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A university research manager wants to determine how ten academic disciplines compare to each other in relation to five different funding categories. The manager collects 2-way classification data for 796 researchers.
You can use this data to demonstrate Simple Correspondence Analysis.
| Worksheet column | Description |
|---|---|
| CT1 | Number of researchers at funding level A (highest funding) |
| CT2 | Number of researchers at funding level B |
| CT3 | Number of researchers at funding level C |
| CT4 | Number of researchers at funding level D (lowest funding) |
| CT5 | Number of researchers at funding level E (unfunded) |
| RowNames | The row names (academic disciplines): Geology Biochemistry Chemistry Zoology Physics Engineering Microbiology Botany Statistics Mathematics |
| ColNames | The column names (funding levels):A B C D E |
| RowSupp1 | Additional row of supplementary data for museum researchers |
| RowSupp2 | Additional row of supplementary data for or mathematical sciences (sum of Mathematics and Statistics) |
| RSNames | The row names for the supplementary data:Museums MathSci |
The example and data are from M. Greenacre (2007). Correspondence Analysis in Practice. Taylor and Hill, page 75.
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