Does sample size affect confidence interval?
Understand the Problem
The question is asking how the size of the sample impacts the width or reliability of the confidence interval in statistics. In general, larger sample sizes lead to narrower confidence intervals, indicating more precise estimates of population parameters.
Answer
Yes, it does. Increasing the sample size narrows the confidence interval.
Yes, sample size affects confidence intervals. Increasing the sample size causes the confidence interval to become narrower, while decreasing the sample size makes the confidence interval wider.
Answer for screen readers
Yes, sample size affects confidence intervals. Increasing the sample size causes the confidence interval to become narrower, while decreasing the sample size makes the confidence interval wider.
More Information
As the sample size increases, the standard error decreases, which results in a narrower confidence interval. This relationship helps in making estimates of population parameters more precise.
Tips
A common mistake is to think that increasing the sample size always makes the confidence interval more accurate. While it narrows the interval, the accuracy of the interval also depends on how representative the sample is of the population.
Sources
- A Single Population Mean: Using the Normal Distribution - courses.lumenlearning.com
- Impact of Sample Size on Confidence Intervals | STAT 200 - online.stat.psu.edu
- Impact of Sample Size on Confidence Intervals - MAKE ME ANALYST - makemeanalyst.com
