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To calculate the **sample standard deviation** of runs scored per team, we will follow these steps using the data points shown on the plot.

The dot plot shows data for runs scored per team in one season, and from the image, we can interpret the scores as:

- 600 (1 occurrence)
- 660 (1 occurrence)
- 720 (2 occurrences)
- 780 (3 occurrences)
- 840 (1 occurrence)

We will now compute the sample standard deviation:

1. Find the mean (average) of the data.
2. Subtract the mean from each data point and square the result (variance calculation).
3. Find the sum of these squared values.
4. Divide the sum by \( n - 1 \) (since it's a sample, where \( n \) is the number of data points).
5. Take the square root to obtain the sample standard deviation.

Let me compute this for you.The sample standard deviation of runs scored per team in one season is **76.9** (rounded to the nearest hundredth).

Would you like further details or have any other questions?

Here are 5 related questions you might find helpful:
1. How is sample standard deviation different from population standard deviation?
2. How do you interpret the value of a standard deviation in the context of this data?
3. How would the standard deviation change if there were more extreme values in the data set?
4. What other summary statistics could be useful for analyzing this data?
5. How can standard deviation help in comparing team performances across multiple seasons?

**Tip**: Always use sample standard deviation (with \( n-1 \)) when your data represents a sample rather than the whole population.

What is the sample standard deviation of runs scored per team in one season, to the nearest hundredth?

Learn how to calculate the sample standard deviation of runs scored per team in one season, using data points such as 600, 660, 720, 780, and 840. This guide covers key statistical concepts like variance, mean, and the standard deviation formula.

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