2022-04-10

Objectives and Background

  • Determine if there are trends with passengers
  • Model predicts future passenger growth and trends
  • Show exploratory analysis and model fitting
  • Show the final model and provide recommendations
  • Data is of airline passengers from 1949 to 1960
  • Attributes: Monthly passengers in thousands of passengers

Scatter Plot and Correlation

Boxplots of Monthly Passengers

Auto Correlation Function

Partial Auto Correlation Function

Fitted Model and Predictions

Conclusions and Recommendations

  • Time series analysis able to predict passsenger growth and seonal trends from the data
  • ADF test, ACF, PACF plots support chosen model
  • No outliers were in the dataset
  • Time series analysis provide prediction and confidence levels
  • Recommend revisiting model every year to prove the validity of the model
  • Recommend investigating advertising effectiveness