Levels Of Measurement Flashcards
3 kinds of levels of measurement
Ordinal
Nominal
Interval/ratio
Nominal data and give examples
Often referred to as categorical data, the frequency count 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.
Eg; country of birth, career choice, taste in music
Ordinal data and examples
It has the same properties as nominal 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.
- positions in a competition, choices on scale eg measuring happiness on a likert scale , relative height among a group of people
Interval data and give examples
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 any point on the scale used (e.g. 9.69872375 seconds not limited to a small set of discrete categories.
Eg, weight in grams, temp in degrees c and length in mem
What is the distinction between ratio and interval data
Ratio data is interval data with an absolute 0 point but is treated as interval data in aqa
Which kinds of data can be converted into another
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.
Converting interval to ordinal
Start with participant interval scores, for example, biological measures like galvanic skin response, reaction times or psychometric scores (e.g. 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 to nominal
To convert ordinal data to nominal data, separate categories are created. E.g. fast reaction/slow reaction, intelligent/unintelligent, extravert/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.
