# Statistics notes - types of data

(Redirected from Ordinal)
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## One possible typology

### Ratio data (ordered, meaningful zero point, linear scale, (often) continuous)

 This article/section is a stub — probably a pile of half-sorted notes and is probably a first version, is not well-checked, so may have incorrect bits. (Feel free to ignore, or tell me)

Properties:

• ordered/monotonous (larger value means larger represented thing)
• linearly comparable, e.g. twice the distance in these numbers means twice the amount of difference in represented thing)
• meaningful zero point
• the combination of the above imply numbers are proportional: twice the number directly means twice the amount of different thing

Examples:

• weight
• length
• time amount - reaction time, hours of study, time required to run a marathon
• age
• temperature in Kelvin
• number of responses (note: overlap with discrete numeric)
• many physical measurements in general
though not all - can depends on units and their implied zeroing. For example, Farenheit and Celcius are not zeroed according to energy

### Interval data (ordered, no meaningful zero point, possible linear scale, (often) continuous)

Properties:

• ordered/monotonous (larger value means larger represented thing)
• comparability often not linear, though could be for any given case
• no particularly meaningful zero point

Interval data is quantitative data in a numbering system in which there is no sensible zero point.

This means the assumption of linear relationships may be incorrect (often the most important difference compared to ratio data)

• ...because of the zero point
• ...because the scale is arbitrary
• ...and/or because of other reasons

### Ordinal data (ordered, but no obvious numbering so not linear; discrete)

Examples:

• highest level of education
• questionnaire items of the 'strongly disagree to strongly agree in five steps' sort
• age groups ('age up to 20', 'age 20-29', 'age 30-39') (note: in this case based on ratio data)
• socioeconomic status (sort of)
• most any ranking

Asking people to rate on a few-point scale is often seen as ordinal, while there is overlap with continuous interval data.

### Nominal/categorical data (unordered; qualitative; discrete)

Examples:

• labels, such as {T,A,G,C}
• choosing from multiple choice options
• distinguishers such as {green,blue} or {true,false}, discrete genders, blood type
• brand names
• left/right-handedness
• political affiliation

## More words

### Further terms that matter

Continuous data refers to valued numbering that is not restricted to be discrete/integer.

so ratio or interval data in the above list.

Quantitative data - basically anything not categorical, so referring to nominal/categorical.