Engineering Management, Information, and Systems...

2004-08 Spring 2004

Dallas Central Appraisal District: Property Valuation

Project

Mark Haddad, Tim Hampton

Dallas Central Appraisal District Property Valuation Project

EMIS 4395 May 6, 2004

Mark Haddad Tim Hampton

Engineering Management, Information, and Systems Department

Southern Methodist University School of Engineering Dallas, Texas 75275

CONTENTS

I. Management Summary

II. Background and Description of Problem

III. Analysis of the Situation

IV. Technical Description of Model & Analysis

V. Conclusion and Critique

VI. Univariate Statistics and Model

VII. Definitions of Variables

VIII. Output

I. MANAGEMENT SUMMARY

The goal of our project was to build a model that can accurately valuate

residential properties for the Dallas Central Appraisal District. We were able to create a

valuation model through the Statistical Analysis System (referred to as SAS from here

on). The process involved us building a model that would valuate Addison singe family

homes, and give output in price. We would then compare our results with the actual sales

price of the particular home, which would have been sold in the past three years. We then

worked to improve on the model by eliminating extremities, and redefining our

population. Our goal was to create the most accurate model possible. We ended up testing

the model on 144 homes in the city of Addison. All of the homes were of similar stature

due to the extremities that we left out. Through repeated trials, we were able to create a

model that had a mean error of $1230 from the sales price of the home. This means that

when comparing the property price from our model to the 144 different prices the homes

were sold for, the average error was $1230. The most accurate of our valuations had a

difference of only $189.44.

II. BACKGROUND AND DESCRIPTION OF PROBLEM

By "Accurate," we mean having the smallest margin of error possible in

comparison to actual sales price data. Many valuation models exist today and their

effectiveness is measured by how close it can get to actual sales data. Error method is

determined, based on how close a model is to the actual prices each home was sold for.

Different models can be run on the same property and can yield different results. The

Dallas Central Appraisal District has their own method of home valuation. They compare

homes with similar homes around them, and try to find the closest resembling property.

This is called a "comp." The comp is then adjusted based on factors that may vary, e.g.

an extra bedroom, and the property's value is assessed. However, it is debatable whether

the DCAD or any appraising board would correctly be able to determine the value of a

bedroom, or an extra master bath. If, however, a model can be determined that can price a

property by the square foot, it would be valuable in being able to assess the correct value

on a comp for an appraiser using this method, or in valuating the entire home in itself.

Important to note, is that no model is perfect. It is impossible to judge the exact

value of a home down to the dollar. Models instead are judge on effectiveness by margin

of error through repeated trial usage under different samples of properties. Industry

standards say a good model is said to be within 10% of the sales price more than 50% of

the time. If it is with in 20% of the sales price, 90% time, this qualifies a decent model.

Upon first assessment of our project, we noticed that we had vast amounts of data,

spread out over Dallas County. Dallas County contains a huge area, and is very diverse. It

consists of many different cities, with extreme variations in different properties.

Examples of variations include size, age, and city code. It contains eleven

different school districts. A simple comparison can yield a newly built mansion in

Highland Park, ten thousand square feet, to a small house in south Dallas, built thirty

years ago, seven hundred square feet in size. This is too huge of a variation, and we

therefore had to break the data down into smaller pieces to be able to better valuate.

Location is the most important factor in property valuation. Homes vary due to

the city they are classified as being in more than for any other factor. Two homes of the

same size, age and number of rooms, can differ by thousands of dollars due only to the

fact that one is located in Dallas while the other is located in Highland Park. This actual

scenario, which exists today, is known as the "Highland Park Factor." An example was

given to us in which two otherwise equal homes, separated by a freeway and a city line,

differed in price of $150,000. Reasons for this include the different ISD's (independent

school districts) that the homes belong to, the different average police response times,

and of course the ability for the owner to tell the guys on the golf course that he has a

place in Highland Park versus a place in Dallas. (This is a seldom discussed but very

powerful valuation tool all in itself). The location factor is present in properties all over

the country, and is the reason we had to eliminate this great variation to get started on

building a reasonable model.

III. ANALYSIS OF THE SITUATION

We were originally supplied data through Professor Tom Thibodeau, who teaches

real estate finance at the Cox School of Business. The data set contained prices for every

property in Dallas County, both residential and commercial, and was originally obtained

from the Dallas County Appraisal District. The data was incredibly vast, covering too

many variations in properties. It consisted of both residential and commercial properties.

The location factor in itself was too great to overcome. We realized we would be unable

to create an accurate valuation model in a few months, so we chose one city to look at.

By using Addison as our test city, we were able to eliminate many extremities.

Addison is a fairly "new" city when compared with others in DC. Most homes are of the

same age (or in a close proximity), being less than thirty years old. The average square

foot of an Addison home is 2,196. Other factors also help to narrow down variation:

There are only two IDS in the city, the homes have the same community college, they are

subject to the same city and county tax, and they all share the same police and fire

department.

Our model is set to look at what one might consider a "typical" home. This means

that they were single family homes of similar size and shape, and they all shared similar

features, both internal and external. All of the houses had attached garages. We were able

to filter out all homes that did not fit this basic form. This is discussed in further detail

later. This method of valuation allowed for the most precise model to be run, in that we

did not have many varying features skewing up the model and throwing it off. We were

thus able to focus on the actual error itself, instead of having to attribute much of it to

variation error.

IV. TECHNICAL DESCRIPTION OF MODEL & ANALYSIS

We first came up with a very basic formula, taking the square foot of a home and

multiplying it by $165. We obtained this number by taking the average price per square

foot off of ten residential Addison properties sold (DCAD data). Average price per square

foot = $Price of property / number of square feet. We then ran our model versus the

Addison properties selected and took the mean error, which was computed by comparing

the prices the model gave to the actual sales data of a ten home sample.

The mean error is the average error in price (our model's price versus the price

the property sold for) over the ten properties. Our mean error came to be $79,081.50,

which is an enormous error. A model that is off an average of almost one hundred

thousand dollars is not something that many will want to use to valuate a home.

We then ran our data through SAS, using univariate analysis to explain the data.

Univariate analysis is a form of statistics that will look at each variable and analyze it,

versus looking at all data input and summarizing it (which is known as descriptive

statistics). UA takes into account the range as well as the central tendency of all the

values, and then describes the pattern of response to each variable. This worked to our

advantage being that we could analyze and understand our model in pieces, and look at

the effect of each factor, versus seeing how it ran as a whole.

We then created a stem and leaf plot of the results of our model.

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As shown, outliers can throw off the model, by skewing the error mean. We

therefore moved to throw out any outliers that are of extreme value. This would allow us

to reduce error mean and run more accurate models in the future. Doing so was easier

said then done. From there, we added PROC codes that would filter out data that was not

close to our "typical home" model. We deleted any home with living area greater than

5000 sq ft. We figured any home of this size is too great. We threw out any homes with

prices less than $10,000 or greater than $5 million. This also would not be considered

typical among our standards and would work against our model.

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are not going to have a significant effect in our model, and may, in fact, skew the results.

We also set a wet bar limit. Having one wet bar versus not having one had a significant

impact on the model. However, having additional wet bars did not have very much

effect. Therefore we changed any home with more that one wet bar, to be viewed as a

home with only one. The same was done with pools. What we were doing is setting the

pool and wet bar value as binary, which acts like an on/off switch. This means they are

based on either being there and having an impact, or not being there. They were not based

on a number as the other variables were. Each variable (sq ft, age, pool) was given a

coefficient value, and that value was run through our model to come up with a result

called yhat. Yhat then has its exponent taken, and is subtracted from the DCAD sales

price of the home to give us our error.

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We had to take into account the year of sale, for that can have a great impact on

property valuation. Aside from everything, the economic factor is a very important and

needs to be accounted for. The general prices of real estate rise and fall with movement in

the economy. Interest rates and market forecasts can have profound effects on property

valuation. The general trend is that when interest rates fall, the prices of homes rise, and

vice versa. Property is also generally on a rising trend when looked at decade by decade.

To account for these economic factors which have fluctuated prices over the years, we

only took homes sold after 2001 into account, in order to reduce any error could result

from time and economic factors.

We also went through the Addison data and threw out any values that seemed to

be errors. Some values just did not make any sense (e.g. a 246 sq ft home), and were thus

eliminated. Some homes did not have a sales price, either because they had never been

sold, or due to input error. Stored as ".", these were filtered out with all other error

values.

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We then reran our model and measured our error versus the previous model. The

residual was then plotted. It had improved from before. However we still saw outliers

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with the raw data supplied, and our model is run and compared to the actual sales prices

of the homes. The model is tested against 144 properties in Addison. The price per square

foot is given. What our PROC does, is come up with a number that each year of age takes

off of the price of the home. It then goes on into the other variables, stating how much

more valuable per bedroom, how much per bathroom, the value that a pool brings, the

value that a wet bar brings, etc. The results are then displayed, showing the account

number, sales price, and yhat price (our model price) for each property.

If. CONCLUSIONS AND CRITIQUE

We were able to successfully formulate a model that can accurately price single

family homes in the city of Addison. The original data covered the entire city and thus

had too much variation to build a small scale model. We therefore isolated a certain

category of homes which we called "typical" and attempted to run our model on them:

Through repeated trial and error, we were able to reduce the effect of outliers, which

were distorting our model. Homes with extreme values were deleted, and others had

variables changed in order to better run with our model. We also eliminated any errors

present in the data given to us by DCAD. We narrowed down our population to 144

homes and ran our model finally achieving normal distribution among the output. All

properties had been sok since 2001 to reduce time and economic factor variation. Our

mean error was $1230, meaning an average difference of $1230 between our model and

the last sales price of the property. Our recommendations for further improvement of the

model include reducing the physical size of the location variables to allow for more

accurate results. Another is reducing the area of the population, running the model over

city blocks or smaller grids instead of on an entire city. This would further reduce error

due to variation, and allow for a smoother running model. Further improvement could be

reached through the addition of proximity variables, which are variables that can offset

the price of the home depending on how close they are to a property. Examples are

parks, lakes schools, and police stations.

Our model is fairly easy to run and apply by the user. It is programmed in a way,

which would allow updates fairly easily, which is an important feature in a model where

constantly changing variables and factors need to continuously be updated.

LIBNAME DCAD 'C:\TEMP\DCAD ';

TITLE Input DCAD Master;

DATA DCAD . addison; set DCAD.master02; if X611 eq 'CA' and Xii eq 111 then output;

run;

PROC contents;, run;

1* PROC FREQ;

TABLESX8 Xii X12

X13 X14 X39 X147 X157 X158 X159 X160 X161 X162 X163 X164

X165 X166 X167 X169 X171 X175 X177 X178 X184 X187 X188 X194 X218 X219 X229 X546 X550 X554

X610 X611 X613 X615 X617 X632 X634 X636 X638 X640 X642

RUN;'

PROC UNIVARIATE; VAR

Xi45 Xi49

X208 X222 X225 X547 X548 X551 X552 X555 X556 X558 X559 X560 X561 X562 X563 X564 X565 X566

X628

run;

DATA temp; set DCAD.addison; price x558; livarea = x145; if livarea > 5000 then delete; age = 2001 - x149; baths = x166 + 0.5*xi67; if baths gt 5 then baths = 5; firepi = x218; wetbar = x219; if wetbar gt 1 then wetbar = 1; pool = 0; if x225 > 10 then pool = 1; if price eq then delete; if price < 10000 then delete; if price > 5000000 then delete; year = 10000* (x559/10000 - mt (x559/10000)) if year it 2001 then delete; lnprice = iog(price);

mergvar run;

PROC univariate; var price livarea age

run;

PROC freq; tables baths firepi wetbar pool year x177 x178 x184;

run;

PROC contents position; run;

PROC reg DATA=temp; model inprice = livarea age baths firepl wetbar pool; output out=outres

r=residual; run;

PROC univariate PLOT NORMAL DATA=outres; var residual;

run;

DATA temp2; set outres; if abs(residual) > .3 then delete;

run;

PROC reg outest= beta DATA=temp2; model lnprice = livarea age baths firepi wetbar pool; output out=outres2

r=residual; run;

PROC contents DATA=beta; run;

PROC print DATA=beta; run;

PROC univariate PLOT NORMAL DATA=outres2; var residual;

run;

DATA temp3 (KEEP=intercept blivarea bage bbàths bfirepl bwetbar bpool mergvar);

set beta; blivarea = livarea; bage = age; bbaths = baths; bfirepl = firepl; bwetbar = wetbar; bpool = pool; mergvar

run;

DATA temp4; merge temp2 temp3; by mergvar;

inyhat = intercept + blivarea*livarea + bage*age + bbaths*baths + bfirepl*firepl + bwetbar*wetbar + bpool *pcl

yhat = exp (inyhat); prederr= price - yhat;

run;

PROC univariate PLOT NORMAL;

var price yhat prederr; run;

PROC print DATA=temp4; var XO price yhat livarea age baths;

run;

DATA temp5; set temp4; if XO eq '100043200A0020000' then output;

run;

PROC print; run;

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DALLAS CENTRAL APPRAISAL DISTRICT

File Description: FOAMFI

Appraisal Master File

Record Length=2406 Version: 08

Page 1

2/2 /1z Date: 4-19-2000

Field Name Type Lgth Columns Comments

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DALLAS CENTRAL APPRAISAL DISTRICT Page 2

File Description: FDAMFI


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DALLAS CENTRAL APPRAISAL DISTRICT Page 3 File Description: FDAMFI




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LGL-BLK-NUM-AMFI

-

AN 05 01+69-01+73 -

FILLER AN 01 0471+-01+74

LGL-BLK-SUFF-AMFI AN 03 01+75-01+77

FILLER AN 01 01+78-0478

LGL:BLK_OVFLAMFI AN 15 01+79-01+93

F ILLER AN 08 01+94-0501

LEGAL-DESC-5TH-AMFI AN 33 0502-0534

LGL5-MAP-PLAT-CITY-LEGL-AMFI AN 11+ 0502-0515

FILLER AN 11 0502-0512 SEE COPYBOOK FOR

LGL5-ALT-KEY-LOT-AMFI AN 03 0513-0515 FURTHER BREAKDOW

FILLER AN 08 0516-052.

