Cumulative graphs are used when aba

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In Part Two we described considerations and procedures for selecting and defin- ing target behaviors and discussed detailed methods for measuring behavior; we also examined techniques for improving, assessing, and reporting the veracity of measurement. The product of these measurements, called data, is the medium with which the behavior analyst works. But what does the behavior analyst do with the data? The five chapters in Part Three are devoted to the presentation and interpretation of behavioral data and to the design, conduct, and evaluation of ex- periments analyzing the effects of interventions.

In Chapter 6 we describe the graphic displays used by researchers, practi- tioners, and consumers to make sense of behavioral data. We discuss considera- tions for selecting, constructing, and interpreting the major types of graphs most often used by behavior analysts. Although measurement and graphic displays can reveal whether, when, and to what extent behavior has changed, they alone can- not reveal what brought about the behavior change. Chapters 7 through 10 are devoted to the analysis in applied behavior analysis. Chapter 7 describes the req- uisite components of any experiment in behavior analysis and explains how re- searchers and practitioners apply steady-state strategy and the three elements of basic logic—prediction, verification, and replication—-to seek and verify func- tional relations between behavior and its controlling variables. In Chapters 8 and 9 we describe the logic and operation of the reversal, alternating treatments, multiple baseline, and changing criterion designs—the most commonly used experimental designs in applied behavior analysis. Chapter 10 covers a wide range of topics necessary for developing a more complete understanding of be- havioral research. Beginning with the assumption that the research methods of any science should reflect the characteristics of its subject matter, we examine the importance of analyzing behavior at the level of individual client or research par- ticipant, discuss the value of flexibility in experimental design, identify some common confounds to the internal validity of experiments, present methods for assessing the social validity of an applied behavior analysis, and describe how replication is used to determine the external validity of research. We conclude Chapter 10 and Part Three with a series of issues and questions that should be considered in evaluating the “goodness” of a published study in applied behavior analysis.

P A R T 3

Evaluating and Analyzing Behavior Change

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C H A P T E R 6

Constructing and Interpreting Graphic Displays of Behavioral Data

Key Terms

bar graph cumulative record cumulative recorder data data path dependent variable graph

independent variable level line graph local response rate overall response rate scatterplot semilogarithmic chart

split-middle line of progress Standard Celeration Chart trend variability visual analysis

Behavior Analyst Certification Board® BCBA® & BCABA® Behavior Analyst Task List ©, Third Edition

Content Area 7: Displaying and Interpreting Behavioral Data

7-1 Select a data display that effectively communicates quantitative relations.

7-2 Use equal-interval graphs.

7-3 Use Standard Celeration Charts (for BCBA only—excluded for BCABA).

7-4 Use a cumulative record to display data.

7-5 Use data displays that highlight patterns of behavior (e.g., scatterplot).

7-6 Interpret and base decision making on data displayed in various formats.

© 2006 The Behavior Analyst Certification Board, Inc.,® (BACB®) all rights reserved. A current version of this document may be found at www.bacb.com. Requests to reprint, copy, or distribute this document and ques- tions about this document must be submitted directly to the BACB.

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Applied Behavior Analysis, Second Edition, by John O. Cooper, Timothy E. Heron, and William L. Heward. Published by Merrill Prentice Hall. Copyright © 2007 by Pearson Education, Inc.

Chapter 6 Constructing and Interpreting Graphic Displays of Behavioral Data 127

Applied behavior analysts document and quan- tify behavior change by direct and repeated measurement of behavior. The product of these

measurements, called data, is the medium with which behavior analysts work. In everyday usage the word data refers to a wide variety of often imprecise and subjec- tive information offered as facts. In scientific usage the word data means “the results of measurement, usually in quantified form” (Johnston & Pennypacker, 1993a, p. 365).1

Because behavior change is a dynamic and ongoing process, the behavior analyst—the practitioner and the researcher—must maintain direct and continuous con- tact with the behavior under investigation. The data ob- tained throughout a behavior change program or a research study are the means for that contact; they form the empirical basis for every important decision: to con- tinue with the present procedure, to try a different inter- vention, or to reinstitute a previous condition. But making valid and reliable decisions from the raw data themselves (a series of numbers) is difficult, if not impossible, and in- efficient. Inspecting a long row of numbers will reveal only very large changes in performance, or no change at all, and important features of behavior change can easily be overlooked.

Consider the three sets of data that follow; each con- sists of a series of numbers representing consecutive mea- sures of some target behavior. The first data set shows the results of successive measures of the number of responses emitted under two different conditions (A and B):

Condition A Condition B

120, 125, 115, 130, 114, 110, 115, 121,

126, 130, 123, 120, 110, 116, 107, 120,