Statistical Reports
Based on the quality of data, AccuriZ can produce different statistical reports to provide a macro overview of a community or for specific purposes, detailed statistical
reports can be produced given specific levels of stratification. Some common statistical studies are as follows:
AccuriZ provides a scientific, unbiased approach for independent valuation. This approach is the culmination of years of experience and rigorous research using proprietary
series of algorithms to deliver the most accurate results- results that are not just close but precise.
AccuriZ follows a procedural structure aimed at delivering property valuation estimates that represent the most accurate market
value for the period defined. The most critical element in property valuation is the physical data that exists for a property.
Proprietary algorithms that have been developed over years of testing enable AccuriZ
to clean and stratify data so that accurate valuation estimates can be produced.
When operating in a vacuum, the absence of data yields
a poor valuation. At AccuriZ, we operate with precision, not in a vacuum.
Our analysis of property sales dating back to 1990 enables AccuriZ to develop
a powerful time-line covering the past 16 years. The reporting available as a result
provides real estate trends by zip code throughout New York State (and soon in other
regions as well).
4-3-2-1 Rule
An empirical rule that ascribes 40 percent of the value of a standard lot (see lot, standard)
to the quarter of the lot fronting on the street, 30 percent to the next quarter,
20 percent to the third quarter, and 10 percent to the rear quarter. Compare Harper
rule; Hoffman rule; one-third, two-thirds rule. Note: Lots with a depth greater
than the standard lot cannot be valued in accordance with this rule as stated above.
The rule is sometimes altered by omitting the word "standard." It thereby becomes
applicable to extra deep lots but produces inconsistent results as applied to lots
of varying depths.
Accuracy
Accuracy. The closeness of a measurement, computation, or estimate to the true,
exact, or accepted value. Accuracy also can be expressed as a range about the true
value. See also precision and statistical accuracy.
Adjustments
Modifications in the reported value of a variable, such as sale price. For example,
adjustments can be used to estimate market value in the sales comparison approach
by modifications for differences between comparable and subject properties. Note:
Adjustments are applied to the characteristics of the comparable properties in a
particular sequence that depends on the method of adjustment selected.
Algorithm
A computer-oriented, precisely defined set of steps that, if followed exactly, will
produce a pre-specified result, for example, the solution to a problem.
Additive Model
A model in which the dependent variable is estimated by multiplying each independent variable
by its coefficient and adding each product to a constant.
Adaptive Estimation
Procedure (AEP or Feedback)
A computerized,
iterative, self-referential procedure using properties for which sales prices are
known to produce a model that can be used to value properties for which sales prices
are not known. Also called "feedback."
Comparable Sales; Comparables
(1) Recently sold properties that are similar in important respects to a property
being appraised. The sale price and the physical, functional, and locational characteristics
of each of the properties are Compared to those of the property being appraised
in order to arrive at an estimate of value. (2) By extension, the term "comparables"
is sometimes used to refer to properties with rent or income patterns comparable
to those of a property being appraised.
Confidence Interval
A range of values, calculated from the sample observations, that are believed, with
a particular probability, to contain the true population parameter (mean, median,
COD). The confidence interval is not a measure of precision for the sample statistic
or point estimate, but a measure of the precision of the sampling process (see reliability).
Confidence Level
The required degree of confidence in a statistical test or confidence interval;
commonly 90, 95, or 99 percent. A 95 percent confidence interval would mean, for
example, that one can be 95 percent confident that the population measure (such
as the median or mean appraisal ratio) falls in the indicated range.
Mean
A measure of central tendency. The result of adding all the values of a variable
and dividing by the number of values. For example, the mean of 3, 5, and 10 is 18
divided by 3, or 6. Also called arithmetic mean.
Median
A measure of central tendency. The value of the middle item in an uneven number
of items arranged or arrayed according to size; the arithmetic average of the two
central items in an even number of items similarly arranged; a positional average
that is not affected by the size of extreme values.
Model Calibration
The development of adjustments, or coefficients based on market analysis, that identifies specific
factors with an actual effect on market value.
Multiplicative Model
A mathematical model in which the coefficients of independent variables serve as powers (exponents)
to which the independent variables are raised or in which independent variables
themselves serve as exponents; the results are then multiplied to estimate the value
of the dependent variable.
Ratio Study
A study of the relationship between appraised or assessed values and market values.
Indicators of market values may be either sales (sales ratio study) or independent
"expert" appraisals (appraisal ratio study). Of common interest in ratio studies
are the level and uniformity of the appraisals or assessments. See also level of
appraisal and level of assessment.
Regression Coefficient
The coefficient
calculated by the regression algorithm for the data supplied that, when multiplied
by the value of the variable with which it is associated, will predict (for simple
regression) or help to predict (for multiple regression) the value of the dependent
variable. For example, in the equation, Value = $10,000 + $5,000 + number of rooms,
$5,000 is a regression coefficient.
Regression Line
The line on a graph that represents the relationship defined by the regression coefficients.
For example, the line from the relationship given in the definition of regression
coefficient would cross the y-axis at the value $10,000 and would go up $5,000 for
each movement of 1 to the right. This example illustrates one of the subtleties
required in understanding regression analysis: in fact, there is no line, because
the independent variable is not a continuous variable, but it is easier to talk
about the relationship by pretending that the variable is continuous and represent
the relationship by a line rather than the more nearly correct series of vertical
bars on a bar chart.
