Logistic regression is a statistical analysis method to predict a binary outcome, such as yes or no, based on prior observations of a data set. A logistic regression model predicts a dependent data variable by analyzing the relationship between one or more existing independent variables. For example, in health, Logistic regression can also be used in the following areas: • To identify risk factors and plan preventive measures; • In drug research to tease apart the effectiveness of medicines on health outcomes across age, gender and ethnicity;

I used data of 318 individuals with and without diabetes type 2.The aim is to examine the relationship between age, gender, BMI, diet type, smoking status and family history of disease and build a model for predicting diabetes risk.