Respuesta :
Answer:
The correct option is a.
Step-by-step explanation:
The standard deviation of the sampling distribution of sample mean ([tex]\bar x[/tex]) is known as the standard error. It is denoted by [tex]\sigma_{m}[/tex].
The formula to compute the standard error is:
[tex]\sigma_{m}=\frac{\sigma}{\sqrt{n}}[/tex]
As the population standard deviation is divided by the square root of the sample size, the standard error can never be more than the population standard deviation, σ.
Also, since the population standard deviation is directly proportional to the standard error, the value of [tex]\sigma_{m}[/tex] is affected by the value of σ.
And since the sample size is inversely proportional to the standard error, the value of [tex]\sigma_{m}[/tex] decreases as the value of n increases.
The sample mean is a statistic, i.e. it represents a specific characteristic (here, the average) of the sample.
The standard deviation of any statistic measures the variability of the statistic.
So, the standard error measures the variability in sample means.
Thus, the correct option is a.
