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Everything about Normalization (statistics)
Statistical procedure
In statistics and applications of statistics, normalization can have a range of meanings. In the simplest cases, normalization of ratings means adjusting values measured on different scales to a notionally common scale, often prior to averaging. In more complicated cases, normalization may refer to more sophisticated adjustments where the intention is to bring the entire probability distributions of adjusted values into alignment. In the case of normalization of scores in educational assessment, there may be an intention to align distributions to a normal distribution. A different approach to normalization of probability distributions is quantile normalization, where the quantiles of the different measures are brought into alignment. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Normalization (statistics)A 5-minute orientation
- Skim a recent paper: Cluster-Instance Normalization: A Statistical Relation-Aware Normalization for Generalizable Person Re-IdentificationInfluential work since 2022
- Pick up a classic book: Level-Crossing Problems and Inverse Gaussian DistributionsThe most-reprinted book on the subject
- Read the landmark paper: The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis.Cited 4,277 times
- Go sideways: StudentizationA closely related topic
- Go sideways: Student's t-distributionA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis.
A Complete Color Normalization Approach to Histopathology Images Using Color Cues Computed From Saturation-Weighted Statistics
Processing of Data Generated by 2-Dimensional Gel Electrophoresis for Statistical Analysis: Missing Data, Normalization, and Statistics
Limit distributions of generalized order statistics under power normalization
Constraints on the Inner Cluster Mass Profile and the Power Spectrum Normalization from Strong Lensing Statistics
Effective and Efficient Batch Normalization Using a Few Uncorrelated Data for Statistics Estimation
Feature normalization based on non-extensive statistics for speech recognition
A case study on choosing normalization methods and test statistics for two‐channel microarray data
🆕 Influential since 2022
Cluster-Instance Normalization: A Statistical Relation-Aware Normalization for Generalizable Person Re-Identification
Adversarial Attacks and Batch Normalization: A Batch Statistics Perspective
A Simple Normalization Technique Using Window Statistics to Improve the Out-of-Distribution Generalization on Medical Images
HyNCF: A hybrid normalization strategy via feature statistics for collaborative filtering
Meta Affine Transformation: A Batch-Statistics-Free Adaptive Normalization Method for Robust Few-Shot Learning and Domain Adaptation
📚 Books worth reading
Level-Crossing Problems and Inverse Gaussian DistributionsVsevolod K. Malinovskii · 2021
Distributions of Test StatisticsA. M. Mathai · 1990- 📕Climatic guide for Seattle, Washington and adjacent Puget Sound areaUnited States. Weather Bureau · 1961
- 📕Climatic guide for New York City, New York and nearby areasUnited States. Weather Bureau · 1959
- 📕Climatic guide for Baltimore, MarylandUnited States. Weather Bureau · 1956
- 📕Climatic guide for Chicago, Illinois areaUnited States. Weather Bureau · 1962
- 📕Selected techniques of statistical analysis for scientific and industrial research, and production and management engineeringColumbia University · 1947
Testing for normalityHenry C. Thode · 2002
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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