Respuesta :
Answer:
A. To reduce the variability of the estimate
Step-by-step explanation:
The larger the sample, the less variability there is.
The smaller the sample, the more variability there is.
Bias has to do with how randomly the sample is selected. Assuming that method doesn't change, the bias doesn't change.
Using the Central Limit Theorem, it is found that the effect of this increase is to:
A. To reduce the variability of the estimate.
What does the Central Limit Theorem state?
It states that the sampling distribution of sample means of size n has standard error [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].
From this, we can get that a larger sample size leads to a smaller standard error, that is, less variability, hence option A is correct.
More can be learned about the Central Limit Theorem at https://brainly.com/question/25800303