Defining Variables
While there are many different types of variables, this guide will focus on the main two discussed in quantitative research: independent and dependent variables.
Note: correlational research does not identify independent and dependent variables as the analysis is not dependent on the direction of the relationship.
Real-World Examples
Is there a difference in IQ based on gender?
Since the IQs of the groups are being compared, we're looking to see if IQ depends on a person's gender. This makes IQ the dependent variable. That makes 'gender' the independent variable since we're looking to see if a person's gender influences their IQ. Each gender classification would be considered a level of the independent variable.
Do higher dosages of the medication lead to improved blood sugar regulation?
The key phrase here is "lead to". This indicates which variable has the influencing role. Since we are looking to see if the different dosage leads to a different blood sugar level, that makes the dosage the independent variable. Similarly, we're looking to see if the blood sugar levels change as we change the dosage. This means that the blood sugar levels are the dependent variable.
Does regular attendance in afterschool programming influence school pride after graduation?
We can break this down into something simpler: Does Variable A influence Variable B? Since we know the independent variable is the one that holds an influencing role, that means Variable A is the independent variable. In this scenario, that's "regular attendance in afterschool programming". Therefore, Variable B, or "school pride after graduation" is the dependent variable.
Tips to Think About
Tip 1: You will find that independent and dependent variables are often referred to in other ways. For instance, independent variables are sometimes called factors or predictor variables. Dependent variables are sometimes referred to as the outcome variable.
Tip 2: One way to differentiate between whether a variable is independent or dependent is to consider when each variable occurred. Typically, the change in the independent variable must occur first, since we're looking to see if that change leads to a change in the dependent variable.
Tip 3: Keep in mind even if you do find a statistical relationship between two variables, that does not automatically mean one caused the other. This idea is a core principle in statistics: correlation does not equal causation. Only carefully controlled experiments can be used to draw causal conclusions.