Dichotomous thinking or binary thinking in
statistics
Statistics (from German language, German: ', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a s ...
is the process of seeing a discontinuity in the possible values that a
p-value
In null-hypothesis significance testing, the ''p''-value is the probability of obtaining test results at least as extreme as the result actually observed, under the assumption that the null hypothesis is correct. A very small ''p''-value means ...
can take during
null hypothesis significance testing: it is either above the significance threshold (usually 0.05) or below. When applying dichotomous thinking, a first p-value of 0.0499 will be interpreted the same as a p-value of 0.0001 (the null hypothesis is rejected) while a second p-value of 0.0501 will be interpreted the same as a p-value of 0.7 (the null hypothesis is accepted). The fact that first and second p-values are mathematically very close is thus completely disregarded and values of p are not considered as continuous but are interpreted dichotomously with respect to the significance threshold. A common measure of dichotomous thinking is the
cliff effect
In telecommunications, the (digital) cliff effect or brick-wall effect is a sudden loss of digital signal reception. Unlike analog signals, which gradually fade when signal strength decreases or electromagnetic interference or multipath inc ...
.
A reason to avoid dichotomous thinking is that p-values and other statistics naturally change from study to study due to random variation alone; decisions about refutation or support of a scientific hypothesis based on a result from a single study are therefore not reliable.
Dichotomous thinking is very often associated with p-value reading
but it can also happen with other statistical tools such as interval estimates.
[{{cite journal , last1=Helske , first1=Jouni , last2=Helske , first2=Satu , last3=Cooper , first3=Matthew , last4=Ynnerman , first4=Anders , last5=Besancon , first5=Lonni , title=Can Visualization Alleviate Dichotomous Thinking? Effects of Visual Representations on the Cliff Effect , journal=IEEE Transactions on Visualization and Computer Graphics , publisher=Institute of Electrical and Electronics Engineers (IEEE) , volume=27 , issue=8 , date=2021 , issn=1077-2626 , doi=10.1109/tvcg.2021.3073466, arxiv=2002.07671 , pages=3397–3409, pmid=33856998 , s2cid=233230810 ]
See also
*
Statistical hypothesis testing
A statistical hypothesis test is a method of statistical inference used to decide whether the data provide sufficient evidence to reject a particular hypothesis. A statistical hypothesis test typically involves a calculation of a test statistic. T ...
*
Splitting (psychology)
Splitting, also called binary thinking, dichotomous thinking, black-and-white thinking, all-or-nothing thinking, or thinking in extremes, is the failure in a person's thinking to bring together the dichotomy of both perceived positive and negative ...
References
Logic and statistics