Comm215/Sections AA and D Fall 2021 DAP.

• DAP Report Submission/Uploading deadline before 23:59:59 on the December 7^th, 2021.

Objectives In the DAP:

The data analysis assignment is designed to apply the basic statistical concepts learned in the course. You will be using techniques learned in this course in an applied setting. This project contains Region_X_Property.xlsx an EXCEL filedataset.

Important Points:

Software : You can use Excel with add-ins or MINITAB.

Must be typed & uploaded as a PDF file.

To be completed in groups of 5 people (all must be from the same Section)

• Due date
• Before 23:59:59 on the December 7^th, 2021.
• Uploaded Via Moodle as an Assignment for each individual Section

Your submitted work should contain the following;

• 1- Cover page's with a title includes the group's Section
• 1. Introduction: The introduction explains what you are doing and why within the context of your analysis. Give a description of the nature and the scope of the case, the importance of the problem and the need for its resolution.

Last Name Alphabetically

First Name

Student ID

2 - Table of content

3 - Your report, containing three brief paragraphs.

1. Discussion: The discussion presents the results to the questions asked below (in the order in which they asked). You may refer to any tables, charts, illustrations you have included in your appendix (see below).

1. Conclusion: The Conclusion draws inference about your results, and it is also where it will become clear if you have learned your material. Show what you know by giving insightful and relevant explanations of your results as well as any recommendations you may have. Use the results from asked questions to build a relevant story that will become yours.

Appendix- include all relevant tables, charts, results and illustrations required to answer the case questions and arrive to conclusion(s).

These must be organized in the order in which each question appears and Labelle with a brief and clear explanation below each table, charts, and results.

Finally the DAP printout should not be more than 12 pages in total.

You should copy and paste only the relevant results, such as graphs, charts, tables,...findings,... and illustrations. Not raw data.

NOTE!

Theprofessorreservestherighttodeductsomeorallpointsfromagroupprojectwhichdoesnotadheretotheabovecriteria

PleaserefertoyourcourseoutlineandreviewthesectionregardingAcademicIntegrityandPlagiarism!Some examplesofplagiarismare

o Copyingdirectlyorimproperlycitingtheworksofothers

o Participatedinunauthorizedcollaboration

o Payingtohavetheprojectcompleted

o Acceptingpaymentinordertoincludenon-participatingmembersintothegroup.

Grading Method:

Typed, Calibri & Font size 12pt.

1% for one page report on the analysis, including the final mathematical model

of the Total Value including the predicted value.

The remaining 7% goes for the 7 questions.

Project Description:

The Region_X_Property.xlsx dataset contains the following variables.

List of Variables:

Total Value, Land Value, # Acres Land Area, First floor Sq. Feet, Out door Condition, Heating System, # Rooms, # Bedrooms, # Completed Bathrooms,# of Uncompleted Bathroom and # Fire-place.

A Real Estate Company - REC, has hired your team as a consultant group to know what are the significant factors that influence determining the Total Value of a property in the

Region. In doing so REC expects your team to come up with a mathematical model to make reasonable projections of properties Total Value in the Region.

To complete this project your team members are given a random sample of 80 properties whith the following variables collected for each property:

Total Value, Land Value, # Acres Land Area, First floor Sq. Feet, Out door Condition, Heating System, # Rooms, # Bedrooms, # Completed Bathrooms,# of Uncompleted Bathroom and # Fire-place.

In your case study compute the 7 relevant questions (but you are not limited to)

1

Perform a comparative analysis of the Total Valueof houses up to 140,000 (List A) with those of at least 140,000 (List B), show the List with the less variable.

In your analysis, at least these three features should be explained ;

Shapes,... any outliers, measures of central tendencies and measures of dispersions. Interpret the results in the context of the problem

2

Use an appropriate graph to display Total Value (when n=80), interpret the shape and identify any outliers. Plot the Outside Condition,explain the scale of measurement for this variable also show the average for the Outside Condition.

3

Setup a contingency table between Heating Systemand # of Fire-place. Is there a significant relationship between these two variables( use =0.10). For those houses with at least 2 fire places set up a 95% confidence interval for the proportion of properties heated by the Natural Gas system.

4

At =0.10 test REC claims that in Region _X mean Land Valueis more than 15% of the average Total Value( based on the given data set).Explain your conclusion in the concept of the problem use the p- value approach. With the significant level set at 10% how strong sample evidence supportsREC's claim.