LGL5-AL T-KEY-REGIO N -AMFI ZO 01 0524-0524

LGL 5- ALT- KEY - CITY - AMFJ ZO 02 0525-0526

LGL5- ALT - KEY - AODTI ON - AM FI AN 05 0527-0531 L G L5- ALT - KEY - CNTY -BLO C K- AMF AN 03 0532-0531+

Notes;AN=alphanumeric, NU=numeric, PDpacked decimal, ZD=zoned decimal



Page 4



Record Length=2 1+06 Version: 08

Date: 4-19-2000


I S

S I

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S

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• I

•

ADDRESS-CORRECT-AMFI AN 01 0535-0535

JDT-AMFI PD 05 0536-0540 CURRENT SALES DATE; MMDDYYYY

PREV-JOT-AMFI PD 05 0541-0545 PREV SALES DATE; MMDDYYYY

PREV2-JDT-AMFI PD 05 0546-050 PREV2 SALES DATE; MMDDYYVY

RESI-COMPSALE1-SALE-DATE PD 05 0551-0555 EXPANDED GREGORIAN; MMDDYYYY

RESI-CCMPSALE2-SALE-DATE PD 05 0556-0560 EXPANDED GREGORIAN; MMODYYYY

RESI-COMPSALE3-SALE-DATE PD 05 0561-0565 EXPANDED GREGORIAN; MMDDYYYY

FILLER AN 19 0566-0584

PREV-ACCT-MKT-VAL-AMFI PD 06 0585-0590 ACCUM-CONTRIB-VALUE-AMFI PD 06 0591-0596

-----------------------------

FILLER PD 03 0597-0599

JOURNAL-ENTRY-AMFI - ZD 03 0600-0602 --

DEED-CHANGE-AMFI AN 01 0603-0603

WKSHT-PRINT-SWITCH-AMFI AN 01 06o4-06Q4 ' '-NOT PRINTED,'l'-PRINTED

CUR-NAME-BUS-ESTAB-AMFI AN

-

50

--- -

0605-061,

- ----- -- 1 ---------- -' EL

LAND-AREA1-AMFI PD 04 0656-0659

_

-- FRONTAGE]-AMFI PD 04 o66o-o63

LAND-DEPTH1-AMFI - PD oh 0664-066'

LAND-PRICE1-FLAG-AMFI AN 01 0668-0668 'F'-FLAT 'A'-ACRE,'S'-SQFT, 'R'-FRONtAGE.

PRICE-OF-LAND1-AMFI PD 05 0669-06 7.1. S9(9)V99

LAND-AREA2-FLAG-AMFI AN

---------------------------------

01 0675-0675 'A'-ACRE,'F'-SQFT ' ' FLAT PR

LAND-AREA2-AMFI PD 04 0676-0679

FRONTAGE2-AMFI PD 04 0680-0683

LAND-DEPTH2-AMFI PD 04 0684-0687

LAND-PRICE2-FLAG-AMFI AN 01 o688-o688 'F'-FLAT, 1 A'-ACRE, 'S'-SQFT, 'R'-FRONTAGE.

PRICE-OF-LANO2-AMFI PD 05 o689-0'694 S9(9)V99

LAND-AREA3-FLAG-AMFI AN 01 o695-o65 'A'-ACRE,'F'-SQFT ' ' FLAT PR

LAND - ARE A 3-AMFI PD 04 0696-0699

-- FRONTAGE 3- AMFI PD 04 0700-07.C3

L AN D-DE PTH 3- AMFI PD 04 0704-0707

LAND-PRICE3-FL AG- AMFI AN 01 0708-0708 'F-FLAT, 'A'-ACRE, 'S'-SQFT

Notes;ANalphanumer Ic, NU=numeric, PO=packed decimal, ZD =zoned decimal


..

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I S S

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Record Length=2406 Version: 08 Date: 4-192000


:•. 'R'-FRONTAGE.

PRICE -O F -LANO3- AMII PD 05 0709-07 114 S9(9)V99

LAND-AREA4-FLAG-AMFI AN 01 0715-0715 'AACRE,'F'SQFT' ' FLAT PR

LAND-AREA+-AMFI PD 014 0716-0719

FRONTAGE I+-AMFI PD 014 0720-072.3

LAND-DEPTH I+-AMFI PD 014 0724-0727 -

LAND-PRICE4-FLAG-AMFI AN 01 0728-0728 'FFLAT 'A'-ACRE,'S'-SQFT, 'R'FR0NiAGE

PRICE-OF-LAND4-AMFI PD 05 0729-0734 S9(9)V99

LAND-PERCENT-ADJ-FLAG-AMFI AN '

LAND-PERCENT-ADJ-AMFI PD 02 0736-0737__

LAND-DESCRIPTION-AMFI AN 01 0738-0738

ALPS-ADJ-PRICE1-AMFI PD 05 0739-0743 S9(7)V99

ALPS-ADJ-PRICE2-AMFI PD 05 0744-0748 S9(7)v99

ALPS-ADJ-PRICE3-AMFI PD-9:9? __

--------------------------

ALPS-ADJ-PRICE4-AMFI PD 05 07514-0758__________________

S9(7)V99

ALPS-SOIL-TVPI-AMFI ZO 01 0759-079

ALPS-SOIL-TYP2-AMFI ZD 01 0760-0760

ALPS-SOIL-TYP3-AMFI ZD 01 0761-0761

ALPS-SOIL-TYP14-AMFI ZO 01 0762-0762

TOPOGRAPHY-AMFI AN 01 0763-0763 'L'-LEVEL 'S'-SLOPE 'H'-HIGH, 'D'-LOW, 'A'-ROUGH, 'ó'-OTHER.

STREET-COND-AMFI AN 01 0764-0764 'D'-DIRT, 'G'-GRAVEL, 'A'-ASPHALT 'C'-CONCRETE, 'U'OR ' '-NoT ENTERED.

STREET-CURB-AMFI AN 01 0 7 65-0765 1Y1 - YES , 1N1 - NO ,' '-NOT ENTERO

STREET-GUTTER-AMFI AN 01 07 66 -0766 'Y'-YES,'N'-NO,' '-NOT ENTERO

SIDEWALK-AMFI AN 01 0767-0767* 'Y'-YES,'N'-NO,' '-NOT

ALLEY-AMFI AN 01 0768-0768 Y'-YES,'N'-NO,' '-NOT

WATER-AMFI AN 02 0769-0770 'NO'-NONE, 'WW'-WELL, 'PW'- PUBLIC,' '-NOT ENTERED.

GAS-AMFI AN .01 0771-077 1 'Y'-YES,'N'-NO,' '-NOT ENTERD

ELECTRICITY-AMFI AN 01 0772-077.2 'Y'-YES,'N'-NO,' '-NOT ENTERD

FILLER AN 01 0773-0773

WASTE-DISPOSAL-AMFI AN 02 0774-077 'SW'-SEWERAGE, 'ST-SEPTIC,

Notes;AN=alphanumer Ic, NU=numeric, PD=packed decimal, ZD=zoned decimal


I T I A L

AN

PD

AN

Z

AN

BI

PD

PD

AN

AN

PD

PD

AN

AN

AN

CONS RUCTION A

OLe 0776-0779

01+ 07800783

04 0784-0787

01 0788-0788

02 0789-0790

02 0791-0792

03 0793-0795

06 0796-0800

04 0801-o.865

01 o8o6-o8o6

05 0807-0811

02 0812-081-3

02 081 1+-081;&

0816-0817

02 08i808;'19

AN 02 0820-o82

AN

ANI I'BV'-BRICK/VENEER, 'BR'-BRICK,

'SN'-STONE, 'BC'-BRICK/COMMON 'BP'-BRICK/PRESS, 'SL'-STEEL, 'ST'-ST.UCCO, 'SV'-T0NE/VENEER, 'SM'- SOLID/MASONRY 'FR'-FRAME 'AS'-ASBESTOS , 'CR'-COMP/ ROLL, l wD I WOQô/sHINGLES T WB'-WEATHER/BOARD 'AL'- ALUMINUM ,'FB'-FIBERBOARÔ,'CB'-CONCRETE,'CT'- CONCRETE/TILE 'VY'-VINLY,'MA'-MASONITE,'SS'-STUCO 'CL'-CLAY, 'PS-PERMAST0NE, 'BX'-BOX SHINGLES, 'BB'- BOX ATTEN.

AN 02 0825-0826 ** SAME AS WALL1-AMFI **

---- - AN 02 0827:0828. 'HP'-HIP,'GA'-GABLE 'SH'-SHED

FL'-FLAT, 'MA' -MANS RO, 'GL'-GAMBREL'SB-SALT BOX 'IR'-IRREGULAR, 'SW-SAWTOOTH, 'TW'-TUSS/WOOD, 'IS' -TRUSS/STEEL, 'CD' -CUTUP/DORMER

.d

---- ---------

01 0822-0822

02 o823-OA

'F '-F INISHED, 'U' -UNFINISHED

I ..

•

I

S

I

S

S

S

S S S

S

•

RE S 1 DEl

F I LLER

LIVING-AREA-AMF I

FILLER

NUM-OF-L lvi NG-UN I TS-AMF I

F I LLER

YR-BUILT-RES-AMF I

REVAL-PCT-FACTOR-AMF I

CONTRI B-PERMIT-VALUE-MW I

F I LLER

BLDG-PRICE -FLAG-RES-AMF I

BLDG-PRICE-RES-AMFI

BLDG-DEPRE-RES-AMF I

CONSTRUC-MATER-AMF I

FRAMEWORK-RES-AMF I

FOUND-RES-AMF I

BASEMENT-RES-AMF I

BASEMENT-COMPLETED-RES--AMF I

EXT-WALL1:AMFI

EXT-WALL2-AMF I

ROOF-TYPE-RES-AMF I

Notes:

'-NOT ENTERED.

ID SIZE

BINARY; YYYY

USED TO MASS REVAL BY NHBD

'U'-UNIT, 'F'-FLAT

'BR'-BRICK 'ST'-STUCCO, 'VN'VENEER, '0T-OTHER.

'MS' -MASONRY ''-METAL, 'CC'-CONCRET, 'FR-FRAME, 'W-FACTORY

'SL'-SLAB 'PB'-PIER/BEAM 'GB'-GRAT/BEAM, 'PT'-POSf, 'BL'-BLOCK, ' IP'-IRON PIPE, 'W-GIRDER/GRAVEL, 'FS'-SUPPORT, 'BR'-BRICK, 'ST-STONE.

'OO'-NOT ENTERED 'NO'-NONE, 'PA'-PARTIAL, IFUt_FULL.

DALLAS CENTRAL APPRAISALDISTRICT

Page 6

File Description: F. DAMFI


Record Length =2406 Version: 08

Date: 4-19-2000


AN=alphanumeric, NU=numeric, PD=packed decimal, ZDzoned decimal


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DALLAS CENTRAL APPRAISAL DISTRICT Page 7 File Description: FOAMFI


Record Length=2406 Version: 08 Date: 4-19-2000


ROOF-COMP-RES-AMFI AN 02 10829-0830 I IICP'-COMPOSITION,'TN'-TiN,

'CS'-COMP)SHINGLE,'WD'-WOOD,'SK'-SHAKE 'AS'- ASBESTOS, COPPER, 'ci

'TL'-TiLE 'AL'-ALUMINUM 'SE'-LATE, 'CO'- '-00RR/IION, 'CR'-ROLL/?OMP, 'TG'-TAR

GRAVEL.

RESIDENTIAL PLUMBING AND HEATING

BATH-FULL-RES-AMFI PD 02 0831-0832 BATH-HALF-RES-AMFI PD 02 0833-0831+ PLUMBING-FILLER] AN 06 0835-081+0

KITCHENS-NUM-AMFI ZO 01 0841-0841

FILLER AN 01 042-o812

AC-TYPE-AMFI AN 02 043-0814'CF-CENTRAL/FULL, 'CP'-CENTRA

L/PA TIAL, 'WI '-WIltD W, 'WL'-WALL, 'NO'-NONE, 'CS'- COOL NG $ M.

FILLER AN 03 0845-0847

HEAT-AMFI --------------------------AN 2'CF-CENTRAL/FULL, 'CP'-CENTRA

L/PA hAL, 'CG'-CENT AL/GRAVITY, 'FF'-FLOOR/FURNACE 'WL'-WALL,'RT'-RADIANT,'RR'-RADIATOR, 'GH'-STOVE/ GAS/ UTAN/WOOD, 'NO' -NONE.

FILLER -

RESIDENTIAL GARAGES AND CARPORTS

GARAGE-PORTI-AMFI AN 01 0910-0910'G'GARAGE, 'C'-CARPORT

GARAGE-STALLS1-AMFI PD 02 0911-0912

GARAGE-PORT1-AREA-AMFI PD 03 0913-0915 GARAGE-PORT1-OEPRE-AMFI PD 02 0916-0917

GARAGE-PORT1-PRFLG-AMFI AN 01 0918-09l8 'F'-FLATPR,'U'-UNITPR.

0919-0925

GARAGE-PORT1-PR-AMFI PD 03 0926-0928

— -----------------------------

GARAGE-PORT1-LOC-AMFI AN 02 0929-0930 'AT'-ATTACHED, 'DT'-DETACHED

GARAGE-PORT l-MAT-AMF I AN 02 0931-0932 BK' -BRIcK, 'FR' -FRAME,111 IILIAL.

GARAGE-PORT1-FLOOR-AMF I

AN

02 0933-0931+ 'OF-DIRT, 'CF'-CONCRETE

GARAGE-PORT2-AMFI

AN

01 0935-0935 'G'-GARAGE, 'C'-CARPORT

GARAGE-STALLS2-AMF I

PD

02 0936-0937

GARAGE-PORT2-AREA-AMF I

PD

03 0938-09L+Q

GARAGE-PORT2-DEPRE-AMF I

PD

02 091+l_091s2

GARAGE-PORT2-PRFLG-AMF I

AN

01 0943-0943 'F'-FLATPR, 'U'-UNITPR

Notes;AN=alphanumer Ic, NU=numeric, PD=packed dcimal, ZD=zoned decimal


09414-0950

0951-0953

0954-0955

0956-0957

0960-0960

096 1-09-62

0963-0965

0966-0967

0968-0968

0969-0975

0976-0978

0979-0980

0981 -0982

- AT'-ATTACHED, 'DT'-DETACHED

'BK'-BRICK, 'FR'-FRAME, 'MT-METAL.

'OF -DIRT, 'CF'-CONCRETE

'G'-GARAGE, 'C'-CARPORT

'F '-FLATPR, 'U'-UNITPR.

'AT' -ATTACHED, 'DT' -DETACHED

'BK'-BRICK, l FR'-FRAME, 'MT' -METAL.

