The list of helpful broad references about Statistics is categorized as follows:
- Statistics books
- Statistical Software 
- Statistics online courses
- Statistics research papers

Statistics References

The marriage of Statistics, Computer Science, and Domin knowledge built Data Science.

Data science is interdisciplinary

A few of the common statistical paradoxes are:"

- Monty Hall's paradox 
- Berkson's paradox
- Simpson's paradox

Common statistical paradoxes

Probability is the branch of math concerned with the likelihood of an event occuring, or the likelihood that an event is true. 

Probability Theory

Bayesian statistics is an approach to inferential statistics where a researcher specifies the prior probability that the null hypothesis and alternative hypotheses are true before conducting a study. Once the study is conducted, the probabilities are updated based on the newly collected data. This approach offers a potential alternative to traditional null hypothesis testing by providing a logical framework for quantifying uncertainty using probability distributions.

Bayesian Statistics

Components of Statistical Analysis

Descriptive statistics are a set of quantitative techniques used to summarize, organize, and visually display the data collected from a research sample. Important examples include measures of central tendency (such as the mean, median, and mode), which describe average scores, and measures of dispersion (such as the range, standard deviation, and variance), which indicate how spread apart the scores are.

Descriptive Statistics

Statistics is the process of gathering, analyzing, and interpreting information in order to help people make decisions when faced with uncertainty.

University of Michigan - Ann Arbor

- Discrete mathematics
- Probability and statistics
- Mathematical software
- Information theory
- Mathematical analysis
- Continuous mathematics

Mathematics of computing in ACM Computing Classification

- Logic
- Math
- Statistics
- Information
- Computing Science

List of Formal Sciences

Illowsky, B., & Dean, S. (2013). Introductory Statistics. Houston, Texas: OpenStax.

PDF link: [d3bxy9euw4e147.cloudfront.net/oscms-prodcms/media/documents/IntroductoryStatistics-OP_LXn0jei.pdf](https://d3bxy9euw4e147.cloudfront.net/oscms-prodcms/media/documents/IntroductoryStatistics-OP_LXn0jei.pdf)
Online version: [openstax.org/books/introductory-statistics/pages/1-introduction](https://openstax.org/books/introductory-statistics/pages/1-introduction) 

Introductory Statistics

Statistics

The linear algebra necessary to further explain Machine Learning in our capacity, requires a basic understanding of 
- Linear Systems of Equations
- Linear Transformations
- Vector Spaces
- Orthogonality
- Eigenvalues


Linear Algebra

Information theory is the mathematical understanding of parameters and rules of transmitting and processing information through communication systems.

Information Theory

- Computation of transforms
- Computations in finite fields
- Computations on matrices
- Computations on polynomials
- Number-theoretic computations
- Interpolation
- Numerical differentiation
- Interval arithmetic
- Arbitrary-precision arithmetic
- Automatic differentiation
- Mesh generation
- Discretization

Numerical Analysis

The study of quantity (number theory), space (geometry), structure (algebra) and change (mathematical analysis)

Math

The science of analyzing, collecting, classifying, manipulating, storing, retrieving, moving, disseminating and protecting information.

Information Science

Computing sciences include the study of methods of statistical computation and its applications.

Computing Sciences

The interdisciplinary study of reasoning and the pursuit of truth.

Learn Before

Related

Learn After