The accompanying data represent the weights​ (in grams) of a random sample of 48​ M&M plain candies. Complete parts​ (a) through​ (f).
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Part 1
​(a) Determine the sample standard deviation weight. 

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.

The accompanying data represent the weights​ (in grams) of a random sample of 48​ M&M plain candies. Complete parts​ (a) through​ (f). Part 1: (a) Determine the sample standard deviation weight.

Learn how to calculate the sample standard deviation for the weights of 48 M&M plain candies. This statistical analysis uses the formula for sample standard deviation to interpret real-world data. Suitable for students in Grades 11-12 or introductory college statistics courses.

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