Editing Confirmation bias (section)

=== Hypothesis testing (positive test strategy) explanation (Klayman and Ha) ===
Klayman and Ha's 1987 paper argues that the Wason experiments do not actually demonstrate a bias towards confirmation, but instead a tendency to make tests consistent with the working hypothesis.<ref name="klaymanha" /><ref>{{Harvnb|Oswald|Grosjean|2004|pp=81–82, 86–87}}</ref> They called this the "positive test strategy".<ref name=kunda112 /> This strategy is an example of a [[heuristics in judgment and decision making|heuristic]]: a reasoning shortcut that is imperfect but easy to compute.<ref name="plous233">{{Harvnb|Plous|1993|p=233}}</ref> Klayman and Ha used [[Bayesian probability]] and [[information theory]] as their standard of hypothesis-testing, rather than the falsificationism used by Wason. According to these ideas, each answer to a question yields a different amount of information, which depends on the person's prior beliefs. Thus a scientific test of a hypothesis is one that is expected to produce the most information. Since the information content depends on initial probabilities, a positive test can either be highly informative or uninformative. Klayman and Ha argued that when people think about realistic problems, they are looking for a specific answer with a small initial probability. In this case, positive tests are usually more informative than negative tests.<ref name="klaymanha">{{Citation |last1=Klayman |first1=Joshua |first2=Young-Won |last2=Ha |year=1987 |title=Confirmation, disconfirmation and information in hypothesis testing |journal=[[Psychological Review]] |volume=94 |issue=2 |pages=211–228 |issn=0033-295X |url=http://www.stats.org.uk/statistical-inference/KlaymanHa1987.pdf |access-date=14 August 2009 |doi=10.1037/0033-295X.94.2.211 |citeseerx=10.1.1.174.5232 |s2cid=10853196 |archive-date=1 October 2011 |archive-url=https://web.archive.org/web/20111001031955/http://www.stats.org.uk/statistical-inference/KlaymanHa1987.pdf |url-status=live }}</ref> However, in Wason's rule discovery task the answer—three numbers in ascending order—is very broad, so positive tests are unlikely to yield informative answers. Klayman and Ha supported their analysis by citing an experiment that used the labels "DAX" and "MED" in place of "fits the rule" and "doesn't fit the rule". This avoided implying that the aim was to find a low-probability rule. Participants had much more success with this version of the experiment.<ref>{{Harvnb|Lewicka|1998|page=239}}</ref><ref>{{Citation |last1=Tweney |first1=Ryan D. |first2=Michael E. |last2=Doherty |year=1980 |title=Strategies of rule discovery in an inference task |journal=[[The Quarterly Journal of Experimental Psychology]]|issn=1747-0226 |volume=32 |issue=1 |pages= 109–123 |doi=10.1080/00335558008248237|s2cid=143148831 }} (Experiment&nbsp;IV)</ref>

{| style="margin:auto"
|-valign="top"
| [[Image:Klayman Ha1.svg|thumb|alt=Within the universe of all possible triples, those that fit the true rule are shown schematically as a circle. The hypothesized rule is a smaller circle enclosed within it. |If the true rule (T) encompasses the current hypothesis (H), then positive tests (examining an H to see if it is T) will not show that the hypothesis is false.]]
| [[Image:Klayman Ha2.svg|thumb|alt=Two overlapping circles represent the true rule and the hypothesized rule. Any observation falling in the non-overlapping parts of the circles shows that the two rules are not exactly the same. In other words, those observations falsify the hypothesis.|If the true rule (T) ''overlaps'' the current hypothesis (H), then either a negative test or a positive test can potentially falsify H.]]
| [[Image:Klayman ha3 annotations.svg|thumb|alt=The triples fitting the hypothesis are represented as a circle within the universe of all triples. The true rule is a smaller circle within this.|When the working hypothesis (H) includes the true rule (T) then positive tests are the ''only'' way to falsify H.]]
|}

In light of this and other critiques, the focus of research moved away from confirmation versus falsification of an hypothesis, to examining whether people test hypotheses in an informative way, or an uninformative but positive way. The search for "true" confirmation bias led psychologists to look at a wider range of effects in how people process information.<ref>{{Harvnb|Oswald|Grosjean|2004|pp=86–89}}</ref>