SOLUTION: ?SAS Real Estate Enrollment Log in And Database Uploads Project

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SAS Enrollment, Log In and Database Uploads This set of associates procure succor you delay the present piece of your SAS application. 1. First, you scarcity to record delay SAS, if you own not aldisposed executed so. To do that, follow this associate: https://odamid.oda.sas.com/SASODAControlCenter/enroll.html?enroll=edd990e3f7a9-4d72-a448-34d0459dcd22 (Links to an palpable position.). This is the indication in page for SAS, so you may absence to bookmark it so you can abundantly come-back posterior. If you own previously registered, then you may log in from close. Otherwise, click on "Register for an account" and register. Unintermittently you own recorded, SAS procure transmit you a user ID, which procure probably be your email discourse (precedently the @) and a reckon (usually cipher). 2. If you prevent the over bookmark and go tclose to indication in each interval, SAS may ask you for a course principle. It is not inevitable to penetrate one - merely click on "Respin to the Dashboard". If you would love to escape that each interval, unintermittently you own recorded, merely click on this link: https://odamid.oda.sas.com/SASLogon/login?service=https%3A%2F%2Fodamid.oda.sas. com%2FSASODAControlCenter%2Fj_spring_cas_security_check 3. At this design, you procure merely click on "SAS Studio" and you are then disposed for the exercise. 4. Below are associates to two videos patent clear by Dr. Jeff Bohler for IS3310. The pristine one includes some applications you do not scarcity to do for this rank, but you may discover it succorful in learning to range SAS. It clear-ups how to register in SAS and it as-well-mannered shows you how to build a scatterplot from an sound groundsbase. Close is that link: https://web.microsoftstream.com/video/24bc9551-a073-4bb9-bf1b-8f90612bc932 (Links to an palpable position.) 5. The present video is wclose Dr. Bohler is clear-uping how to upentrust a groundsbase. YOU NEED THIS! This is wclose you procure acquire how to upentrust the Excel spreadsheet delay the Authentic Estate Data in prescribe to finished the Ticklish Thinking Application for QM3345. Link to Dr. Bohler's video on uploading a database: https://web.microsoftstream.com/video/d4551f6c-cbc4-402d-bd77-3edcd410cea5 Name: _______________________________________________ SAS® Forecasting Scheme for Ticklish Thinking This scheme utilizes the “Real Property – Base” groundsbase. The design is twofold: - Build ticklish holding skills scarcityed to building grounds segregation uprightly for potent decision making. Analyze profitable grounds in-effect and skillfully in prescribe to build an explanatory respin design. The Authentic Property - Base groundsbase embraces the subjoined shiftings for 101 settlements (* NOTE: These shiftings are shown as leading shiftings delayin the groundsbase): a. b. c. d. e. f. g. h. i. j. k. l. *Unit# *Type *Location *U/S/R Price Sq. Ft. Lot (Acres) Garage BRs Baths *Pool Age (An assigned groundsbase key) (H = House, C = Condo/Apartment) (1 through 10 – voting limit wclose located) (Urban vs. Suburban vs. Rural colonization) (The expense the scion ended up selling for in 2017) (Heated/Cooled & Steadfast balance footage) (Acreage of possessions) (Number of steadfast adept and/or enclosed parking positions) (Number of competent bedrooms) (Number of bathrooms – no tub or wash involved as .5) (No=No Access; HA=Shared Pool; AG=Above Ground; IG=In Ground) (Age of settlement in rounded year at end of 2017) At a tall raze, close are the plods you are going to perform: 1. Downentrust the Excel spreadsheet delay the Authentic Property Grounds in it and originate the requested Scatterplots. NOTE: It is weighty that the Dependent Shifting (Price) is on the Y-axis and the Independent Shifting is on the X-axis. The prescribe of the two columns procure order that. 2. Perform Respin Segregation delayin Excel to enumerate how well-mannered-mannered the prescribed Independent Variables clear-up changes in the Dependent Variable. 