Association for Behavior Analysis International

The Association for Behavior Analysis International® (ABAI) is a nonprofit membership organization with the mission to contribute to the well-being of society by developing, enhancing, and supporting the growth and vitality of the science of behavior analysis through research, education, and practice.


47th Annual Convention; Online; 2021

All times listed are Eastern time (GMT-4 at the time of the convention in May).

Event Details

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Paper Session #73
CE Offered: BACB
Behavior Analysis Was Never Clear About "Slope" in Graphed Data
Saturday, May 29, 2021
12:00 PM–12:25 PM
Area: PCH
Instruction Level: Intermediate
Chair: Chad Kinney (Florida Tech)
CE Instructor: Chad Kinney, Ph.D.
Behavior Analysis Was Never Clear About "Slope" in Graphed Data
Domain: Applied Research
CHAD KINNEY (Florida Tech)
Abstract: Behavior analysts (and mathematicians alike) have struggled with accurate and reliable quantification of geometric slope on non-homogenous and non-standard graphs. Virtually all graphs in behavior analysis are non-homogenous (i.e., scale values/distances are unequal between axes), and most are non-standard. However, this presentation does NOT advocate increased use of standard displays. Instead, newly discovered mathematical equations will demonstrate that a standard semi-log display is no longer necessary to quickly achieve reliable and accurate quantification of geometric slope—even if data are plotted across various custom-made non-standard graphs with linear axes. This presentation will demonstrate how the new equations clarify the relation between algebraic and geometric slope, and reveal applications that will be used to improve interrater agreement of visual inspection (and more) in the future.
Target Audience:

Attendees should have basic understanding of algebraic slope, angles of inclination, and ratios.

Learning Objectives:

At the conclusion of the presentation, participants will be able to (1) describe the difference between algebraic and geometric slope, and (2) describe how altering the new equation of graphic induced variability (i.e., the Graphic Variability Quotient [GVQ]) measurably alters the appearance of slope and variability on any time-series graph. 




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