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MGSC 7000 Assignment
创建日期：2024-04-17 17:51:57
标签： MGSC 7000
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MGSC 7000 Assignment 1 

  This is a Group Assignment. Work as a team and submit one assignment per team.  Please answer the following questions using R.  The deliverable for this assignment is a R file with all the codes for each of the question.  Before answering each question, clearly mention what question you are answering then provide the code in the subsequent lines. After providing the code you need to use # to provide your comments in the code to explain what the code is doing so it can be easily read by another person.  Some questions need your interpretation. You need use # provide interpretation at the end of each question. Points will be deducted for failure to provide interpretation. For example: For Question 2 (a). You should clearly mention that the average selling price of laptops is $508.1, the median price was $500.1 etc.. Question 1: The file Housing.csv contains data collected by the US Census on housing. This data is obtained from the StatLib archive . The dataset has 506 cases (i.e., different areas within Boston). The data was originally published by Harrison, D. and Rubinfeld, D.L. `Hedonic prices and the demand for clean air', J. Environ. Economics & Management, vol.5, 81-102, 1978. There are 14 variables in the dataset. Data Dictionary: CRIM per capita crime rate by town ZN proportion of residential land zoned for lots over 25,000 sq.ft. INDUS proportion of non-retail business acres per town. CHAS Charles River dummy variable (1 if tract bounds river; 0 otherwise) NOX nitric oxides concentration (parts per 10 million) RM average number of rooms per dwelling AGE proportion of owner-occupied units built prior to 1940 DIS weighted distances to five Boston employment centers RAD index of accessibility to radial highways TAX full-value property-tax rate per $10,000 PTRATIO pupil-teacher ratio by town LSTAT % lower status of the population MEDV Median value of owner-occupied homes in $1000 a. Create a table that tells us mean of median value of owner-occupied homes (i.e., average of MEDV) that are near Charles River vs. those that are not (see CHAS variable). [5 points] b. Create a table that informs us the mean proportion of residential land zoned for lots over 25,000sqft (ZN variable) for different RAD (index of accessibility to radial Page 2 highways) levels. For example, the table should tell us what is the mean ZN when RAD=2 and so on. [5 points] c. Add a new variable called CAT_MEAN to the dataset. This variable should be a binary variable with CAT_MEAN=1 if the median value of owner occupied homes is above $30,000 else 0. [10 points] d. Create a table to inform how many homes in the dataset have or do not have tract bounds with the river. [5 points] e. Create a correlation table for all the variables in the data. Provide a detailed analysis based on the correlation table. [10 points] f. Create a table with only CRIM, INDUS, CHAS, and MEDV variables and with only the observations with MEDV more than 30. [5 points] Question 2: The file LaptopSales.csv contains data collected on laptops sold during 2008. This data was obtained from ENBIS – the European Network for Business and Industrial Statistics. Below is the data dictionary. LaptopSales Date purchase date Configuration A numerical code representing a combination of screen size, battery life, RAM, etc. Each code corresponds to a particular combination. Customer Postcode postcode in London of the customer Store Postcode postcode in London of the store Retail Price price of laptop in GBP Screen Size screen size of laptop (Inches) Battery Life battery life of laptop (Hours) RAM RAM size of laptop(GB) Processor Speeds processor speed of laptop (GHz) Integrated Wireless? whether the laptop has integrated wireless or not HD Size HD size of laptop (GB) Bundled Applications? whether the laptop comes with bundled applications or not customer X X geo coordinates for customer location. customer Y Y geo coordinates for customer location. store X X geo coordinates for store location store Y - Y geo coordinates for store location Imagine you are a Data Scientist for a company called ABC Laptops. Utilizing this data you need to help your company with their business planning decision. Answer the following questions. These are Page 3 open-ended questions. As a scientist, your answers