3. Upentrust the Authentic Property groundsset into SAS Studio. 4. Perform a order of Respin Analyses in SAS Studio to discover a rectify set of explanatory variables. 5. Response a ticklish holding application concerning forecasting and the grounds set we own. Here are the plods in detail: 1. Originate the subjoined charts in Excel using the charting tools and the involved shiftings in “Real Estate - Base.xlsx” (Remember, Expense is your Dependent Variable) a. Originate a new tab in the spreadsheet determined “Scatterplots”. After creating each Scatterplot on the initiatory tab, provoke it to the Scatterplot tab you originated. b. Originate a Scatterplot using the shiftings Expense and Sq. Ft. c. Originate a Scatterplot using the shiftings Expense and Lot (Acres). d. Originate a Scatterplot using the shiftings Expense and Garage. e. Originate a Scatterplot using the shiftings Expense and BRs. f. Originate a Scatterplot using the shiftings Expense and Baths. g. Originate a Scatterplot using the shiftings Expense and Age. 2. What character of correspondentity do you see between these shiftings established on the scatterplots? a. Between Expense and Sq. Ft. (Circle)? No correspondentity Weak Moderate Strong Moderate Strong Moderate Strong Moderate Strong Moderate Strong Moderate Strong b. Between Expense and Lot (Circle)? No correspondentity Weak c. Between Expense and Garage (Circle)? No correspondentity Weak d. Between Expense and BRs (Circle)? No correspondentity Weak e. Between Expense and Baths (Circle)? No correspondentity f. Weak Between Expense and Age (Circle)? No correspondentity Weak 3. In the Excel spreadsheet granted, using the Grounds Segregation Add-in, run a respin segregation delay Price as the Dependent Shifting and Lot, Garage and BRs as the Independent Variables and chosen to own Excel originate a new tab determined “Regression Model”. It is recommended that you run separate reverts delay each shifting sole to see how sound each R2 is. 4. Contribute the subjoined from the “Excel Model”: a. Coefficient of Determination (R-squared) ___________________ b. Y-Intercept for the Respin Model ___________________ c. Slope esteem for X1 (Lot) ___________________ d. Slope esteem for X2 (Garage) ___________________ e. Slope esteem for X3 (BRs) ___________________ 5. Do you hold we scarcity all three general Independent shiftings in our Respin design to predict changes in Expense (Circle)? Yes No Explain: _________________________________________________________________________ _______________________________________________________________________________ _______________________________________________________________________________ 6. Which shifting(s) would you reprovoke (Circle)? Lot Size Garage BRs 7. Of the subjoined shiftings in the spreadsheet, which shifting would you chosen present to add to the design (i.e., you hold it would originate a sounder foreshowing of Price)? Type Location U/S/R Sq. Ft. Baths Pool Age 8. Run a SAS Respin Design on the Authentic Property – Base groundsbase using Expense as the Dependent Variable (Y) and embrace the initiatory Independent Variables (minus any you transportd in plod 6) and adding the shifting you chose in plod 7. Print your design output and spin it in delay the assignment. (NOTE: You may own to reproduce this application until you discover a alliance of variables that gives you a taller R2). 