The core of any research is measurement. It can be defined as the method of assigning numbers to things. It is essential in research as everything has to be reduced to numbers.

Assigning numbers to properties of things is easy. However, it is quite difficult in other cases. Measuring social conformity or intelligence is much complex than measuring weight, age or financial assets, which can be directly measured directly with some standard unit of measurement. Measurement tools of abstract/qualitative concepts are not standardized, and the results are not very accurate.

A clear understanding of the level of measurement of variables is important in research because it is the level, which determines what type of statistical analysis has to be conducted. The collected data can be classified into distinct categories. If there are limited categories, then they are known as *discrete* variables. If there are unlimited categories, they are known as *continuous* variables. The **nominal level** of measurement describes these categorical variables. Nominal variables include demographic properties like sex, race, religion, etc. This is considered as the most basic level of measurement. No ranking or hierarchy is present in this level.

The variables that can be sequenced in some order of importance can be described by the **ordinal level**. Opinions and attitude scales or indexes in the social sciences are ordinal in nature. Ex.: Upper, middle, and lower class. In this case, the order is known; however, the interval between the values is not meaningful.

Variables that have more or less equal intervals are described by the **interval level** of measurement. Crime rates come under this measurement level. Temperature is also an interval variable. Here, the interval between variables can be interpreted; but, ratios are not meaningful.

**Ratio level** describes variables that have equal intervals and a reference point. Measurement of physical dimension such as weight, height, distance, etc. falls under this level.