AN

07

PD

03

AN

02

AN

02

AN

02

AN

01

Pa

02

PD

03

PD

02

AN

01

AN

07

PD

03

AN

02

AN 02

S ..

r

S

I

I

S

S

. 1:)

S S

S S

S

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Record Length=2 1+06 Version: 08

Date: 14-19-2000


F I LLER

GARAGE-PORT2-PR-AMF I

GARAGE-PORT2-LOC-AMF I

GARAGE-PORT2-MAT-AMF I

GARAGE-PORT2-FLOOR-AMF I

GARAGE - PORT 3- AMF I

GARAGE-STALLS3-AMF I

GARAGE - PORT3-AREA - AMF I

GARAGE-PORT3-DEPRE-AMFI

GARAGE-PORT3-PRFLG-AMF I

FILLER

GARAGE-PORT3-PR-AMF I

GARAGE - PORT3- L QC - AMF I

GARAGE-PORT3-MAT-AMF I

GARAGE-PORT3-FLOOR-AMFI AN 02 0983-094 'OF'-DIRT, 'CF'-CONCRETE

GARAGE1-UNIT-PSF-AMFI PD 03 0985-0987 'PRICE PER SQ FT GARAGE]'

GARAGE2_UNIT : PSF_AMFI PD 03 0988-0990 'PRICE PER SQ FT GARAGE2'

GARAGE3-UNIT-PSF-AMFI PD 03 0991-0993 'PRICE PER SQ FT GARAGE3'

EST-REPROD-UNIT-COST-AMFI PD 03 0994-096 'PRICE PER SQ FT GARAGE3'

FILLER AN 08 0997-10q4

HS:INDICATOR_AMFI AN 01 1005-1005

HS :PRINTDATE_AMFI PD 05 1006-1010

AG-INDICATOR-AMFI AN 01 1011-1011

AG-PRINT-DATE-AMFI PD 05 1012-1016

SS:INDICATOR:AMFI AN 01 1017-1017

SS:pRiNT_DATE_AMFI PD 05 1ol8-1o2

FILLER - - AN 76 1023-1098

RESIDENTIAL SERVENT'S QUARTERS

SERV-QTRS-AREA-AMFI PD 03 1099-1101

SERV-QTRS-DEPRE-AMFI PD 02 1102-1103

SERV:QTRSPR_UNITAMFI PD 03 11014-1106

FILLER AN 03 1107-1109

Notes:AN=alphanumeric, NU=numeric, PDpacked decimal, ZO =zoned decimal







SERV-QTRS-PR-AMFI PD 04 1110-111.3

SERV-QTRS-AGE-AMFI PD 02 1114-1115

SERV-QTRS-NUM-STORIES-AMFI ZO 01 1116-111.6 - -

FILLER AN 01 111 7- 111 7 - - - -

SERV-QTRS-CONSTR-AMFI AN 02 1118-1119 I FR I: FRAME, 'MS1-MASONRY

SERV-QTRS-LOC-AMFI AN 02 1120-1121 'DT'-DETACHED,'AT'-ATTACHED

RESIDENTIAL FEATURES: FIREPLACES, POOLS, ETC

FIREPLACE-RES-AMFI PD 02 1122-1123

--WETBAR-AMFI PD 02 1124-1125

ELEVATORS-RES-AMFI AN 01 1126-1126 'Y'-YES, 'N-NO

FILLER AN 11 1127-1137

SAUNA-PRICE-AMFI PD 03 1138-1140

FILLER AN 20 1141-1160

POOL-FILLER1 AN 11 1161-1171 **,* UNUSED POOL FIELD ****

POOL-PRICE-RES-AMFI PD 03 1172-1174

-------- --- --------- - -------1!:ii

POOL-FILLER2 AN 01 1177-1177 **** UNUSED POOL FIELD ****

POOL:CONSTR_RES_AMFI AN 02

-

1178-1179 'FG'-FIBERGLASS, 'CC'-CONCRETE 'SL'-STEEL,'VY'-VINYL

RESIDENTIAL ACCESSORY BUILDINGS

ACCESS-BLOG1-AMFI AN 01 1180-1180 :'G'-GREENHOUSE,'B'-BARN 'O'-OUT BUILDING,'M'-MOILE.

ACCESS-BLDG1OESCAMFI AN 25 118I-1205

ACCESS-BLDG1-MAIN-AREA-AMFI PD 03 1206-1268 -

ACCESS-BLDG1-UNIT-PR-AMFI PD 03 1209-1211

ACCESS-BLDG1-FLAT-PR-AMFI PD 03 1212-121Z

ACCESS:BL0G1_PR_AMFI -- PD 03 1215-1217

ACCESS-BLDG1-DEP-TBL-AMFI PD 02 1218-1219

ACCESS-BLDG2-AMFI AN 01 1220-1220 * SAME AS ACCESS-BLOG1_AMFI 'c

ACCESS-BLOG2-DESC-AMFI AN 25 1221-1245 --

ACCESS-BLOG2-MAIN-AREA-AMFI PD 03 1:8

ACCESS-BLDG2-UNIT-PR-AMFI PD 03 1249-1251

ACCESS-BLDG2-FLAT-PR-AMFI PD 03 1252-1254

- ------------

ACCESS-BLDG2-PR-AMFI PD 03 1255-1257

Notes:AN=alphanumeric, NU =numeric, PD =packed decimal, ZO =zoned decimal



Page 10



Record Length2406

Version: 08

Date: 4-19-2000


ACCESS-BLDG2-DEP-TBL-AMFI PD 02 1258-1259

ACCESS-BLDG3-AMFI AN 01 1260-12.60 * SAME AS ACCESS-BLDG1-AMFI *

- ACCESS-BLDG3'-0ESC-AMFI AN 25 1261-1285

ACC E S S- BLDG3-MAIN - AREA - AMFI PD 03 1286-1288

ACCESS-BLDG3- UNIT- PR -AMFI PD 05 1289-1291

ACCESS-B LDG 3- FLAT- PR - AMFI

-

PD 03 1292-1294

-- ACCESS-BLOG3-PR-AMFI

-

PD 03 1295-127 -----------------------------

ACCES S -B LDG3- DEP -TBL - AMFI PD 02 1298-129

RES-NEIGH-COST-FAC-AMFI PD 02 1300-1301

EFF-AGE-NOT-CUR-AMFI PD 02 1302- 1 303 RESIDENTIAL ACTUAL AGE

ALT-NBSSA-REG-AMFI ZO 01 1304-1304

ALT-NBSSA-ISD-AMFI AN 02 1305-1306

ALT-NBSSA-NC-AMFI AN 03 1307-I309

- ALTNBSSA:BLOGCLASSAMFI -PD 02 13l0-111

ALT-NBSSA-BLOG-SUB1-AMF1 AN 01 1312-1312

ALT-NBSSA-SIZE-CO-AMFI PD 02 1313-1314

ALT_NBSSAAGE_CD:AMFI PD 02 1315-1316

FILLER -AN85 ----17:1401

**********

COMMERCIAL CONSTRUCT I 0t1AND SIZE

YR-BUILT-AMFI PD 03 0776-0778

NUM:UNITS:AMFI PD 03 0779-0181

FILLER AN 02 0782-0783

RD-QUESTIONAIRE-FLAG1-AMFI AN 01 0781+-074

-- - - FILLER PD 02 0785-0786

FILLER PD 02 0787-078

- FILLER

-

PD 02 0789-0790

- FILLER - - PD 02 0791-0792

FILLER PD 03 0793-075

CONTRIB-VAL-FILLER PD 06 0796-001

FILLER PD 08 o802-0809

NUM-STORIES-AMFI PD 02 o8io-o8ii

STORY-HT-AMFI PD 02 0812-08.13

BLDGNUMAMFI PD 02 0811p0815

Notes;ANa1phanumer id NU=numeric, PD-packed decimal, ZD =zoned decimal


S.

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.. •)

S

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Record Length=2406

Version: 08 Date: 4-19-2000

Field Name

Type Lgth Columns

Comments

'00'-NOT ENTERED 'NO'- 'PA'-PARTIAL, IFULFULL.

-

AN 01 0853-0853 'F'FINISHED,'U'UNFIN

ZO 02 0854-0855

PD 04 0856-0859

PD 99:9 ________________________________

AN 02 0864-0865 'FO'-YES,' '-NO.

AN 02 0866-0867 'CB'-YES,.' '-NO.

AN 02 0868-0869 'PI'-YES,' '-NO.

AN 02 0870-0811'CS'-YES,' '-NO.

AN 02 0872-0873 'BL'-YES,' '-NO.

AN 02 0874-0875 'BR'-YES,' '-NO.

AN 02 0876-0817 'PO'-YES,' '-NO.

AN 02 0879-0880'WO'-WOOD,'HT'-HEAVY TIMBER,

'ST'-LIGH STEEL, 'S '-STRUCTURE STEEL, 'SC'-STEEL/ CONCRETE, 'RC'-REINFORCE CONCRETE, 'WP'-WELDED PIPE 'P1 '-PILA TERS,'SW'-SOLID WALL

AN 02 0881-0882 ic* SAME ASFRAMEl-AMFI

AN 02 o883-o884'BV'-BRICK VENEER,'SV'-STONE/

VENE R,'S '-STUCCO VENEER 'CB'-CEMENT BLOCK ,'MA'- MARBLE,'CY'-CLAY TILE 'MS t -METAL SIDING,'WS'-WOOD SIDING, 'SH'-SHINGLES, T PG'PLATE GLASS, 'HY'-HAYOIT 'CP'-CONCRETE POUR-'CC'-CONCRETE PRECAST, 'CM'-CONCRETE METAL, 'CA T -CONCRETE ASBESTOS, 'SM' -STRUCT URE METAL, 'WW'-WIN.00W WALLS,' IF'-INSULATED GLASS, 'FB'-FACE BRICK,'CB'-COMMON BRICK 'CF'-CONCRETE FRAME, 'SF' -SHEET FRAME, 'WF '-WOOD RAME, 'WB' -WEATH :ERBOARD, 'CT'CONCRETE TILE 'SC'STEELCONCRETE FRAM, 'AS' -ASBESTOS SH I NGLS.

W85-oH,

6AN 02 I *.SAME AS EXTER I OR-WALL-AMF I

Notes:AN=alphanumer ic, NU =numer ic, PD=packed decimal, ZD=zoned decimal Not for public distribution

BLDG-ARE A-AMF I

PD

01e

FILLER

PD

03 0820-082 2

FILLER

AN

06 0823-0828

FILLER

PD

03 0829-083]

FILLER

AN

06

FILLER

PD

03

FILLER

AN

06 0841-o84.6

BASEMENT-AREA--AMF I

PD

04 0847-0850

BASEMENT-TYPE-AMF I

AN

02 0851-0852

BASEMENT-FIN I SH-AMF I

BASEMENT-SUB-LVLS-AMF I

FOUND-AREA-AMF I

FILLER

FOUND-FOOTINGS-AMF I

FOUND-CONCRETE-BEAM-AMFI

FOUND-P I ERS-AMF I

FOUND-CONCRETE-SLAB-AMF I

FOUND-BLOCKS-AMF I

FOUND-BR I CK-AMF I

FOUND-POST-AMFI

FOUND-DOCK-H I GH-AMF I

FRAME 1 -AMF I

FRAME 2-AMF I

EXT-WALL-AMF I

EXT-WALL-SECONDARY-AMF I

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Record Length =2406 Version: 08

Date: 4-19-2000


FILLER AN 014 0887-0890

ROOF-TYPEl-AMFI AN 02 0891-0892'HP'-HIP GABLE, 'FL'-FLAT, 'SH'

SHED 'MA'-MANITOR ' R'-ARCHED, 'MS'-MANSARD, 'CA'-CANOY,'S '-SAWTOOTH.

ROOF-TYPE2-AMFI AN 02 093-o894 ** SAME AS ___22I:!.!_ ROOF-STRUC-AMFI AN 02 0895-0896

'ST'-STEEL TRUSS,.1WT'-WOOD TRUS ,'WJ -WOOD JOJ I 'WS'-WOOD STEEL,'PC'-PRE

--- CAST C0NCRETE,'P!'P!E,'WR'-WOOD RAFTER

ROOFING-COMP1-AMFI AN 02 0897-0898'TG'-TAR GRAVEL,'CM'-CORRIGAT

ED METAL, STURCTURE

CO'-COMPO ITION 'WS'-WOOD SHINGLE,'SIi'- 'CN'-00NCJETE, 'SD'-STEEL METAL DECK,

'WD'-WOOD OECK,TGY'-GYPSUM,'AS'ASBEST0S,'CT' CLAY TILE

ROOFING-COMP2-AMFI AN 02 0899-0900 * SAME AS ROOFING-COMP1-AMFI*

ACOUSTICAL-TILE-AMFI AN 01 0901 -090 1 'Y'-YES,'N'-NO.

INTERIOR-WALL1-AMFI - - AN 02 0902-0903'PL'PLASTER 'SR'-SHEETROCK,

'PW-PAIN 'PA'-PAN 'PP'-PAER, 'TL'-TILE, L1NGL',

'AC'-ACC0UTICAL TILE,'C-CELLOTEX,'MB'-MARBLE, 'UN'-UNFINISHED.

INTERIOR-WALL2-AMFI AN 02 0904-0905* SAME AS INTERIOR-WALL-AMFI*

FLOOR1-AMFI AN 02 90 0906-09071.1CS'-CONCRETE, 'CP' -CONCRETE

SUSPND ' Z'-TERRAZ,'TI'-TILE,'PI'-PINE 'HW'- HARDW000, 'CO'-COMPOSITION, 'SI' -STONE, ICALCARPET 'EA'-EARTH.

-------------------

FLOOR2-AMFI AN 02 0908-09Q.0.1** SAME AS FLOOR1-AMFI

SUB-FLOOR-AMFI AN 01 09 10 -09 10 . 'Y'-YES,'N'-NO

CONSTRUCT ION-TYPE-COM-AMF -------:. 'S'-STRUCTURE STEEL,'C'-

REI ORCE CONCRETE,'M'-MASONARY,'F'-FRAME,'P' PRE- NGIN ERED STEE

ESCALATOR-NUM-AMFI PD 02 0912-0913

ESCALATOR-WIDTH-AMFI PD 02 0914-0915'

ESCALATOR-RISE-AMFI PD 02 0916-0917

ESCALATOR-FLAT-PR-AMFI PD 01+ 0918-0921

ELEVATOR-NUM-AMFI PD 02 0922-0923

ELEVATOR-STOPS-AMFI PD 02 0924-0925

ELEVATOR-NUM-PASSENGER-AMFI PD 02 0926-0927

ELEVATOR-NUM-FREIGHT-AMFI PD 02 0928-092.9

ELEVATOR-PRICE-FLAG-AMFI AN 01 0930-0930 'U'-UNIT, 'F'-FLAT

Notes:AN=alphanurner Ic, NUnumer Ic, PDpacked decimal, ZDzoned decimal


PD

:IAL F

PD

PD

PD

PD

PD

PD

PD

PD

AN

AN

AN

LUMBI

03

03

03

03

03

02

03

03

08

01

02

S.

