Chapter 4:

Time Series Analysis

4.1

Decomposition of Time Series, Identifying Stationarity, Additive vs Multiplicative, Linear Regression for Time Series, and White Noise Process

4.2

Random Walk, Transformation of Time Series, and Time Series Metrics

4.3

Autocorrelation and Autoregressive Models

4.4

Moving Average and Exponential Smoothing

4.5

Modeling Seasonality with Binary Variables, Trigonometric Functions, and Seasonal Autoregressive Models

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Chapter Notes