# What happens if error bars overlap?

## What happens if error bars overlap?

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.

Do you want error bars to overlap?

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.

What do error bars indicate?

Error bars are graphical representations of the variability of data and used on graphs to indicate the error or uncertainty in a reported measurement. They give a general idea of how precise a measurement is, or conversely, how far from the reported value the true (error free) value might be.

### What do large error bars indicate?

The length of an Error Bar helps reveal the uncertainty of a data point: a short Error Bar shows that values are concentrated, signalling that the plotted average value is more likely, while a long Error Bar would indicate that the values are more spread out and less reliable.

What do standard error bars show?

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).

How do you interpret error bars?

## What is a good standard error in regression?

The standard error of the regression is particularly useful because it can be used to assess the precision of predictions. Roughly 95% of the observation should fall within +/- two standard error of the regression, which is a quick approximation of a 95% prediction interval.

When should you not use error bars?

Rule 3: error bars and statistics should only be shown for independently repeated experiments, and never for replicates. If a “representative” experiment is shown, it should not have error bars or P values, because in such an experiment, n = 1 (Fig. 3 shows what not to do).