This presentation will explore the relationship between car speed and stopping distance using built-in R dataset cars.

\[Y = \beta_0 + \beta_1X + \epsilon\] Mathematical formula that will be used for this model: this will allow us to calculate the predicted stopping distance based on speed.

Null Hypotheis (\(H_0\)): \[H_0: \beta_1 = 0\] Alternative Hypothesis (\(H_a\)): \[H_a: \beta_1 \neq 0\] In this analysis, we are examining whether a car’s speed has significant impact on the distance it travels.

The scatter plot shows how distance increases as speed increases.

In conclusion, based on our analysis of the cars dataset, we found a positive correlation between speed and distance. As speed increases, the distance required to stop also increases. Additionally, the model is statistically significant, which allows us to reject the null hypothesis.