[social4i size=”large” align=”float-right”] DataCamp recently launched two new online R courses on time series analysis.
- Chapter One: Exploratory Time Series Data Analysis (FREE) Learn how to organize and visualize time series data in R.
- Chapter Two: Predicting the Future Conduct trend spotting, learn the white noise model, the random walk model, and the definition of stationary processes.
- Chapter Three: Correlation Analysis and the Autocorrelation Function Review the correlation coefficient, then practice estimating and visualizing autocorrelations for time series data.
- Chapter Four: Autoregression Discover the autoregressive model and several of its basic properties.
- Chapter Five: A Simple Moving Average Learn about the simple moving average model, then compare the performance of several models.
- Chapter One: Time Series Data and Models Investigate time series data and learn the basics of ARMA models, which can explain the behavior of such data.
- Chapter Two: Fitting ARMA Models Discover the wonderful world of ARMA models and learn how to fit these models to time series data.
- Chapter Three: ARIMA Models Learn about integrated ARMA (ARIMA) models for nonstationary time series.
- Chapter Four: Seasonal ARIMA Learn how to fit and forecast seasonal time series data using seasonal ARIMA models.