S

S

S

S

•i}

S

S

Record Length=21.06

Field Name

ELEVATOR-PR I CE-AMF I

COMMERC

COM-PLUMB--F I XTURES-AMF I

COM-PLUMB-REST-AMF I

COM-PLUMB-COMMODE-AMF I

COM-PLUMB-URINAL-AMF I

COM-PLUMB-LAVS-AMF I

COM-SPR I NK-NUM-AMF I

APT-PLUMB-BATH--F ULL-AMF I

APT-PLUMB-BATH-HALF-AMF I

F I LLER

APT-PLUMB-SPRINKLERS-AMF I

APT-H-C-AMF I

NG AND HE?

0935-0937

0938-0940

0941-0943

0944-0946.

0947-0949.

0950-0951

0952-0954

0955-0957

0958-0965

O966-096

0967-o968

II NG

'Y'-YES, 'N-NO

'HE' -HEATERS, 'RA' -RADIATORS 'FA'-FORCED AIR,'CW'-CHILLEO AIR,'AC'-CENTRAL AIR

HEAT-AC-PRICE-AMFI PD 01. 0969-0972

FILLER AN 03 0973-09Z.5

COOLING-SYSTEM-AMFI AN 01 0976-0976 'Y'-YES, 'N'-NO

COMMERCIAL-HEATING-AMFI AN 02 0977-0978 ' IH'-INDUSTRIAL,'OH'-OVERHEAO

c'c****c*** COMMERCIAL FEATURES I .E. FIREPLACES, SECURITY, ETC *'c**'c*****

OVERHEAD-000R-AMFI AN 02 0979-0980 'OD'-YES,' '-NO

DOCK-LEVELER-AMFI AN 02 0981-0982 'DL'-YES,' '-NO

FIRE-SMOKE-DETECTOR-AMFI AN 02 0983-0984 'SD'-YES,' '-NO

WET-BAR-AMFI AN 02 0985-0986 'WB'-YES,' '-NO

FIREPLACES-AMFI AN 02 0987-0988 'FP'-YES,''-NO --

TV-SECURITY-AMFI AN 02 0989-0990 'TV'-YES,' '-NO

SKYLIGHTS-AMFI AN 02 0991-0992 'SL'-YES,' '-NO

REFRIGERATED-AMFI AN 02 0993-0994 'RE'-YES' '-NO

FILLER AN 03 0995-0997 Iiiiiiiiiiiiiiiiii ii iii CONSTR-CONDITION-AMFI AN 01 0999-0999 'E'-EXCELLENT, 'G'-GOOD,

'F'-FAIR,'P'-POOR.

REPRODUCTION-COST-NEW-AMFI PD 05 1000-1001.

FILLER AN 59 1005-103

Notes;AN=alphanumeric, NU=numeric, PD=packed dimal, ZD=zoned decimal


Page 13



Version: 08

Data: 4-19-2000

Type Lgth Columns

Comments


Date: 4-19-2000





..

.-

.&

S

S S S

S S S S

S

..

S

S S S

S S S S

S

S

S ..

Field Name Type Lgth Columns. Comments

**********

COMMERCIAL ADDITIONAL IMPROVEMENTS

AODL-IMPT1-OESC-AMFI AN 15 1064-1078

ADOL-IMPT1-CLASS-AMFI PD 02 1079-1080

ADDL-IMPT1-CONSTR-AMF I AN 02 1081-108

ADDL-IMPT1-QUAL-AMFI AN 01 1083-1083'E'-EXCELLENT.'G'-GOOD A'-AVERAGE,'L'-L0W COAT

ADDL-IMPT1-NUM-AMFI PD 02 1084-1085

ADDL-IMPT1-AREA-AMFI PD 04 1086-1089

ADDL-IMPT1-PERMETER-AMFI PD 04 1090-1093

ADDL-IMPT1-PRFLAG-AMFI AN 01 1094-1094 'W-UNIT, 'Ft-FLAT

ADDL-IMPT1-PR-AMFI PD 0.4-

1095:1098

ADDL-IMPT1-EXT-WALL-AMFI AN 02 1099-1100

AODL-IMPT2-DESC-AMFI AN 15 1101-1115

ADDL-IMPT2-CLASS-AMFI PD 02 iii6-iii7

ADDL-IMPT2-CONSTR-AMFI AN 02 1118-1119

ADDL-IMPT2-QUAL-AMFI AN 01 1120-1120 *SAME AS IMPROVEMNT-QU

ADDL-IMPT2-NUM-AMFI PD 02 1121-112

ADDL-IMPT2-AREA-AMFI PD 04 1123-1126

ADDL-IMPT2-PERIMETER-AtIFI PD 04 1127-1130

ADDL-IMPT2-PRFLAG-AMFI AN 01 1131-1131 'U'-UNIT,'F'-FLAT

ADDL-IMPT2-PR-AMFI PD 04 1132-115

ADDL-IMPT2-EXT-WALL-AMFI AN 02 1136-1137:

FILLER AN 22 1138-119 -

FILLER PD 05 1160-1161+

COND-NEXT-COND-ACCT-NUM-AMFI AN 20 1165-1184

COND-PRIOR-COND-ACCT-NUM-AMF AN 20 1185-1204

FILLER PD 02 1205-1206

FILLER PD 02 1207-1208

FILLER PD 02 1209-121

FILLER PD 02 1211-1212.

FILLER PD 02 1213-1214

FILLER 15-u6

FILLER AN

--------------

01. 1217-1220

COMMERCIAL PROPERTY INCOME/EXPENSES *1c*c1cc**

Notes:ANalphanumeric, NUnumeric, PD=packed deima1, ZD=zoned decimal


..

•; • )

S

•

•; •:) S

S

S .,.

S • •


Page 15

File Description: FDAMF1



Date: -19-2000

Field Name Type Lgth Columns-. Comments

APPR-IND-VAL-COST-AMFI PD 05 1221-1225

A PD 05 1226:1230

APPR-IND-VAL-SALES-AMFL PD 05 1231:1235

APPR-IND-VAL-FLAG-AMFI AN 01 1236-1236

APT-TENANT-NOl-AMFI PD 02 1237-1238

APT-RENT-AREA1-AMFI PD 05 1+ 1239-123 -

APT-INCOME-CODE1-AMFI AN 01 1244-12441F

7-FLAT 1 'U -UNIT, 'S'-SQFT

APT-RENT-INCM1-VAL-AMFI PD 05 1245-12149

APT-TENANT-NO2-AMFI PD 02 1250-1251

APT-RENT-AREA2-AMFI PD 05 1252-1256

APT-INCOME-CODE2-AMFI AN 01 1257-125.7 'F'-FLAT,'U'-UNIT,'S'-SQFT

APT-RENT-INCM2-VAL-AMFI PD 05 1258-1262

APT -T E N ANT- NO3-AMFI PD 02 1263-1264

APT_RENT_AREA3:AMFI PD 05 1265-1269

APT - INCOME - C ODE 3-AMFI AN 01 1270-1270 'F'-FLAT'U'-UNIT, 'S'-SQFT

APT - RENT - INCM3-VAL -AM F I PD 05 1271-1275

APT-TENANT-N04-AMFI PD 02 1276-127.7

APTRENT_AREA4:AMFI PD 05 -

1278:128.

- ----------------- ---- - --- 1283-1281:E : .:

APT-RENT-INCM4-VAL-AIIFI PD 05 1284-1288

ACT-MARK-EXP-FLAG-AMFI AN 01 1289-I289.

BUSS-EXP-INSUR-AMFI - P0 04 1290-1293

BUSS-EXP-TAXES-AMFI

-

PD 04 1294-1297

BUSS-EXP-MGMT-AMFI PD 01+ 1298-1301

BUSS-EXP-UTIL-AMFI PD 01 1302-1305

BUSS-EXP-TRASH-AMFI PD 04

--

1306-130'

1O1313

BUSS-EXP-WAGES-AMFI PD 04 1314-131.7

---------------------------------

--------- -- --1318-13Z]

BUSS-EXP-MAINT-AMFI PD 04 1322-1325

BUSS-EXP-TELE-AMFI PD 04 1326-1329

BUSS-EXP-LEGAL-AMFI PD 04 1230-1333

BUSS-EXP-CLEAN-AMFI -- PD 04 1334-133'7

Notes:AN=alphanumeric, N1J=numeric, P0 =packed decimal, ZD=zoned decimal


• .) I

S:

S S

S

•




Record Length=2 1+06 Version: 08 Date: 4-19-2000


BUSSEXPMISC-AMFI P0041338-1341

BUSS-EXP-OTHER-AMFI - -- PD 05 1342-1346

--

PERCT-EFF-GROSS-INC-AMFI PD 02 131+7-1348

BUSS-VAC-LOSS-PCT-AMFI PD 02 1349-1350

BUSS-EXP-TYPE-CODE-AMFI AN 01 1351-1351

BUSS-EXP-TOTAL-AMFI PD 05 1352-1356

COST-GAR-CPORT-AMFI PD 04 1357-1360

COST-POOL-AMFI PD OLe 1361-1364

COST-TENANTS-CT-AMFI PD 04 1365-1368

COST-ADDL-BLDG-AMFI PD 04 1369-1372

COST-AREA-VAL-AMFI PD OLe 1373-1376

COST-ADJ-VAL-OVRD-AMFI AN 01 1377-1377 '0'-OVERRIDDEN, 'F-FLAT RCN

COSTAOj : VAL_AMFI PD 01+ 1378-1381 S9(5)V99

COST-LUMP-SUM-HEAT-AC-AMFI PD 04 1382-1385

1386:1389 ----------------------------

COST-LUMP-SUM-ESCLTRS-AMFI PD 04 1390-1393

COSTLUMPSUMELVATRS-AMFI PD 04 1394-1397

COST-LUMP-SUM-SPRINKS-AMFI P0 04 1398-1401

MASTER FILE COMMON INFORMATION

CALLS — AREA—AMFI AN 158 11+02-1559

VAL I DATOR- INPUT REDEFINES CALLS-AREA-AMF I

VI-CALLS

VI-PART1 AN 79

VI-PART2 AN 79

I : CALLS:R - REDEFINES VI-CALLS

VI AN 01 OCCURS 158 TIMES

NEW FIELD AND EXPANSION

PANEL — AMFI AN 03 1560-1562

PANEL — DATE — AMFI PD 03 1563-1565 JULIAN DATE

PANEL-AMT-AMFI PD 06 1566-1571

RENDITION-AMFI AN 02 1572-1573

RENDITION-AMT-AMFI PD o6 1574-1579

FILLER AN 01 1580-1586-----------------------------

Notes;AN=alphanumeric, NU=numeric, P0=packed decimal, ZDzoned decimal


Field Name Type Lgth Columns Comments I

.,

S

... •

MARKET-AREA-AMFI AN 06 1581-1586

PARCEL-ID-AMFI AN 06 1587-1592

ALPS-MKT-AREA-AMFI AN 06 1593-1598

APT-RENT-RATE-CODE-I-WI AN 01 1599-1599 'M'-MODEL, A1-ACTUAL

APT-RENT-AREA1-T-AMFI PD 05 1600-1604


APIRENTAREA3TAMFI PD 05 1610-16:14


APT-RENT-INCM1-VAL-T-AMFI PD 05 1620-1624

APT-RENT-INCM2-VAL-T-AMFI PD 05 1625-1629

APT -RENT - I NCM3-VAL-T-AMFI PD 05 1630-1634

APT-RENT-INCM4-VAL-T-AMFI PD 05 1635-1639.

APT-POT-GRSS-INCM1-T-AMFI PD 06 161+0:1645

APT-POT-GRSS-INCM2-T-AMFI PD 06 16464651:

APT - POT - GRSS- IN CII3-T-AMF I PD 06 1652-1657

APT-POT-GRSS-INCM4-T-AMF I PD 06 1658-166.3

BUSS-VAC-LOSS-PCT-CODE-T-AMF AN 01 1664-1664 'M'-MODEL, 'A'-ACTUAL

BUSS-VAC-LOSS-PCT-T-AMFI PD 02 1665-1666

BUSS-EXP-TYPE-CODE-T-AMFI AN 01 1 667- 166 7 'Il'-MODEL, 'A'-ACTUAL

BUSS-EXP-INSUR-T-AMFI PD 04 1668-1671

BUSS-EXP-TAXES-T-AMFI PD 01+ 1672-1675

BUSS-EXP-MGMT-T-AMFI PD 04 1676-1679

BUSS-EXP-UTIL-T-AMFI iü 04 1680-1683

BUSS-EXP-MISC-T-AMFI PD 01+ i68-i687

BUSS-EXP-TOTAL-T-AMFI - PD 05 1688-1692

- BUSS-EXP-PCT-T-AMFI PD 02 1693-1694

BUSS-INCM-CAP-RATE-T-AMFI PD 02 1695-1696

BUSS-INCM-CAP-RATE-CODE-T-AM AN 01 1697-1697 'M'-MODEL, 'A'-ACTUAL

APPR-IND-VAL-INCM-NEW-T-AMFI PD 05 1698-1702

APT-POT-GRSS-1NCM1-AMFI PD 05 1703-1707

APT-POT-GRSS-INCM2-AMFI PD 05 1708-1712

APT-POT-GRSS-INCM3-AMFI PD 05 1713-1717

APT-POT-GRSS-IMCM1+-AMFI PD 05 1718-1722

Notes;AN=alphanumeric, NU-numeric, PD=packed dcima1, ZOzoned decimal





Record Lerigth=206 Version: 08 Date: 4-19-2000

-ACTIVE RI VE SPLIT.. ,

1778-178:6

1787-177

1788-18 1

1813-1820

1821-1822

1823-1827

'C'-ACTIVE COUNTY,'A'-ACTIVE INSTATE 'F'-ACTIVE TRANS, E'-INACtIVE ERROR,'T'-INACTIV

MANW L, 'R NACT

E TR NSFEF

AN 09

AN

01

AN

25

AN -0- i -

AN

02

PD

05

KEY FOR LEGAL SEARCH

ZD 02 1828-1829

AN 04 1830-183,3

AN 01 1834-1834

AN 03 1835-1837






iziiiiiiz ::ii NEW-OPERID-LASTUPD-AMFI AN 06 1724-1729 6 BYTE OPERATOR ID

NEW-OPERID-PREVUPD-AMFI AN 06 1730-1735 6 BYTE OPERATOR ID PREVIOUS

APPR-NOTICE-PRODUCED-AMFI AN 01 1736-1736

CONTRIB-PERMIT-VALUE-PREV-AM PD 05 1737-1741 -

-- DATA-NUMBER-AMFI AN 10 1742-1751

APPRAISER ASSIGNED C0IES

COM-DEPRE-PCT-PHYS-AMFI PD 02 1752-1753

COM-DEPRE-PCT-FUNC-AMFI PD 02 1754-1755

COM-DEPRE-PCT-ECON-AMFI PD 02 1756-1757

FILLER AN 02 1758-1759

APPROACH-FIN-APPR-AMFI AN 01 176o-176b 'S-SALES, 'C'-COST, 'I'

