Time Series Modeling

Predictive Analytics
  • 8 Videos | 37m 7s
  • Includes Assessment
  • Earns a Badge
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Time series modeling is a common forecasting method, such as making stock market predictions. It has made its way into many varied applications, including inventory management and healthcare. Explore the features of time series modeling.

WHAT YOU WILL LEARN

  • identify key characteristics of time series forecasting
    distinguish between stationary time series and nonstationary time series data
    recognize the various components of time series data
    identify features of autoregressive models
  • identify features of moving average models
    identify features of ARMA models
    identify various steps required to make a forecast
    apply time series modeling concepts

IN THIS COURSE

  • Playable
    1. 
    Time Series Overview
    4m 53s
    UP NEXT
  • Playable
    2. 
    Stationary and Nonstationary Data Series
    5m 8s
  • Locked
    3. 
    Time Series Decomposition
    3m 39s
  • Locked
    4. 
    Autoregressive Models
    5m 22s
  • Locked
    5. 
    Moving Average Models
    3m 20s
  • Locked
    6. 
    Autoregressive Moving Average (ARMA) Models
    4m 16s
  • Locked
    7. 
    Parameterization and Forecasting
    3m 39s
  • Locked
    8. 
    Exercise: Apply Time Series Modeling Concepts
    3m 20s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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