To determine the sample standard deviation of the weights of the M&M plain candies, the following formula is used:

$s = \sqrt{\frac{\sum (x_i - \overline{x})^2}{n-1}}$

Where:

• $s$ is the sample standard deviation,
• $x_i$ are the individual data points (weights),
• $\overline{x}$ is the sample mean,
• $n$ is the number of data points (48 in this case).

If you provide the list of the M&M weights, I can help you compute the sample standard deviation.

Do you have any questions or want more details on this process?

Here are 5 related questions to explore further:

1. How is the sample standard deviation different from the population standard deviation?
2. What is the purpose of using $n-1$ instead of $n$ in the sample standard deviation formula?
3. How do outliers affect the standard deviation?
4. Can the standard deviation be negative?
5. How do you interpret the value of a standard deviation in the context of this data?

Tip: In real-world data analysis, sample standard deviation is often used when you only have a subset of data from a larger population, while population standard deviation is used when you have the entire data set.