Time Series Modeling

Predictive Analytics    |    Intermediate
  • 8 videos | 33m 37s
  • Includes Assessment
  • Earns a Badge
Rating 4.0 of 87 users Rating 4.0 of 87 users (87)
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

  • 4m 53s
    In this video, you will learn how to identify key characteristics of time series forecasting. FREE ACCESS
  • 5m 8s
    In this video, you will learn the difference between stationary and nonstationary time series data. FREE ACCESS
  • Locked
    3.  Time Series Decomposition
    3m 39s
    After completing this video, you will be able to recognize the various components of time series data. FREE ACCESS
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    4.  Autoregressive Models
    5m 22s
    To identify features of autoregressive models, find out how. FREE ACCESS
  • Locked
    5.  Moving Average Models
    3m 20s
    During this video, you will learn how to identify features of moving average models. FREE ACCESS
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    6.  Autoregressive Moving Average (ARMA) Models
    4m 16s
    In this video, you will learn how to identify features of ARMA models. FREE ACCESS
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    7.  Parameterization and Forecasting
    3m 39s
    In this video, you will identify various steps required to make a forecast. FREE ACCESS
  • Locked
    8.  Exercise: Apply Time Series Modeling Concepts
    3m 20s
    Find out how to apply time series modeling concepts. FREE ACCESS

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