Mass Appraisal Models Using SPSS – 2 day 15 CE hours
NOTE: Laptop computer required with SPSS version 19 or higher
Limited class size: 18 Students Maximum
This two-day workshop is designed for appraisers and modelers alike for creating assessment values based on a group of residential market sales. This hands-on workshop places students in a simulation where, using SPSS, they step through a proven case study while understanding how property adjustments are developed and predicted residential property values are created.
Using actual data, students determine time adjustments and use multiple regression to calculate and understand the major adjustments of a property. After exploring the data, calculating a monthly time adjustment, and applying an iterative regression method, the students will learn and develop both an additive and multiplicative model and compare the results, identifying the key differences and benefits.
As a result, the students will develop confidence in explaining assessment valuation and the knowledge to apply these mass appraisal methods back in the office.
- Basic computer skills:
- Navigate from one screen to another and copy/paste/open/close files
- Working knowledge of Excel
- Previous experience with SPSS is recommended, but not required.
- Students must arrive to the workshop with a laptop that includes Microsoft Excel and either a copy of SPSS (version 19 or higher) OR a trial version downloaded from IBM (prior to the workshop, detailed instructions will be provided on how and when to download it)
Instructor: Geoff Lycas
- Monday All Day Session
August 26, 2019
8:00 am - 5:00 pm
- Tuesday All Day Session
August 27, 2019
8:00 am - 5:00 pm
Venue: Beaver Run Resort
Venue Phone: 1-800-525-2253
Venue Website: https://www.beaverrun.com/Address:
Individuals can make reservations at any time by calling: 1-800-525-2253 and referencing “CATA 2019” – OR – a member can register online here.
In order to receive discounted group rates, please make your reservations prior to July 27, 2019.
For additional details, view the Lodging Information PDF.