Regression Analysis

To evaluate relationships between variables for both bivariate and multivariate.

EXPECTED LEARNING OUTCOMES
By the end of the course unit students should be able to;

• Analyze the correlations and estimate regression parameters for the regression models.
• Explain linear estimations, multiple linear equations, and partial correlation coefficients.
• Describe Gauss-Markov linear model.
• Explain procedures under analysis of convenience models.
• Describe tests related to linear models.
• State and explain Cochran’s theorem of model selection procedure.
• Describe the use of dummy variables.
• List methods of simple transformations required to remove non linearity in parameters.