Everything about Normal distribution
Probability distribution
In probability theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is The parameter is the mean or expectation of the distribution, while the parameter is the variance. The standard deviation of the distribution is the positive value (sigma). A random variable with a Gaussian distribution is said to be normally distributed and is called a normal deviate. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Normal distributionA 5-minute orientation
- Skim a recent paper: Data Distribution: Normal or Abnormal?Influential work since 2022
- Pick up a classic book: Stable Non-Gaussian Random ProcessesThe most-reprinted book on the subject
- Read the landmark paper: Statistical notes for clinical researchers: assessing normal distribution (2) using skewness and kurtosisCited 3,539 times
- Go sideways: Chi distributionA closely related topic
- Go sideways: Central limit theoremA closely related topic
📖 Definitions
Noun Any of a family of continuous probability distributions such that the probability density function is the Gaussian function
🏆 Landmark papers (most cited)
Statistical notes for clinical researchers: assessing normal distribution (2) using skewness and kurtosis
A generalized normal distribution
The Folded Normal Distribution
The Discrete Normal Distribution
Normal Distribution
Approximate skew normal distribution
Alpha-skew-normal distribution
Evaluating the Normal Distribution
🆕 Influential since 2022
📚 Books worth reading
- 📕Stable Non-Gaussian Random ProcessesGennady Samoradnitsky · 2017
Level-Crossing Problems and Inverse Gaussian DistributionsVsevolod K. Malinovskii · 2021- 📕Quasi-linear regime of gravitational instability as a clue to understanding the large-scale structure in the UniverseSergei F. Shandarin · 1992
Models for repeated measurementsJames K. Lindsey · 1993
Distributions of Test StatisticsA. M. Mathai · 1990
Lower confidence limit expressions for P(X>y) and P(X>Y) under normalityW. Max Woods · 1991
The multivariate normal distributionYung Liang Tong · 1990
Testing for normalityHenry C. Thode · 2002
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
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