This project presents a comprehensive statistical analysis of internet speed data, conducted as part of the MAT10251 course. The analysis begins with calculating a confidence interval for the proportion of time download speeds exceed 40 Mbps, followed by a one-sample z-test to determine if the mean download speed surpasses the advertised speed of 41 Mbps. A two-sample t-test is then employed to compare average download speeds across two trials. Furthermore, the project includes both simple and multiple linear regression models. The simple linear regression predicts upload speed based on download speed, while the multiple linear regression incorporates both download speed and time of day (evening vs. not evening) as predictors for upload speed. The project provides detailed Excel outputs, statistical tests, and interpretations of the results, including R-squared values and p-values for all models, and concludes with appendices containing key statistical data and references.