Intro to Time Series Analysis in R

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在此指導項目中,您將:

Fit various types of time series models to real world data and use them to forecast the future.

Understand how to assess model fit in time series data.

Know the reasons why time series models and methodology are an important toolkit for any data scientist.

Clock2 hours
Beginner初級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

In this 2 hour long project-based course, you will learn the basics of time series analysis in R. By the end of this project, you will understand the essential theory for time series analysis and have built each of the major model types (Autoregressive, Moving Average, ARMA, ARIMA, and decomposition) on a real world data set to forecast the future. We will go over the essential packages and functions in R as well to make time series analysis easy.

您要培養的技能

  • Time Series Forecasting
  • Time Series
  • Time Series Models
  • Box Jenkins Method
  • Statistical Hypothesis Testing

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Time Series Data Overview

  2. Why Time Series?

  3. Key Concepts: Autocorrelation / Autocovariance

  4. Key Concepts: Stationarity

  5. Checking for Stationarity

  6. Transforming for Stationarity

  7. Basic Model Types: AR, MA, ARMA, ARIMA, Decomposition

  8. And More!

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

授課教師

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