There are three controllable factors A (humidity), B (pressure) and c (temperature) in a Taguchiparameter design. The goal is to minimize the impurity of a chemistry product. the values of themean response and SN ratio has been calculated from the observation and are displayed in thetable belowOuter arrayRunASN4.3.22.4.3.6.7.6.8.3.9.Use Taguchi Empirical optimization approach to identify the best design66.4.4)2)22.2.3.2.22.2]3)2.4.

The number factors is k=3Given the values corresponding to the mean response (y¯) and Signial to…

Answered: There are three controllable factors 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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Heights (cm) and weights (kg) are measured for 100 randomly selected adult males, and range from heights of 130 to 190 cm and weights of 41 to 150 kg. Let the predictor variable x be the first variable given. The 100 paired measurements yield x = 167.53 cm, y 81.32 kg, r 0.259, P-value 0.009, and y = 106+ 1.09x. Find the best predicted value of y (weight) given an adult male who is 181 cm tall. Use a 0.10 significance lev. The best predicted value of y for an adult male who is 181 cm tall is kg. (Round to two decimal places as needed.)
Solids (grams) obtained from a material as y, with respect to drying time (Hours) as x. Ten experiments were carried out to obtain the following observations: Table on the picture (a) Create a scatter diagram for the data. (b) Estimated regression model according to the data conditions. (c) Calculate Model Accuracy (R²) and Relationship Between Variables (r²)
A company has recorded expenditure on advertising and the resulting sales for six months are as follows: Month Expenditure Sales(Y) March 20 170 April 40 240 May 50 260 June 60 300 July 30 220 August 40 250 Required: i. Plot the data on a scatter diagram and commentii. Calculate the line of best fit through the data, and interpret your values of α and βiii. Determine the explanatory power of your systemiv. Forecast sales when advertising expenditure is: 500 and 100 respectively
Use the following equations to perform calculations necessary to complete the CFU. Use the table below to calculate Z, skewness, and kurtosis. Use the table below to calculate Z, skewness, and kurtosis. X Z Z^3 Z^4 4 4 5 6 7 8 9 9 10 10 12 Ez^3 Ez^4 N = 11 Mean = 7.63 SD = 2.66 Calculate the skewness for the data above and Round to two decimal points.
Calculate the co-efficient of correlation and obtain the least square regression lines for the following data : 3 x: . 1 2 4 5 6 7 8 9 у: 8 10 12 11 13 14 16 15 Also obtain an estimate of y which should correspond on the average to x = 6.2.
Two samples, sizes 40 and 50 respectively, are taken from a population with unknown mean μ and unknown variance 2σ . The data is shown below. Sample I X1 35 36 37 38 39 f 3 7 15 10 5 Sample II X2 35 36 37 38 39 40f 10 21 8 6 3 2 Using the data from the two samples above, obtain unbiased estimates of i. The population mean ii. The population variance
Mist (airborne droplets or aerosols) is generated when metal- removing fluids are used in machining operations to cool and lubricate the tool and workpiece. Mist generation is a concern to OSHA, which has recently lowered substantially the workplace standard. The article "Variables Affecting Mist Generaton from Metal Removal Fluids" (Lubrication Engr., 2002: 10-17) gave the accompanying data on x = fluid-flow velocity for a 5% soluble oil (cm/sec) and y = the extent of mist droplets having diameters smaller than 10 μm (mg/m³): x y 89 177 189 354 362 442 965 .40 .60 .48 .66 .61 .69 .99 a. The investigators performed a simple linear regres- sion analysis to relate the two variables. Does a scat- terplot of the data support this strategy? b. What proportion of observed variation in mist can be attributed to the simple linear regression relationship between velocity and mist? c. The investigators were particularly interested in the impact on mist of increasing velocity from 100 to 1000 (a…
5. Data in the table below were collected to investigate the relationship between pressure and the corresponding scale reading for the purpose of calibration. We t a linear regression x= pressure y=scale reading x 8 10 8 10 40 50 40 50 y 11 18 14 15 70 90 72 88 A Compute the mean of x data x standard dev and y standard dev y 8 2 8 2 B { x=8528 { y= 26,794 compute SSxy and SSxx i=1 i i=1 i c Find the estimated slope b1 and estimated intercept b0 Answer in other question D Give the fitted regression line. (f) What is the estimated scale reading when the pressure is 12? .
Psi is a measure of compressive strength, or the ability of the material to carry loads and handle compression. The desired concrete psi rating used for sidewalks and residential driveways ranges from 2500psi to 3000psi obtained from mixing cement, stone, and sand in different ratios but with the same amount of water. The summary of the psi's of three (3) such concrete mixes made by three (3) different civil engineering students is given as follows: Mean vector: The variance-covariance matrix: Concrete mix Mean Concrete mix 1 Concrete mix 2 Concrete mix 3 Concrete mix 1 | Concrete mix 2 2700 18 12 2 3000 12 16 3 2400 Concrete mix 3 16 25 Let the random variable Y be the vector of the psi's of concrete mixes obtained by the students, i.e. Y1, denotes the psi of concrete mix made by student 1, Y2 is the psi of concrete mix made by student 2 and Y3 is the psi of concrete mix psi made by student 3. (a) Find (i) the multivariate probability distribution function (pdf) of Y. (ii) the…
Heights (cm) and weights (kg) are measured for 100 randomly selected adult males, and range from heights of 139 to 188 cm and weights of 38 to 150 kg. Let the predictor variable x be the first variable given. The 100 paired measurements yield x = 167.62 cm, y = 81.37 kg, r 0.113, P-value = 0.263, and y = - 105+1.01x. Find the best predicted value of y (weight) given an adult male who is 142 cm tall. Use a 0.05 significance level. %3D The best predicted value of y for an adult male who is 142 cm tall is kg. (Round to two decimal places as needed.)
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
I need to find the two models in part b. Please give final answer

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