Overview
Context
When working with data that contains many variables, we are often interested in studying the relationship between these variables using multivariate statistics.
In this Multivariate Probability Distributions in R course offered by Data Camp, you'll learn about common multivariate probability distributions, including the multivariate normal, the multivariate-t, and some multivariate skew distributions.
You will then be introduced to techniques for representing high dimensional data in fewer dimensions, including principal component analysis (PCA) and multidimensional scaling (MDS).
Programme Structure
Chapters
- Reading and plotting multivariate data
- Multivariate Normal Distribution
- Other Multivariate Distributions
- Principal Component Analysis and Multidimensional Scaling
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
Language
Delivered
Campus Location
- New York City, United States
Disciplines
Statistics View 109 other Short Courses in Statistics in United StatesWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- This course is suitable for beginners although a working knowledge of R is required for this course. It provides an introduction to multivariate data, distributions, and statistical techniques for analyzing high dimensional data.
- Professionals in fields like data science, finance, economics, and engineering would benefit from this course. It would also be useful for actuaries, statisticians, and researchers.
PREREQUISITES
- Foundations of Probability in R
Tuition Fees
-
International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
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Domestic
Applies to youIn-StateFree
Additional Details
This course can be accessed for free with the Data Camp Premium or Teams subscriptions