标准差和标准误的选择 (SD) 和 (SEM)
Which error bar should you choose?
It is easy to be confused about the difference between the standard deviation (SD) and standard error of the mean (SEM).
The SD quantifies scatter - how much the values vary from one another.
The SEM quantifies how accurately you know the true mean of the population. The SEM gets smaller as your samples get larger. This makes sense, because the mean of a large sample is likely to be closer to the true population mean than is the mean of a small sample.
The SD does not change predictably as you acquire more data. The SD quantifies the scatter of the data, and increasing the size of the sample does not increase the scatter. The SD might go up or it might go down. You can't predict. On average, the SD will stay the same as sample size gets larger.
If the scatter is caused by biological variability, your probably will want to show the variation. In this case, graph the SD rather than the SEM. You could also instruct Prism to graph the range, with error bars extending from the smallest to largest value. Also consider graphing every value, rather than using error bars.
If you are using an in vitro system with no biological variability, the scatter can only result from experimental imprecision. In this case, you may not want to show the scatter, but instead show how well you have assessed the mean. Graph the mean and SEM or the mean with 95% confidence intervals.
Ideally, the choice of which error bar to show depends on the source of the variability and the point of the experiment. In fact, many scientists always show the mean and SEM, to make the error bars as small as possible.
