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Time Series Analysis in R

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Certification

Time Series Analysis in R

Learn the basics of extracting meaningful insights from time series data.

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Description

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Features

This course includes

Duration

4 hours
Video Content
4 hours
Level
Intermediate
Instruction Type
Self Paced
Delivery Method
Online
Available on
Mobile, Desktop, Laptop
Accessibility
Limited Access
Language
English
Subtitles
English

Skills

Time Series ModelingR ProgrammingData Analysis

Learning Goals

You will learn several simplifying assumptions that are widely used in time series analysis, and common characteristics of financial time series
In this chapter, you will conduct some trend spotting, and learn the white noise (WN) model, the random walk (RW) model, and the definition of stationary processes
You will discover the autocorrelation function (ACF) and practice estimating and visualizing autocorrelations for time series data
You will also practice simulating and estimating the AR model in R, and compare the AR model with the random walk (RW) model

Course Content

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Prerequisites/Requirements

Intermediate R

Instructors

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David S. Matteson

Associate Professor at Cornell University

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Course Overview

Hands-On Training, Instructor-Moderated Discussions

Post course interactions

Virtual labs

International faculty

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