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MIS5208 - Spring 2020 - Data Analytics for IT Auditors

DATA ANALYTICS FOR IT AUDITORS AND CYBERSECURITY

Data Analytics for IT Auditors

MIS 5208.001 ■ Spring 2020 ■ Caswell Anderson
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    • ACL
      • Part 01 – Introduction to the Course and to Fraud
      • Part 02 – Fighting and Preventing Fraud
      • Part 04 – Data Driven Fraud Detection – Investigating Concealment and Money Laundering
    • ACL Labs
      • Lab 01 – Install ACL / Review and Work with On-Line Documentation
      • Lab 02 – ACL Analytics Basics | CPE (1.5)
      • Lab 03 – Fraud Scandals of Note
      • Lab 04 – ACL Analytics Foundations (CPE) (ACL 101 V4 CPE)
      • Lab 05 – Remediating Issues & Reporting Results (CPE) (ACL 105 V1 CPE)
      • Lab 06 – ACL Analytics Introduction to Scripting (CPE) (ACL 106 V1 CPE)
      • Lab 07 – Basics of Datetime Fields Learning Series (Basic-Intermediate) (ACL 210)
      • Lab 08 – Basics of Datetime Fields Learning Series (Basic-Intermediate) (ACL 210) (Continued…)
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    • Final Exam
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Edward Tufte ‘s Principles of Graphical Integrity

April 22, 2017 by Caswell Anderson

Who is Edward Tufte?

Edward Tufte is an analytical design theorist, educator, and landscape sculptor best known for his self-published books on analytical design. Furthermore, Edward Tufte was famously known for noting his writings and impact on information design such as scatter graphs, bar charts and line graphs including so many more graphical graphs , and also Edward Tufte was a pioneer of data visualisation meaning how data (a.k.a information) is presented as graphical content for important use.

Image result for edward tufte

Measuring Misrepresentation

The lie factor is calculated by dividing the size of the effect shown in the graphic by the size of the effect in the data.

If the lie factor is GREATER THAN 1 the graph OVERSTATES the effect.

Related image

Principles of Graphical Integrity

  1. The representation of numbers, as physically measured on the surface of the graph itself, should be directly proportional to the numerical quantities represented.
  2. Clear, detailed and thorough labeling should be used to defeat graphical distortion and ambiguity. Write out explanations of the data on the graph itself. Label important events in the data.
  3. Show data variation, not design variation
  4. In time-series displays of money, deflated and standardized units of monetary measurement are nearly always better than nominal units.
  5. The number of information carrying (variable) dimensions depicted should not exceed the number of dimensions in the data. Graphics must not quote data out of context.
  6. Graphics must not quote data out of context

Source:

http://classes.engr.oregonstate.edu/eecs/spring2015/cs419-001/Slides/tufteDesign.pdf

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