In "Orthogonal Design for Process Optimization and Its Application to Plasma Etching" (Solid State Technology, May 1987), G. Z. Yin andD. 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 inintegrated circuit manufacturing. Three flow rates are used in the experiment, and the resulting uniformity (in percent) for sixreplicates is shown below.ObservationsC2F, Flow(SCCM)2341252.7 4.6 2.6 3.0 3.2 3.81604.9 4.6 5.0 4.2 3.6 4.22004.6 3.4 2.9 3.5 4.1 5.1Use 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.

Formula for LSD: LSD=tα2,dfMSW1n1+1n2 Excel Procedure: Enter the data for flows of 125, 160 and 200…

Answered: In "Orthogonal Design for Process…

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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15.3 #6 The authors of the article "Age, Spacing and Growth Rate of Tamarix as an Indication of Lake Boundary Fluctuations at Sebkhet Kelbia, Tunisia"† used a simple linear regression model to describe the relationship between y = vigor (average width in centimeters of the last two annual rings) and x = stem density (stems/m2). The estimated model was based on the following data. Also given are the standardized residuals. x 4 5 6 9 14 15 15 19 21 22 y 0.75 1.20 0.55 0.60 0.65 0.55 0.00 0.35 0.45 0.40 Std resid −0.28 1.92 −0.90 −0.28 0.54 0.24 −2.05 −0.12 0.60 0.52 (a) What assumptions are required for the simple linear regression model to be appropriate? (Select all that apply.) A) The random errors associated with different observations are dependent on one another. B) The distribution of e at any given x is not normal. C) The distribution of e at any given x is normal. D) The distribution of e at any particular x value has mean value 0. E) The random…
A civil engineer is interested in several designs for a drainage canal used to divert floodwaters from around a city. The drainage times of a reservoir attached to each of five different channel designs obtained from a series of experiments using similar initial flow conditions are given in the following table. Channel Type Drainage time (min) 41.4 43.4 50.0 41.2 37.7 37.3 49.3 33.7 52.1 32.6 27.3 34.8 32.3 з 22.5 24.8 37.1 29.9 44.9 47.2 48.5 a Can you conclude that there is a difference in the mean drainage times for the different channel designs? b. Which pairs of designs, if any, can you conclude to differ in their mean drainage times?
The data in worksheet 2.2 have spec limits USL/LSL = 40 ± 1. Perform the process capability analysis (Cp, Cpk, Pp, and Ppk) and diagnose the process, i.e. what problems are present? What steps should be taken to improve the process and how effective will they be?
Please help me with this question.
Question 6: Simulate a data set with 150 observations y; = 40+ 6x + 2x² + 3x³ +€, where €; follows independent normal distribution N(0, 1). a) Perform polynomial regression on your simulated data set and using x, I(x²), 1(x³) as the predictors. Compare the estimated coefficients with the true model and report the R-square. b) Formulate the design matrix of this regression and write down the first two rows of the design matrix based on your data set. c) Perform polynomial regression on your simulated data set and using z, I(x²), 1 (x³), 1 (x¹) as the predictors. Compare the estimated coefficients with the true model.
An article in the ACI Materials Journal (Vol. 84, 1987, pp. 213-216) describes several experiments investigating the rodding of concrete to remove trapped air. A 3-inch x 6-inch cylinder was used, and the number of times this rod was used is the design variable. The resulting compressive strength of the concrete specimen is the response. The data are shown in the following table. Compressive Strength (psi) Observations Rodding Level 10 15 20 25 1530 1530 1440 1610 1650 1500 1560 1730 1530 1500 1490 1510 (a) Is there any difference in compressive strength due to the rodding level? Use a = 0.05. Calculate to 2 decimal places for Is there statistical evidence to say that rodding level affects compressive strength? (b) Find to 2 decimal places the P-value for the F-statistic computed in part (a). P-value= (c) Analyze the following residual plots to determine model adequacy, Does the assumption of normality seem reasonable? Does there appear to be an outlier in the data? Does the assumption…
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?
question 2
A number of studies have shown lichens (certain plants composed of an alga and a fungus) to be excellent bio-indicators of air pollution. An article gives the following data (n = 13) on x = NO3- wet deposition (g N/m²) and y = lichen (% dry weight): x 0.05 0.10 0.11 0.12 0.31 0.37 0.42 0.58 0.68 0.68 0.73 0.85 0.92 y 0.53 0.58 0.45 0.54 0.57 0.53 1.03 0.89 0.90 1.02 0.91 1.00 1.66 Predictor Constant no3 depo Estimate 0.39329 0.9286 0.1767 S = 0.1866 R-sq = 71.5% Standard Error 0.09566 t Stat 4.11 5.26 p-value 0.002 0.000 R-sq (adj) = 68.9% (a) What are the least square estimates of B and ẞ₁? (Round your answers to three decimal places.) bo = = (b) What is the margin of error for a 95% CI for ẞ₁? (Round your answer to four decimal places.) Margin of Error = (c) Predict lichen N for an NO3 - deposition value of 0.7. (Round your answer to three decimal places.) % dry weight (d) What is the estimate of σ? (Round your answer to four decimal places.) S = % dry weight
4

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