This Module's discussion topic: As the sample size increases, the precision of estimates tends to improve, meaning that the estimates become more accurate and reliable. This relationship can be understood through the concept of sampling error. When we take a larger sample size, we are effectively reducing the amount of sampling error because we are capturing a more representative sample of the population. A larger sample size $($generally$)$ tends to reduce the impact of random variation and extreme values, which can result in more precise and reliable estimates.

So$,$ this week, let's discuss the sample size issue.

What are the challenges businesses face when determining an appropriate sample size? How could we overcome the challenges?