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# Confidence Intervals V. Hypothesis Testing

Suppose you read the following statement:

The mean value for the intervention group was 29 points lower than for the control group (p-value < 0.05).  This might correspond to either of the following 95% confidence intervals:

• Treatment difference: 29.3 (22.4, 36.2)
• Treatment difference: 29.3 (11.8, 46.8)

If exact p-value is reported, then the relationship between confidence intervals and hypothesis testing is very close.  However, the objective of the two methods is different:

• Hypothesis testing relates to a single conclusion of statistical significance vs. no statistical significance.
• Confidence intervals provide a range of plausible values for your population.

## Which one?

• Use hypothesis testing when you want to do a strict comparison with a pre-specified hypothesis and significance level.
• Use confidence intervals to describe the magnitude of an effect (e.g., mean difference, odds ratio, etc.) or when you want to describe a single sample. rev. 05-Aug-2019  Confidence Intervals

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