Difference between revisions of "Data types"
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==Qualitative data== | ==Qualitative data== | ||
| − | Qualitative data | + | Qualitative data are 'categorical' (or binary) data, and as such are often not expressed numerically. These types of data can be classified as '''nominal''' and '''ordinal''': |
===Nominal=== | ===Nominal=== | ||
| + | Nominal data include binary ('yes/no') and categorical data types, and are characterised by lacking any order between the different categories. As such, examples of nominal data are disease status (positive/negative), sex (male/female), breed and coat colour. As there is no numerical meaning to the data, nominal data are usually summarised with percentages or proportions. | ||
===Ordinal=== | ===Ordinal=== | ||
| + | Ordinal data | ||
==Quantitative data== | ==Quantitative data== | ||
Revision as of 09:04, 13 December 2010
Epidemiological investigation requires a good understanding of different data types, as this will strongly influence data analysis and interpretation. Data can broadly be classified as qualitative and quantitative, as shown below, although through manipulation, these types can be changed. Within each of these groups, data types can be classified further.
Qualitative data
Qualitative data are 'categorical' (or binary) data, and as such are often not expressed numerically. These types of data can be classified as nominal and ordinal:
Nominal
Nominal data include binary ('yes/no') and categorical data types, and are characterised by lacking any order between the different categories. As such, examples of nominal data are disease status (positive/negative), sex (male/female), breed and coat colour. As there is no numerical meaning to the data, nominal data are usually summarised with percentages or proportions.
Ordinal
Ordinal data
Quantitative data
Quantitative data are expressed numerically.