HISTORICAL DATA

FILLER AN 01 1761-176.1

PREV-REVAL-YEAR-AMFI PD 03 1762-1761+

OPERATOR-LAST-UPDATE-AMFI AN 03 1765-1767 SEE "NEW-OPERID-LASTUPD"

FILLER PD 03 1768-1770 NOT USED AT THIS TIME

OPERATOR-NEXT-TO-LAST-AMFI AN 03 1771-177,3 SEE "NEW-OPERIO-PREVUPD"


CURR-STATUS-CODE-AMFI AN 01 1777-1777

SOC I AL-SECUR ITY-NUM-AMF I

F I LLER

PREV-OWNER-NAME-AMF I

DRIVERS-LICENSE-NUM-AMF I

F I LLER

NEW- STREET-Z I PCODE 1 -AMF I

LEG5-NEW-KEY-AMF I

LEG5-NEW-KEY-CITY-AMF I

LEG5-NEW-KEY-C I TY-BLK-A1IF I

LEG5-NEW-KEY-SUB-D I V-AMF I

LEG5-NEW-KEY-DIVISION-AMF I

Notes;AN=alphanumeric, NU=numeric, PD=packed decimal, ZD=zoned decimal



Page 19



Record Lngth=2406

Version: 08

Date: 14-19-2000

.-O •

I S

S

S

•: •

S

Columns

1838- i8140

18141-18143

1844-1846

181+7-181+9

1850-1852

1853-18,55

1856-1858

1859-1861

1862-1862

1863-1863,

1864-1864

1871-187:5

1876-1878

1879- 1879

1880-188.2

1883-1887

1888-1890

1891-1891

1892-18-94

1895- 1839

l9OO-192

HISTORY..

Field Name

LEG5_NEW:KEY_LOT_AMF I

ALPS- PERCENT-OWN l-AMF I

ALPS-PERCENT-OWN2-AMFI

ALPS-PERCENT-OWN3-AMF I

ALPS-PERCENT-OWN I+--AMF I

ALPS-SPTB-0O2-AMF I

ALPS-SPTB-0O3-AMFI

ALPS-SPTB-CD4-AMF I

ALPS -MASS-UPDT-FLAG-AMF I

FREEZE-CODE-AMF I

DEED-DATE-FREEZE-CODE-AMF I

MOST-CURR-PERMIT-VAL-AMF I

MOST-CURR-APPRAISER-AMF I

PREV-PERMIT-CODE-AMF I

F I LLER

PREV-PERMIT-AMT-VAL-AMF I

PREV-APPRAISER-AMFI

PREV2-PERMIT-CODE-AMFI

F I LLER

PREV2-PERMIT-AMT-VAL-AMF I

PREV2-APPRAISER-AMF I

***)'C****)'

----------------------------- SUB

Type Lgth

AN

03

PD

03

PD

03

PD

03

PD

03

AN

03

AN

03

AN

03

AN

01

AN

01

AN

01

PD

05

AN

03

AN

01

PD

03

PD

05

AN

03

AN

01

PD

03

PD

05

AN

03

JECT ;ALES

SAME AS CURR PERMIT


SAME AS CURR PERMIT


* * ** * IC * * * *

Comments

V9(5)

-V9(5)

_V9(5)

_V9(5)

ARB-FLAG-AMFI AN 01 1865-1865 - --- -----'Y' = HAS PANEL VALUE = NO RECORD EXISTS

I X I = ARB RECORD EXISTS 'S' = SUPPLEMENTAL RECORD

EXISTS 'C' = PROTEST CONSENTED

= PROTEST RESOLVED = PROTEST DISMISSED

'V ACCOUNT IN VID

FILLER AN 01 1866-1866 ***FUTURE EXPANSION

BUILDING PERMITS

MOST-CURR-PERMIT-CODE-AMFI AN 01 1867-1867 'O'-MISC, '1 '-NEW, '2'-ADD IMP, '- REPAIR, '14'-REMOVE IMPV,

• ''-REMOVE PART,:6'-REMODEL, '-MOVE FROM,''-MOVE TO, • '-PARTIALLY COMPLETE


Notes:ANalphanumeric, NU=numeric, PD=packed .dacimal, ZO=zoned decimal







MOST-CURR--QUAL-AMT-AMFI PD 05 1903-1907 CURRENT SALES PRICE

FILLER PD 03 1908- 191p NOT USED AT THIS TIME

TIME-ADJ-PRICE-AMFI PD 051911-191 CURRENT AOJ SALES PRICE

PREV-QUAL-AMT-AMFI PD 05 1916-1920 PREVIOUS SALES PRICE

FILLER PD 031921-1923 NOT USED AT THIS TIME

PREV-ADJ-PRICE-AMFI PD 05 1924-1928 PREVIOUS AOJ SALES PRICE

PREV2-QUAL-AMT-AMFI PD 05 1929-1933 PREV2 SALES PRICE

FILLER-------------------------------:! 2 --------------------- H------

PREV2-ADJ-PRICE-AMFI PD 05 1937-194.1 PREV2 ADJ SALES PRICE

COMMERCIAL COMPARABLE SALE'S

COMPAR-SALES1-ACCT-NUM-AMFI AN 20 191+2-1961

COMPAR-SALES1-LOC-VAL-AMFI PD 04 1962-1.965

COMPAR-SALES1-QUAL-VAL-AMFI PD 04 1966-1969

COMPAR-SALES1-COND-VAL-AMFI PD 01+ 1970-1973

COMPAR-SALES2-ACCT-NUM-AMFI AN 20 1974-1993

COMPAR-SALES2-LOC-VAL-AMFI PD 04 1994-1997

COMPAR-SALES2-QUAL-VAL-AMFI PD 04 1998-2001

COMPAR-SALES2-COND-VAL-AMFI PD 04 2002-2065

COMPAR-SALES3-ACCT-NUM-AMFI AN 20 2006-2025

COMPAR-SALES3-LOC-VAL-AMFI PD 04 2026-209

COMPAR-SALES3-QUAL~VAL-AMFI PD 04 ---------------------------- 99:2P CQMPARSALES3CONO-VALAMFI PD 04 2031+2037

COMPAR-SALES4-ACCT-NUMAMFI AN 20 2038_205.7

COIIPAR-SALES4--LOC-VAL-AMFI PD 04 2058-2061

COMPAR-SALES L.-QUAL-VAL-AMF I PD 04 2062-2065

COMPAR-SALES4-COND-VAL-AMFI PD 04 2066-2069

COMPARSALES S :ACCT_N UM_ AMFI AN 20 2070-2089

COMPAR-SALES5-LOC-VAL-AIIFI PD 04 2090-2093

COMPAR_SALES5 : QUAL_VALAMFI PD 04 2094-2097

COMPAR-SALES5-COND-VAL-AMFI P0 04 2098-2101

*********

RESIDENTIAL COMPARABLE SALES (REOEF INES COMMERCIAL)

RESI-COMPSALEI-ACCT-NUM-AMFI AN 20 1942-1961

FILL-- --------1962964 NOT USED AT THIS

Notes;AN=alphanumer ic, NU=numer Ic, PD=packed dcima1, ZD=zoned decimal



File Description: FDAMF1




-- -1968---------------------------------------

RESI-COMPSALE1-SALE-PR--- -- --

RESI-COMPSALE1-ADJ-PRICE PD 04 1969-197, 2

-------

-

FILLER AN 01 1973-1973

RESI-COMPSALE2-ACCT-NUM-AMFI AN 20 1964-1993 -

FILLER PD 03 l 99 4 - 1 9 6 NOT USED AT THIS TIME RESI-COMPSALE2-SALE-PRICE PD 04 1997-2000

RESI-COMPSALE2-ADJ-PRICE PD

-

--1-

04 2001-2004-----------------------------

-

FILLER AN 01 2005-2005 -

RESI-COMPSALE3-ACCT-NUM-AMFI AN 20 2006-2025


RESI - C OMPSALE 3- SALE - PRICE PD 014 2029-2032

RESI-COMPSALE3-ADJ-PRICE--

04 2033- 20 36---- FILLER

- - -

AN

-

65--,

-2037-2101

-

CODES I.E. ZONING, MAPSCO

ZONING-IN-EFFECT-AMFI AN 06 2102-2107

USPS-DEL-POINT-AMFI AN 06 2108-2113

DPBC-W-CHKDGT-AMFI AN 03 2114-2116

FILLER - AN 03 2117-2119

MAPSCO-CODES-AMFI AN 05 2120-21214

CONDITION-CODE-AMFI AN 01 2125- 212 5 'E'-EXCELLENT,G'-GOOD, 'A'-AVERAGE, 'L'-LOW,

'-UNKNOWN.

QUALITY-CODE-AMFI AN 01 2126-2126 ** SAME AS CONDITION-CODE *

TAXING_9!9ELES COUNTY-TAX-AUTH-AMFI AN 02 2127-2128

CITY-TAX-AUTH-AMFI - AN 02 2129-2130

CITY-ACCT-NUM-AMFI AN 25 2131-2155

PARK-HOSP-TAX-AUTH-AMFI AN 02 2156-2157

PARK-HOSP-ACCT-NUM-AMFI AN 25 2158-212

COMU-COLG-TAX-AUTH-AMFI AN 02 2183-2184

COMU-COLG-ACCT-NUM-AMFI AN 25 2185-2209

ISD-TAX-AUTH-CODE-AMF I AN 02 2210-2211

ISD-TAX-AUTH-ACCT-NUM-AMFI AN 25 2212-2236

SPEC-DIST1 -TAX - AUTH - CODE - AMFII ANj 02 122372238

Notes:ANalphanumeric, NU-numeric, PD=packed decimal, ZD=zoned decimal



Page 22

S. • 4

.w S

S

I ...

S

I

•\ • :k)

• • I



Record Length206

Version: 08

Date: -19-2000

Field Name

Type Lgth Columns Comments

GIS-REFERENCE-ACCT-NUM-AMFI AN 7 2 239- 2 255 GIS REFERENCE NUMBER

FILLER AN 07 2256-2262

WORKSHT-REQUESTOR-AMFI AN 01 2263-2263 REGION TO WHOM ONLINE

.. WORKSHEET WAS REQUESTED

NEW-REGION-AMFI ZO 01 2264-2261+

TAX-CONSULTANT-CODE-AMFI AN 03 2265-2267

COUNTY-ACCOUNT-NUMBER-AMFI AN 17 2268-2284 -

ALPS-MKT-ADJ1-AMFI PD 02 2285-2286

ALPS-MKT-ADJ2-AMFI PD 02 2287-2288

ALPS-MKT-AOJ3-AMFI PD 02 2289-2296

ALPS-MKT-ADJ L+-AMFI PD 02 2291-2292

ALPS-SEC-ZONING-AMFI AN 06 2293-2298

ALPS-SPTB-CD1-AMFI AN 03 2299-2301

FILLER AN 03 2302-231+

FROZEN-COMPS-INDICATOR-AMFI AN 01 2305-2305 'Y'-STORED COMPS

NOT-IN-DISPUTE-FLAG-AMFI AN 01 23O6-23Q6 ' '-NOT IN DISPUTE 'A'-AUTOMATIC ASSIGNMENT 'R'-RETURNED NOTICE 'D'-DUE PROCESS 'F'-FLOW CHART 'Y'-IN DISPUTE("Y" CODE TO BE

PHASED OUT

ONLINE-UPDATED-AMFI AN 01 2307-2307

HAND-SEL-SWITCH-AMFI AN 01 2308-230

LAST-YR1-ROLL-AMT-AMFI PD 06 2309-2314 STORED MARKET VALUE

LAST-YR1-ROLL-CALC-AMFI AN 01 2315-231.5

FILLER AN 02 2316-231,7 NOT USED AT THIS TIME

LAST-YR1-IMPV-VAL-AMFI PD 05 2318-2322 STORED IMPROVEMENT VALUE

TAX-ROLL1-CNTY-AIIFI AN 02 2323-2321+ COUNTY CODE

9COUNTY TAXABLE VALUE

TAX-ROLL1-CITY-AMFI

- -

AN

- -

02 2331-2332 CITY CODE

TAX-ROLL1-CITY-EX-AMFI 2333-2338 CITY TAXABLE VALUE

----------- -------

TAX-ROLLI-SCHOOL-AMFI - AN 02 2339-2349 ISO CODE

TAX-ROLL1-SCHOOL-EX-AMFI PD

-----------

06 2341-2346 ISO TAXABLE VALUE

TAX-RI-SPEC-DISTI~AMFI AN 02 2347-2348 SPEC 01ST COD

TAX-R1-SPEC-OIST1-EX-AMFI PD 06 2349-235 SPEC 01ST TAXABLE VALUE

Notes;AN=alphanumeric, NU=numeric, PDpacked decimal, ZD =zoned decimal


- ZO



Appraisal Master Fi.ie


Field Name Type Lgth Columns. Comments

TAX-R1-PARK-HOSP-AMFI AN 02 2355-2356 HOSPITAL CODE

TAX-R1-PARK-HOSP-EX-AMFI PD 06 2357-2362 HOSPITAL TAXABLE VALUE

TAX-R1-COMM-COL-AMFI AN 02 2363-2364+ COMMUNITY COLLEGE CODE

TAX-RI-COMM-COL-EX-AMFI PD 06 2365-2370 COMM COLG TAXABLE VALUE

ALPS-TOT-LO-VAL--AMFI PD 06 2371-2376 * NOT CURRENTLY USED

ALPS-HMSD-FLAG1-AMFI AN 01 2377-2377 'X'-LAND NOT HOMESTEADABLE

ALPS-HMSD-FLAG2-AMFI AN 01 2378-2318 'X'-LAND NOT HOMESTEADABLE

A L PS- HMSD-FLAG3-AMFI AN 1 'X'-LAND NOT HOMESTEADABLE

ALPS-HMSD-FLAG4-AMFI

-

AN 01

-----

2380-2380 'X'-LAND NOT HOMESTEADABLE

ALPS-AG-USE1-AMFI AN 02 2381-2382

2383238

2379-2379

FOR ALL OCCURENCES: - ' '-LAND NOT QUALIFIED FOR

ALPS-AG-USE2-I AMF AN 02 -4 AGRICULTURAL EXEMPTION -- • - 'DC'-DRYCROP LAND

ALPS-AG-USE3-AMFI AN 02 2 385-2386 'IP-IMPROVED PASTURE ---------------------

'NP'-NATIVE PASTURE ALPS-AG-USE4-AMFI AN

-----

02

---------

2387-2388 'WL'-WASTELAND

FILLER

--------------------------------------

----------------------------------------

AN 02 2389-2390

CARRIER-ROUTE-AMFI AN 04 2391-2394


MOST-CURR-APPR-INITIALS-AMFI AN 03 2398-2400


' PREV-APPRAISER-INITIALS--AMFI AN 1 03 12404-24o6

Notes:AN=alphanumeric, NU=numeric, PD =packed decimal, ZOzoned decimal


S ..

