Two new online R courses on time series (via DataCamp)

January 18, 2017

DataCamp recently launched two new online R courses on time series analysis.

Introduction to Time Series Analysis

What You’ll Learn:

  • 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.

Play now…

ARIMA Modeling with R

What You’ll Learn:

  • 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.

Play now…

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