The human mind is geared to look at patterns and attach immediate explanation to the patterns, consciously or subconsciously, and sometimes that conclusion or explanation might not be apt. This course discusses the common fallacies and paradoxes in statistics and data analysis, as well as common pitfalls in data visualization. The course also teaches general guidelines that help you avoid those pitfalls to ensure a fair and accurate representation of facts.

Learn how to

• Identify fallacies and paradoxes that might lead to misinterpretation of data.
• Identify common pitfalls in graphical visualizations.
• Measure distortion in graphs.
• Use SAS Visual Analytics to create several graphs while avoiding common pitfalls.

Who should attend

Visual analysts, report or dashboard designers, business intelligence consultants, business analysts

Formats available	Standard duration
Classroom:	2 days
Live Web Classroom:	4 half-day session(s)

Before attending this course, you should be able to create simple graphs such as bar charts, pie charts, and scatter plots using any software. Familiarity with SAS Visual Analytics is highly recommended but not mandatory.

This course addresses SAS Visual Analytics, SAS Studio software.

Introduction

• Introduction to graphicacy.
• Introduction to SAS Visual Analytics.
• Introduction to data representation pitfalls.

Common Data Misinterpretations and Paradoxes

• Common data misinterpretations.
• Paradoxes in statistics.
• Spurious correlations.

Common Visual Misrepresentations

• Common data visualization pitfalls.
• Measuring distortion in graphs.
• Reasons for misleading visualizations and consequences.

Common Remedies for Pitfalls in Visualization

• Avoid inappropriate choice of colors.
• Avoid inappropriate choice of graphical objects.
• Avoid overuse of custom or complex graphs.
• Review case study: Tackling visual clutter.