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Error bars are the mean ± SD for n = 3.
The red point and error bars are the mean and standard deviation of these V r estimates.
The horizontal bars are the mean 95% confidence levels of the LIDAR biomass map pixels for the BAY model, sampled from the posterior predictive distribution that acknowledges spatial dependence (see Methods).
Bars are the mean values (± standard error of the mean [SEM]) of Mi-csq-1, Mi-eif-3, Mi-GDP-2, Mi-Y45F10D.4, and Mi-actin genes expression data (Cq) in three independent biological replicates, with 35 plants per condition.
Bars are the mean of three independent cultures, with errors bars representing ± SD.
The circles and error bars are the mean ±95% binomial confidence intervals across trials on the easiest (blue), middle (purple) and hardest (magenta) thirds of trials defined by the absolute value of the ratios of left vs right click rates.
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The error-bar plot is used in Figures 3 and 4. The center of the error bar is the mean of the estimation error and the length of the bar equals twice the standard deviation.
The following formula was used to calculate SN where yi-bar is the mean value, si the variance, and yi the value of the performance characteristic for each given experiment.
Where x i is the current cell value, x j is the value of the cell separated by a given distance, x(bar) is the mean, and W is the number of cells surrounding the current one and found within the given distance.
Results presented are mean values (n = 3) and error bars are the standard error of the mean.
Error bars are the estimated variance of the mean.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com