15. Match each experiment design to its description.AnswerDescriptionCorrelation matrixResolution IIIResolution VGeneratorFoldingConfoundingHalf-fractional factorialResolution IVPareto chart of effectsPlackett-Burman(a) Describes how a term in a model gets contributions from/ is polluted by other termsin the model(b) Method of adding runs to a Resolution III design to make it Resolution IV(c) Bar chart of effect size or t statisic used to display coefficient magnitude and signifi-cance(d) Design that confounds main effects with two-factor interactions(e) Design that confounds main effects with four-factor interactions(f) Design that confounds two-factor interactions with each other(g) Experiment design with one-half of the runs from a full-factorial design(h) Confounding relation used to create additional columns (one or more) of factor levelsin a fractional factorial design(i) Reveals the degree of confounding between all of the terms that could be included ina model(j) Experiment design with an integer multiple of 4 runs that can have Runs - 1 studyvariables

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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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A large supermarket chain has invested heavily in data, technology, and analytics. Feeding predictive models with data from an infrared sensor system to anticipate when shoppers will reach the checkout counters, they are able to alert workers to open more checkout lines as needed. This has allowed them to lower their avera checkout time from four minutes to less than 30 seconds. Consider the data in the following table containing 32 observations. Suppose each observation gives the arrival time (measured in minutes before p.m.) and the shopping time (measured in minutes). O Arrival Time (minutes before 6:00 p.m.) Shopping Time (Minutes) 58 21 59 83 54 96 39 13 0 133 55 0 92 12 4 28 Shopping Time (minutes) 23 18 25 28 40 45 33 25 12 53 21 13 37 15 12 17 20 40 60 80 100 120 Arrival Time (Minutes Before 6:00 p.m.) Arrival Time (minutes before 6:00 p.m.) 140 38 AO 15 78 32 23 18 24 38 57 113 30 109 (a) Develop scatter diagram for arrival time as the independent variable. 47 104 72 112…
A data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y. (b) Given that x= 3.3333, s= 2.5033, y = 4.0667, s, = 1.9449, and r= - 0.9585, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a). 3 4 5.8 6.3 5.1 3.4 1.8 2.0 重 (a) Choose the correct graph below. OA. O B. OD. 本y 7- Ay 本y 7- AY 7- 0- 0. 0- 0. 6. There appears to be relationship. (b) ŷ =[]x+ (D (Round to three decimal places as needed.) (c) Choose the correct graph below. O A. О В. OC. O D. Ay 7- Ay 7- 0- 0. 9. 6. O Time Remaining: D TCOA2334403 U 10-8-2014 MAIN TCOA2330401 (2) Q 出

A data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y. (b) Given that x= 3.6667, sy = 2.2509, y= 3.6833, s, = 1.8809, and r= - 0.9511, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a). 1 4 4 6 6 y 5.0 6.3 4.2 3.4 1.4 1.8 (a) Choose the correct graph below. OA. B. OC. OD. Ay 74 Ay Ay 7- .. .. There appears to be a linear, negative relationship. (b) y=x+ O (Round to three decimal places as needed.) (c) Choose the correct graph below. O A. B. OC. D. Ay 0-
A data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y (b) Given that x =3.5000, s, = 2.2583, y = 4.4667, s, = 1.7682, and r= -0.9416, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a). 6 3 4 5.4 68 5.6 4.0 2.3 2.7 1 y (a) Choose the correct graph below. O A Oc. Q There appears to be V relationship (b) y=+ O (Round to three decimal places as needed.) (c) Choose the correct graph below. O A OB. OC. OD.
5
A baseball team claims that the mean length of its games is 2.4 hours. State H0 and Ha in words and in symbols. Then determine whether the hypothesis test for this claim is left-tailed, right-tailed, or two-tailed. Explain your reasoning. State the null hypothesis in words and in symbols. Choose the correct answer below. A. The null hypothesis expressed in words is, "the mean length of a baseball team's games is at most 2.4 hours." The null hypothesis is expressed symbolically as, "H0: μ≤2.4." B. The null hypothesis expressed in words is, "the mean length of a baseball team's games is more than 2.4 hours." The null hypothesis is expressed symbolically as, "H0: μ≠2.4." C. The null hypothesis expressed in words is, "the mean length of a baseball team's games is at least 2.4 hours." The null hypothesis is expressed symbolically as, "H0: μ≥2.4." D. The null hypothesis expressed in words is, "the mean length of a baseball…
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Statistics students in Oxnard College sampled 9 textbooks in the Condor bookstore and recorded the number of pages in each textbook and its cost. The bivariate data are shown below: Number of Pages (xx) Cost(yy) 726 35.3 737 45.85 355 24.75 255 14.75 754 34.7 797 49.85 898 59.9 424 18.2 391 31.55 A student calculates a linear modelyy = Incorrect xx + . (Please show your answers to two decimal places)Use the model to estimate the cost when number of pages is 777.Cost = $ (Please show your answer to 2 decimal places.)
Correlation 1. Eunice Consultancy took a random sample of the monthly office rents per square meter and the percentage of vacancy office space in 15 different cities. The results are shown in the table below. Monthly Rent Vacancy Rate X 01218609912201158912 4,000 7,500 5,300 6,200 8,000 5,000 9,000 3,400 4,400 5,100 8,000 9,000 9,900 8,800 9,000 a. Construct a scatter diagram. b. Calculate the coefficient of correlation using the Pearsons' Product-Moment Coefficient of Correlation and the Spearman's Rank-Order Coefficient of Correlation. c. Calculate the coefficient of correlation using the Spearman's Rank-Order Coefficient of Correlation. d. Interpret the results.
Bivariate data obtained for the paired variables x and y are shown below, in the table labeled "Sample data." These data are plotted in the scatter plot in Figure 1, which also displays the least-squares regression line for the data. The equation for this line is y = 14.87+0.88x. In the "Calculations" table are calculations involving the observed y-values, the mean y of these values, and the values y predicted from the regression equation. Sample data Calculations 160+ x y (x-1)² (-5)² (v-^^)² 150+ 107.2 110.7 396.0100 457.7032 2.2320 122.0 130.3 140- 0.0900 70.0569 65.1249 131.5 122.1 130- 72.2500 0.0001 72.0801 142.5 129.9 120. 0.4900 93.5089 107.5369 152.5 160.0 110- 864.3600 341.1409 119.4649 Send data to Excel LL 130 130 140 150 160 Column sum: 1333.2000 Column sum: 962.4100 Column sum: 366.4388 Figure 1 Answer the following. (a) The least-squares regression line given above is said to be a line that "best fits" the sample data. The term "best fits" is used because the line has an…
Anarticle in Technometrics by S. C. Narula and J. F. Wallington Prediction, Linsar Regression, anda Minimum Sum of Relative Erro Vol. 19, 1977) presents data on the selling price (y) and annual taxes (x) for 24 houses. The taxes include local, school and county ta The data are shown in the following table. Sale Price/1000 Taxas/1000 25.9 4.9176 29.5 5.0208 27.9 4.5429 25.9 4.5573 29.9 5.0597 29.9 3.8910 30.9 5.8980 28.9 5.6039 35.9 5.8282 315 5.3003 31.0 6.2712 30.9 5.9592 30.0 5.0500 36.9 8.2464 419 6.6969 40.5 7.7841 43.9 9.0384 37.5 5.9894 37.9 7.5422 44.5 8.7951 37.9 6.0831 38.9 8.3607 36.9 8.1400 45.8 9.1416
A data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y. (b) Given that x=3.8333, sx=2.4014, y=3.6500, sy=1.7942, and r=−0.9539, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a).

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