Airline Passengers Forecasting Using Time Series Methods

In this section, we will estimate airline passengers using time series methods.

📌 We used the following methods for airline passenger forecasting:

SES: Single Exponential Smoothing

DES: Double Exponential Smoothing

TES: Triple Exponential Smoothing

ARIMA: Autoregressive Integrated Moving Average

SARIMA: Seasonal Autoregressive Integrated Moving Average

Business Problem

📌 In this section, we estimate the number of passengers in the coming years by examining the number of passengers in the past years.

📌 This dataset contains how many passengers traveled monthly from 1949 to 1960.

Month: the date in the month is a variable.

Passengers: estimates the number of passengers per month.