Stats, Graphs and Data Science I

This 14 hour hands-on workshop introduces and exploits “big data” tools, computation, and predictive methods for valuation.  It emphasizes applied solution-based learning, using real data, for objective evidence-based results.  Data science results are simpler, more useful, and intuitively sensible.

Students leave with immediately useful skills:

  1. Apply visual methods to structure assignments and define markets.

  2. Classify and technically quantify comparable data selection.

  3. Adjust and interpolate, using contrasting and simple regression.

  4. Discern calculated, estimated, and biased adjustment estimators.

  5. Get the complexities, pitfalls, hype, and flim-flam of multiple regression.

  6. See the potential of real data analysis software, such as open-source R.

Analytics software is provided, as well as example data sets and templates for use in form and narrative reporting.  The use of these tools is particularly useful for sparse-data appraisal problems through the support of location (spatial), and price indexing (time) adjustments.  Local commercial and/or residential data sets are used in presented examples

  1. This course is prerequisite to intermediate and advanced courses offered by education, leading to auditable valuation practices.