Intro to Time Series Analysis in R

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在此指导项目中,您将:

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初级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

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.

您要培养的技能

Time Series ForecastingTime SeriesTime Series ModelsBox Jenkins MethodStatistical Hypothesis Testing

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  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!

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

讲师

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