Chi-square, Student and Fisher-Snedecor Statistical Distributions and Their Application

The Chi-square distribution is the distribution of the sum of squared standard normal deviates. The degree of freedom of the distribution is equal to the number of standard normal deviates being summed. For the first time this distribution was studied by astronomer F. Helmert in connection with Gaus...

Full description

Bibliographic Details
Main Author: F. V. Motsnyi
Format: Article
Language:English
Published: State Statistics Service of Ukraine, the National Academy of Statistics, Accounting and Audit (NASAA), the National Academy for Public Administration (NAPA) under the President of Ukraine 2018-07-01
Series:Статистика України
Subjects:
Online Access:https://su-journal.com.ua/index.php/journal/article/view/167
id doaj-05be0a21cddf44f9b66e57146c81461e
record_format Article
spelling doaj-05be0a21cddf44f9b66e57146c81461e2020-11-25T02:38:29ZengState Statistics Service of Ukraine, the National Academy of Statistics, Accounting and Audit (NASAA), the National Academy for Public Administration (NAPA) under the President of UkraineСтатистика України 2519-18532519-18612018-07-01801162310.31767/su.1(80).2018.01.02167Chi-square, Student and Fisher-Snedecor Statistical Distributions and Their ApplicationF. V. Motsnyi0National Academy of Statistics, Accounting and AuditThe Chi-square distribution is the distribution of the sum of squared standard normal deviates. The degree of freedom of the distribution is equal to the number of standard normal deviates being summed. For the first time this distribution was studied by astronomer F. Helmert in connection with Gaussian low of errors in 1876. Later K. Pearson named this function by Chi-square. Therefore Chi –square distribution bears a name of Pearson’s distribution. The Student's t-distribution is any member of a family of continuous probability distributions that arises when estimating the mean of a normally distributed population in situations where the sample size is small and population standard deviation is unknown. It was developed by W. Gosset in 1908. The Fisher–Snedecor distribution or F-distribution is the ratio of two-chi-squared variates. The F-distribution provides a basis for comparing the ratios of subsetsof these variances associated with different factors. The Fisher-distribution in the analysis of variance is connected with the name of R.Fisher (1924), although Fisher himself used quantity for the dispersion proportion. The Chi-square, Student and Fisher – Snedecor statistical distributions are connected enough tight with normal one. Therefore these distributions are used very extensively in mathematical statistics for interpretation of empirical data. The paper continues ideas of the author’s works [15, 16] devoted to advanced based tools of mathematical statistics. The aim of the work is to generalize the well known theoretical and experimental results of statistical distributions of random values. The Chi-square, Student and Fisher – Snedecor distributions are analyzed from the only point of view. The application peculiarities are determined at the examination of the agree criteria of the empirical sample one with theoretical predictions of general population. The numerical characteristics of these distributions are considered. The theoretical and experimental results are generalized. It is emphasized for the corrected amplification of the Chi-square, Student and Fisher – Snedecor distributions it is necessary to have the reliable empirical and testing data with the normal distribution.https://su-journal.com.ua/index.php/journal/article/view/167sample, general population, random value, the chi-square distribution, student distribution, fisher – snedecor distribution, ‎numerical characteristics. ‎
collection DOAJ
language English
format Article
sources DOAJ
author F. V. Motsnyi
spellingShingle F. V. Motsnyi
Chi-square, Student and Fisher-Snedecor Statistical Distributions and Their Application
Статистика України
sample, general population, random value, the chi-square distribution, student distribution, fisher – snedecor distribution, ‎numerical characteristics. ‎
author_facet F. V. Motsnyi
author_sort F. V. Motsnyi
title Chi-square, Student and Fisher-Snedecor Statistical Distributions and Their Application
title_short Chi-square, Student and Fisher-Snedecor Statistical Distributions and Their Application
title_full Chi-square, Student and Fisher-Snedecor Statistical Distributions and Their Application
title_fullStr Chi-square, Student and Fisher-Snedecor Statistical Distributions and Their Application
title_full_unstemmed Chi-square, Student and Fisher-Snedecor Statistical Distributions and Their Application
title_sort chi-square, student and fisher-snedecor statistical distributions and their application
publisher State Statistics Service of Ukraine, the National Academy of Statistics, Accounting and Audit (NASAA), the National Academy for Public Administration (NAPA) under the President of Ukraine
series Статистика України
issn 2519-1853
2519-1861
publishDate 2018-07-01
description The Chi-square distribution is the distribution of the sum of squared standard normal deviates. The degree of freedom of the distribution is equal to the number of standard normal deviates being summed. For the first time this distribution was studied by astronomer F. Helmert in connection with Gaussian low of errors in 1876. Later K. Pearson named this function by Chi-square. Therefore Chi –square distribution bears a name of Pearson’s distribution. The Student's t-distribution is any member of a family of continuous probability distributions that arises when estimating the mean of a normally distributed population in situations where the sample size is small and population standard deviation is unknown. It was developed by W. Gosset in 1908. The Fisher–Snedecor distribution or F-distribution is the ratio of two-chi-squared variates. The F-distribution provides a basis for comparing the ratios of subsetsof these variances associated with different factors. The Fisher-distribution in the analysis of variance is connected with the name of R.Fisher (1924), although Fisher himself used quantity for the dispersion proportion. The Chi-square, Student and Fisher – Snedecor statistical distributions are connected enough tight with normal one. Therefore these distributions are used very extensively in mathematical statistics for interpretation of empirical data. The paper continues ideas of the author’s works [15, 16] devoted to advanced based tools of mathematical statistics. The aim of the work is to generalize the well known theoretical and experimental results of statistical distributions of random values. The Chi-square, Student and Fisher – Snedecor distributions are analyzed from the only point of view. The application peculiarities are determined at the examination of the agree criteria of the empirical sample one with theoretical predictions of general population. The numerical characteristics of these distributions are considered. The theoretical and experimental results are generalized. It is emphasized for the corrected amplification of the Chi-square, Student and Fisher – Snedecor distributions it is necessary to have the reliable empirical and testing data with the normal distribution.
topic sample, general population, random value, the chi-square distribution, student distribution, fisher – snedecor distribution, ‎numerical characteristics. ‎
url https://su-journal.com.ua/index.php/journal/article/view/167
work_keys_str_mv AT fvmotsnyi chisquarestudentandfishersnedecorstatisticaldistributionsandtheirapplication
_version_ 1724790562822815744