.

S

S

.., •) S.

O :")

Input DCAD Master 15:52 Tuesday, May 4,

2004 52

The CONTENTS Procedure

Data Set Name: DCAD.ADDISON Observations: 1377

Member Type: DATA Variables: 93

Engine: V8 Indexes: 0

Created: 16:22 Tuesday, May 4, 2004 Observation Length: 472

Last Modified: 16:22 Tuesday, May 4, 2004 Deleted Observations: 0

Protection: Compressed: NO

Data Set Type: Sorted: NO

Label:

Engine/Host Dependent Information-----

Data Set Page Size: 16384

Number of Data Set Pages: 42

First Data Page: 1

Max Obs per Page: 34

Obs in First Data Page: 11

Number of Data Set Repairs: 0

File Name: C:\TEMP\DCAD\addisonsas7bdat

Release Created: 8.0202MO

Host Created: WIN—PRO

Alphabetic List of Variables and Attributes-----

# Variable Type Len Pos Label

fffHfffffHHffHffffffffffffHffHfHHffffffffffffffffffffffHffHfff 93 I Num 8 88

I XO Char 17 96 DCAD 17 CHARACTER ACCOUNT NUMBER

2 X8 Char 1 113 RCD-TYPE

3 X10 Char 3 114 NEIGHBORHOOD-CODE

6 XII Num 3 335 PROPERTY-CLASS

7 X12 Num 3 338 BUILDING-CLASS

8 X13 Char 1 120 BUILDING-SUB-CLASS-1


10 X20 Char 25 122 TAXP-NAME-ADDI

II X21 Char 25 147 TAXP-NAME-ADD2

12 X22 Char 25 172 TAXP-NAME-ADD3

13 X23 Char 23 197 TAXP-CITY-ADD4

14 X24 Char 2 220 TAXP-STATE-ADD4

15 X26 Num 8 0 TAXP-ZIPCODE

16 X39 Char 2 222 PROP-LOC-STREET-CITY-CODE

17 X40 Char 23 224 PROP-LOC-STREET-NAME

18 X41 Char 4 247 PROP-LOC-STREET-TYPE

19 X42 Char 2 251 PROP-LOC-STREET-DIRECTION

20 X43 Num 7 341 PROP-LOC-STREET-NUMBER

21 X44 Char 5 253 PROP-LOC-STREET-CONDO-BLDG

22 X45 Char 5 258 PROP-LOC-NEW-CONDO

23 XI07 Char 1 263 LAND-AREAI-FLAG

24 X108 Num 7 348 LAND-AREAI

25 X109 Num 7 355 FRONTAGE1


2004 53




If ffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff 26 X110 Num .7 362 LAND-DEPTH1

27 X113 Char 1 264 LAND-AREA2-FLAG

28 X114 Num 7 369 LAND-AREA2


30 X116 Num 7 383 LAND-DEPTH2

31 X145 Num 7 390 LIVING-AREA

32 X147 Num 3 397 NUMBER-OF-LIVING-UNITS

33 X149 Num 3 400 YEAR-BUILT

34 X157 Char 2 265 CONSTRUCTION MATERIAL

35 X158 Char 2 267 FRAMEWORK

36 X159 Char 2 269 FOUNDATION

37 X160 Char 2 271 BASEMENT PRESENT

38 X161 Char 1 273 BASEMENT FINISHED

39 X162 Char 2 274 EXTERIOR WALL I TYPE

40 X163 Char 2 276 EXTERIOR WALL 2 TYPE

41 X164 Char 2 278 ROOF TYPE

42 X165 Char 2 280 ROOF COMPOSITION

43 X166 Num 3 403 FULL-BATHS

44 X167 Num 3 406 HALF-BATHS

45 X168 Char 6 282 PLUMBING

46 X169 Nurn 3 409 KITCHENS-NUM

47 X171 Char 2 288 A/C-TYPE

48 X175 Char 2 290 HEAT

49 X177 Char 1 292 GARAGE 1-CARPORT

50 X178 Num 3 412 GARAGE 1-STALLS

51 X184 Char 2 293 GARAGE 1-LOCATION




55 X208 Num 5 418 SERVANTS QUARTERS

56 X218 Num 3 423 FIREPLACE

57 X219 Num 3 426 WETBAR

58 X222 Num 5 429 SAUNA-PRICE

59 X225 Num 5 434 POOL-PRICE

60 X229 Char 1 298 ACCESSORY-BLDGS

61 X546 Char 1 299 MOST CURRENT PERMIT CODE

62 X547 Num 5 439 MOST CURRENT PERMIT DATE

63 X548 Num 8 8 MOST CURRENT PERMIT VALUE

64 X550 Char 1 300 PREVIOUS PERMIT CODE

65 X551 Num 5 444 PREVIOUS PERMIT DATE

66 X552 Num 8 16 PREVIOUS PERMIT VALUE

67 X554 Char 1 301 PREVIOUS 2 PERMIT CODE

68 X555 Num 5 449 PREVIOUS 2 PERMIT DATE

69 X556 Num 8 24 PREVIOUS 2 PERMIT VALUE

70 X558 Num 8 32 CURRENT SALES PRICE

71 X559 Num 5 454 CURRENT SALES DATE

72 X560 Num 8 40 CURRENT ADJ SALES PRICE


2004 54



N Variable Type Len Pos Label

HfffffffffffffffffHffffffffHffffffffffffffHffffffffffffffHffffHfff 73 X561 Num 8 48 PREVIOUS SALES PRICE

74 X562 Num 5 459 PREVIOUS SALES DATE

75 X563 Num 8 56 PREVIOUS ADJ SALES PRICE

76 X564 Num 8 64 PREV2 SALES PRICE

77 X565 Num 5 464 PREV2 SALES DATE

78 X566 Num 8 72 PREV2 ADJ SALES PRICE

79 X605 Char 6 302 ZONING-IN-EFFECT

80 X607 Char 5 308 MAPSCO-CODE

81 X610 Char 2 313 COUNTY-TAX-AUTH

82 X611 Char 2 315 CITY-TAX-AUTH

83 X613 Char 2 317 PARK-HOSP-TAX-AUTH

84 X615 Char 2 319 COMU-COLG-TAX-AUTH

85 X617 Char 2 321 ISD-TAX-AUTH-CODE

86 X628 Num 8 80 STORED MARKET VALUE

87 X632 Char 2 323 COUNTY CODE

88 X636 Char 2 325 CITY CODE

89 X636 Char 2 327 ISD CODE

90 X638 Char 2 329 SPECIAL DISTRICT CODE

91. X640 Char 2 331 HOSPITAL CODE

92 X642 Char 2 333 COMMUNITY COLLEGE CODE

4 XA10 Char 1 117

5 XBIO Char 2 118


2004 55

The UNIVARIATE Procedure

Variable: price

Moments

N 146 Sum Weights

Mean 245507.5 Sum Observations

Std Deviation 92931.6506 Variance

Skewness 2.1986074 Kurtosis

Uncorrected SS 1.00523E13 Corrected SS

Coeff Variation 37.8528764 Std Error Mean

146

35844095

8636291692

8.47718125

1.25226E12

7691.07813

Basic Statistical Measures

Location Variability

Mean 245507.5 Std Deviation 92932

Median 237450.0 Variance 8636291692

Mode 250000.0 Range 663855

Interquartile Range 92000

Tests for Location: Mu00

Test -Statistic- p Value------

Students t t 31.92108 Pr > Itl <.0001

Sign M 73 Pr > IMI <.0001

Signed Rank 5 5365.5 Pr > IS' <.0001

Quantiles (Definition 5)

Quantile Estimate

100% Max 755000

99% 621000

95% 380000

90% 335000

75% Q3 277000

50% Median 237450

25% QI 185000

10% 141500

5% 133000

1% 124000

0% Min 91145


2004 56


Variable: price

Extreme Observations

Lowest Highest - - - -

Value Obs Value Obs

91145 14 435000 50

124000 16 560000 69

126000 13 595000 68

126500 17 621000 70

130000 5 755000 60


2004 57


Variable: livarea

Moments

N 146 Sum Weights


Std Deviation 592..474773 Variance


Uncorrected SS 755243888 Corrected SS


146

320678

351026.356

2.01017811

50898821.7

49. 0335611



Mean 2196.425 Std Deviation 592.47477


Mode 1425.000 Range 3561

Interquartile Range 825.00000

Tests for Location: MuOO

Test -Statistic- p Value

Students t t 44.79431 Pr > 'tI <.0001

Sign M 73 Pr > Ml <.0001

Signed Rank 5 5365.5 Pr > SI <.0001


Quantile Estimate

100% Max 4849.0

99% 3771.0

95% 3116.0

90% 2893.0

75% Q3 2578.0

50% Median 2102.5

25% QI 1753.0

10% 1425.0

5% 1409.0

1% 1288.0

0% Min 1288.0


2004 58


VariabLe: livarea


- - - -Lowest- - - - - - - -Highest- - -

Value Obs Value Obs

1288 16 3576 50

1288 14 3633 29

1321 39 3725 26 1325 92 3771 68

1330 12 4849 60


2004 59


Variable: age

Moments

N 146 Sum Weights




Uncorrected SS 23593 Corrected SS




Mean 11.48630 Std Deviation

Median 9.00000 Variance

Mode 9.00000 Range

InterquartiLe Range

146

1677

29. 8653283

.1.2088915

4330.4726

0.45227983

5.46492

29. 86533

19. 00000

10. 00000

Tests for Location: MuOO


Students t t 25.39645 Pr > it' <.0001

Sign M 73 Pr > iMi <.0001

Signed Rank 5 5365.5 Pr > Si <0001


Quantile Estimate

100% Max 21

99% 21

95% 21

90% 19

75% Q3 18

50% Median 9

25%Q1 8

10% 6

5% 5

1% 3

0% Min 2


2004 60


Variable: age


- - -Lowest- - - - - - -Highest- - -

Value Cbs Value Obs

2 21 21 45

3 20 21 46

3 19 21 47

• 4 69 • 21 48

5 82 21 49


2004 61

The FREQ Procedure

Cumulative Cumulative

baths Frequency Percent Frequency Percent

HffHffffHHfffHfffffHffHfffffffffffffffffffffffHhff 1.5 1 0.68 1 0.68

2 52 35.62 53 36.30

2.5 65 44.52 118 80.82

3 15 10.27 133 91.10

3.5 12 8.22 145 99.32

4.5 1 0.68 146 100.00


firepl Frequency Percent Frequency Percent

JfJffffHHfffffHffHfffHffufffHfffffffHfufffHfuffffff 0 1 0.68 1 0.68

1 131 89.73 132 90.41

2 13 8.90 145 99.32

3 1 0.68 146 100.00


wetbar Frequency Percent Frequency Percent

fffffffffffffffffHfffffHfffffffHfufffffHffHfflhf)dfHff

0 92 63.01 92 63.01

1 54 36.99 146 100.00


pool Frequency Percent Frequency Percent

ffffffHfffffffffffLffffHufffHffHffHfHffHfHff3c

0 122 83.56 122 83.56

1 24 16.44 146 100.00


year Frequency Percent Frequency Percent

ffffffffffHffffffffffffffIffffffffffHff5ffffHffffff3ccj

2001 81 55.48 81 55.48

2002 65 44.52 146 100.00

GARAGE 1-CARPORT


X177 Frequency Percent Frequency Percent

$fffffHfIfHIfffHHHIfffffffffffHJfffHffffffHffIfff G 146 100.00 146 100.00

Input DCAD Master 15:52 Tuesday, May 4, 2004 62

The FREQ Procedure

GARAGE 1-STALLS


X178 Frequency Percent Frequency Percent fffffffffff3Cfffffffffffffffffffffffffffffffffffffffffff If

0 137 93.84 137 93.84 2 8 5.48 145 99.32 3 1 0.68 146 100.00

GARAGE 1-LOCATION


X184 Frequency Percent Frequency Percent

fffffffffffffffffffffffffffffffffffffffffffffffffffffffff AT 146 100.00 146 100.00


2004 63


Data Set Name: WORK.TEMP Observations: 146

Member Type: DATA Variables: 103

Engine: V8 Indexes: 0

Created: 16:23 Tuesday, May 4, 2004 Observation Length: 552

Last Modified: 16:23 Tuesday, May 4, 2004 Deleted Observations: 0

Protection: Compressed: NO

Data Set Type: Sorted: NO

Label:


Data Set Page Size:

Number of Data Set Pages:

First Data Page:

Max Obs per Page:

Obs in First Data Page:

Number of Data Set Repairs:

File Name:

Release Created:

Host Created:

16384

6

29

7

0

C:\DOCUME-l\thampton\LOCALS-1\Temp\SAS

Temporary Files\_TDIO20\tempsas7bdat

80202M0

WIN—PRO



fffffHfffffffHHfHHHffffffffHffffffHffffHfffffffffffffffffffHLff 93 I Num 8 88

I X0 Char 17 176 DCAD 17 CHARACTER ACCOUNT NUMBER

2 X8 Char 1 193 RCD-TYPE


6 XII Num 3 415 PROPERTY-CLASS





II X2I Char 25 227 TAXP-NAME-ADD2












23 X107 Char 1 343 LAND-AREAI-FLAG

24 XI08 Num 7 428 LAND-AREA1


2004 64


Alphabetic List of Variables and Attributes.....


fffffHHfffffHHffffffffffffffffffffffffHfH.ffffufffffffffffffffffffff 25 X109 Num 7 435 FRONTAGEI

26 X110 Num 7 442 LAND-DEPTHI






32 X147 Num 3 477 NUMBER-OF-LIVING-UNITS











43 X166 Num 3 483 FULL-BATHS



46 X169 Num 3 489 KITCHENS-NUM


48 X175 Char 2 370 HEAT

























2004 65


Alphabetic List of Variables and Attributes.....

