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Airline Passengers Forecasting Using Time Series Methods

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


๐Ÿ“Œ 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

๐Ÿ“Œ In this section, we estimate the number of passengers in the coming years by examining the number of passengers in the past years.

Dataset Story

๐Ÿ“Œ 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.