Project Cost (S/m?) YearLocation BuildingNumber of QualityConstructionNoIndexMethods IndexТуре0.9 Office0.87 Office0.95 OfficeStoriesIndex1387.519994022269.1200018113737.4201464.1.21.1 Office1.1 School1.13 Office0.95 Hospital0.87 Office1.05 Hospital1.13 Garage1Office4343.42000825392.920001131250.8200220.57430.619991448602.82007319430.61998410341.21998111452.120014.4112493.120001.16 School141.113667.420021.16 School741.450.95 Hospital1 Hospital1.13 Hospital1.13 Office14915.02015615511.32000741.1516369.2199931.117398.32001241.13 Office1.13 Office18343.4199910219430.62008223120532.820040.87 Office271.13 Hospital1.13 Warehouse1.13 Hospital1.08 Office21389.7200010322258.32001123417.72002141.0524215.31998125202.420001.13 School111.13 Office1.13 Warehouse1 School1.13 Hospital1.13 Hospital1.07 School1.07 School1.13 School1.13 Hospital1.13 Warehouse1.02 Warehouse1.05 Warehouse1.13 Warehouse26373.52001327162.520082128194.81999329419.819991.230387.5200521.231227.120002261.6322.9296.032200062332001313419992135121.61999136156.12011137107.61999138158.8200511 Making a conceptual cost estimating for a construction project using Artificial Neural Network (ANN)Description: Historical data collected from 38 construction projects "Data in the second picture" are givenUsing this data, you are required to estimate total cost of a 12 story 17,350 m2 (total area) office buildingthat is planned to be constructedin 2020. Location Index for the office building is 1.07, Quality Index is 3, and Construction MethodsIndex is 1.1 with ANN.Required:*) Details of all ANN model(s): The number of hidden layers, neurons in each layer, transferfunction in each layer, training function, weight/bias learning function, and performance function.*) Your total cost estimate for the office project.*) And a brief discussion about how accurate is your estimate.Time Indices:Building Type IndicesTimeTimeYearYearBuilding typeindexindexBuildingindices19982.0720093.4319992.3120103.54Warehouse1.2020002.4920113.65Garage2.0920012.6720123.78School2.9620022.9520133.9120033.0120144.07Office3.0520043.0820154.32Hospital3.1520053.1120164.4620063.1920174.7820073.2320184.8620083.29

Name: Project Cost (S/m?) YearLocation BuildingNumber of QualityConstructio
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Description: Project Cost (S/m?) YearLocation BuildingNumber of QualityConstructionNoIndexMethods IndexТуре0.9 Office0.87 Office0.95 OfficeStoriesIndex1387.519994022269.1200018113737.4201464.1.21.1 Office1.1 School1.13 Office0.95 Hospital0.87 Office1.05 Hospital

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1 0.87 Office 0.95 Office 1.1 Office 1.1 School 1.13 Office 0.95 Hospital 0.87 Office 1.05 Hospital 1.13 Garage 1 Office 1.16 School 1.16 School 0.95 Hospital 1 Hospital 1.13 Hospital 2000 18 1 1 4 2014 1.2 4 2000 8. 1 9 2000 11 1 8 2002 0.5 6 1999 14 1 8 2007 3 1 6 1998 4 1 2 1998 21 1 2001 4 4 1 1 2000 2002 1 4 1.1 4 7 4 1.45 2015 1 3 2000 7 4 1.15 2 1999 3 3 1.1 423 24

1 0.87 Office 0.95 Office 1.1 Office 1.1 School 1.13 Office 0.95 Hospital 0.87 Office 1.05 Hospital 1.13 Garage 1 Office 1.16 School 1.16 School 0.95 Hospital 1 Hospital 1.13 Hospital 2000 18 1 1 4 2014 1.2 4 2000 8. 1 9 2000 11 1 8 2002 0.5 6 1999 14 1 8 2007 3 1 6 1998 4 1 2 1998 21 1 2001 4 4 1 1 2000 2002 1 4 1.1 4 7 4 1.45 2015 1 3 2000 7 4 1.15 2 1999 3 3 1.1 423 24

