Misinterpretations of 'p' and 'sig'
Falk and Greenbaum (19952) carried out a study on common misinterpretations of the logic of tests of significance among Israeli psychology students, which partly replicates one by Oakes (19864). Typically, most of these misinterpretations confuse p-values (ie, the probability of the data when assuming that the null hypothesis is true) and, especially, statistical significance, with the probability of proving or disproving hypotheses (be this the null hypothesis or an alternative hypothesis).
Falk and Greenbaum found that almost 87% of the students held at least one misinterpretation out of the four presented (see table 1). Most of the students misinterpreted p-values as the probability of the null hypothesis being true.
|Table 1. Frequencies and percentages of misinterpretations regarding tests of significance|
|Significance disproves the null hypothesis||2||3.8%|
|The p-value informs of the probability of the null hypothesis||42||79.2%|
|Significance proves the alternative hypothesis||0||0.0%|
|The p-value informs of the probability of the alternative hypothesis||2||3.8%|
|(Participants who answered that all of above were false)||7||13.2%|
Jose D PEREZGONZALEZ (2012). Massey University, Turitea Campus, Private Bag 11-222, Palmerston North 4442, New Zealand. (JDPerezgonzalez).
Want to know more?
- Wiki of Science - Hypotheses testing (disambiguation)
- This Wiki of Science page lists alternative methods for testing data or hypotheses.
- Wiki of Science - Null hypothesis significance testing
- This Wiki of Science page reflects on the pseudoscientific bases of the null hypothesis significance testing (NHST) procedure.
- Wiki of Science - Related studies
- You can find more information on two related studies in Wiki of Science: Oakes (1986) and Haller and Krauss (2000).