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.
|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.