Levels of Measurements

What is nominal data?

Often referred to as categorical data, the frequency of a particular variable is recorded at this level of measurement. These variables are discrete (they don’t overlap), and the categories have no natural order

Examples of nominal data; country of birth, career choice and taste in music

What is ordinal data?

Also a form of categorical data; however, the categories have a natural order. The difference between each point in an ordinal scale is not consistent

Examples of ordinal data; include positions in a competition (1st, 2nd, 3rd). Choices of a Likert scale (eg how happy do you feel 1-7) and relative height amount a group of people (tall, medium, small/tallest to smallest)

What is interval data?

Interval scales are precise due to having the same distance (equal intervals) between each adjacent point in a standardised scale. Interval data is continuous; the value recorded could be at any point on the scale used (eg 9.69872375 seconds)

Examples of interval data; weight in grams, length in millimetres, temperature in celsius and time in seconds

Ratio data

Ratio data is interval data with an absolute zero point but is treated as interval data in this course eg temperate in Kelvin as it cannot go below 0 degrees

Converting interval data to ordinal data..

Start with participant interval scores, for example, biological measures like reaction times or psychometric scores (Eg IQ, personality, depression, aggression) on a standardised test

Each participant is assigned a rank score to turn the interval measure into an ordinal measure. This is done by listing each participant from the highest scoring to the lowest scoring (using the interval measurement to place each participant). Any participants with the same interval score share the same rank position

Converting ordinal data to nominal data..

To convert ordinal to nominal, separate categories are created. Eg fast reaction/slow reaction, intelligent/unintelligent, extrovert/introvert, depressed/happy, aggressive/passive. The highest ranked half of the participants are assigned to one category, and the other half to the other category

How does converting between types of data work?

It is possible to convert from a higher level of measurement to a lower level of measurement (but not the other way around). Interval can be converted into ordinal, and ordinal can be converted into nominal