# Estimating population standard deviation from subsample means [duplicate]

I would like to estimate the standard deviation of a population. The data I have is the size and mean of each of $$k$$ independent uniform subsamples: $$(n_1, \mu_1), (n_2, \mu_2), \ldots, (n_k, \mu_k)$$. Here, the $$i$$'th subsample has $$n_i$$ elements, and those $$n_i$$ elements have a mean of $$\mu_i$$.

What is the best way to utilize all $$2k$$ values to produce the best estimate of the population standard deviation $$\sigma$$?

Let $$\mu$$ be the population mean and $$\sigma$$ be the population SD. You have observations $$x_i$$ of $$k$$ independent variables $$X_i$$ having a common mean $$\mu$$ and variances $$\sigma^2/n_i,$$ $$i=1,2,\ldots, k.$$

You are noncommittal about the sense of "best." To make this specific, let us find the Least Squares estimator of $$\sigma.$$ This is a Weighted Least Squares problem with weights $$1/(1/n_i)=n_i,$$ whence

$$\hat\mu = \frac{1}{n_1+n_2+\cdots+n_k}\, \left(n_1x_1 + n_2x_2 + \cdots + n_k x_k\right)$$

with residuals

$$r_i = x_i - \hat\mu$$

which entails

$$\hat\sigma^2 = \frac{1}{k-1}\, \left(n_1 r_1^2 + n_2 r_2^2 + \cdots + n_k r_k^2\right).$$

We may therefore take

$$\hat \sigma = \sqrt{\hat\sigma^2}$$

as a "best" estimate of $$\sigma.$$

As a check, straightforward algebra will verify that $$E[\hat\mu] = \mu$$ and $$E[\hat\sigma^2]=\sigma^2,$$ standard properties of Least Squares estimates. As another check, these calculations reproduce exactly the output of the lm function in R using the $$n_i$$ in its weights argument.

• Thanks, this makes a lot of sense. Btw, I think you have an extra subscript in your residual equation. Apr 5, 2020 at 15:44
• Thank you for the careful review! I have fixed that typo.
– whuber
Apr 5, 2020 at 17:31
• I found that this question appears to have been asked previously, with the top answer coming from you!: stats.stackexchange.com/q/24936/2221 Should this question be removed since it's a repeat? Or is there something sufficiently unique about this question to warrant keeping them both? Apr 6, 2020 at 0:11
• That's a good find (as you might imagine, I had totally forgotten about it). Maybe the best resolution would be for me to add this post as an edit to my answer there. What do you think?
– whuber
Apr 6, 2020 at 12:41
• Sure, would you like to do that? I think this question/answer is a little cleaner so I think there is value to having it. Apr 6, 2020 at 12:46