9. Contribute the subjoined from the SAS Model: a. Coefficient of Determination (R-squared ). ________________________ b. Y-Intercept for the Respin Model ________________________ c. Slope esteem for each of your Independent Variables. i. Var_______________________ ________________________ ii. Var_______________________ ________________________ iii. Var_______________________ ________________________ iv. Var_______________________ ________________________ v. Var_______________________ ________________________ 10. Did your SAS design contribute a sounder Coefficient of Determination (Circle)? Yes No Critical Thinking Question: 11. A capacious authentic property posse is involved to use correspondent grounds plus their own sales grounds to forecast total sales for the hereafter year for each of their agents and they own pulled grounds from their Finance memorials. They are involved to congregate the best grounds to build a Respin design. a. Would it find signification to use the identical grounds as we used over in the SAS design? Why or why not? __________________________________________________________________________________ __________________________________________________________________________________ b. Recommend two grounds elements you hold they probably own profitable to succor them predict sales for each of their sales nation. 1. ______________________________________________ 2. ______________________________________________ GRADING RUBRIC Overall Score Possible = 100 Problem Area Did the tyro originate the Excel tab for Scatterplots? Possible Points 2 Did the tyro originate the emend scatterplots and provoke them to the new tab? 3 Did the tyro find a chosenion for each emblem of relationship? 5 Did the tyro run Grounds Segregation on the Excel spreadsheet creating a new tab for the design output? 10 Did the tyro contribute the emend design output esteems from the spreadsheet in the collection muniment? 10 Did the tyro response Ticklish Thinking questions 5, 6 and 7? 20 Did the tyro run a respin design in SAS and contribute a print out of the design output? 20 Did the tyro contribute the emend design output esteems from SAS in the collection muniment and response the decision collection (#10)? 10 Did the tyro finished all faculty of the Ticklish Thinking collection #11? 20 Total Ticklish Thinking Points 100 Points Awarded Unit # 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 Type H H H H H H H H H C H H H H H H H H H C H H H H H H H H H C H H H H H H H H H C H H H H H H Location 10 2 5 6 9 1 3 7 4 8 10 2 5 6 9 1 3 7 4 8 10 2 5 6 9 1 3 7 4 8 10 2 5 6 9 1 3 7 4 8 10 2 5 6 9 1 U/S/R R U S S S U S R S U R U S S S U S R S U R U S S S U S R S U R U S S S U S R S U R U S S S U Price $ 54.000 $ 98.000 $ 125.700 $ 250.000 $ 411.500 $ 56.500 $ 289.500 $ 420.000 $ 199.800 $ 249.900 $ 77.000 $ 78.600 $ 199.800 $ 279.500 $ 842.000 $ 66.720 $ 311.450 $ 311.520 $ 187.500 $ 311.750 $ 98.000 $ 112.000 $ 146.850 $ 301.500 $ 690.000 $ 71.200 $ 275.000 $ 598.230 $ 176.500 $ 405.200 $ 68.521 $ 101.500 $ 117.650 $ 266.000 $ 601.500 $ 39.800 $ 401.500 $ 782.000 $ 201.500 $ 199.650 $ 119.500 $ 88.420 $ 188.500 $ 231.100 $ 485.200 $ 48.999 Sq. Ft. 1100 1875 1350 2612 2190 1800 1605 2199 2120 900 1950 1420 2090 2770 3650 1600 2288 2000 1880 980 3011 2980 1850 3520 3300 1905 2850 3250 1900 1150 2015 2190 1750 2190 3450 1064 2540 4200 1980 850 1865 1750 1700 2045 2700 