Burim Fusha homework with program R on Hypothesis and Regression.

This project presents a comprehensive analysis of housing prices using the dataset hprice1. It involves the exploration of relationships between price and key independent variables, descriptive statistics, and linear regression analysis. Additionally, the study examines the residuals, multicollinearity, and the normality of residuals to ensure the robustness of the regression model. Visualizations and statistical tests are employed to derive meaningful insights. Key Components: Exploratory Data Analysis with plots of dependent and independent variables. Descriptive statistics summarizing the dataset. Linear regression analysis to determine significant predictors of housing prices. Residual analysis, multicollinearity test, and normality check of residuals.

A step-by-step guide to setting up the default versions of the three interactive Cancer InFocus applications