In this class we will cover the basics of time series modeling. First, we will focus on time series assumptions such as stationarity and autocorrelation. Then we will focus in this class on AR, MA, ARMA, and ARIMA models and when to use each type of model.

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Data Available Here and Code Available Here

• Practical Time Series Analysis by Aileen Nielsen: Chapter 3, Time Series-Specific Exploratory Methods Section; Chapter 6
• Forecasting: Principles and Practices, Chapter 8: ARIMA Models
• ARIMA Models in Python