This publication presents a comprehensive statistical analysis of two continuous variables: Minutes and Drinks. Using R, I explored the data through descriptive statistics, histograms, and normality tests (Shapiro-Wilk). Both variables showed positive skewness and leptokurtic distributions, indicating non-normality. To assess the relationship, I conducted both Spearman and Pearson correlation tests. Results revealed a strong, positive, and statistically significant correlation (Spearman ρ = 0.92, Pearson r = 0.95, p < .001). This suggests that as time spent (Minutes) increases, the number of drinks consumed also increases. The report includes: Cleanly formatted R code and outputs Visualizations (histograms and scatterplots with regression line) Clear interpretation of results written as comments within the R script This RPubs publication demonstrates how to combine data visualization, normality testing, and correlation analysis into a reproducible workflow using R Markdown.