Title: How to Interpret the Width of a Confidence Interval - The Analysis Factor
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Content: How to Interpret the Width of a Confidence Interval - The Analysis Factor
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How to Interpret the Width of a Confidence Interval
by Christos Giannoulis 2 Comments
One issue with using tests of significance is that black and white cut-off points such as 5 percent or 1 percent may be difficult to justify. Significance tests on their own do not provide much light about the nature or magnitude of any effect to which they apply. One way of shedding more light on those issues is to use confidence intervals. Confidence intervals can be used in univariate, bivariate and multivariate analyses and meta-analytic studies. What Determines the Width of the Confidence Interval? A narrow confidence interval enables more precise population estimates. The width of the confidence interval is a function of two elements: Confidence level
Sampling error
The greater the confidence level, the wider the confidence interval. If we assume the confidence level is fixed, the only way to obtain more precise population estimates is to minimize sampling error. Sampling error is measured by the standard error statistic.