Measurement scales

Nominal Scales
A weakest level of measurement with no data ranking, by categorizing each member of the population or sample using an integer for each category.

Example :gender, male or female

Ordinal scales
A stronger level of measurement with order ranking, by placing each member of the population or sample into a category in respect to some characteristic but not quantifying the differences between two scale values.

Example: Rank on a scale of 1-5 your degree of satisfaction; restaurant ratings

Interval Scale
Provide a ranking across members, by assigning a number from a scale for each member of the population or sample. Assure that differences between scale values are equal. Scale values can be added or subtracted in a meaningful way, i.e. allow to quantify the difference between two interval scale values, but there is no natural zero.

Example: temperature scales are interval data with 20oC warmer than 18oC and a 2oC difference has some physical meaning. Note that 0oC is arbitrary, so that it does not make sense to say that 20oC is twice as hot as 10oC.

Ratio scales
The strongest level of measurement, with all the characteristics of interval scales plus a true zero point. It allows computation of meaningful ratios, addition and subtraction.

Example: physical measurements of height, weight, length are typically ratio variables. It is meaningful to say that 10 m is twice as long as 5 m. This is because there is a natural zero.