Beginning Time Series Analysis and Forecasting with R

Time series data is found in any field. This course will teach you how to handle this specific type of data and how to create forecasting models.
Course info
Rating
(43)
Level
Beginner
Updated
Jan 8, 2018
Duration
2h 5m
Table of contents
Description
Course info
Rating
(43)
Level
Beginner
Updated
Jan 8, 2018
Duration
2h 5m
Description

Do you want to create a time series model and use it for forecasting? Nearly everyone working in a quantitative field has to work with time series data. This sort of data has specific rules, functions and visualizations which you will learn in this course, Beginning Time Series Analysis and Forecasting with R. First, you'll learn about time series data, which is data captured along a timeline. That means time series data has a specific order (a timestamp) which allows different types of analysis and modeling. Next, you'll explore how these models can be used to create forecasts which are widely used in many fields ranging from finance to academia or medicine. R is the favorite tool among data scientists to do time series analysis. Knowing this, you'll finally touch on the variety of add on packages that were created especially for that purpose, most prominently the package “forecast” by J Hyndman. By the end of this course, you'll not only know about the underlying statistics of time series but also about models like ARIMA, exponential smoothing or simpler types of models. Of course you will use these models to create forecasts!

About the author
About the author

Martin is a trained biostatistician, programmer, consultant and data science enthusiast. His main objective: Explaining data science in a straightforward way. You can find his latest work over at: r-tutorials.com

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