In this case, the datasets library will be used, which contains the data that I am going to use in this practical case. The library is installed by default in R, so to load it use the command library. The data that I will use is the commonly known iris.

For this exercise I use the r dataset called mtcars to show how to use the Biplot in the Principal Components Analysis. Motor Trend Auto Road Testing Description The data was extracted from the 1974 American magazine Motor Trend and includes fuel consumption and 10 aspects of automobile design and performance for 32 cars (1973–74 models).

Another example of correspondence analysis with comments. Enjoy it

This is a simple example to show how correspondence analysis does.

With this exercise I learned about principal component analysis. I hope you find it easy to understand, like me.

I am very proud to share this case with you because this exercise taught me again to respect the rules. You can find many ways to use the dataset on Internet, I show someone this way of playing with them and the other did not have enough creativity to change it and made a copy. I believe in open culture and education and that one of the multiple ways to learn is by copying or learning by doing it. Lots of love.

In this exercise I post the steps to prepare the data. How to select the most suitable linear model and analyze it.

Estimating proportions and predicting future samples. In this case, I will show how to do a simple prediction.

This is the second part of the exercise **Beyesian inference**

This is a exercise to practice the Beyesian Inference. I hope it helps you understand theory a little more