Final answer:
When assessing the relationship between a Factor predictor and a binary target variable, identify the independent and dependent variables, create a scatter plot, conduct regression analysis for the line of best fit and the correlation coefficient, and determine the significance and linearity of the relationship.
Step-by-step explanation:
When assessing the bivariate relationship between a Factor predictor variable and a binary target variable, you should examine several statistical components to determine the nature and strength of the relationship.
- The independent variable in this context is the Factor predictor variable, and the dependent variable is the binary target variable. It's essential to correctly identify these to structure the analysis properly.
- A scatter plot should be drawn to visually assess the relationship between the variables. This can give an initial indication of whether there is a possible association.
- Regression analysis is used to find the line of best fit and the correlation coefficient, which quantifies the strength and direction of the relationship.
- The significance of the correlation coefficient must be interpreted to determine if the relationship observed is statistically significant.
- An assessment should be made regarding whether there is a linear relationship between the variables.
If working with categorical data, such as a factor predictor, alternative methods like logistic regression or chi-square tests for independence might be more appropriate than traditional linear regression and correlation.