AVM Glossary

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  • Anything that is stored electronically on a computer is software. The storage device is hardware. There are two general categories of software, operating systems and the utilities that allow the computer to function, and applications, programs that allow users to work with the computer, e.g. word processing, spreadsheets, databases, AVMs.
  • Refers to the location of, proximity to, or orientation of objects with respect to one another in N - Dimensional space. Generally refers to phenomena that can be mapped in two or three dimensions on or near the earth's surface.
  • A standard nonparametric test is useful in examining assessment bias, among other things. It is based on the correlation of two sets of ranks.
  • A unit of area equal to a square one foot in length on each side.
  • See Uniform Standards of Professional Appraisal
  • Analysts frequently measure the dispersion of valuation error in terms of a standard deviation, a common statistical formula which measures how tightly these variances are clustered around the mean percentage error. If the distribution of an AVM’s valuation errors follows a normal bell-shaped curve, then roughly 68 percent of its value estimates will fall within plus or minus one standard deviation of the mean-variance. A lower standard deviation indicates a tight concentration around the mean-variance; an elevated standard deviation suggests that the model performs inconsistently.
  • A measure of the precision of a measure of central tendency; the smaller the standard error, the more reliable the measure of central tendency. Standard errors are used in calculating a confidence interval about the arithmetic mean and the weighted mean.
  • An expression for the standard deviation of the observed values about the regression line; thus it provides an estimate of the variation likely to be encountered in making predictions from the regression equation.
  • (1) To transform a variable to standard form; that is, to make the mean of the frequency distribution equal to zero and the standard deviation equal to one. (2) To adjust, for appraisal purposes, reported data such as income and expenses, so as to remove the effects of non - Real estate factors, such as abnormally good or bad management, weather, and the like. The more common term for this adjustment process is "normalization."
  • The closeness between the statistical estimate and the true (but unknown) population parameter value it was designed to measure. It is usually characterized in terms of error or the potential significance of error and can be decomposed into sampling error and nonsampling error components. Accuracy can be specified by the level of confidence selected for a statistical test. See accuracy.
  • A reference to how closely the survey results from a sample can reproduce the results that would be obtained from the entire population (a complete census). The amount by which a sample statistic can vary from the true population parameter is due to error. Even if all the sample data are perfectly accurate, random (sampling) error affects statistical precision (measured by the standard error or standard deviation). The dispersion of ratios in the population and the sample size have a controlling influence over the precision of any statistical estimate. When the reliability of a(...)
  • (1) Numerical descriptions calculated from a sample, for example, the median, mean, or coefficient of dispersion. Statistics are used to estimate corresponding measures, termed parameters, for the population. (2) The science of studying numerical data systematically and of presenting the results usefully. Two main branches exist: descriptive statistics and inferential statistics.
  • A kind of multiple regression analysis in which the independent variables enter the model, and leave it if appropriate, one by one according to their ability to improve the equation’s power to predict the value of the dependent variable.
  • A kind of multiple regression analysis in which the independent variables enter the model, and leave it if appropriate, one by one according to their ability to improve the equation's power to predict the value of the dependent variable.
  • A perception that a property continues to be contaminated even though it has been cleaned up. Stigma may affect property value.
  • The division of a sample of observations into two or more subsets according to some criterion or set of criteria. Such a division may be made to analyze disparate property types, locations, or characteristics, for example.
  • To divide, for purposes of analysis, a sample of observations into two or more subsets according to some criterion or set of criteria.
  • The property being valued.
  • Having the quality of requiring judgment in arriving at an appropriate answer or value for a variable (such as the quality class of a structure). See objective; qualitative variable; quantitative variable.
  • Subjective data are items for which the proper value is a matter of judgment and more difficult to verify. Examples include construction class, condition, effective year built, neighborhood desirability, and view.
  • A group of properties within a sample, smaller than the sample, usually although not necessarily defined by stratification rather than by sampling.
  • The appraisal principle that states that a potential owner will pay no more for a property than the amount for which a property of like utility may be purchased; that a property's value tends to be set by the cost of acquiring an equally desirable substitute.
  • The sum of the squared deviations from the predicted values (rather than the mean value).
  • The result obtained by adding all the squares of the individual deviations from some given value. Usually it is the sum of the squares of the deviations of the individual values of a variable from the mean value.
  • A feature of a property exceeding in quality or amount the corresponding feature in a typical property of the same use. Superinsulation is one example. Superadequacies fall into the larger category of functional obsolescence.
  • The capability of overlaying, normally an aerial image and a line map, for the purpose of data collection or data maintenance.

Sources:

a)       AVMetrics

b)      AVMs 201: A Practical Guide to the Implementation of Automated Valuation Models, Jim Kirchmeyer, 2008.

c)       IAAO 2015, Glossary for Property Appraisal and Assessment, 2015. (2013 online: https://www.iaao.org/media/Pubs/IAAO_GLOSSARY.pdf )

d)      Collateral Assessment & Technologies Committee, Summary of Definitions & Terms, 2006.

e)      Joint Industry Task Force on AVMs, IAAO Standard on AVM Glossary, September 2003. https://www.iaao.org/media/standards/AVM_STANDARD.pdf

f)        Appraisal Institute, Joint Industry Task Force on Automated Valuation Models, Work Group Terminology, 2005.

g) Merriam-Webster (https://www.merriam-webster.com/)