Editing Log-normal distribution (section)

=== Technology ===
* In [[Reliability (statistics)|reliability]] analysis, the log-normal distribution is often used to model times to repair a maintainable system.<ref>{{cite book | last1 = O'Connor | first1 = Patrick | last2 = Kleyner | first2 = Andre | year = 2011 | title = Practical Reliability Engineering | publisher = John Wiley & Sons | isbn = 978-0-470-97982-2 | page = 35 }}</ref>
* In [[wireless communication]], "the local-mean power expressed in logarithmic values, such as dB or neper, has a normal (i.e., Gaussian) distribution."<ref>{{cite web | title = Shadowing | website = www.WirelessCommunication.NL | url = http://wireless.per.nl/reference/chaptr03/shadow/shadow.htm |url-status = dead | archive-url = https://web.archive.org/web/20120113201345/http://wireless.per.nl/reference/chaptr03/shadow/shadow.htm | archive-date = January 13, 2012 }}</ref> Also, the random obstruction of radio signals due to large buildings and hills, called [[Fading|shadowing]], is often modeled as a log-normal distribution.
* Particle size distributions produced by comminution with random impacts, such as in [[ball mill]]ing.<ref>{{Cite journal | last1 = Dexter | first1 = A. R. | last2 = Tanner | first2 = D. W. | date = July 1972 | title = Packing Densities of Mixtures of Spheres with Log-normal Size Distributions | url = https://www.nature.com/articles/physci238031a0 | journal = Nature Physical Science | language = en | volume = 238 | issue = 80 | pages = 31–32 | doi = 10.1038/physci238031a0 | bibcode = 1972NPhS..238...31D | issn = 2058-1106}}</ref>
* The [[file size]] distribution of publicly available audio and video data files ([[MIME types]]) follows a log-normal distribution over five [[orders of magnitude]].<ref>
{{cite journal | last1 = Gros | first1 = C | last2 = Kaczor | first2 = G. | last3 = Markovic | first3 = D | title = Neuropsychological constraints to human data production on a global scale | journal = The European Physical Journal B | year = 2012 | volume = 85 | issue = 28 | pages = 28 | doi = 10.1140/epjb/e2011-20581-3 | arxiv = 1111.6849 | bibcode = 2012EPJB...85...28G | s2cid = 17404692 }}</ref>
* File sizes of 140 million files on personal computers running the Windows OS, collected in 1999.<ref>{{Cite journal | last1 = Douceur | first1 = John R. | last2 = Bolosky | first2 = William J. | date = 1999-05-01 | title = A large-scale study of file-system contents | journal = ACM SIGMETRICS Performance Evaluation Review | volume = 27 | issue = 1 | pages = 59–70 | doi = 10.1145/301464.301480 | issn = 0163-5999 | doi-access = free }}</ref><ref name=":3" />
* Sizes of text-based emails (1990s) and multimedia-based emails (2000s).<ref name=":3" />
* In computer networks and [[Internet traffic]] analysis, log-normal is shown as a good statistical model to represent the amount of traffic per unit time. This has been shown by applying a robust statistical approach on a large groups of real Internet traces. In this context, the log-normal distribution has shown a good performance in two main use cases: (1) predicting the proportion of time traffic will exceed a given level (for service level agreement or link capacity estimation) i.e. link dimensioning based on bandwidth provisioning and (2) predicting 95th percentile pricing.<ref>{{cite arXiv | last1 = Alamsar | first1 = Mohammed | last2 = Parisis | first2 = George | last3 = Clegg | first3 = Richard | last4 = Zakhleniuk | first4 = Nickolay | year = 2019 | title = On the Distribution of Traffic Volumes in the Internet and its Implications | eprint = 1902.03853 | class = cs.NI }}</ref>
* in [[physical test]]ing when the test produces a time-to-failure of an item under specified conditions, the data is often best analyzed using a lognormal distribution.<ref>ASTM D3654, Standard Test Method for Shear Adhesion on Pressure-Sensitive Tapesw</ref><ref>ASTM D4577, Standard Test Method for Compression Resistance of a container Under Constant Load>\</ref>