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Answered

Select the true statement about the relationship between sample size and the standard deviation of distribution of sample means, also known as the standard error.

a. As sample size increases, standard error increases.
b. Sample size does not have an impact on standard error.
c. As sample size increases, standard error decreases.
d. As sample size decreases, standard error decreases.

Answer :

Answer:

c. As sample size increases, standard error decreases.

Step-by-step explanation:

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].

Thus:

The standard error is inversely proportional to the square root of the sample size, that is, as the sample size increases, the standard error decreases, and the correct answer is given by option c.

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