Chapter 9: Visualizing Data | Data Science SSM Study Guide, Boxplot Analysis & Solutions 2026

Chapter 9 Visualizing Data Critical Thinking [9.1, LO 9.1.1] 1. For the following five-number summary of a dataset of textbook cost per student per semester, create a horizontal boxplot. Minimum = $83First Quartile = $255Median = $481Third Quartile = $604Maximum = $793 Analyze the boxplot and comment on variability, symmetry, and skewness. Solution a: Python code: # import matplotlib import t as plt import numpy as np # Given values for the five-number summary minimum = 83 q1 = 255 median = 481 q3 = 604 maximum = 793 # Create a boxplot using the given values ot([[minimum, q1, median, q3, maximum]], vert=False, widths=0.1) # Add labels and title l('Textbook Cost ($)') ('Boxplot Showing Textbook Cost per Student per Semester') # Show the plot () This resource covers Chapter 9: Visualizing Data from Data Science SSM. It focuses on graphical representation of data to identify patterns, variability, and distribution shapes for better data interpretation and decision-making. Key topics include histograms, bar charts, boxplots, five-number summaries, measures of spread, outliers, skewness, and symmetry. It also introduces Python-based data visualization using libraries such as Matplotlib for creating and interpreting statistical plots.