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Part 1
Listed below are amounts of​ strontium-90 (in​ millibecquerels, or​ mBq) in a simple random sample of baby teeth obtained from residents in a region born after 1979. Use the given data to construct a boxplot and identify the​ 5-number summary.

122
124
127
130
133
135
138
139
142
144
146
146
148
150
153
158
161
161
164
170

Here is the boxplot of the strontium-90 levels in baby teeth. It visualizes the five-number summary and shows the distribution of the data, including the minimum, Q1, median, Q3, and maximum.

Would you like further details or have any other questions? Here are some related questions to explore:

1. How can you interpret outliers from a boxplot?
2. What is the interquartile range (IQR) of this dataset?
3. How can you identify skewness from a boxplot?
4. How would the boxplot change if there were extreme outliers?
5. What are some common uses of a five-number summary in data analysis?

**Tip:** The IQR (Interquartile Range) is a key measure of spread, defined as \( Q3 - Q1 \), which helps to understand the variability of the data.

Listed below are amounts of​ strontium-90 (in​ millibecquerels, or​ mBq) in a simple random sample of baby teeth obtained from residents in a region born after 1979. Use the given data to construct a boxplot and identify the​ 5-number summary. Data: 122, 124, 127, 130, 133, 135, 138, 139, 142, 144, 146, 146, 148, 150, 153, 158, 161, 161, 164, 170.

Explore how to construct a boxplot and identify the five-number summary using strontium-90 levels from a sample of baby teeth. This statistical problem involves descriptive analysis, including minimum, quartiles, median, and maximum. Suitable for students in Grades 9-12, this example highlights the five-number summary and interquartile range (IQR) in data analysis.

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