Final answer:
The correct answer is that as the sample size increases, the standard deviation decreases. This decrease in standard deviation, specifically the standard error, reflects increased precision in estimating the population mean. The confidence interval also narrows as the sample size grows.
Step-by-step explanation:
As the sample size increases, the correct choice would be B. Standard deviation decreases. This is because as we collect more data, our estimates tend to become more precise. Specifically, the standard deviation of the sampling distribution of the sample means (often called the standard error) becomes smaller as the sample size increases, assuming that all other factors remain constant. Moreover, the confidence interval will narrow with increasing sample size, contrary to choice A, as less variability in the sample means requires less margin for error in estimating the true population means. Additionally, while the mean becomes a more accurate estimate of the population mean with an increased sample size, the wording 'more accurate' is less specific than the decrease in standard deviation. Finally, 'variability decreases' could be a misinterpretation because the inherent variability of the data does not necessarily change, but our certainty about the data's representation of the population does.