Data Levels of Measurement (2024)

FAQs

Data Levels of Measurement? ›

Statisticians often refer to the "levels of measurement" of a variable, a measure, or a scale to distinguish between measured variables that have different properties. There are four basic levels: nominal, ordinal, interval, and ratio.

There are four types of measurement (or scales) to be aware of: nominal, ordinal, interval, and ratio. Each scale builds on the previous, meaning that each scale not only “ticks the same boxes” as the previous scale, but also adds another level of precision.

Psychologist Stanley Stevens developed the four common scales of measurement: nominal, ordinal, interval and ratio. Each scale of measurement has properties that determine how to properly analyse the data. The properties evaluated are identity, magnitude, equal intervals and a minimum value of zero.

The nominal level of measurement classifies data into mutually exclusive (nonover- lapping) categories in which no order or ranking can be imposed on the data.

Nominal Level: This is the simplest level of measurement, where data is categorized into mutually exclusive groups with no intrinsic order or ranking. Examples of nominal scales include gender (male, female) or eye color (blue, brown, green).

Gender is an example of a nominal variable because the categories (woman, man, transgender, non-binary, etc.) cannot be ordered from high to low. Olympic medals are an example of an ordinal variable because the categories (gold, silver, bronze) can be ordered from high to low.

An interval scale is one where there is order and the difference between two values is meaningful. Examples of interval variables include: temperature (Farenheit), temperature (Celcius), pH, SAT score (200-800), credit score (300-850).

As you explore various types of data, you'll come across four main categories: nominal, ordinal, discrete, and continuous. Understanding these data categories can help you choose the appropriate analysis techniques and make sense of the information you encounter.

Scales of analysis are the size of the lens through which we view a given geographic area and are generally considered local, national, regional, and global scales.

Is age an ordinal variable? Depending on the question, age can be a nominal or ordinal variable. If the question is "How old are you?" it's a nominal variable. If the question is "What age range are you in?" it's an ordinal variable.

How to determine levels of measurement? ›

by Tim Bock. In psychology and many disciplines that draw on psychology, data is classified as having one of four measurement scale types: nominal, ordinal, interval, and ratio. The measurement scale indicates the types of mathematical operations that can be performed on the data.

Level measurements are classified into two types– direct and indirect level measurements or performed by contact or non-contact transmitters. Direct level measurements are considered ideal for small level changes, which are observed in various industrial tanks.

The measures in ordinal scale do not have absolute value hence the real difference between adjacent values may not have the same meaning. For example, the values in the age scale “less than 20” and “20-50” do not have the same meaning as “50-80” and “over 80”.

Ordinal data is data that can be ranked or ordered. Examples include data taken from a poll or survey. Nominal data is data that can be made to fit various categories. Examples include whether an animal is a mammal, fish, reptile, amphibian, or bird.

As we've discussed, nominal data is a categorical data type, so it describes qualitative characteristics or groups, with no order or rank between categories. Examples of nominal data include: Gender, ethnicity, eye colour, blood type.

The Kirkpatrick Model is a globally recognized method of evaluating the results of training and learning programs. It assesses both formal and informal training methods and rates them against four levels of criteria: reaction, learning, behavior, and results.

Having begun to read, good readers operate cognitively at four highly interrelated and overl~apping levels of meaning : the literal, the interpretive, the critical, and the creative.

The basic units of measurement are for length, mass, time and temperature.