Outliers in Data Sets
Explore and identify outliers in various data sets using statistical methods like the interquartile range (IQR).
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Outliers in Data Sets
Name:
Date:
Score:
Read each question carefully and provide clear, concise answers. Show all your work when necessary.
1. In your own words, define what an 'outlier' is in the context of a data set. Why is it important to identify outliers?
2. Consider the data set: {5, 12, 15, 16, 18, 20, 22, 25, 50}. What is the Interquartile Range (IQR) for this data set?
10
13
15
22
3. An outlier is typically defined as any data point that falls more than 1.5 times the (IQR) below the first quartile (Q1) or above the (Q3).
4. For the data set {10, 12, 15, 18, 20, 22, 25, 30, 70}:
a. Calculate Q1, Q3, and the IQR.
b. Determine if there are any outliers using the 1.5 * IQR rule. Show your calculations.
5. The following box plot represents the scores on a recent math test.
Based on the box plot, what score would likely be considered an outlier?
6. Outliers always have a significant impact on the mean of a data set.
True
False
7. Describe a real-world scenario where identifying outliers would be crucial. Explain why it's important in that context.
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