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The dot plot shown in the image displays the distribution of the number of strokes needed by 31 players to complete the ninth hole in a mini-golf course. This distribution can be analyzed to determine the most appropriate measure of center to estimate the expected number of strokes for the ninth hole.

From the dot plot, it is evident that the distribution of strokes is right-skewed, as there are more data points concentrated on the lower end (fewer strokes) and some outliers on the higher end (more strokes). In such cases, the median is generally a more reliable measure of center than the mean, because the median is less affected by outliers and skewed data.

Therefore, the correct choice for the measure of center in this case is:
- **The median is the best choice because the data is skewed to the right.**

Would you like more details on how median and mean are affected by data distributions, or do you have any other questions? Here are some related topics you might find interesting:
1. How to calculate the median from a dot plot.
2. The impact of outliers on the mean versus the median.
3. Examples of data distributions where the mean would be more appropriate than the median.
4. How to identify skewness in a data distribution visually.
5. The importance of using the appropriate measure of central tendency in statistical analysis.

**Tip:** When dealing with a skewed distribution, always consider using the median to better represent the typical value in your data set.

Which measure of center is best to use to determine the expected number of strokes required for the ninth hole?

Learn how to select the best measure of center (mean or median) when analyzing skewed data distributions using a dot plot. This problem focuses on statistical concepts such as the median and how it better represents data that is skewed to the right, like in the strokes required for a mini-golf hole.

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