In: Statistics and Probability
how can correlational tests and logistic regression be used to understand the relationships between variables
Regression analysis is a related technique to assess the relationship between an outcome variable and one or more risk factors or confounding variables. The outcome variable is also called the response or dependent variable and the risk factors and confounders are called the predictors, or explanatory.
In correlation analysis, we estimate a sample correlation coefficient. It ranges between -1 and +1 and quantifies the direction and strength of the linear association between the two variables. The correlation between two variables can be positive or negative .
The sign of the correlation coefficient indicates the direction of the association. The magnitude of the correlation coefficient indicates the strength of the association.
For regression, if two variables are related it means that when one changes by a certain amount the other changes on an average by a certain amount, If y represents the dependent variable and x the independent variable, this relationship is described as the regression of y on x.