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Statistical Analysis and Predictive Modeling of NYC Taxi Trip Data

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Statistical Analysis and Predictive Modeling of NYC Taxi Trip Data

A Comprehensive Approach to Data Cleaning, Outlier Detection, Interpolation, and Hypothesis Testing

Stony Brook CSE 544 (Probability and Statistics for Data Science) Project featuring Manthan Singh, Bindu Bhargava Reddy Chintam, Anish Philip, Hein Zaw.

  • Outlier Detection
  • Linear Interpolation of missing data-points
  • Performing Wald’s test, Z-test and T-test (H0: Feature in April and May are the same)
  • Performing K-S test and Permutation test (H0: Trip Distance and Fare Amount follow the same distribution)
  • Multiple Linear regression using Normal Equation
  • Time Series Analysis (EWMA, Auto Regression, Simple Moving Average)
  • Chi-Square Test (H0: Tip Amount is dependent on the passenger category)
  • Bayesian Test (Updated mean, Updated standard deviation and Maximum A Posterior of posterior distribution)

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Statistical Analysis and Predictive Modeling of NYC Taxi Trip Data

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