need to provide as much information as possible to the company. a) At what prices are the laptops actually selling for? That is create a table with the summary statistics for the retail price column. You can report min, max, mean, median, sd etc… [5 points] b) Create columns called “Month” and “Week.” These columns should tell us the month and week when the laptop was sold. [Hint: You will recognize that the Date column is in character format and needs to be converted to Date format.] [10 points] c) Are the prices consistent across retail outlets? How are the prices varying across retail outlets? (Hint: every retail store has a unique Store Postcode. You need to first calculate the mean selling prices by group and report it.) [5 points] d) How does price change with configuration, ram, and screen size? That is, what is the mean and median prices for different configurations, ram, and screen size. [10 points] e) Which stores are selling the most? [10 points] f) What is the revenue from each store? What percent of revenue from each store is from selling 15in monitor vs. 17in monitor? [10 points] g) Create a new data table with revenue for each store, number laptops sold by each store, what percent of the total revenue does each store contribute, and what percent of sales volume does each store contribute. [10 points] 

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关键词一 关键词二 关键词三 关键词四 关键词五 和法规和的发更好的风格和 ECON 615 FINC 612 CSC148 COMP 639 ACCT 203 ACCT 211 PSYC 101 MTH2009 COMP52315 PSYCO 432 statistics MATH4063 11 xxx 1 MA1MSP MAST30028 MATH3888 CS341 EEE30002 ES2F5 MCD4160 CC0933 ECON 1101 MCHM3001 CHEM3118 COMMGMT 2511 COMP41280 STAT 631 24T1 IRE379 SENG365 ECON433 FIT3139 MATH4602 LING5621M FINS5516 ECON3208 MN2177 L2 SM EEET1415 Finance DS4023 COMP3004 7CCSMRTS K1S5B6 Stat230 CSCI4211 CSI2132 ECON30130 MAS6100 ENVS222 COM2107 INFO1112 STAT 4004 FIT2100 comp2022 COMP4691 Physics 307 Econ 659 probability CSCI316 fir29 CSCI203 COMP3160 COMP6714 INFO1113 Physics 7B Physics Photonics S203031 STAT2005 COMP90015 CSCI 2110 CSCC46 Information CSC477 COMP4650 Statistical COMP 346 COMP1017 ELEC340 MATH1007 Programming function STAT 244 CS 134 Java cse13s Math 108A FW20 ECON3389 CSE 130 Science 331 COMP9020 engineering COSC 445 CSE 5523 GAME2012 visualization MATH 235 Math 370 CSC343 COGS 108 EE524 COMP10200 STAT 416 3FK4 MSCI 311 ECON6113 ACC40700 EMESTER1 MAS8383 ECO 512 STAT 8310 CMN3102 MA577 CMPT 225 COMP0045 Methods Equations MATH 113 Math 3283W ICS-33 EN4302/ENT603 BIA B350F MA318 MTHM506 MECH 5315M ECONOMICS MAS8382 COM 2004 PX3142 XJEL 3662 STAT 231 MGT B399F PX4131 COM2108 30AM MSCI521 ECONM1015 ACFI304 GR5241 MATH10101 ECON 2070 COMS31900 EFIM20011 CSE 250B ACSE-5 STAT4207 SOFT2412 ELEC 331 AY2020 MSIN0209 FIT2094 CS 241L ST404 CS 411 3D CA3 INF4002 COMP3506 SIT718 CS 188 CS 170 MATH 138 CSE 251A CMT118 DATA5207 CMPT307 CMPT459 T1 PGEE11108 COSC 3P32 ME 163 MATH96007 7QQMM203 EE6227 BA 574 STA 4234 ECO206Y1Y ECO2008 MT2300 MATH 11158 CS 527 MACM 316 CSE474 2DI70 ISE 525 COMP3411 EMAT30007 7CCSMBDT MFIN704 MFIN704W21 MfIB ECE 438 CS 436 F36 CS5344 FE 621A FE621 TBA 612 ECM3151 ECMM422 MF1 MSIN0107 ESSMENT CS 5854 MFIT 5008 MIPS R4000 ENG5274 BU52018 ENG2079 BIOA02 STA2570 F0 INF553 STAT 440 STAT3008 COMP9417 COMP6451 6COM1042 BU52006 ST303 HW-1 CISC-235 CS 510 MATH3161 ECN 140 ECE391 Comp 3613 CVEN 9625 PRG455 UESTION 1 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MATH 239 QF5203 INFR08010 IT114105 FIT2093 ECON3124 ECON1195 MATH 337 STAT 3006 COMP202 COMP3130 MATH3609 COMP 250 CS6140 IEEE ELE00041I FIN40090 CIV 5899 MATH3066 IGNMENT MATH 2009 STAT3405 HIST 101 MATH 3281 CEGE0042 ICT532 LAB 7 LAB 5 MCO455 CSIT214 Q4 IFB104 A1 ECO220Y5Y DA5020 CMPSC473 FIN9007 DSCI553 MSCI534 COMP3308 CSE-112 CMPT 310 EE104 F 2C P20 ALY2010 BUSM060 STA258 ECO00030M R BIOSTAT 274 COS6012-B FIT3155 CMPUT 340 EC421 INFS4205 ECOM135 NATS 1740 COMP809 MBE 6005 STA465 CSSE2310 CIVL2700 DATA4700 CMPSC 473 ISE 529 CS5044 MAST30020 COMP2207 ENGG1001 COMP0046 FIT3165 STAT GR5241 MECH0007 vATHK1001 ANALYTIC ATHK1001 MATH352001 HW3 S1 BMAN 24662 COMP 636 Stat-461 STAT 302 STAT 2132 STAR534 ENG4137 CMP3752M CS3103 BISM3222 STA 135 ME155A IIMT3601 ECON3371 ECON 3371 HW4 FINA 5840 DT211C CTEC3902 MAT005 MATH2148 S261F Econ 332 MATH3734 MIS41270 7CCMFM13 SYST 664 CIS434 CENG10014 MT4111 MT4527 ECMM424 CMT219 Math 136 MATH 3120 COMP10002 MAST20009 MATH0058 BEEM117 ISYE 6420 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