Theoretically, the standard error of the mean decreases as the sample size increases measures the variability of the sample mean from sample to sample is never larger than the standard deviation of the population All of the Above

All of the above

Step-by-step explanation:

The formula for the standard error of the mean is:

σM =σ/√N

where,

σM = standard error of the mean

σ = standard deviation of sample

√N = square of sample size

As the sample size of a population rises, it should be noted that the standard error of the mean will decrease. This is due to the fact that when there's an increase in sample size, there'll be cluster of the sample mean around the population mean.

Also, the the standard error of the mean measures the variability of the sample mean from sample to sample and is never larger than the standard deviation of the population.

Therefore, the answer will be "all or the above".

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step-by-step explanation: