https://file.aiquickdraw.com/mathbot/file/1725543113537tfy55wkh.jpg

The box plot above visualizes the dataset along with the 5-number summary, highlighting the minimum, Q1, median, Q3, and maximum values. As seen in the plot, there are no outliers.

Would you like further details on any of the steps, or do you have any other questions?

Here are 5 related questions that can deepen your understanding:
1. How does changing the dataset affect the standard deviation?
2. What is the relationship between IQR and the detection of outliers?
3. How can you interpret skewness from the box plot?
4. How would the 5-number summary change if outliers were present?
5. What are the pros and cons of using a box plot compared to a histogram?

**Tip**: The interquartile range (IQR) is useful for comparing variability between datasets without being affected by extreme values.

Consider the following dataset: 244, 361, 294, 100, 439, 285, 291, 307, 186, 24, 180, 363, 475, 285. Calculate the standard deviation. Write the 5-number summary for this data set. Calculate the Interquartile range. Identify any outliers. Show your working out. Construct a box plot showing the outliers.

Learn how to analyze a dataset by calculating the standard deviation, five-number summary, and interquartile range (IQR). Identify outliers using the IQR method and construct a box plot to visualize the data distribution. Suitable for high school students in Grades 10-12.

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