WF ED 540, Data Analysis, Fall 2017
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This document discusses tidy data principles for data analysis: 1. Each variable must have its own column. 2. Each observation must have its own row. 3. Each value must have its own cell. It also discusses different measurement levels for variables including nominal, ordinal, interval, and ratio scales and provides examples of each.
WF ED 540, Data Analysis, Fall 2017
- 1. DataAnalysis inWF ED 18 September 2015
- 4. 1. Each variable must have its own column:
- 5. 1. Each variable must have its own column: 2. Each observation must have its own row:
- 6. 1. Each variable must have its own column: 2. Each observation must have its own row: 3. Each value must have its own cell:
- 8. UNTIDY
- 9. UNTIDY TIDY
- 10. YES, for understanding (transformation, visualization, and modeling)
- 11. YES, for understanding (transformation, visualization, and modeling) NO, for communication
- 13. An entity that has two or more mutually exclusive values
- 14. An entity that has two or more mutually exclusive values
- 15. An entity that has two or more mutually exclusive values
- 16. An entity that has two or more mutually exclusive values Some examples?
- 17. Measurement is a process of assigning values to variables based on rules
- 18. Type Level Example Nominal Unordered categories Gender is either male or female Ordinal Ordered categories Size is small, medium or, large Interval No true zero, but equal intervals % items correct on achievement test as a measure of ability Ratio True zero and equal intervals % items correct on achievement test
- 19. DataAnalysis inWF ED 18 September 2015