Data Visualization: Exploring and Explaining with Data
- Length: 448 pages
- Edition: 1
- Language: English
- Publisher: Cengage Learning
- Publication Date: 2021-05-18
- ISBN-10: 035763134X
- ISBN-13: 9780357631348
- Sales Rank: #1126067 (See Top 100 Books)
DATA VISUALIZATION: Exploring and Explaining with Data is designed to introduce best practices in data visualization to undergraduate and graduate students. This is one of the first books on data visualization designed for college courses. The book contains material on effective design, choice of chart type, effective use of color, how to both explore data visually, and how to explain concepts and results visually in a compelling way with data. The book explains both the “why” of data visualization and the “how.” That is, the book provides lucid explanations of the guiding principles of data visualization through the use of interesting examples.
Cover Brief Contents Contents About the Authors Preface Chapter 1: Introduction 1-1: Analytics 1-2: Why Visualize Data? 1-3: Types of Data 1-4: Data Visualization in Practice Summary Glossary Problems Chapter 2: Selecting a Chart Type 2-1: Defining the Goal of Your Data Visualization 2-2: Creating and Editing Charts in Excel 2-3: Scatter Charts and Bubble Charts 2-4: Line Charts, Column Charts, and Bar Charts 2-5: Maps 2-6: When to Use Tables 2-7: Other Specialized Charts 2-8: A Summary Guide to Chart Selection Summary Glossary Problems Chapter 3: Data Visualization and Design 3-1: Preattentive Attributes 3-2: Gestalt Principles 3-3: Data-Ink Ratio 3-4: Other Data Visualization Design Issues 3-5: Common Mistakes in Data Visualization Design Summary Glossary Problems Chapter 4: Purposeful Use of Color 4-1: Color and Perception 4-2: Color Schemes and Types of Data 4-3: Custom Color Using the Hsl Color System 4-4: Common Mistakes in the Use of Color in Data Visualization Summary Glossary Problems Chapter 5: Visualizing Variability 5-1: Creating Distributions from Data 5-2: Statistical Analysis of Distributions of Quantitative Variables 5-3: Uncertainty in Sample Statistics 5-4: Uncertainty in Predictive Models Summary Glossary Problems Chapter 6: Exploring Data Visually 6-1: Introduction to Exploratory Data Analysis 6-2: Analyzing Variables One at a Time 6-3: Relationships between Variables 6-4: Analysis of Missing Data 6-5: Visualizing Time Series Data 6-6: Visualizing Geospatial Data Summary Glossary Problems Chapter 7: Explaining Visually to Influence with Data 7-1: Know Your Audience 7-2: Know Your Message 7-3: Storytelling with Charts 7-4: Bringing It All Together: Storytelling and Presentation Design Summary Glossary Problems Chapter 8: Data Dashboards 8-1: What Is a Data Dashboard? 8-2: Data Dashboards Taxonomies 8-3: Data Dashboard Design 8-4: Using Excel Tools to Build a Data Dashboard 8-5: Common Mistakes in Data Dashboard Design Summary Glossary Problems Chapter 9: Telling the Truth with Data Visualization 9-1: Missing Data and Data Errors 9-2: Biased Data 9-3: Adjusting for Inflation 9-4: Deceptive Design Summary Glossary Problems References Index
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