To find the sample size for this data set, we need to sum the frequencies shown in the histogram. Here’s the breakdown of frequencies based on the histogram bars:

• For 80-90 mg: frequency = 2
• For 90-100 mg: frequency = 4
• For 100-110 mg: frequency = 8
• For 110-120 mg: frequency = 12
• For 120-130 mg: frequency = 8
• For 130-140 mg: frequency = 4
• For 140-150 mg: frequency = 2

Adding these frequencies together:

$2 + 4 + 8 + 12 + 8 + 4 + 2 = 40$

Thus, the sample size $n$ is 40.

Would you like further details on how histograms relate to sample sizes or other aspects of this question?

Here are five related questions that might deepen your understanding:

1. How is sample size used to determine the reliability of a data set?
2. What are some methods to calculate the sample mean and variance from a histogram?
3. How do frequency distributions impact the shape and interpretation of histograms?
4. What is the difference between sample size and population size in statistics?
5. How do you interpret intervals in histograms, such as the 80-90 mg interval in this example?

Tip: In histograms, each bar’s height represents the frequency, which is the count of data points within that interval, providing a quick visual of data distribution.