Age is what type of level of measurement

There general rule is that you can go down in level of measurement but not up. However, many variables that get captured as ordinal have a similar variable that can be captured as interval or ratio data, if you so choose. If you collect a variable as ratio data, you can always decide later to group the data for display if that makes sense for your work.

There are some other terms that are frequently used to talk about types of data. We are choosing not to use them here because there is some disagreement about their meanings, but you should be aware of them and what their possible definitions are in case you encounter them in other resources.

We talked about both nominal and ordinal data above as splitting data into categories. Some texts consider both to be types of categorical data, with nominal being unordered categorical data and ordinal being ordered categorical data. Qualitative data, roughly speaking, refers to non-numeric data, while quantitative data is typically data that is numeric and hence quantifiable.

There is some consensus with regard to these terms. Certain data are always considered qualitative, as they require pre-processing or different methods than quantitative data to analyze. Examples are recordings of direct observation or transcripts of interviews.

Surely it can be meaningfully transformed by going from years to days etc. If I eat another pound of food, I gain another pound: does that make me twice as heavy?? Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Password. Post as a guest Name. Email Required, but never shown. Featured on Meta. Now live: A fully responsive profile. Version labels for answers. Linked 5. Related 2. Hot Network Questions.

Question feed. We can help you with agile consumer research and conjoint analysis. Apart from product and pricing research, Conjoint. Fully-functional online survey tool with various question types, logic, randomisation, and reporting for unlimited number of responses and surveys. The level of measurement refers to the relationship among the values that are assigned to the attributes for a variable.

What does that mean? That variable has a number of attributes. For purposes of analyzing the results of this variable, we arbitrarily assign the values 1 , 2 and 3 to the three attributes.

The level of measurement describes the relationship among these three values. In this case, we simply are using the numbers as shorter placeholders for the lengthier text terms. In this case, we only use the values as a shorter name for the attribute.

First, knowing the level of measurement helps you decide how to interpret the data from that variable. The only time that age would not be considered a ratio variable is if the data we collect on age is in categories. For example, we may send out a survey and ask people to report which age bracket they belong in from the following choices:.

In this scenario, age would be treated as an ordinal variable because a natural order exists among the potential values. This represents a rare scenario where we would not classify age as a ratio variable.