II Variable Type Len Pos Label

ffHfffffffffffffffffHffHfufffffffffffffffffHfffffffffHffffHfffHHf 72 X560 Num 8 40 CURRENT ADJ SALES PRICE

73 X561 Num 8 48 PREVIOUS SALES PRICE

74 X562 Num 5 539 PREVIOUS SALES DATE



77 X565 Num 5 544 PREV2 SALES DATE




81 X610 Char 2 393 COUNTY-TAX-AUTH



84 X615 Char 2 399 COMU-COLG-TAX-AUTH







91 X640 Char 2 411 HOSPITAL CODE


4 XAIO Char 1 197

5 XBIO Char 2 198

96 age Num 8 112

97 baths Num 8 120

98 firepl Nüm 8 128

95 livarea Num 8 104

102 Inprice Num 8 160

103 mergvar Num 8 168

100 pool Num 8 144

94 price Num 8 96

99 wetbar Num 8 136

101 year Num 8 152


2004 66


Variables Ordered by Position-----


fffffHIffffffffHffffffffffffHfHffffffffffHfffffffffffffHHHfffffff I X0 Char 17 176 DCAD 17 CHARACTER ACCOUNT NUMBER

2 X8. Char 1 193 RCD-TYPE


4 XAIO Char 1 197

5 XBIO Char 2 198

6 Xli Num 3 415 PROPERTY-CLASS





II X21 Char 25 227 TAXP-NAME-ADD2












23 X107 Char 1 343 LAND-AREAI-FLAG

24 XI08 Num 7 428 LAND-AREAI

25 X109 Nurn 7 435 FRONTAGEI

26 XIIO Mum 7 442 LAND-DEPTHI






32 X147 Mum 3 477 NUMBER-OF-LIVING-UNITS











43 X166. Mum 3 483 FULL-BATHS



46 X169 Mum 3 489 KITCHENS-NUM



2004 67The CONTENTS Procedure

Variables Ordered by Position -----


fff,CffffffuffffHffffffffffffffffffffffffffffffffffffffffffffffHffHffff 48 X175 Char 2 370 HEAT





53 X188 Nurn 3 495 GARAGE 2-STALLS



















72 X560 Num 8 40 CURRENT ADJ SALES PRICE

73 X561 Num 8 48 PREVIOUS SALES PRICE

74 X562 Nurn 5 539 PREVIOUS SALES DATE



77 X565 Nurn 5 544 PREV2 SALES DATE




81 X6I0 Char 2 393 COUNTY-TAX-AUTH



84 X615 Char 2 399 COMU-COLG.TAX-AUTH







91 X640 Char 2 411 HOSPITAL CODE


93 I Num 8 88

94 price Num 8 96


2004 68


Variables Ordered by Position-----


HfffffffffffffffffffHfHffffffHfffHHfHffffffHHfHffffffffffHfHf 95 livarea Num 8 104

96 age Num 8 112

97 baths Num 8 120

98 firepl Num 8 128

99 wetbar Num 8 136

100 pool Num 8 144

101 year Num 8 152

102 Inprice Num 8 160

103 mergvar Num 8 168


2004 69

The REG Procedure

Model: MODEL1

Dependent Variable: Inprice

Analysis of Variance

Sum of Mean

Source DF Squares Square F Value Pr > F

Model 6 14.00267 2.33378 139.42 <.0001

Error 139 2.32672 0.01674

Corrected Total 145 16.32939

Root MSE 0.12938 R-Square 0.8575

Dependent Mean 12.35260 Adj R-Sq 0.8514

Coeff Var 1.04738

Parameter Estimates

Parameter Standard

Variable DF Estimate Error t Value Pr > iti

Intercept 1 11.61588 0.07440 156.13 <.0001

livarea 1 0.00044706 0.00003082 14.51 <.0001

age 1 .0.01070 0.00244 .4.38 <.0001

baths 1 .0.05377 0.03317 -1.62 0.1073

firepl 1 -0.01852 0.03437 -0.54 0.5909

wetbar 1 .0.00659 0.02546 .0.26 0.7962

pool 1 0.19968 0.03431 5.82 <.0001


2004 70


VariabLe: residual (Residual)

Moments

N 146 Sum Weights 146

Mean 0 Sum Observations 0

Std Deviation 0.12667411 Variance 0.01604633

Skewness -0.0499784 Kurtosis 1.82782753

Uncorrected SS 2.32671797 Corrected SS 2.32671797

Coeff Variation . Std Error Mean 0.01048362



Mean 0.000000 Std Deviation 0.12667

Median 0.011803 Variance 0.01605

Mode - Range 0.94482




Students t t 0 Pr > iti 1.0000

Sign M 10 Pr > 1M1 0.1155

Signed Rank S 176.5 Pr > IS' 0.7315

Test

Shapiro-Wi 1k

Kolmogorov-Smi rnov

Cramer-von Mises

Anderson - DarLi ng

Tests for Normality

--Statistic - - -

W 0.976372

D 0.075386

W-Sq 0.176495

A-Sq 0.965397

p Value ------

Pr < W 0.0126

Pr > D 0.0415

Pr > W-Sq 0.0105

Pr > A-Sq 0.0160


Quantile Estimate

1007. Max 04824060

99% 0.2881872

95% 0.2053115

90% 0.1365897

75% Q3 0.0717640

50% Median 0.0118028

25% QI -0.0792144


2004 71


Variable: residual (Residual)


Quantile Estimate

10% -0.1702379

5% -0.1886671

1% -0.2931200

0% Mm -0.4624150


Lowest------ Highest-----

Value Obs

Value Obs

-0.462415 14

-0.293120 26

-0.281509 23

-0.266832 101

-0.242015 79

0.251131 127

0.269786 69

0.275432 137

0.288187 59

0.482404 70

Stem Leaf Boxplot

48 S 1 0

4

3

3

25789 4

2113 3 I 1569 3

1 000112223334444 15 I O 5555556666666778888899999 25 .......

0 00000001111112222222233333344444 32 *. .+. .

-0 4444433333222221100 19 I -0 9999987666555 13 .......

-1 44332111000 11

-1 9998877766555 13

-2421 3

-2 987 3 I .3

-3

-4

-46 1 0

- ._+_ - - .+-. _.+. - _.+__ ..+_ - -

Multiply Stem.Leaf by 10**.1


2004 72

0.475+

1++

-0.475+*



Normal Probability Plot*

++ ***+*

***+

+++**

** * * *

*******

****+

***++

******

***+

.+-. ..+_ ._.+.. ..+. . . .+. .. .+. . ..+. .. .+. . . .+. . -2 .1 0 +1 +2


2004 73

The REG Procedure

Model: MODELI

Dependent Variable: Inprice

Analysis of Variance

Sum of Mean

Source DF Squares Square F Value Pr > F

Model 6 12.63409 2.10568 155.70 <.0001

Error 137 1.85276 0.01352

Corrected Total 143 14.48686

Root MSE 0.11629 R-Square 0.8721

Dependent Mean 12.35222 Adj R-Sq 0.8665

Coeff Var 0.94147

Parameter Estimates

Parameter Standard

Variable DF Estimate Error t Value Pr > Iti

Intercept 1 11.64386 0.06722 173.22 <.0001

livarea 1 0.00042213 0.00002854 14.79 <.0001

age 1 -0.00972 0.00220 -4.42 <.0001

baths 1 .0.04843 0.03059 -1.58 0.1157

firepl 1 .0.01504 0.03090 .0.49 0.6272

wetbar 1 -0.01887 0.02355 .0.80 0.4243

pool 1 0.21617 0.03113 6.94 <.0001


2004 74


128

Data Set Name: WORK.BETA

Member Type: DATA

Engine: V8

Created: 16:23 Tuesday, May 4, 2004

Last Modified: 16:23 Tuesday, May 4, 2004

Protection:

Data Set Type: EST

Label: Parameter Estimates and Statistics

Observations: I

Variables: 12

Indexes: 0

Observation Length:

Deleted Observations: 0

Compressed: NO

Sorted: NO


Data Set Page Size: 12288

Number of Data Set Pages: 1

First Data Page: 1

Max Obs per Page: 95

Obs in First Data Page: 1

Number of Data Set Repairs: 0

File Name: C:\DOCUME1\thamPtOn\LOCALS1\TemP'1S

Temporary Files\_TD1020\beta.saS7bdat

Release Created: 80202MO

Host Created: WIN_PRO



5 Intercept Num 8 8 Intercept

3 _DEPVAR_ Char 9 112 Dependent variable

I _MODEL_ Char 32 72 Label of model

4 _RMSE_ Num 8 0 Root mean squared error

2 _TYPE_ Char 8 104 Type of statistics

7 age Num 8 24

8 baths Num 8 32

9 firepl Num 8 40

6 livarea Num 8 16

12 Inprice Num 8 64

11 pool Num 8 56

10 wetbar Num 8 48

S

S

S

S S S S S S S

S S

S S S S S

S S

S

S

S

15:52 Tuesday, May 4, Input DCAD Master

2004 75

Obs _MODEL_ _TYPE_ DEPVAR_ _RMSE_ Intercept

I MODELI PARMS t.nprice 0.11629 11.6439

.0097161

tivarea age

.000422133 -

Obs baths firepi wetbar pool Inprice

1 -0.048433 -0.015041 -0.018873 0.21617 -1


2004 76



Moments


Mean -0.0001388 Sum Observations -0.019989

Std Deviation 0.11466503 Variance 0.01314807

Skewness -0.1276154 Kurtosis 0.1129338

Uncorrected SS 1.88017673 Corrected SS 1.88017396

Coeff Variation -82604.281 Std Error Mean 0.00955542



Mean -0.00014 Std Deviation 0.11467

Median 0.01180 Variance 0.01315

Mode . Range 058131




Student's t t -0.01453 Pr > ItI 09884

Sign M 10 Pr > IMI 0.1130

Signed Rank S 176 Pr > 1St 0.7269

Test

Shapiro-Wi 1k

Kolmogorov-Smi rnov

Cramer-von Mises

Anderson-Darling

Tests for Normality

--Statistic---

W 0.988004

D 0.076297

W-Sq 0.125528

A-Sq 0.671844

p Value ------

Pr < W 0.2497

Pr >.D 0.0395

Pr > W-Sq 0.0501

Pr > A-Sq 0.0816


Quantile Estimate

100% Max 0.2881872

99% 0.2754318

95% 0.1870753

90% 0.1309660

75% Q3 0.0710168

50% Median 0.0118028

25% Qi -0.0737679


2004 77




Quantile Estimate

10% .0.1564728

5% -0.1874783

1% -0.2815092

0% Mm -0.2931200


Lowest Highest

Value Obs Value Obs

-0.293120 25 0.227417 136

-0.281509 22 0.251131 125

-0.266832 99 0.269786 68

.0.242015 77 0.275432 135

-0.224289 140 0.288187 58

Stem Leaf II Boxplot

25789 4

2113 3 I 1569 3

1 000112223334444 15 I O 5555556666666778888899999 25 .......

0 00000001111112222222233333344444 32 * -----*

-0 4444433333222221100 19 +

-0 9999987666555 13 .......

-1 44332111000 11 I -1 9998877766555 13 I -2 421 3 I -2987 3 0

- _+. .__+-. ._+-- ._+_. ._+. - -

Multiply Stem.Leaf by 10**.1


2004 78



NormaL Probability Plot**+*+* 0.275+

******

I ******* I *****++

***+ •1 ++****

I +*** .0. 275+*+*+* ...................................................

.2 .1 0 +1 +2


2004 79The UNIVARIATE Procedure

Variable: price

Moments

N 144 Sum weights 144

Mean 243971.875 Sum Observations 35131950

Std Deviation 87190.0233 Variance 7602100165

Skewness 2.2264541 Kurtosis 9.6259415

Uncorrected SS 9.65831E12 Corrected SS 1.0871E12

Coeff Variation 35.7377355 Std Error Mean 7265.83528





Mode 250000.0 Range 631000



Test -Statistic- p Value......

Students t t 33.57795 Pr > It' <.0001


Signed Rank S 5220 Pr > ISI <.0001

Test

Shapiro-Wi 1k

Kolmogorov-Smi rnov

Cramer-von Mises

Anderson-Darling

Tests for Normality

--Statistic - - -

W 0.83914

D 0.133117

W-Sq 0.472639

A-Sq 3.278441

p Value ------

Pr < W <0.0001

Pr > D <0.0100

Pr > W-Sq <0.0050

Pr > A-Sq <0.0050


Quantile Estimate

100% Max 755000

99% 595000

95% 375000

90% 332000

75% Q3 276000

50% Median 237450

25% QI 186500


2004 80


Variable: price


Quantile Estimate

10!. 144900

5% 134500

1% 126000

0% Min 124000


Lowest Highest - - - -

Value Obs Value Obs

124000 15 412000 58

126000 13 435000 49

126500 16 560000 68

130000 5 595000 67

132900 38 755000 59

Stem Leaf II Boxplot

76 1 *

7

6

60 1 *

56 1 *

5

4

414 2 0

3 5556888 7 I 3 00012223344 11 I 2 55555556666666666677777778888888889999999 41 .......

2 00000000111222222222233333333333444444444 41 *--+--*

1 556666666667888888888999 24 .......

