Algebra, Calculus, Functions, Geometry, Staistics and Probability and Trigonometry.
The book is appropriately comprehensive, covering the basics as well as interesting and important applications of Bayesian methods.
Think Stats is an introduction to Probability and Statistics for Python programmers.
*Think Stats emphasizes simple techniques you can use to explore real data sets and answer interesting questions. The book presents a case study using data from the National Institutes of Health. Readers are encouraged to work on a project with real datasets.
*If you have basic skills in Python, you can use them to learn concepts in probability and statistics. Think Stats is based on a Python library for probability distributions (PMFs and CDFs). Many of the exercises use short programs to run experiments and help readers develop understanding.
These open-source mathematics homework problems are programmed for the WeBWorK mathematics platform and correspond to chapters in OpenStax Introductory Statistics. They were created through a Round Eight Textbook Transformation Grant.