Useful Links

These are links to complementary materials to increase your knowledge on the several topics covered during the course.

Videos lectures

• Crash Course Statistics Playlist. This playlist contains many topics that are discussed in this course, described in a light and educational way. It is a great complimentary material.
• Crash Course Sociology: These two videos describe how the ideas of experimentalism and the scientific method apply to a completely different field. Many of these concepts also apply to some areas of computer science, such as Human Computer Interaction studies.
  • Sociology and the Scientific Method
  • Sociology Research Methods

Online Materials

• Understanding Science. This website holds a discussion of science as an interactive process closely tied with society.

• Design and Analysis of Experiments. Lecture notes by Felipe Campelo, sister course to this one.

• Applied Statistics Courses by Peter Hoff

• D.W. Stockburger, The Sampling Distribution. In: Introductory Statistics: Concepts, Models, and Applications. A more detailed look at the concept of “sampling distribution” from lecture 02.
• J.G. Ramírez, Statistical Intervals: Confidence, Prediction, Enclosure. In lecture 02 we learned about confidence interval. This text extends the discussion a bit by talking about other types of interval indicators.

Statistic Reviews By Whitley And Ball

A series of short articles that offer a good review of the topics discussed in this course.

• Review 1: Visualization – https://ccforum.biomedcentral.com/articles/10.1186/cc1455
• Review 2: Samples and Population – https://ccforum.biomedcentral.com/articles/10.1186/cc1473
• Review 3: Hypothesis Test – https://link.springer.com/article/10.1186/cc1493
• Review 4: Sample Sizes – https://link.springer.com/article/10.1186/cc1521
• Review 5: Comparison of Means – https://link.springer.com/article/10.1186/cc1548
• Review 6: Non-Parametric Methods – https://link.springer.com/article/10.1186/cc1820

R Programming Language

• R for beginners. An introduction to the R programming language, and its main characteristics.

• Rstudio. A graphical interface for R, very useful for writing, reading and executing R code.

• ggplot2. ggplot2 is a very powerful R library for creating beautiful plots from data. Much better than the native plotting functions in R.

Academic Materials

Others

• Existential Comics. Online comics about philosophy. Sometimes contain insightful discussions about the philosophy of science.