Four Steps for Conducting Bivariate Analysis
The statistics we use for bivariate analysis are determined by levels of measurement for the two variables. We normally will want to take four steps in conducting a bivariate analysis. Keep in mind, we use statistics to test a bivariate hypothesis. In commonsense terms, we are using statistics to explain the relationship between the two variables and to determine the strength and significance of the relationship. I will use the relationship between gender and party identification to illustrate a bivariate analysis.
Here are the four steps:
Step 1: Define the nature of the relationship in terms of how the values of the independent variables relate to the values of the dependent variable.
For example, if I am testing the relationship between gender and party identification, then I will ultimately say something to the effect of:
Step 2: Identify the type and direction (if applicable) of the relationship.
Step 3: Determine if the relationship is statistically significant, i.e. different from the null hypothesis (meaning there is no expected relationship), and generalizable to the population.
Step 4: Identify the strength of the relationship, i.e. the degree to which the values of the independent variable explain the variation in the dependent variable.