Biostatistics is the use of math and statistics to answer questions about health, medicine, or biology. For example, we might want to know how many people in a group are overweight or have asthma.

It’s also important to see how these problems change over time or in different places. Sometimes, we compare groups of people to see if certain habits, like smoking or exercising, are linked to certain health problems.

Since we can’t ask everyone in a population, we study smaller groups, or samples. Biostatistics helps us collect, study, and understand the data from these samples to learn more about the whole population.

In this post, we’ll learn about one of the most basic concepts in biostatistics: levels of data measurement.

Let’s dive in!

## Data Levels of Measurement

A variable has one of four different levels of measurement:

- Nominal
- Ordinal
- Interval
- Ratio

Two of these belong to qualitative data type, i.e., Nominal and Ordinal. They cannot be measured.

The other two of these belong to quantitative data type, i.e., Ratio and Interval. These can be measured.

**Nominal:**It categorizes variables according to qualitative labels (or names). These labels and groupings don’t have any order or hierarchy to them, nor do they convey any numerical value.

**Ordinal**: It categorizes variables into labeled groups, and these categories have an order or hierarchy to them. For example, you could measure the variable “income” on an ordinal scale as follows: low income, medium income, and high income.

**Interval:**It is a numerical scale that labels and orders variables, with a known, evenly spaced interval between each of the values.

**Ratio:**It is exactly the same as the interval scale, with one key difference: The ratio scale has what’s known as a “true zero.” A good example of ratio data is weight in kilograms.

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