Is the sample mean and variance always unbiased?

In summary, the conversation discusses whether the sample mean and sample variance are always unbiased estimates of the true expected value and variance of a random variable X, or at least asymptotically unbiased. The speaker argues that while they are the maximum likelihood estimators for certain distributions, there is no reason for them to be unbiased for all distributions. However, simulations have not yet found an example where the sample mean and sample variance are biased. The topic being discussed is not hypothesis testing, but rather the use of sample mean and sample variance as unbiased estimates for unknown distributions.
  • #1
logarithmic
107
0
I'm wondering if the sample mean [tex]\sum{x_i}/n[/tex] and sample variance [tex]\frac{1}{n-1}\sum{(x_i-\bar{x})^2}[/tex] is always an unbiased estimate of the true expected value and variance of the random variable X, where x_i are iid samples. Or at least asymptotically unbiased.

I don't think it is, since the sample mean (and variance) is only the MLE of a few distributions, like the normal and poisson. So I see no reason for it to be unbiased for all distributions.

However, I've been running some simulations on R, and I cannot seem to find an example of a distribution where the sample mean isn't unbiased, same for the sample variance.
 
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  • #2
Is it Hypothesis Testing ?
 
  • #3
xiaoB said:
Is it Hypothesis Testing ?
No, not hypothesis testing. I just want to know, given some numbers from any unknown distribution, whether if I use the sample mean and sample variance, I will get an unbiased estimate for the true mean and variance.
 

FAQ: Is the sample mean and variance always unbiased?

Is the sample mean always an unbiased estimator of the population mean?

Yes, the sample mean is always an unbiased estimator of the population mean. This means that on average, the sample mean will equal the population mean.

Is the sample variance always an unbiased estimator of the population variance?

No, the sample variance is not always an unbiased estimator of the population variance. It can be biased if the sample is small or if the population variance is unknown.

How do you determine if the sample mean and variance are unbiased?

To determine if the sample mean and variance are unbiased, you can compare them to the population mean and variance. If the sample mean and variance are equal to the population mean and variance, then they are unbiased estimators.

Can the sample mean and variance be biased in certain situations?

Yes, the sample mean and variance can be biased in certain situations. For example, if the sample is not representative of the population or if there are outliers in the data, the sample mean and variance may be biased.

Why is it important for the sample mean and variance to be unbiased?

It is important for the sample mean and variance to be unbiased because they are used to estimate the population mean and variance. If they are biased, the estimates will not accurately reflect the true values of the population parameters.

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