Course Notes - Department of Mathematics and Statistics

2. studies which have measured binary outcomes, establishingodds ratios and relative risks.• In both cases there are potentially other variables which have aneffect and/or possible confounding factors other than the treatmentsor exposures which influence the outcomes. We must allowfor these confounders otherwise invalid conclusions will be drawnabout the real effects of the treatments or exposures.Three Types of Regression• Simple linear regression• Multiple regression• Logistic regressionRelationship between two variables• Predictor variable (X) also known as the covariate or independentvariable or explanatory variable.• The X’s are known exactly (i.e. no error)• Outcome variable (Y) also known as the response, dependent.• The Y’s have random error associated with them.• Simple linear regression deals with the case where the relationshipis approximately a straight line.Scatter Plots• A scatterplot is a 2-D graph of the measurement for two numericalvariables. It gives a basic understanding of the relationshipbetween the two variables.• We plot the predictor variable on the x-axis and the outcomevariable on the y-axis204