Title: Using Confidence Intervals to Compare Means - Statistics By Jim
Headings: Using Confidence Intervals to Compare Means
Using Confidence Intervals to Compare Means
Comparing Groups Using Confidence Intervals of each Group Estimate
Jumping to Conclusions
Using the Wrong Types of Confidence Intervals
Assessing Confidence Intervals of the Differences between Groups
Interpreting Confidence Intervals of the Mean Difference
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Content: To learn more about unstandardized and standardized effect sizes, read my post about Effect Sizes in Statistics. As with all CIs, the width of the interval for the mean difference reveals the precision of the estimated effect size. Narrower intervals suggest a more precise estimate. And, you can assess whether the full range of values is practically significant. Remember, statistical significance doesn’t necessarily indicate that the results are meaningful in the real world. For more information about this issue, see Practical vs. Statistical Significance. When the interval is too wide (imprecise) to be helpful and/or the range includes differences that are not practically significant, you have reason to hesitate before making decisions based on the results. These types of CI results indicate that you might not obtain meaningful benefits even though the difference is statistically significant. There’s no statistical method for answering questions about how precise an estimate must be or how large an effect must be to be practically useful. To use the confidence interval of the difference to answer these questions, you’ll need to apply your subject-area knowledge.