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Multivariate Probability Distributions in R

IntermediateSkill Level
4.7+
38 reviews
Updated 05/2025
Learn to analyze, plot, and model multivariate data.
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RProbability & Statistics4 hr15 videos50 Exercises3,900 XP8,755Statement of Accomplishment

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Course Description

When working with data that contains many variables, we are often interested in studying the relationship between these variables using multivariate statistics. In this course, you'll learn ways to analyze these datasets. You will also 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).

Prerequisites

Foundations of Probability in R
1

Reading and plotting multivariate data

In this introduction to multivariate data, you will learn how to read and summarize it. You will learn how to summarize multivariate data using descriptive statistics, such as the mean vector, variance-covariance, and correlation matrices. You'll then explore plotting techniques to provide insights into multivariate data.
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2

Multivariate Normal Distribution

This chapter will introduce you to the most important and widely used multivariate probability distribution, the multivariate normal. You will learn how to generate random samples from a multivariate normal distribution and how to calculate and plot the densities and probabilities under this distribution. You will also learn how to test if a dataset follows multivariate normality.
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3

Other Multivariate Distributions

This chapter introduces a host of probability distributions to model non-normal data. In particular, you will be introduced to multivariate t-distributions, which can model heavier tails and are a generalization of the univariate Student's t-distribution. You will be introduced to various skew distributions, which are specifically designed to model data that are right or left skewed.
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4

Principal Component Analysis and Multidimensional Scaling

In the final chapter, you will be introduced to techniques for analyzing high dimensional data, including principal component analysis (PCA) and multidimensional scaling (MDS). You will also learn to implement these techniques by analyzing data.
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Multivariate Probability Distributions in R
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Don’t just take our word for it

*4.7
from 38 reviews
82%
13%
5%
0%
0%
  • Tung
    2 months ago

    .

  • Daanial
    3 months ago

  • Victor
    5 months ago

  • AMRANE
    6 months ago

  • Dorian
    6 months ago

    well work, it's a great lesson.

  • Vitalii
    7 months ago

Daanial

AMRANE

Vitalii

FAQs

Is this course suitable for beginners?

Yes, 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.

What topics will be covered in the course?

The course covers reading and plotting multivariate data, multivariate normal distributions, other multivariate distributions, and principal component analysis and multidimensional scaling.

Does this course provide a certificate?

Yes, you will receive a certificate of completion after finishing the course.

Who will benefit from this course?

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.

What techniques will I learn in this course?

You will learn how to read and summarize multivariate data, generate random samples from a multivariate normal distribution, calculate and plot densities and probabilities, test for multivariate normality, and implement techniques for analyzing high dimensional data.

Is a working knowledge of R necessary for this course?

Yes, a working knowledge of R is necessary for this course. If you are new to the R language, we suggest you take the "Introduction to R" and "Foundations of Probability in R" courses before starting this one.

Will I learn how to interpret results from multivariate distributions?

Yes, you will learn how to interpret results from multivariate distributions and visualize the resulting data.

Will I be able to work with real world datasets?

Yes, you will have the opportunity to work with real world datasets and practice your analytical skills.

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