Chapter 4: But what do the nuns think?

The last case study in this course uses an extensive survey of Catholic nuns fielded in 1967 to once more put your practical machine learning skills to use. You will predict the age of these religious women from their responses about their beliefs and attitudes.

1Surveying Catholic sisters in 1967

2Choosing an appropriate model

3Visualizing the age distribution

4Tidying the survey data

5Exploratory data analysis with tidy data

6Visualizing agreement with age

7Building a simple linear model

8Training, validation, and testing data

9Using your validation set

10Predicting age with supervised machine learning

11Training, validation, and testing data

12Making predictions

13Choosing between models

14Estimating uncertainty for new data

15Wrapping up

About this course

This is a free, open source course on supervised machine learning in R using the caret package. In this course, you'll work through four case studies and practice skills from exploratory data analysis through model evaluation. Ines Montani designed the web framework that runs this course, and Florencia D'Andrea helped build the site.

Contributions and comments on how to improve this course are welcome! Please file an issue or submit a pull request if you find something that could be fixed or improved.

Creative Commons License

About me

My name is Julia Silge and I'm a data scientist and software engineer at RStudio where I build modeling tools. I am both an international keynote speaker and a real-world practitioner focused on data analysis and machine learning practice. I love making beautiful charts and communicating about technical topics with diverse audiences.