4 Chemical Oxygen Demand (COD) is a necessary water fine parameter due to the factsimilar to BOD, it affords an index to examine the effect discharged wastewater willhave on the receiving environment. Table 4 shows the means for the removalreduction of COD in wastewater by three different treatment methods. Test thehypothesis that the reduction percentage is no different for each treatment method. Usethe 5% level of significance. Table '4: The means for the removal reduction of COD in wastewater by three differenttreatment methods (in percentage)Treatment 1Treatment 2Treatment 340506050607040709080608060809090

Introduction: Denote μ1, μ2, μ3 as the true mean reduction percentage of COD in wastewater, using…

Answered: Chemical Oxygen Demand (COD) is a…

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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Use ”margin.table” to get the Titanic marginal table for factors 1 (class of accomodations) and 4 (survival). Apply the chi-square test to see if class and survival are dependent. Do it both by hand and with ”chisq.test” in R. Attached is the data output from R-studio. Please apply the chi-aquare test on that by hand method ASAP needed. Thanks.
I want to summarize what is the most and least resistant to salinity?
TRUE OR FALSE. WLS is the lone effective remedial measure of heterosdasticity where values with larger dispersions are given larger weights.
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.
2. To investigate the effect of pH and catalyst concentration on product viscosity (sSt). Two levels of pH were used 5.6 and 5.9 and two catalyst concentration 2.5 and 2.7. Four products were tested with each combination of pH and catalyst. a. Use the estimate table below to test for main effects and interaction using a = 0.05. What are your conclusions? Predictor Constant Coefficient SDCoeff 191.563 165.49 pH 2.937 1.158 2.52 Catalyst -0.062 1.158 -0.05 pH*Catalyst 5.812 1.158 5.02 b. What is the value for the overall average viscosity? c. Write the regression model for this experiment. d. Below the interaction plot for the experiment. Discuss the information provided by the plot. To maximize viscosity what would be the recommended setting? Interaction Plot for Viscosity Data Mears 200 195 190- 185 Catalyst Concentration Mean Product Viscosity (cSt)
9.48) Acid gases must be removed from other refinery gases in chemical production facilities in order to minimize corrosion of the plants. Two methods for removing acid gases produced the corrosion rates (in mm/yr) are listed below in experimental tests: Method A: 0.3, 0.7, 0.5, 0.8, 0.9, 0.7, 0.8 Method B: 0.7, 0.8, 0.7, 0.6, 2.1, 0.6, 1.4, 2.3 Estimate the difference in mean corrosion rates for the two methods, using a confidence coefficient of 0.90. What assumptions must you make for your answer to be valid?
2. A new device was designed to measure the glycemic index in blood for diagnostic purposes of patients with diabetes. The first rounds of testing were performed on healthy volunteer subjects. Device 2 was compared with the measurements from the reference instrument (Device 1), the data obtained is synthesized in the table below. Perform the appropriate analysis for validate the measurements delivered by the new device. Dispositivo 1 Dispositivo 2 [mg/dl] [mg/d] Sujeto 1 Sujeto 2 Sujeto 3 101 102 91 100 102 109 Sujeto 4 67 86 Sujeto 5 Sujeto 6 Sujeto 7 Sujeto 8 Sujeto 9 Sujeto 10 Sujeto 11 Sujeto 12 Sujeto 13 87 95 99 102 91 100 85 93 110 113 91 100 87 96 91 99 102 120 Sujeto 14 Sujeto 15 Sujeto 16 Sujeto 17 Sujeto 18 Sujeto 19 Sujeto 20 Sujeto 21 Sujeto 22 91 99 86 90 88 99 100 116 89 100 94 98 79 94 92 112 100 116
Arsenic is a chemical element that occurs in many minerals, usually in conjunction with sulfur and metals, and also as a pure elemental crystal. The main use of metallic arsenic is for strengthening alloys of copper and lead. Unfortunately, arsenic occurs in some ground water. In large quantities it is toxic for multicellular life. A mean arsenic level of 8 particles per billion (ppb) is considered safe for agricultural use. A well in Texas is used to water cotton crops. This well is tested regularly for arsenic. A random sample 37 tests gave a sample mean of 7.2 ppb arsenic with standard deviation of 1.9 ppb. Assume that arsenic levels are normally distributed. We are to use the sample data and test if mean arsenic level in the well in question is less than 8 ppb. a. Test statistic isb. The ? − value of the test isc. At the significance level calculated in part c), we conclude that mean arsenic level in thewell is
Is there any significant difference in yield between the two varieties shown below? Show calculations and explain your condusion.
In the process of treating fresh water into mineral water in the production section, the pH value is an important component to monitor. In September 2023, after the annual overhaul, data was collected for 20 days, with 4 times each day. The data for pH value acquisition is detailed in the table next to this. Create a Control Chart that is appropriate for the type of data and the number of samples
5.Data were collected from 175 pharmaceutical companies. Monthly profit (in 10 M$) was regressed on production cost, number of workers, and the location of the company (0: rural, 1: urban). The analysis results are given below. Regress profit location cost workers Source | SS df MS Number of obs = 175 F( 3, 171) 323 Model | 14142.4781 Residual | 2495.7314 11 3 4714.15937 Prob > F 0.0000 R-squared Adj R-squared 14.5949206 0.8503 0.8489 Total | 16638.2095 174 95.6218937 Root MSE 3.3422 Profit| Сof. Std. Err. P>|t| [95% Conf. Interval] Location | -2.326 Cost | -2.753 Workers .07714 _cons 52.701 .7901811 -4.78 0.000 -1.7033 -3.084 .6977087 6.42 0.000 -1.7549 -4.1916 .0086406 3.78 0.000 .04476 .110660 2.923818 15.43 0.000 48.6362 56.7942 Write a short report based on the above results.
Given the “data” determined by y = x^3 + (x-1)^2 with x = 0.1, 1.2, 2.3, and 2.9, calculate SSTO, SSR, and R^2. Then recalculate these using x = 0.3, 1, 2.45, and 2.8. Does where you collect your data (i.e., which values of x) appear to impact your interpretation of how good the linear model fits?.

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