MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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### Five Number Summary: Understanding Outliers and IQR

---

**The five number summary of a dataset was found to be:**

\-18, 6, 10, 11, 23

---

**Questions:**

1. **What is the IQR?**

   _Answer:_ `__________`

2. **Find the lower limit** (ie: an observation is considered an outlier if it is below this).

   _Answer:_ `__________`

3. **Find the upper limit** (ie: an observation is considered an outlier if it is above this).

   _Answer:_ `__________`

4. **Do we have any outliers?**

   - o No
   - o Yes

   _Answer:_ `__________`

---

**Explanation of Terms:**

- **IQR (Interquartile Range)**: A measure of statistical dispersion, or how spread out the data points are in a dataset. It is calculated as the difference between the third quartile (Q3) and the first quartile (Q1). 

- **Lower Limit**: To determine if a data point is an outlier on the lower end, we use the formula: Q1 - 1.5 * IQR.

- **Upper Limit**: To determine if a data point is an outlier on the upper end, we use the formula: Q3 + 1.5 * IQR.

- **Outliers**: Data points that fall below the lower limit or above the upper limit.

By understanding and applying these concepts, you can accurately identify outliers and gain more insights from your data analysis.
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Transcribed Image Text:### Five Number Summary: Understanding Outliers and IQR --- **The five number summary of a dataset was found to be:** \-18, 6, 10, 11, 23 --- **Questions:** 1. **What is the IQR?** _Answer:_ `__________` 2. **Find the lower limit** (ie: an observation is considered an outlier if it is below this). _Answer:_ `__________` 3. **Find the upper limit** (ie: an observation is considered an outlier if it is above this). _Answer:_ `__________` 4. **Do we have any outliers?** - o No - o Yes _Answer:_ `__________` --- **Explanation of Terms:** - **IQR (Interquartile Range)**: A measure of statistical dispersion, or how spread out the data points are in a dataset. It is calculated as the difference between the third quartile (Q3) and the first quartile (Q1). - **Lower Limit**: To determine if a data point is an outlier on the lower end, we use the formula: Q1 - 1.5 * IQR. - **Upper Limit**: To determine if a data point is an outlier on the upper end, we use the formula: Q3 + 1.5 * IQR. - **Outliers**: Data points that fall below the lower limit or above the upper limit. By understanding and applying these concepts, you can accurately identify outliers and gain more insights from your data analysis.
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