Error Bars Overlap
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Graphpad.com FAQs Find ANY word Find ALL words Find EXACT phrase What you can conclude when two error bars overlap (or don't)? FAQ# 1362 Last Modified 22-April-2010 It is tempting to look at whether two error bars overlap or not, and try to reach a conclusion
Error Bars Reliability
about whether the difference between means is statistically significant. Resist that temptation (Lanzante, 2005)! SD real difference range bars error bars SD error bars quantify the scatter among the values. Looking at whether the error bars overlap lets you compare the difference between
Standard Error Bars Don't Overlap
the mean with the amount of scatter within the groups. But the t test also takes into account sample size. If the samples were larger with the same means and same standard deviations, the P value would be much what does it mean when error bars don't overlap smaller. If the samples were smaller with the same means and same standard deviations, the P value would be larger. When the difference between two means is statistically significant (P < 0.05), the two SD error bars may or may not overlap. Likewise, when the difference between two means is not statistically significant (P > 0.05), the two SD error bars may or may not overlap. Knowing whether SD error bars overlap or not does not let you what does overlap in standard deviation mean conclude whether difference between the means is statistically significant or not. SEM error bars SEM error bars quantify how precisely you know the mean, taking into account both the SD and sample size. Looking at whether the error bars overlap, therefore, lets you compare the difference between the mean with the precision of those means. This sounds promising. But in fact, you don’t learn much by looking at whether SEM error bars overlap. By taking into account sample size and considering how far apart two error bars are, Cumming (2007) came up with some rules for deciding when a difference is significant or not. But these rules are hard to remember and apply. Here is a simpler rule: If two SEM error bars do overlap, and the sample sizes are equal or nearly equal, then you know that the P value is (much) greater than 0.05, so the difference is not statistically significant. The opposite rule does not apply. If two SEM error bars do not overlap, the P value could be less than 0.05, or it could be greater than 0.05. If the sample sizes are very different, this rule of thumb does not always work. Confidence interval error bars Error bars that show the 95% confidence interval (CI) are wider than SE error bars. It doesn’t help to observe that two 95% CI error bars overlap, as the difference b
in a publication or presentation, you may be tempted to draw conclusions about the statistical significance of differences between group means by looking at whether the error bars overlap. Let's look at two contrasting examples. What can you conclude when standard error bars do not
If Error Bars Overlap Are They Significant
overlap? When standard error (SE) bars do not overlap, you cannot be sure that the if error bars overlap is there a significant difference difference between two means is statistically significant. Even though the error bars do not overlap in experiment 1, the difference is not statistically
Overlapping Error Bars Excel
significant (P=0.09 by unpaired t test). This is also true when you compare proportions with a chi-square test. What can you conclude when standard error bars do overlap? No surprises here. When SE bars overlap, (as in experiment 2) http://www.graphpad.com/support/faqid/1362/ you can be sure the difference between the two means is not statistically significant (P>0.05). What if you are comparing more than two groups? Post tests following one-way ANOVA account for multiple comparisons, so they yield higher P values than t tests comparing just two groups. So the same rules apply. If two SE error bars overlap, you can be sure that a post test comparing those two groups will find no statistical significance. However if two https://egret.psychol.cam.ac.uk/statistics/local_copies_of_sources_Cardinal_and_Aitken_ANOVA/errorbars.htm SE error bars do not overlap, you can't tell whether a post test will, or will not, find a statistically significant difference. What if the error bars do not represent the SEM? Error bars that represent the 95% confidence interval (CI) of a mean are wider than SE error bars -- about twice as wide with large sample sizes and even wider with small sample sizes. If 95% CI error bars do not overlap, you can be sure the difference is statistically significant (P < 0.05). However, the converse is not true--you may or may not have statistical significance when the 95% confidence intervals overlap. Some graphs and tables show the mean with the standard deviation (SD) rather than the SEM. The SD quantifies variability, but does not account for sample size. To assess statistical significance, you must take into account sample size as well as variability. Therefore, observing whether SD error bars overlap or not tells you nothing about whether the difference is, or is not, statistically significant. What if the groups were matched and analyzed with a paired t test? All the comments above assume you are performing an unpaired t test. When you analyze matched data with a paired t test, it doesn't matter how much scatter each group has -- what matters is the consistency of the changes or differences. Whether or not the
