Different types of information can be used in statistical analysis. Understanding the type of variable being analyzed can make it easier to determine how to measure it and utilize the results. A qualitative variable is descriptive in nature and usually measured by counting. A quantitative variable is reported numerically. Further a discrete quantitative variable is generally derived by counting while a continuous discrete variable results from measuring. Below are descriptions of the types of variables used in statistical analysis:
- Qualitative Variables – If the characteristic being studied is non-numeric it is referred to as qualitative. This implies that the variable is descriptive in nature. An example of a qualitative variable would be ‘type of automobile owned’.
- Quantitative Variables – When the variable studied is reported numerically it is called Quantitative. An example of a quantitative variable would be the life of an automobile battery stated in months.
- Discrete Variable – This type of variable can assume only certain values. Discrete variables generally result from counting. The number of customers that come to the counter of an auto repair shop within an hour would be an example. The number would not be the same every hour but would be a specific number.
- Continuous Variable – This type of variable can assume any value within a specified range. Continuous variables typically result from measuring. For example the air pressure in a tire would yield a specific PSI.