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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Treatment 1 2 3 4 3.52 3.47 3.54 3.74 3.36 3.73 3.52 3.83 3.57 3.38 3.61 3.87 4.19 3.87 3.76 4.08 3.88 3.69 3.65 4.31 3.76 3.51 3.51 3.98 3.94 3.35 3.86 3.64 3.71 Children were given one of four different drugs at random, and the response measure was liver weight as a percentage of body weight. The responses were Compute the overall mean and treatment effects. (10 Marks) Compute the Analysis of Variance table for these data. (4 Marks) What would you conclude about the four drugs?
The store manager of a business that sells jackets is curious if the weather temperature (in degrees Celsius) per day is related to the daily sales (in pesos) earned by the store. He took some random samples and recorded the temperatures and sales for the selected days, which can be found in the next slide. Calculate the correlation coefficient and interpret the result.
Female: 15 14.85 15.2 14.25 13.85 13 13.6 13.7 14.05 12.7 14.05 13.65 13.25 13.25 13.55 12.95 13.55 13.05 11.85 13.2 11 13.8 12.25 12.1 12.1 11.6 11.9 12.05 10.75 11.2 10.55 11.1 10.45 9.6 13.85 14.25 14.8 14 14.5 13.75 13.55 12.55 13.2 13.7 13.35 13.25 12.95 13.4 13.35 13.3 12.3 13.55 12.8 12.4 13.1 12.3 12.6 12.65 11.9 10.2 12.05 11.7 10.4 10.75 9.8 9.6 10.75 9.75 9.55 9.05 14.65 14.2 15.35 14.6 14.3 14.75 13.65 13.7 14.25 13.8 14.1 13.6 14 14.25 13.2 14.4 13.25 13.7 13.15 13.05 13.45 12.4 13.3 12.75 12.2 12.6 11.55 11.6 11.6 10 10.9 10.35 11.75 11.3 10.3 10.9 Male: 13.55 13.75 13.5 14.25 13.35 13.85 13.5 13.1 12.8 12.35 13.25 10.6 12.6 13.35 13.5 13.55 12.9 11.8 13.05 13.4 12.05 11.05 11.8 11.8 11.9 12.35…
What is the confidence level of each of the following confidence intervals for u? Complete parts a through e. Click the icon to view the table of normal curve areas. a. x+1.96 % (Round to two decimal places as needed.) b. x+1.645 % (Round to two decimal places as needed.) c. X+2.575 % (Round to two decimal places as needed.) d. x+1.282 % (Round to two decimal places as needed.) e. x+0.99 % (Round to two decimal places as needed.)
State Sales Tax Rate* Alabama Alaska Arizona 4% 0% Hawaii Idaho 6.6% Illinois Florida Georgia Arkansas California 7.25% Iowa Colorado 6% Indiana 4% Massachusetts 6.25% 6% Michigan 6% Minnesota 61% 7% Mississippi 6% Missouri Montana 2.9% Kansas 6.3% Connecticut 6% Kentucky 6% Delaware 0% Louisiana 4% 6% Maine 4% Maryland 5% 6% Nebraska Nevada New Hampshire New Jersey 6.875% 7% 4.225% 0% 5.5% 6.85% 0% New Mexico New York North Dakota North Carolina 5.75% Ohio Oklahoma Oregon Pennsylvania Rhode Island 5.125% 7% South Carolina 4% 5% 5.5% 4.5% 0% 6% 7% 6% South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming 4% 7% 6.25% 4.7% 6% 4% 6.5% 6% 5% 4%
Household Paper Plastic 1 15.09 9.11 2 16.39 9.7 3 6.33 3.86 4 9.45 3.02 5 6.98 2.65 6 8.72 9.2 7 11.42 12.81 8 6.67 6.09 9 6.16 5.88 10 16.08 14.36 11 13.61 8.95 12 11.08 12.47 13 9.41 3.36 14 6.44 8.4 15 12.43 8.57 16 7.98 6.09 17 3.27 0.63 18 13.31 19.7 19 7.72 3.86 20 12.73 14.83 21 6.96 7.6 22 17.65 11.26 23 14.33 6.43 24 2.8 5.92 25 9.83 6.26 26 9.55 9.2 27 11.36 10.25 28 7.57 5.92 29 12.32 11.17 30 20.12 18.35
Commercial Residential4.17 9.795.38 5.973.22 8.095.42 5.814.91 8.552.59 3.973.53 8.113.01 8.664.69 10.356.17 6.980.33 5.675.13 4.056.35 6.156.47 9.853.98 5.67
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AaBb AaBbCcDdl Heading 1 Heading 2 Normal Title No Spacing Company Actual Estimated 0.38 2.31 AT&T 1.29 American Express Citigroup Coca-Cola Dupont Exxon-Mobil General Electric Johnson & Johnson McDonald's Wal-Mart 2.01 2.59 1.60 3.43 1.78 2.18 1.84 2.19 1.71 2.72 1.51 2.28 2.18 0.77 1.55 1.81 1.74 Total 18.42 19.45 Difference: 1.03 Use a level of significance of .05 and test for any difference between the population mean actual and population mean predicted earnings per share. What is the p-value? What is a. your conclusion? What is the point estimate of the difference between the two means? Did the analysts tend to underestimate or over estimate the earnings? b. At 95% confidence, what is the margin of error for the estimate in part b? What would you recommend based on this information? 8. English (United States) Focus 26 IG MacBook Air 20 F3 F2 F4 F5 F6 F7 F8 F9 F10 F11 23 & 4 8. 9.
maxsnov [1) 15.2 25.4 32.8 14.5 23.6 37.8 43.2 22.9 20.3 21.1 25.7 24.6 25.9 22.5 32.8 # [16) 19.6 11.0 18.2 10.8 21.3 22.0 13.6 21.8 21.0 21.2 12.2 20.2 17.2 40.0 27.8 ## [31] 13.2 20.8 21.4 23.6 35.8 33.9 31.0 18.8 15.8 18.8 17.2 41.2 35.2 31.8 23.8 #* [46] 29.8 20.4 16.0 45.6 20.8 20.0 Consider the data on the maximum daily snowfall amounts per winter season The histogram of the data looks like as follows: Histogram of maxsnow 10 20 30 40 50 maxsnow (1) Which distribution would be a suitable candidate for the population distribu- tion? Provide a brief rationale for your answer. Consider the data set consisting of the following 15 measurements: measurenents aa (1) aa (10] -0.27 -222.00 -1.16 -0.77 -197.00 -0.99 1.49 -0.92 1.83 -1.29 -0.01 -0.33 -1.10 0.50 0.18 There are two errors in the above sample, due to a faulty measurement device. In reality, the second and last measurements should have been 2.22 and 1.97, re- spectively. (2) Select which statements are TRUE: A) The sample mean…