Conclusions that can be drawn from this analysis:
From the linear regression results, we can say that there is a strong positive relationship between the distance travelled by a taxi ride and the time taken for the travel. Also, with just 2 variables the model performance is not that good. It is also evident that the model doesn't follow many statistical assumptions and thus requires transformations to correct the data.
From the multiple linear regression, the model has a better performance when compared to just 2 variables. Also, an interesting finding is that only pickup and dropoff points have an impact on the dependent variable. Thus the location of the pickup and dropoff points has a higher impact on the fare amount charged and trip times. This study also indicates that the time of the pickup and dropoff also doesn't impact the total trip time since traffic movement in NYC is also similar in many areas.
Overall, the analysis of NYC taxi data using Linea Regression for predicting trip times can provide valuable insights into factors that affect trip time and can inform decision-making for transportation planning, resource allocation, and other related areas.