Interpreting Error Bars Standard Error
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opposed to a standard deviation? When plugging in errors for a simple bar chart of mean values, what are the statistical rules for
How To Interpret Standard Deviation Error Bars
which error to report? I guess the correct statistical test will render interpreting error bars on graphs this irrelevant, but it would still be good to know what to present in graphs. Topics Graphs × 720 how to interpret error bars in excel Questions 3,039 Followers Follow Standard Deviation × 239 Questions 19 Followers Follow Standard Error × 120 Questions 11 Followers Follow Statistics × 2,265 Questions 90,796 Followers Follow Nov 5, 2013
Error Bars Standard Error Or Confidence Interval
Share Facebook Twitter LinkedIn Google+ 4 / 1 Popular Answers Jochen Wilhelm · Justus-Liebig-Universität Gießen Very good advices above, but it leaves the essence of the question untouched. The CI is absolutly preferrable to the SE, but, however, both have the same basic meaing: the SE is just a 63%-CI. The SD, in contrast, has a different meaning. I suppose
How To Interpret Error Bars
the question is about which "meaning" should be presented. The SD is a property of the variable. It gives an impression of the range in which the values scatter (dispersion of the data). When this is important then show the SD. THE SE/CI is a property of the estimation (for instance the mean). The (frequentistic) interpretation is that the given proportion of such intervals will include the "true" parameter value (for instance the mean). Only 5% of 95%-CIs will not include the "true" values. If you want to show the precision of the estimation then show the CI. However, there is still a point to consider: Often, the estimates, for instance the group means, are actually not of particulat interest. Rather the differences between these means are the main subject of the investigation. Such differences (effects) are also estimates and they have their own SEs and CIs. Thus, showing the SEs or CIs of the groups indicates a measure of precision that is not relevant to the research question. The important thing to be shown here would be the
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Large Error Bars
About the journal About Nature Methods About the editors Press releases Contact the journal Subscribe For standard error bars excel 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 https://www.researchgate.net/post/When_should_you_use_a_standard_error_as_opposed_to_a_standard_deviation Reddit StumbleUpon Previous article Nature Methods | This Month The 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 http://www.nature.com/nmeth/journal/v10/n10/full/nmeth.2659.html tools PDF PDF Download as PDF (269 KB) 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
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 http://www.graphpad.com/support/faqid/1362/ to look at whether two error bars overlap or not, and try to reach a conclusion about whether the difference between means is statistically significant. Resist that temptation (Lanzante, 2005)! SD error bars SD error bars quantify the scatter among the values. Looking at whether the error bars overlap lets you compare the difference between the mean with the amount of scatter error bars 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 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 how to interpret < 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 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