1. Congratulations
Congratulations on finishing the course on Multivariate probability distributions in R!
2. Reading, summarizing and plotting multivariate data
In this course, you learned how to read different kinds of multivariate data and how to reformat the data before performing statistical analysis. You also learned to use summary statistics and plotting in multiple dimensions to analyze multivariate data.
You learned how to generate random samples from, and calculate the densities and probabilities of, four different multivariate probability distributions: the normal, t, skew-normal and skew-t.
This course also taught you about analytical and graphical techniques for dimension reduction, including principal component analysis, or PCA, and multidimensional scaling, or MDS, which enable you to analyze high-dimensional data.
3. What we have not covered
Although we covered several multivariate statistical distributions, we were not able to discuss the mathematical details and theoretical underpinnings of those distributions.
There is also a range of other continuous distributions, such as the Wishart Distribution and discrete multivariate distributions, which were not covered in this course.
In this course, we mainly focused on the implementation of PCA. Check out other DataCamp courses for more information about linear algebra in R and to learn more detail about PCA.
4. Congratulations!
Congratulations!