Statistics How To

Directional Test

Hypothesis Testing >

A hypothesis test where a direction is specified (e.g. above a certain threshold or below a certain threshold). See: One tailed tests

A directional test is a statistical test that tests a directional hypothesis; a hypothesis which states not only that a null hypothesis is wrong but also that the actual value of the parameter we’re interested in is either greater than or less than the value given in the null hypothesis. Directional tests are appropriate in situations where the experimenter expects a change that is either positive or negative, not both.

Directional tests are also called one-tailed tests. This is because a probability density graph will taper off in only one direction; the critical region is in one tail and the error is all in one direction (either less than or greater than a central point, not both)

Strong and Weak Points of a Directional Test

Directional tests are more powerful than non-directional tests. Their targeted nature also makes them more conclusive: since the entire critical region is concentrated in one tail, data whose test statistic may fall in the region of rejection in a one tailed test may fall outside it in a two tailed test. Thus they are a good choice whenever a researcher is certain, before analysis, that the possibility of change is in only one direction. Where there is any doubt, a two-tailed test should be used instead.


MinitabĀ® 17 Support Team. Comparison of directional hypotheses and nondirectional hypotheses. Retrieved from on July 20.

Bliwise, Nancy. Directional Test. Introductory Statistical Tutorials, Emory University. Retrieved from on July 20, 2018

Vista. Notes on Topic 8: Hypothesis Testing. Lecture Notes.
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McNeil, Keith. Directional and Non-directional Hypothesis Testing: A Survey of Members, Journals, and Textboks. March 97. Paper presented at the annual meeting of the American Educational Research Association (Chicago, IL, March 24-28, 1997). Retrieved from on July 20, 2018.


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