It is also called as resultant variables, predictor or experimental variables. The independent variable is the one that is computed in research to view the impact of dependent variables. A variable that occurs before the independent variable is called an antecedent variable. Many other variables are discussed in minimally are listed are active variable which the researcher evaluates. So there are many different types of variables available that can be applied in varied domains. Such types of variables are implemented for many types of research for easy computations. In statistics, the variable is an algebraic term that denotes the unknown value that is not a fixed value which is in numerical format. Different Types of Variables in Statistics Apart from these, quantitative and qualitative variables hold data as nominal, ordinal, interval and ratio. Such variables in statistics are broadly divided into four categories such as independent variables, dependent variables, categorical and continuous variables. A variable can occurs in any form, such as trait, factor or a statement that will constantly be changing according to the changes in the applied environment. The values that are altering according to circumstances are referred to as variables. The following article provides an outline on Types of Variables in Statistics. Introduction to Types of Variables in Statistics
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