This is an Inferential Statistics project where concepts including Hypothesis Testing and Confidence intervals are used to analyse Cars data to test which fuel type is more efficient.
This project analyses World Health Organisation(WHO) data to predict life expectancy in different countries. Multiple linear regression model is used to draw insights. Different dimensionality reduction techniques were used to pick the best model with the minimal root mean squared error(RMSE).
This project uses the K-nearest Neighbour classification model to predict the likelihood of an individual in Taiwan to default on their next payment. The TidyModels package is used to build the model.