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Instructor Solution Manual Chapter 9 for Principles of Data Science

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DataScience_ISM_Ch09 refers to the Instructor Solution Manual (ISM) for Chapter 9 of OpenStax’s Principles of Data Science. Chapter 9 typically focuses on advanced machine learning techniques, model evaluation, and feature engineering. The ISM is designed to help instructors: Provide step-by-step solutions for all exercises Offer sample answers and explanations for applied and critical thinking questions Support lecture preparation, grading, and class discussion Note: Access to the official ISM is restricted to verified instructors via OpenStax. Students can use the Student Solution Manual (SSM) for odd-numbered problems. Typical Content in DataScience_ISM_Ch09 Worked solutions for all exercises in Chapter 9 Advanced machine learning examples: decision trees, random forests, and clustering Feature selection and engineering techniques Evaluation metrics: ROC, AUC, precision, recall, and

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Data Science
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Data Science

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Principles of Data Science




11/5/24 For more free, peer-reviewed, openly licensed resources visit OpenStax.org. 1

, Principles of Data Science



Chapter 9
Visualizing Data

Critical Thinking
[9.1, LO 9.1.1]
1.
a. For the following five-number summary of a dataset of textbook cost per student per
semester, create a horizontal boxplot.
Minimum=$ 83 First Quartile=$ 255 Median=$ 481Third Quartile=$ 604 Maximum=$ 793
b. Analyze the boxplot and comment on variability, symmetry, and skewness.

Solution a:
Python code:
# import matplotlib

import matplotlib.pyplot as plt
import numpy as np

# Given values for the five-number summary
minimum = 83
q1 = 255
median = 481
q3 = 604
maximum = 793

# Create a boxplot using the given values
plt.boxplot([[minimum, q1, median, q3, maximum]], vert=False,
widths=0.1)

# Add labels and title
plt.xlabel('Textbook Cost ($)')
plt.title('Boxplot Showing Textbook Cost per Student per
Semester')

# Show the plot
plt.show()




11/5/24 For more free, peer-reviewed, openly licensed resources visit OpenStax.org. 2

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