 422 426 427 432 434 437 438 446 447 450 452 457 463 464 (a) Construct a boxplot of the data. 420 430 440 450 460 420 430 440 450 420 430 440 450 460 420 430 440 450 460 Comment on any interesting features. (Select all that apply.) There is one outlier. n The data is strongly skewed. n The data appears to be centered near 428. n There are no outliers. n The data appears to be centered near 438. n There is little or no skew. (b) Is it plausible that the given sample observations were selected from a normal distribution? Yes o No (c) Calculate a two-sided 95% confidence interval for true average degree of polymerization. (Round your answers to two decimal places.) Does the interval suggest that 440 is a plausible value for true average degree of polymerization? o Yes o No Does the interval suggest that 456 is a…arrow_forward
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