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# Continuous Variables

The variables which measure some count or quantity and don’t have any boundaries are are termed as continuous variables. It can be segregated into ratio or interval, or discrete variables. Interval variables have their centralized attribute, which is calibrated along with a range with some numerical values. The example can be temperature calibrated in Celsius or Fahrenheit doesn’t give any two different meaning; they display the optimum temperature, and it’s strictly not a ratio variable.

It can account for only a certain set of values, such as several bikes in a parking area are discrete as the floor holds only a limited portion to park bikes. Ratio variables occur with intervals; it has an extra condition that zero on any measurement denotes that there is no value of that variable. In simple, the distance of four meters is twice the distance of two meters. It operates on the ratio of measurements. Apart from these mentioned variables, a dummy variable can be applied in regression analysis to establish a relationship to unlinked categorical variables. For instance, if the user had categories ”has pet” and ”owns a home” can assign as 1 to ”’has pet” and 0 to ”’owns a home”.

A factor that remains constant in an experiment is termed as a control variable. In an experiment, if the scientist wants to test the plant’s light for its growth, he should control the value of water and soil quality. The additional variable which has a hidden impact on the obtained experimental values are called confounding variables.