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6. The weights (in pounds) of 30 ne 5.5 5.7 5.8 5.9 6 6.7 6.7 6.9 7 7.5 77 7.7 7 6.7 7.4 ] Find the smallest obs a) rn babies are listed below. Construct a boxplot for the data. 6.1 6.3 6.4 6.5 6.6 7.0 7.0 7.1 7.2 7.2 8.0 8.1 8.1 8.3 8.7 tion, Q₁, Q2, Q3, and the largest observation.

6. The weights (in pounds) of 30 ne 5.5 5.7 5.8 5.9 6 6.7 6.7 6.9 7 7.5 77 7.7 7 6.7 7.4 ] Find the smallest obs a) rn babies are listed below. Construct a boxplot for the data. 6.1 6.3 6.4 6.5 6.6 7.0 7.0 7.1 7.2 7.2 8.0 8.1 8.1 8.3 8.7 tion, Q₁, Q2, Q3, and the largest observation.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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### Constructing a Boxplot for Weights of Newborn Babies The weights (in pounds) of 30 newborn babies are provided below. This tutorial will guide you through constructing a boxplot with this data. **Data Set:** 5.5, 5.7, 5.8, 5.9, 6.0, 6.1, 6.3, 6.4, 6.5, 6.6, 6.7, 6.7, 6.7, 6.9, 7.0, 7.0, 7.1, 7.2, 7.2, 7.4, 7.5, 7.7, 7.7, 7.7, 8.0, 8.1, 8.1, 8.3, 8.3, 8.7. ### Step-by-Step Instructions #### a) Find the Smallest Observation, Q1, Q2, Q3, and the Largest Observation 1. **Order the data from smallest to largest.** 2. **Identify the five-number summary:** - Minimum - First Quartile (Q1) - Median (Q2) - Third Quartile (Q3) - Maximum #### b) Find the Right and Left Fences to Identify Outliers (if any) 1. **Calculate the Interquartile Range (IQR):** - IQR = Q3 - Q1 2. **Compute the fences:** - Lower Fence: Q1 - 1.5 * IQR - Upper Fence: Q3 + 1.5 * IQR 3. **Identify outliers:** - Any data points below the lower fence or above the upper fence are considered outliers. #### c) Construct a Boxplot 1. **Draw a number line that includes the range of your data.** 2. **Mark the five-number summary on this line.** 3. **Draw a box from Q1 to Q3, with a vertical line at the median (Q2).** 4. **Draw whiskers from the box to the minimum and maximum values that are not outliers.** 5. **Plot any outliers as individual points.** #### Explaining Distribution Type **Given that the distribution is unim
Transcribed Image Text:### Constructing a Boxplot for Weights of Newborn Babies The weights (in pounds) of 30 newborn babies are provided below. This tutorial will guide you through constructing a boxplot with this data. **Data Set:** 5.5, 5.7, 5.8, 5.9, 6.0, 6.1, 6.3, 6.4, 6.5, 6.6, 6.7, 6.7, 6.7, 6.9, 7.0, 7.0, 7.1, 7.2, 7.2, 7.4, 7.5, 7.7, 7.7, 7.7, 8.0, 8.1, 8.1, 8.3, 8.3, 8.7. ### Step-by-Step Instructions #### a) Find the Smallest Observation, Q1, Q2, Q3, and the Largest Observation 1. **Order the data from smallest to largest.** 2. **Identify the five-number summary:** - Minimum - First Quartile (Q1) - Median (Q2) - Third Quartile (Q3) - Maximum #### b) Find the Right and Left Fences to Identify Outliers (if any) 1. **Calculate the Interquartile Range (IQR):** - IQR = Q3 - Q1 2. **Compute the fences:** - Lower Fence: Q1 - 1.5 * IQR - Upper Fence: Q3 + 1.5 * IQR 3. **Identify outliers:** - Any data points below the lower fence or above the upper fence are considered outliers. #### c) Construct a Boxplot 1. **Draw a number line that includes the range of your data.** 2. **Mark the five-number summary on this line.** 3. **Draw a box from Q1 to Q3, with a vertical line at the median (Q2).** 4. **Draw whiskers from the box to the minimum and maximum values that are not outliers.** 5. **Plot any outliers as individual points.** #### Explaining Distribution Type **Given that the distribution is unim
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