Applied statistics comprises descriptive statistics and the application of inferential statistics. Theoretical statistics considers the logical arguments underlying the justification of approaches to statistical inference, as well as encompassing mathematical statistics.
Machine learning models are statistical and probabilistic models that capture patterns in data through the use of computational algorithms.
The rapid and sustained increase in computing power starting from the second half of the 20th century has had a substantial impact on the practice of statistical science.
The computer revolution has implications for the future of statistics with a new emphasis on "experimental" and "empirical" statistics.
Statistics applies to a wide variety of academic disciplines, including natural and social sciences, government, and business.
The misuse of statistics can produce subtle but serious errors in description and interpretation—subtle in the sense that even experienced professionals can make such errors, and serious in the sense that they can lead to devastating mistakes in decision making.