Table of Contents
Logarithmic Scale
Return to Math, Data Science, Math for Data Science and DataOps, Math for Machine Learning and MLOps, Math for Programmers and Software Engineering, Outline of Mathematics, Outline of Discrete Mathematics, Outline of Probability, Math Bibliography
(BsTcMth 2017) (EsMthDS 2022) (MthPrg 2021)
- Snippet from Wikipedia: Logarithmic scale
A logarithmic scale (or log scale) is a method used to display numerical data that spans a broad range of values, especially when there are significant differences between the magnitudes of the numbers involved.
Unlike a linear scale where each unit of distance corresponds to the same increment, on a logarithmic scale each unit of length is a multiple of some base value raised to a power, and corresponds to the multiplication of the previous value in the scale by the base value. In common use, logarithmic scales are in base 10 (unless otherwise specified).
A logarithmic scale is nonlinear, and as such numbers with equal distance between them such as 1, 2, 3, 4, 5 are not equally spaced. Equally spaced values on a logarithmic scale have exponents that increment uniformly. Examples of equally spaced values are 10, 100, 1000, 10000, and 100000 (i.e., 101, 102, 103, 104, 105) and 2, 4, 8, 16, and 32 (i.e., 21, 22, 23, 24, 25).
Exponential growth curves are often depicted on a logarithmic scale graph.
Research It More
Fair Use Sources
Math: Outline of mathematics, Mathematics research, Mathematical anxiety, Pythagorean Theorem, Scientific Notation, Algebra (Pre-algebra, Elementary algebra, Abstract algebra, Linear algebra, Universal algebra), Arithmetic (Essence of arithmetic, Elementary arithmetic, Decimal arithmetic, Decimal point, numeral system, Place value, Face value), Applied mathematics, Binary operation, Classical mathematics, Control theory, Cryptography, Definitions of mathematics, Discrete mathematics (Outline of discrete mathematics, Combinatorics), Dynamical systems, Engineering mathematics, Financial mathematics, Fluid mechanics (Mathematical fluid dynamics), Foundations of mathematics, Fudge (Mathematical fudge, Renormalization), Game theory, Glossary of areas of mathematics, Graph theory, Graph operations, Information theory, Language of mathematics, Mathematical economics, Mathematical logic (Model theory, Proof theory, Set theory, Type theory, Recursion theory, Theory of Computation, List of logic symbols), Mathematical optimization, Mathematician, Modulo, Mathematical notation (List of logic symbols, Notation in probability and statistics, Physical constants, Mathematical alphanumeric symbols, ISO 31-11), Numerical analysis, Operations research, Philosophy of mathematics, Probability (Outline of probability), Statistics, Mathematical structure, Ternary operation, Unary operation, Variable (mathematics), Glossary, Bibliography (Math for Data Science and DataOps, Math for Machine Learning and MLOps, Math for Programmers and Software Engineering), Courses, Mathematics GitHub. (navbar_math - see also navbar_variables)
© 1994 - 2024 Cloud Monk Losang Jinpa or Fair Use. Disclaimers
SYI LU SENG E MU CHYWE YE. NAN. WEI LA YE. WEI LA YE. SA WA HE.