**Title: Identifying Outliers in Data Using a Five-Number Summary****Text:**Based on this five-number summary, are there any outliers in the data?- **Minimum (Min):** 2- **First Quartile (Q1):** 26- **Median (Med):** 32- **Third Quartile (Q3):** 34- **Maximum (Max):** 57**Options:**- [ ] No outliers- [ ] At least one upper outlier- [ ] At least one lower outlier- [ ] Cannot be determined**Explanation:**A five-number summary provides a concise description of a dataset, summarizing its minimum, first quartile, median, third quartile, and maximum. This summary helps in understanding the distribution and identifying potential outliers.To determine if there are outliers, we typically use the Interquartile Range (IQR), calculated as $ \text{IQR} = \text{Q3} - \text{Q1} $. Any data points below $ \text{Q1} - 1.5 \times \text{IQR} $ or above $ \text{Q3} + 1.5 \times \text{IQR} $ can be considered outliers.Analyzing outliers informs decisions related to data consistency and helps improve data quality for further analysis.

Given, min = 2 Q1 (the first quartile) = 26 Q2(median) = 32 Q3(the third quartile) = 34 max = 57

Answered: No outliers at least one upper outlier

A First Course in Probability (10th Edition)

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Chapter1: Combinatorial Analysis

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Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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