Standard deviation and standard error

What is the difference between standard deviation and standard error

Let’s refer to a normal distribution of data, where there’s more data near the mean than farther away from the mean. You know, that bell curve that we always see drawn over a histogram. (?)

Standard deviation is a measure of the spread of your data around the mean (if it’s normally distributed). Generally, ~ 2/3 of your data is going to be within one standard deviation of the mean & 95% of your values will fall within 2 std dev of the mean. Std dev. is the square root of the variance (the average of the squared differences of all the values from the mean). Std. dev. is a descriptive statistic.

Standard error is used when you are comparing sample means across populations. You’re interested in measuring the difference between two sample means, you want to see how precisely you’ve measured them. It is the standard deviation of the population divided by the square root of the sample size.

Maybe this will help better than I can explain(?) It can be confusing b/c ppl use the terms interchangeably. :thinking:

http://www.differencebetween.net/science/mathematics-statistics/difference-between-standard-deviation-and-standard-error/

Thanks for your solution. I also found same article like answer to my question https://differencebtwn.com/difference-between-standard-deviation-and-standard-error

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You’re welcome. :slight_smile: