Graphing Data Effectively and Avoiding Common Pitfalls
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.
Virtual Training nebo e-Learning?
Máme dostatečnou flexibilitu, takže vybírat můžete jak prezenční termíny, tak online kurzy.
Zkuste živý kurz virtuálněTarget group
- Visual analysts
- report or dashboard designers
- business intelligence consultants
- business analysts
Course structure
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.
Prerequisites
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.
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Jsme vám k dispozici na telefonním čísle +420 222 553 101 vždy od pondělí do pátku: 9:00 - 17:00.
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