5

Perform a simple linear model between Total Value and # of Rooms (model 1) also

Total Value and First floor Sq.F (model 2). Which one of the two models do you recommend to REC and why?

6

Construct a correlation coefficient matrix, is there any multicolinearity problem

among the independent variables? If so show the two most strongly correlated variables.

7

Perform a multiple linear regression analysis between Total Value and the following list of predictors:

Land Value, Land Area, First floor Sq. Feet, Heating System, # Rooms, # Bedrooms, # Completed Bathrooms,# of Uncompleted Bathroom.

i) At = 5%, show whether the overall model is statistically significant.

ii) At significant level of =0.0 1 which variable (s) is (are) insignificant why?

Choose your final/cleaned modelto predict the Total Value for a house in Region _X with a Land value of 50,000$, 1000Sq.f, 1 Completed Bathroom and 1 Uncompleted Bathroom.

.. . AutoSave O OFF A A C ... Region_X_Property Insert v Ex AP- O. Arial v 10 AA ap Wrap Text v General Delete v Conditional Format Cel Sort & Find & Analyze Sensitivity Paste BIUV vAv Merge & Center $ ~ % " Formatting as Table Styles Format v DV Filter Select Data X fx U V W G H K M N O P Q R S T B C D E No. Listing Property Land Values # of Acers # Sq Feet Outdoor Heating # Rooms # Bedrooms # Completed # Uncompleted # Fire-place Land Area First Floor Condition System Bathrooms Bathrooms Total Values 199657 63247 1.63 1726 Good NatGas -ON 78482 38091 0.495 1184 Good NatGas 11996 37665 0.375 1014 Good Electric 116492 0.981 1260 Average Electric AAUAWWNA OO VOU A WN 54062 131263 61546 1.14 1314 Average NatGas V - W WW N NN-N O LO OO VO UI A W N - O - O N NO - O O O - 24412 97177 3.24 1040 Good NatGas 240777 83702 1.942 1752 Good NatGas 381984 84504 .377 2504 Good NatGas 11 137275 88754 3.65 708 Good NatGas 12 131625 58480 1.2 1776 Good Electric AW + 13 11 74365 35353 0.29 984 Average NatGas 14 12 1 18467 40717 0.5 926 Good Electric 15 13 100944 50042 .81 1160 Good NatGas AUINAWA 16 14 127615 81927 3.7 1122 Average Electric 17 15 235286 62396 0.92 1837 Good NatGas -NNON- 18 16 205589 62803 1.208 553 Excellent Electric 19 17 178 8 86 107161 5.88 986 Good Electric 18 100300 39329 0.459 1996 Good Electric 19 80822 44419 0.691 716 Average NatGas 20 100377 45613 0.882 1132 Good NatGas 21 96674 48972 0.93 988 Good Electric 22 115583 48014 0.891 960 Average Electric 23 94439 42148 0.69 Good Electric 26 41843 75824 3.52 990 Good Electric 27 14575 69807 1.7 1025 Good Electric J N J J - - N O N N - - - W W N N - N N W N N W - - - NO - O - N W - N - NONONW - N- 28 229835 65240 .048 2444 Good Electric VUA W W N NW WO WA WAWNNA 27 - NA 29 129962 47316 0.797 936 Good Electric 30 131836 51067 0.929 1152 Good Electric 31 190021 77731 1.9 1545 Good Electric 32 30 118687 50154 0.938 064 Good Electric O O - - WO - ONOOON - - - - o o - - 0 0 - 0 0 0 0 0 - - 0 - - 0-- 31 131781 55625 0.948 Average Electric 32 21579 53680 .694 2068 Good NatGas 35 33 243067 89568 3.4 2048 Good NatGas 36 113131 44685 .446 1262 Average NatGas 37 233032 70364 1.5 2040 Good Electric 38 36 375365 17569 3.9 2932 Average NatGas 39 37 156226 59861 0.91 1625 Average NatGas 40 38 175455 63452 0.948 1864 Good NatGas OWN - N - WWNONNACO - NN- -N- 41 39 127922 59020 1.04 1240 Average Electric 42 40 246357 109720 