Find the range and interquartile range (IQR) for the monthly rainfall (in millime- ters) in Seattle based on the box-and-whisker plot below. Average Monthly Rainfall in Seattle (millimeters) 20 +++▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬+ 140 80 200
Find the range and interquartile range (IQR) for the monthly rainfall (in millime- ters) in Seattle based on the box-and-whisker plot below. Average Monthly Rainfall in Seattle (millimeters) 20 +++▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬+ 140 80 200
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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
Transcribed Image Text:The image depicts a simple two-cell table used to represent statistical measures. The table has two rows:
1. **Range**: This is highlighted in a brown color. The number "1" in a blue circle appears beside it, possibly indicating its position or priority in a list.
2. **IQR (Interquartile Range)**: This is highlighted in a gray color. The number "2" in a blue circle appears beside it, similarly indicating its position or priority.
The table visually organizes these two statistical concepts, which are commonly used in data analysis to measure variability.

Transcribed Image Text:**Understanding Box-and-Whisker Plots**
**Instruction:** Find the range and interquartile range (IQR) for the monthly rainfall (in millimeters) in Seattle, based on the box-and-whisker plot below.
**Diagram: Average Monthly Rainfall in Seattle (millimeters)**
- The box-and-whisker plot displays the distribution of monthly rainfall in Seattle.
- The horizontal axis measures rainfall in millimeters, ranging from 20 to 200.
- The plot includes a box and two "whiskers" extending from either side.
- The left whisker starts at approximately 30 mm, and the right whisker ends around 190 mm.
- The left edge of the box (1st quartile) is at about 70 mm, and the right edge (3rd quartile) is at around 150 mm.
- The line within the box represents the median, which is approximately 120 mm.
**Tasks:**
- **Press each hotspot.**
- **Label the corresponding number below with the requested value.**
This plot helps highlight the spread and central tendency of the rainfall data, allowing for an easy visual interpretation of variability within the dataset.
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