1550 Lot (Acres) 2 0,25 0,25 0,5 0,5 0,25 0,25 12 0,4 0 1 0,5 0,75 0,5 1 0,25 0,5 1,5 0,25 0 3 0,4 0,25 0,5 0,75 0,5 0,25 10 0,4 0 1,5 0,66 0,66 1 0,75 0,5 0,75 5 0,66 0 14 0,75 0,5 0,5 0,5 0,75 Garage 0 1 0 2 1 0 2 2 2 0 1 0 2 2 3 1 2 2 1 1 1 2 0 3 3 1 2 3 2 1 1 1 1 2 2 0 2 3 2 0 1 1 2 1 2 1 BRs 2 3 2 3 3 3 3 3 3 2 2 2 3 3 5 3 3 3 3 2 4 3 3 4 4 3 3 4 3 3 3 3 3 3 3 2 4 5 3 2 3 3 3 3 3 3 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 H H H C H H H H H H H H H C H H H H H H H H H C H H H H H H H H H C H H H H H H H H H C H H H 3 7 4 8 10 2 5 6 9 1 3 7 4 8 10 2 5 6 9 1 3 7 4 8 10 2 5 6 9 1 3 7 4 8 10 2 5 6 9 1 3 7 4 8 10 2 5 S R S U R U S S S U S R S U R U S S S U S R S U R U S S S U S R S U R U S S S U S R S U R U S $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ 366.500 356.420 157.650 288.500 49.874 91.640 179.500 189.500 532.800 52.100 399.500 388.600 175.800 301.500 95.400 96.888 171.630 207.500 577.900 49.875 247.800 497.500 205.000 469.800 77.000 91.400 152.800 401.500 505.000 58.700 285.235 675.500 188.760 302.900 171.680 84.600 166.900 366.900 411.960 68.900 297.600 524.700 181.500 312.800 88.520 79.450 151.960 2390 2050 1830 1014 1450 1800 2015 1950 2888 2012 2450 3450 2200 1050 2220 1995 2100 2750 3120 1011 2120 3890 2100 1250 1090 1900 1040 3850 2950 1000 2850 2740 1850 900 2950 1640 1800 3200 2400 2200 3300 4350 1800 940 1750 1490 1500 0,5 9 0,25 0 0,5 0,5 0,75 0,5 0,5 0,4 0,5 4 0,4 0 8 0,5 1 0,75 0,75 0,25 0,5 22 0,66 0 2,5 0,4 0,25 1 0,5 0,4 0,5 75 0,25 0 11 0,75 0,8 0,75 0,5 0,5 0,5 11 0,4 0 4 0,5 0,5 2 2 1 1 0 2 1 2 2 1 2 2 2 1 2 1 2 2 2 0 2 3 2 2 0 1 1 2 2 1 1 2 1 1 2 1 2 3 2 2 2 2 2 1 1 0 1 4 3 2 2 2 3 3 3 4 3 3 3 3 2 3 2 3 3 4 2 2 4 4 3 3 2 2 4 3 2 3 3 2 2 3 2 3 4 3 3 4 4 3 2 2 3 3 94 95 96 97 98 99 100 101 H H H H H H C H 6 9 1 3 7 4 8 10 S S U S R S U R $ $ $ $ $ $ $ $ 302.900 489.650 64.995 400.500 711.000 172.450 345.900 81.400 2175 2550 850 2752 4540 1590 980 1275 1 0,5 0,25 1 18 0,5 0 2 2 2 0 2 2 1 1 1 3 3 2 3 5 2 3 2 Baths 1 2 1,5 2 2 1 2 2,5 2 2 2 2 2 2,5 5 1,5 2 2 2 1,5 2 2 2 2,5 3,5 1,5 2 2 2 2,5 1,5 2,5 1,5 2,5 3 1,5 2,5 2,5 2 2 2 2 2 2 2,5 2 Pool No No AG No No No HA No No HA No No IG HA HA No No IG IG HA AG No No IG HA AG No No No HA No IG No HA IG No No No HA HA No AG No No No No Age 27 26 82 11 17 21 6 72 15 4 12 16 22 9 4 28 11 21 9 5 35 4 11 3 9 37 5 2 3 0 38 16 22 8 6 31 9 4 8 6 17 21 15 8 15 29 2 2 2 2 1 2,5 2 2,5 2,5 2 2,5 2,5 2,5 2 2 1,5 2 2 3 2 2 3,5 2,5 2,5 1 2 2 3 3 2 2,5 2 2 2 2 2 2 2,5 2 2 2,5 3 2 2 2 1,5 2 No No No HA No No No No No No No No No HA IG No No IG HA No HA IG HA HA AG No IG HA IG AG IG IG No HA AG No No HA No No HA No No HA No No No 13 17 8 2 36 9 12 4 4 16 7 37 2 1 21 15 36 7 2 14 6 3 4 0 35 4 3 7 1 25 2 15 4 1 5 7 2 7 9 17 8 3 12 7 37 32 17 2 2,5 1,5 2,5 3 2 2 1,5 No No No HA No IG HA No 11 11 12 6 14 9 2 24 Name Alison Robert Sven James Maggie Jonathon Wendy Marvin Blanche Michelle Alex Perez Height 66 68 73 69 61 70 62 64 61 66 72 69 Salary 60 65 52 53 52 115 90 82 101 79 88 51 Name Alison Robert Sven James Maggie Jonathon Wendy Marvin Blanche Michelle Alex Perez Age 28 34 51 31 24 57 49 64 61 32 34 29 Salary 60 65 52 53 52 115 90 82 101 79 88 51 Name Alison Robert Sven James Maggie Jonathon Wendy Marvin Blanche Michelle Alex Perez YOE 6 10 5 3 1 32 24 31 36 12 34 2 Salary 60 65 52 53 52 115 90 82 101 79 88 51 Name Alison Robert Sven James Maggie Jonathon Wendy Marvin Blanche Michelle Alex Perez Height 66 68 73 69 61 70 62 64 61 66 72 69 Age 28 34 51 31 24 57 49 64 61 32 34 29 YOE 6 10 5 3 1 32 24 31 36 12 34 2 Salary 60 65 52 53 52 115 90 82 101 79 88 51 ...
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