4.3 1456 Good NatGas 43 41 156761 45692 .517 1245 Good NatGas 44 42 211348 69604 1.64 1556 Good Electric 9 45 43 225129 73274 1.79 2626 Good Electric 12 DWAWAAOAUUAA 46 44 205585 68851 1.36 2695 Good Electric 47 45 115919 59123 1.36 921 Average Electric 48 46 2075 47990 0.66 1008 Average NatGas 49 47 99308 41582 0.45 1644 Good NatGas 50 48 274958 07237 4.03 3076 Good NatGas 275280 81200 1 61 2070 Awoman Sheet1 Sheet2 Sheet3 + + 100% ReadyAutoSave OFF C ... Region_X_Property Home Insert Draw Page Layout Formulas Data Review View Tell me Share Comments Arial v 10 AA = 207 a Wrap Text v General Insert v Ex AY- O. Ex Delete v v Z Paste BIUV DVAv E Merge & Center v $ ~ % " 00 -20 Conditional Format Cell Sort & Find & Analyze Sensitivity Formatting as Table Styles Format v DV Filter Select Data L85 X V fx E G H K L M N P Q R S T V W A B 34 32 215791 53080 0.094 20bo Good NatGas 35 33 243067 956 3.4 2048 Good NatGas 36 34 1 13131 44685 0.446 1262 Average NatGas 9 37 35 233032 70364 1.5 2040 Good Electric 13 38 36 $75365 117569 3.9 2932 Average NatGas 12 39 37 156226 59861 0.91 1625 Average NatGas 10 40 38 175455 63452 .948 1864 Good NatGas 8 41 127922 59020 1.04 1240 Average Electric 42 40 246357 109720 4.3 1456 Good NatGas 12 43 41 156761 15692 0.517 1245 Good NatGas 10 44 42 211348 69604 1.64 1556 Good Electric 9 45 43 22512 7327 1.79 2626 Good Electric 12 46 205585 68851 1.36 2695 Good Electric 18 47 45 1 15919 59123 1.36 921 Averag Electric 48 46 120753 17990 0.66 1008 Average NatGas 49 47 99308 1582 0.45 1644 Good NatGas 8 50 48 274958 07237 4.03 3076 Good NatGas 7 - - - NO - o o- o - - - - o o - - wooNoooN- - 51 49 275289 $4399 161 3270 Average NatGas 13 52 50 221695 84396 2 1745 Good NatGas 53 51 343673 105835 3.39 2374 Good Electric 54 52 37425 12571 5.24 1980 Average NatGas 55 53 453744 13122 5.11 3501 Average NatGas 56 361002 85535 2.66 2937 Good Electric 57 55 133180 636 0.918 1746 Goo Electric D V N OO OO OO OO N A NC 58 56 147436 063 1.18 2047 Average NatGas N - - N - N N N W U N N N U N NA - N N N A N NN - A A O N N N W N - N - W W N W N N ACO - NN A W W W AU AU A O W W A V W W O W A A W OV W W W A D O V A O W A W A A O AU UA A OUNUAG N N N N O - - - N J W W N - - N N - N - W W O N O - ON W - W N N - - - - NON N - - - W W NN 59 198935 78935 1.383 1424 Good NatGas 60 177630 73318 2.7 1472 Average Electric 61 59 35117 86193 1.57 Good Electric 62 60 235269 76478 1.48 1440 Good NatGas 63 6 212037 800 1.52 1952 Good Electric 64 62 232209 77656 1.39 1736 Good Electric 65 03387 41716 0.56 1572 Average Electric 66 360643 2663 5.54 2460 Good NatGas 67 65 30118 71931 1.5 2900 Good Electric 68 153487 49241 0.79 1662 Good NatGas 69 25348 57948 0.862 1720 Good Electric 70 68 257037 57489 0.95 2004 Excellnt Electric - -O O - O O N- ONN- 71 6 136272 15306 0.57 1508 Good Electric 72 70 159669 50301 0.96 2104 Good NatGas 73 71 238888 57166 0.865 1628 Good NatGas 74 72 239024 76711 1.38 2092 Good Electric 75 73 128589 56753 1861 Average NatGas 76 74 145493 1866 0.73 1864 Good NatGas 77 75 140461 44464 0.39 1698 Average Electric 78 76 106124 39078 0.37 1142 Good NatGas 79 77 125425 $7036 0.342 1052 Good Electric 80 78 187903 0.461 2214 Good Electric - - N- - 46169 81 79 111602 41400 0.68 1598 Good Electric 82 80 18725 65899 1678 Good Electric 83 84 Sheet1 Sheet2 Sheet3 + + 100% Ready