Is it bad if error bars overlap?

Is it bad if error bars overlap?

A common myth is that when error bars for two samples do not overlap, the difference is statistically meaningful, a term I use in place of statistically significant. This overlap rule is really an overlap myth; the rule does not hold true for any type of conventional error bar.

What do error bars indicate about statistical significance?

Error bars are graphical representations of the variability of data and used on graphs to indicate the error or uncertainty in a reported measurement. Error bars often represent one standard deviation of uncertainty, one standard error, or a particular confidence interval (e.g., a 95% interval).

What do Range error bars show?

An error bar is a (usually T-shaped) bar on a graph that shows how much error is built in to the chart. The “error” here isn’t a mistake, but rather a range or spread of data that represents some kind of built in uncertainty. For example, the bar could show a confidence interval, or the standard error.

What is the difference between error bars and range bars?

Descriptive error bars show you something about the spread of data. The range will tell you how spread out the data is, from the lowest to highest values.

When do error bars overlap is it statistically significant?

When standard deviation errors bars overlap quite a bit, it’s a clue that the difference is not statistically significant. You must actually perform a statistical test to draw a conclusion. When standard deviation errors bars overlap even less, it’s a clue that the difference is probably not statistically significant.

When to look for error bars on a graph?

The standard deviation error bars on a graph can be used to get a sense for whether or not a difference is significant. Look for overlap between the standard deviation bars:

Which is larger the p value or the SD error bar?

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 < 0.05), the two SD error bars may or may not overlap.

How is the standard error for estimated marginal means calculated?

(This mechanism for calculating the standard error for estimated marginal means also applies to the MIXED command, although random and repeated effects may lead to nonequal standard errors across factor levels.)

https://www.youtube.com/watch?v=GquPk1_CVcM