Variable is a characteristic, number, or quantity that increases or decreases over time, or takes different values in different situations. The variables are the basic units used in statistics for measuring , collecting and analyzing. Variables can be classified in to different categories depending on the usage at the point of analysis. The different variable types are
Dependent and Independent Variable types
An independent Variable can take any value and can be controlled and measured. These are the inputs used for the study. These are also called factors.
A Dependent Variable cannot be controlled. it can only be measured. these are generally output of the changes done to the independent variables. The value of the dependent variable is dependent on the relation on the independent variable. These are called as responses.
It is notable that the dependent and independent variables are not fixed. a dependent variable in one experiment or study may become factor in a different experiment or study.
For Example, The heat generated is dependent on the amount of fuel burnt. (in this case, heat is a dependent variable and amount of fuel is an independent variable.
In a different experiment, the time taken for completely evaporate a substance is dependent on the amount of heat supplied. in this case, the time taken is the dependent variable and amount of heat is an independent variable. It is notable here that amount of heat is dependent in one experinment and independent in another experiment.
Qualitative and Quantitative Variable types
Variables are also classified according to the type of the data they represent. This classification depends on the type of the value associated with the variable.
A Qualitative variable describes the characters in a non numerical form. They are also called as categorical variables. Examples of the values which a categorical variable can take are Good, Bad, Red, Blue, Light, heavy, etc. The variables are result, color, weight etc. This is also called as nominal variable.
A Quantitative variable has a numerical value associated with it. This would be a counted or a measured value. These are also called as Numerical variables. Examples of the values a variable are in numbers, 0, -1, 1,2 etc. the variables are height, weight etc.
Notable that the same variable can be a qualitative or quantitative depending upon the value it takes. for example, if height is give a measured value such as 1.72 Meters, height is a quantitative variable. If the same height is expressed in a comparative value such as tall, short, height is a Qualitative Variable.
Discrete and Continuous Variables.
A discrete variable is something which is an output of counting. This can take only a set of values including negative and fractional values. Examples for a discrete variable are Number of people, charge on electron, etc…. . As a thumb rule, if there a prefix “number of” to the variable, it can be treated as a discrete variable.
A continuous variable can take any value within a specified range. This is generally a measured value. examples of continuous variables are speed, height, distance etc.
Discrete and continuous variables are subset of Numerical variable types
Binomial, Nominal and Ordinal Variables.
A binomial variable can take only two possible values. There is no third option available. For example, result of a test (pass or Fail), Result of tossing a coin (head or tail) etc
A Nominal variable can take several un-ordered values. Examples such as color red, blue, green), Type of bank account( savings, checking etc).
An ordinal variable can have any of the several ordered values. There is clear distinction between the order of the values which are assigned example such as height (tall, short), or response in a survey of satisfaction (excellent, good, poor, etc)
Binomial, Nominal and Ordinal variables are subset of the Qualitative variable types
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