This report explores various forecasting techniques applied to Australian economic and financial datasets. By implementing different time series models, we analyze trends and seasonality and forecast future values. Our objective is to evaluate the effectiveness of models such as NAIVE, SNAIVE, and RW with drift to provide insights into population growth, industry production, and retail behavior.

This assignment explores key time series modeling concepts using the fpp3 framework, focusing on stationarity, transformation, differencing, and ARIMA modeling. Exercises 9.1 through 9.8 from Forecasting: Principles and Practice (3rd ed) are covered using real-world datasets such as Amazon stock prices, Australian air passengers, and US GDP.