category Specials, focuses & supplements Authors & referees Guide to authors For referees Submit manuscript Reporting checklist About the http://www.nature.com/nmeth/journal/v10/n10/full/nmeth.2659.html journal About Nature Methods About the editors Press releases Contact the http://stats.stackexchange.com/questions/114701/standard-error-bars-overlap-but-significance-estimated-marginal-means-versus-o journal Subscribe For advertisers For librarians Methagora blog Home archive issue This Month full text Nature Methods | This Month Print Share/bookmark Cite U Like Facebook Twitter Delicious Digg Google+ LinkedIn Reddit StumbleUpon Previous article Nature Methods | This Month The error bars Author File: Jeff Dangl Next article Nature Methods | Correspondence ExpressionBlast: mining large, unstructured expression databases Points of Significance: Error bars Martin Krzywinski1, Naomi Altman2, Affiliations Journal name: Nature Methods Volume: 10, Pages: 921–922 Year published: (2013) DOI: doi:10.1038/nmeth.2659 Published online 27 September 2013 Article tools PDF PDF Download as PDF (269 KB) error bars overlap View interactive PDF in ReadCube Citation Reprints Rights & permissions Article metrics The meaning of error bars is often misinterpreted, as is the statistical significance of their overlap. Subject terms: Publishing• Research data• Statistical methods At a glance Figures View all figures Figure 1: Error bar width and interpretation of spacing depends on the error bar type. (a,b) Example graphs are based on sample means of 0 and 1 (n = 10). (a) When bars are scaled to the same size and abut, P values span a wide range. When s.e.m. bars touch, P is large (P = 0.17). (b) Bar size and relative position vary greatly at the conventional P value significance cutoff of 0.05, at which bars may overlap or have a gap. Full size image View in article Figure 2: The size and position of confidence intervals depend on the sample. On average, CI% of intervals are expected to span the mean—
Tour Start here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the workings and policies of this site About Us Learn more about Stack Overflow the company Business Learn more about hiring developers or posting ads with us Cross Validated Questions Tags Users Badges Unanswered Ask Question _ Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization. Join them; it only takes a minute: Sign up Here's how it works: Anybody can ask a question Anybody can answer The best answers are voted up and rise to the top Standard error bars overlap but significance - estimated marginal means versus observed means up vote 1 down vote favorite I'm running a Mixed effects model ANOVA with two fixed factors (condition, repetition) and one random factor (subject). Subsequently, a Tukey multiple comparisons test is performed. Now I'd like to plot the means and standard errors (SEMs) of the single conditions in a single error bar plot, and report the p values between the conditions. The problem: while in the Tukey test, I got significant differences and non-overlapping SEMs between certain means, for my plotted real/observed data the SEM bars overlap. This is now counterintuitive, since commonly you would assume that in the case of overlapping, the means are not significantly different. My question is: is the difference between estimated marginal means and observed means due to having a random factor in my model, or what is the reason for the discrepancy? how would you report the data? Would you still plot observed data with the p values and state that the p values are derived from the estimated model? Or would you plot estimated means and standard errors? Thank you! EDIT: I'm adding the multiple comparisons result for a sample case as well as the observed means and standard error plot in case this helps. anova mean standard-error post-hoc share|improve this question edited Sep 8 '14 at 19:13 asked Sep 8 '14 at 13:38 user54643 64 add a comment| 1 Answer 1 active oldest votes up vote 2 down vote Statistical significance is not transitive. If you want to say how much error there is in estimating the means, show error bars around the means. If you want to compare the means, show results of multiple comparisons. Don't mix those two ideas together. It is quite possi