1 233333333444444 15

- _+- - - _+- - __+- -- _+._ - _+_ - - _+_. -

Multiply Stem.Leaf by 10**+5



Variable: price

Normal Probability Plot

775000+ *

I. **

I ++

I +**+++

+*********

I *******

125000+* * **** *****+ ...................................................

-2 -1 0 +1 +2


2004 82


Variable: yhat

Moments


Mean 242741.833 Sum Observations 34954824

Std Deviation 85168.6108 Variance 7253692257

Skewness 2.67154999 Kurtosis 13.5479384

Uncorrected SS 9.52228E12 Corrected SS 1.03728E12

Coeff Variation 35.086087 Std Error Mean 7097.38423





Mode 151753.7 Range 664216


NOTE: The mode displayed is the smallest of 2 modes with a count of 3



Students t t 3420159 Pr > Itl <.0001


Signed Rank S 5220 Pr > ISI <.0001

Test

Shapiro-Wi 1k

Kolmogorov-Smi rnov

Cramer-von Mises

Anderson-Darling

Tests for Normality

- -Statistic ---

W 0.806549

D 0.119134

W-Sq 0.610039

A-Sq 4.028629

p Value ------

Pr < W <0.0001

Pr > D <0.0100

Pr > W-Sq <0.0050

Pr > A-Sq <0.0050


Quantile Estimate

100% Max 806516

99% 564093

95% 387872

90% 332447

75% Q3 280211


2004 83


VariabLe: yhat


Quantile Estimate

50% Median 229869

25% QI 189556

10% 153753

5% 151754

1% 142441

0% Min 142300


Lowest Highest.-. -

Value Obs Value Obs

142300 12 418458 28

142441 38 419059 68

143226 15 435029 25

148253 90 564093 67

149569 7 806516 59

Stem Leaf Boxplot

81 1 *

7

7

6

6

56 1 *

5

4

411224 5 0

3 555669 6 I 3 0000000111112234 16

2 5555555556666778888888888899 28 .......

2 0000000001111111122222222223333333333333444444 46 *..+--*

1 55555555555556666666667888888999999999 38 .......

1444 3 I - ._+_ - - _+_ - - _+_ - _.+__ ._+_ .- _+._._+__ _.+____+.

Multiply StemLeaf by 10**+5


2004 84


Variable: yhat


825000+ *

*

475000+ +

** ** * + + +

++**++

++******** +********

125000+* * *** ++++++

+___ _+.- - _+_ -- _+_- __+_ . - _+____+_ - __+_ ._+__ - .+- - -

-2 -1 0 +1 +2

Input DCAD Master

2004 85The UNIVARIATE Procedure

Variable: prederr

Moments

N 144 Sum Weights




Uncorrected SS 1.41693E11 Corrected SS


15:52 Tuesday, May 4,

144

1771 26. 001

989337504

3.61729863

L41475E11

2621.14466



Mean 1230.042 Std Deviation

Median 1552.854 Variance

Mode . Range

interquartile Range

31454

989337504

238970

30584


Test -Statistic- p Value......

Students t t 0.469277 Pr > It' 0.6396

Sign M 10 Pr > Ml 0.1130

Signed Rank 5 331 Pr > 151 0.5111

Test

Shapi ro-Wi 1k

Kolmogorov-Smi rnov

Cramer-von Mises

Anderson-Darling

Tests for Normality

--Statistic -- -

W 0.943806

D 0.087097

W-Sq 0.359604

A-Sq 2.03818

p Value......

Pr < W <0.0001

Pr > D <0.0100

Pr > W-Sq <0.0050

Pr > A-Sq <0.0050


Quantile Estimate

100% Max 140940.52

99% 111007.71

95% 47553.02

90% 33811.64

75% Q3 16131.77

50% Median 1552.85

25% Q1 -14452.23



Variable: prederr


Quantile Estimate

10% .32729.69

5% -51516.24

1% -82872.18

0% Mm -98029.13


Lowest Highest

Value Obs Value Obs

-98029.1 25 57776.9 27

-82872.2 77 66081.9 135

. 73796.6 140 72726.6 125

-66479.5 99 111007.7 58

-61022.2 78 140940.5 68


2004 87


Variable: prederr

Stem Leaf Boxplot

141 1 *

13

12

111 S

*

10

9

8

73 1 0

66 1 0

508 2 I

4 15588 5

3 0124677 7 I

2 11122334444778 14 I

1 000011224445566689 18 .......

0 01111111122222333444455556677899 32

-0 98887776665554443210 20 I

-1 9987755431000 13 .......

-2 987663322110 12 I

-3 65320 5 I

-4431 3

-5 9621 4 I

-661 2 0

-74 1 0

-83 1 0

-98 1 0

- __+_ ___+-- __+_- __+._ __+_ . - _+_.

Multiply StemLeaf by 10**+4


2004 88


Variable: prederr


145000+ *

*

*++++ +*

I +***** ++***

25000+ ++*****

I ++****

I *******

I *****+

I ***++

I ++** I+++ *

I *

.95000+* ...................................................

-2 -1 0 +1 +2


Obs X0 price yhat livarea age baths

I 100006500B0010000 134500 151753.72 1425 19 2.0 2 100006500B0040000 133000 161400.74 1571 19 2.0 3 10000650000020000 144900 153300.06 1426 18 2.0 4 10000650000090000 133000 164567.79 1571 17 2.0 5 10000650000140000 130000 153235.37 1425 18 2.0 6 100006500D0050000 139000 153235.37 1425 18 2.0 7 100006500E0060000 134900 149569.10 1425 18 2.5 8 100006500E0080000 141500 154646.04 1402 18 2.0 9 100006500E0100000 149000 153235.37 1425 18 2.0

10 100006500F0010000 140900 162976.57 1571 18 2.0 11 100006500G0030000 135000 151753.72 1425 19 2.0 12 100006500G0040000 136000 142300.32 1330 19 2.5 13 100006500G0160000 126000 151753.72 1425 19 2.0 14 100006500H0030000 157000 150287.47 1402 19 2.0 15 100006500H0190000 124000 143226.43 1288 19 2.0 16 100006500J0020000 126500 152956.36 1409 15 2.5 17 100006500J0040000 163000 195729.69 1809 7 2.5 18 100006500J0150000 164500 193656.57 1647 3 2.5 19 100006500J0200000 179000 201010.50 1780 .3 2.5 20 100006500K0020000 184900 190117.57 1625 2 2.5 21 100006500K0040000. 195000 231177.28 2262 9 3.0 22 100006500K0160000 185000 244049.94 2333 9 2.5 23 100007600A0020000 354000 405092.74 2997 6 2.5 24 100007600A0040000 301000 299424.37 2304 7 2.5 25 100007600A0080000 337000 435029.13 3725 5 3.5 26 100007600A0110000 328750 335419.89 3062 6 2.5 27 10000760000050000 290000 232223.06 2214 7 2.5 28 10000760000080000 375000 418458.11 3633 5 3.5 29 10000926195700000 195000 178984.53 1955 21 2.5 30 10000926196060000 159000 167981.82 1667 21 2.0 31 10000926196140000 320000 286188.36 2756 6 3.5 32 10000926196440000 205000 203469.92 2075 19 2.0 33 10000926197180000 181500 180451.74 1894 21 2.5 34 10000926197420000 184900 183673.74 2038 21 3.0 35 10000926197520000 225000 248192.62 2544 12 3.0 36 10000926197660000 194000 185497.09 1958 19 2.5 37 10000926198160000 209900 198458.59 2118 19 2.5 38 10000926198320000 132900 142440.58 1321 21 2.0 39 10000926198380000 255000 253894.81 2508 6 3.5 40 10000926198400000 178000 153752.64 1456 19 2.0 41 10000926198680000 190000 175819.91 1729 19 2.0 42 10000926199050000 179000 178256.14 1865 21 2.5 43 10000926199070000 160000 195386.44 2025 21 2.0 44 10000926199160000 159500 155231.40 1480 21 2.0 45 10000926199340000 159900 160089.44 1553 21 2.0 46 . 10000926199420000 183000 178984.53 1955 21 2.5 47 10000926199430000 159900 156745.89 1503 21 2.0 48 10000926199480000 163750 158743.54 1533 21 2.0 49 10000927412100000 435000 407611.34 3576 19 4.5 50 10000927412280000 332000 286949.02 2492 18 2.5 51 10000927412420000 350000 312541.73 2707 17 2.5


2004 90Obs X0 price yhat livarea age baths

52 10000927414080000 365000 319731.85 2863 18 3.5

53 10000927414100000 380000 356766.54 3087 18 3.5

54 10000927414460000 275000 254275.67 2170 18 2.5

55 10000927414920000 319900 282772.15 2479 18 3.0

56 10000927415000000 335000 312659.93 2694 17 3.0

57 10000927415060000 380000 332446.98 2782 17 2.5

58 10000927415200000 412000 300992.29 3116 17 3.0

59 10002090030060000 755000 806516.24 4849 11 3.5

60 100042200A0040000 200000 197644.21 1753 8 2.0

61 100042200A0090000 220000 192701.15 1693 8 2.0

62 100042200A0150000 283500 303991.91 2945 8 3.5

63 100042200A0180000 .208000 187167.94 1647 9 2.0

64 10004220000010000 260000 255327.92 2510 8 3.0

65 10004220000060000 241400 227054.06 2162 9 2.5

66 100042200C11R0000 198000 188356.96 1755 9 2.5

67 100043200A0020000 595000 564093.05 3771 5 3.0

68 100043200B0010000 560000 419059.48 3146 4 3.5

69 10004350030040000 188000 194829.15 1696 7 2.0

70 10004350030070000 223000 220793.95 2028 7 2.0

71 10004350030080000 250000 230826.28 2155 7 2.5

72 10004350030250000 258500 263209.09 2466 7 2.5

73 10004350030310000 215000 217489.75 1991 6 2.5

74 10004350030530000 198000 205909.45 1781 5 2.0

75 10004350040010000 270000 284830.60 2630 6 2.5

76 10004350040070000 264000 262877.82 2440 6 2.5

77 10004350040150000 305000 387872.18 2862 5 2.5

78 10004350040180000 288000 349022.22 2635 6 . 2.5

79 10004350040210000 259000 264580.22 2500 6 2.5

80 100043900A0020000 230000 225880.64 2045 5 2.0

81 100043900A0150000 225000 215203.55 2012 8 2.5

82 100043900A0230000 233500 209378.93 1947 8 2.5

83 100043900A0400000 215750 191537.32 1713 7 2.5

84 100043900B0010000 267500 275952.18 2578 7 2.5

85 100043900B0110000 199900 196896.13 1721 7 2.0

86 100043900B0120000 210000 209203.71 1922 7 2.5

87 100043900B0130000 217500 206918.70 1919 8 2.5

88 100043900B0260000 230000 188995.35 1647 8 2.0

89 10004790010820000 183000 161282.62 1684 19 3.0

90 10004790030010000 150000 148252.74 1325 19 2.0

91 10004790030050000 174500 162906.00 1640 18 3.0

92 100048100A0060000 229500 233076.66 2201 8 2.5

93 100048100A0190000 264000 253714.36 2425 9 2.5

94 100048100A0250000 240000 221844.76 2084 8 2.5

95 100048100B0060000 250000 235249.65 2246 9 2.5

96 100059500A1130000 229900 213424.38 1981 10 2.0

97 100059500A1150000 269900 313478.29 2437 10 2.5

98 100059500A1460000 262500 247708.78 2085 17 2.5

99 100059500A1530000 229000 295479.54 2879 9 3.0

100 100059500A1550000 229800 205810.19 1974 9 2.5

101 100059500A1560000 275000 284702.36 2721 10 2.5

102 100059500A1820000 284500 279894.02 2715 9 3.0


2004 91Obs X0 price yhat livarea age baths

103 100059500A1830000 245000 248252.32 1827 10 2.0

104 100059500A1860000 291500 347436.72 2715 9 3.0

105 100059500A1880000 285000 280528.88 2663 9 2.5

106 10005950060280000 230000 213751.92 2042 10 2.5

107 100059500B0320000 267000 254678.31 2457 10 2.5

108 100059500B0560000 255000 265806.03 2580 9 2.5

109 1000595000O570000 320000 346690.67 2835 10 3.5

110 10005950000660000 235000 253743.82 2493 10 2.5

111 100059500050R0000 225500 220663.32 2037 9 2.0

112 100059500D0500000 275000 296094.25 2893 9 3.0

113 100059500D0570000 247000 218529.72 2037 10 2.0

114 100059800A0020000 228000 221936.87 2108 9 2.5

115 100059800A0060000 260000 251156.91 2401 9 2.5

116 100059800A0100000 239900 230372.06 2139 9 2.0

117 100059800A0120000 222000 219363.08 2023 9 2.0

118 100059800A0160000 265000 275493.63 2108 9 2.5

119 100059800A0190000 267000 230824.66 2178 8 2.5

120 100059800A0280000 224000 229366.08 2186 9 2.5

121 10005980060030000 254000 275484.68 2597 8 2.5

122 100059800B0160000 305000 305888.60 2845 8 2.5

123 100059800B0190000 201000 199702.21 1867 9 2.5

124 10005990010060000 269000 239494.84 2231 9 2.0

125 10005990020080000 310000 237273.40 2311 9 2.5

126 10005990050020000 240000 232583.60 2219 9 2.5

127 10006020060050000 232500 224233.12 2052 8 2.0

128 10006020060190000 290000 295980.81 2767 8 2.5

129 10006020000010000 280000 283681.95 2097 8 2.0

130 10006020000100000 288000 273977.04 2584 8 2.5

131 1000602000O220000 250000 228533.36 2097 8 2.0

132 100060200D0090000 254000 230764.63 2097 7 2.0

133 100060200D0110000 289000 295980.81 2767 8 2.5

134 100060200D0180000 279900 231445.90 2127 8 2.0

135 100060200D0200000 277000 210918.10 1930 9 2.0

136 100060200D0210000 250000 200330.74 1808 9 2.0

137 100060200D0280000 222000 221598.35 2024 8 2.0

138 100060200D0320000 347000 315097.58 3030 8 3.5

139 100060200E0060000 272500 313108.69 3015 8 3.5

140 100060200E0160000 290000 363796.64 2824 9 3.0

141 100061000A0200000 245000 275176.74 2560 9 2.0

142 100061000A0230000 257500 275176.74 2560 9 2.0

143 100061000B0060000 245000 239191.74 2228 9 2.0

144 100061000B0150000 240000 239191.74 2228 9 2.0

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