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two-tailed test

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6 - A Cautionary Tail: Why You Should Not Do a One-Tailed Test
from Part II - How to Use Statistics
Paul Cairns, University of York
Book:

Doing Better Statistics in Human-Computer Interaction

Published online:

26 January 2019

Print publication:

07 February 2019, pp 80-85
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Summary

A directional hypothesis predicts the specific way in which data are affected by an experimental manipulation. This, therefore, fits well with severe testing by making a concrete, explicit prediction. However, one-tailed testing associated with directional hypotheses regularly receives criticism because it can look like a way to make it easy to achieve statistical significance. This chapter describes why this is a problem and makes the case that despite the fit with severe testing, two-tailed testing is still the better way to do statistical analysis.