Talvir Singh is teaching live on Unacademy Plus
TARGET JRF 2018 30 MOST IMPORTANT TOPICS LAST MINUTE REVISION BY TALVIR SINGH
TYPES OF VARIABLES
VARIABLE ANYTHING THAT VARY IN SOME QUANTITATIVE TERMS. IT MAY BE DISCRETE OR CONTINUOUS.
Types of Variables . The variables are classified into categorical and quantitative variables. Quantitative variables vary in degree or amount such as annual income. Categorical variables vary in type or kind such as gender.
On the basis of causation, the variables are basically of two types, namely independent and dependent variables. 1. Independent variables (symbolized by IV) are presumed to be the cause of another variable. 2. Dependent variables (symbolized by DV) are the presumed effect or outcome. Dependent variables are influenced by one or more independent variables. In research, for example, in the study about impact of coaching on student performance, coaching is IV and student performance is DV.
BASIS FOR COMPARISON DISCRETE VARIABLE CONTINUOUS VARIABLE Meaning Discrete variable refers to the variable that assumes a finite number of isolated values. Continuous variable alludes to the a variable which assumes infinite number of different values Range of specified number Complete Incomplete Values Values are obtained by counting Non-overlapping Distinct or separate values. Values are obtained by measuring Overlapping Any value between the two Classification Assumes values. Represent ed by Isolated points Connected points
In addition, there can be intervening variables and extraneous variables.
1. Intervening variables: These are also termed as mediator variables. They establish link between IV and DV. These are variables through which one variable affects another variable. These are helpful to understand the process. For example, tissue damage is an intervening variable in smoking and lung cancer relationship. We can use arrows (which mean causes or affects) and draw the relationship that includes an intervening variable like the one given below . Smoking isue damageLung cancer
2. Extraneous variable: In real-life situations, there can be many factors or variables that may affect the outcome. These variables are termed as extraneous variables. They actually compete with the independent variable in explaining the outcome. .If an extraneous variable is the real reason for an outcome rather than IV, it is also called as confounding variable because it has confused or confounded the relationship we are interested in.
On the basis of study design The variables can be active variables and attribute variables. Active variables can be manipulated or controlled during the study. Attribute variables such as gender, age, etc. cannot be changed, controlled, or manipulated.
Binary variables Binary variables are variables which only take two values. For example, Male or Female, True or False and Yes or No. While many variables and questions are naturally binary, it is often useful to construct binary variables from other types of data