Course Report
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Course Features
Duration
4 hours
Delivery Method
Online
Available on
Limited Access
Accessibility
Mobile, Desktop, Laptop
Language
English
Subtitles
English
Level
Intermediate
Teaching Type
Self Paced
Video Content
4 hours
Course Description
Highlights
Pedagogy
Top 30 Percentile
Rating & Reviews
Top 30 Percentile
Parameters
Pedagogy
Acquire all major R Programming skills in this course for seamless integration into your daily life. Develop a versatile skill set, allowing you to confidently apply what you've learned in various practical scenarios, enhancing your daily experiences and overall proficiency. An exceptional course in R Programming, this stands out for its Self Paced learning approach. Learners have the flexibility to progress at their own speed, tailoring the experience to their individual needs.
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Rating & Reviews
This highly acclaimed course is among the top-rated in R Programming, boasting a rating greater than 4 and an overall rating of 5.0. Its exceptional quality sets it apart, making it an excellent choice for individuals seeking top-notch learning experience in R Programming.
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Course Overview
Virtual Labs
International Faculty
Post Course Interactions
Hands-On Training,Instructor-Moderated Discussions
Skills You Will Gain
Prerequisites/Requirements
Intermediate R
What You Will Learn
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 Instructors
David S. Matteson
Associate Professor at Cornell University
Course Reviews
Average Rating Based on 3 reviews
100%