A CRITIQUE OF THE USEFULNESS OF INFERENTIAL STATISTICS IN APPLIED BEHAVIOR ANALYSIS

Researchers continue to recommend that applied behavior analysts use i nferential statistics in making decisions about effects of independent variables on dependent variables. In many other approaches to behavio ral science, inferential statistics are the primary means for deciding the importance of effects. Several possible uses of inferential stati stics are considered. Rather than being an objective means for making decisions about effects, as is often claimed, inferential statistics a re shown to be subjective. It is argued that the use of inferential st atistics adds nothing to the complex and admittedly subjective nonstat istical methods that are often employed in applied behavior analysis. Attacks on inferential statistics that are being made, perhaps with in creasing frequency, by those who are not behavior analysts, are discus sed. These attackers are calling for banning the use of inferential st atistics in research publications and commonly recommend that behavior al scientists should switch to using statistics aimed at interval esti mation or the method of confidence intervals. Interval estimation is s hown to be contrary to the fundamental assumption of behavior analysis that only individuals behave. It is recommended that authors who wish to publish the results of inferential statistics be asked to justify them as a means for helping us to identify any ways in which they may be useful.