Confidence Intervals as an Alternative to Significance Testing

The article argues to replace null hypothesis significance testing by confidence intervals. Correctly interpreted, confidence intervals avoid the problems associated with null hypothesis statistical testing. Confidence intervals are formally valid, do not depend on apriori hypotheses and do not result in trivial knowledge. The first part presents critique of null hypothesis significance testing; the second part replies to critique against confidence intervals and tries to demonstrate their superiority to null hypothesis significance testing.

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