Components of the Pearson-Fisher chi-squared statistic
نویسندگان
چکیده
منابع مشابه
Components of the Pearson-Fisher Chi-squared Statistic
The Pearson-Fisher chi-squared test can be used to evaluate the goodnessof-fit of categorized continuous data with known bin endpoints compared to a continuous distribution, in the presence of unknown (nuisance) distribution parameters. Rayner and McAlevey [11] and Rayner and Best [9],[10] demonstrate that in this case, component tests of the Pearson-Fisher chi-squared test statistic can be obt...
متن کاملComponents of the Pearson-Fisher chi-squared statistic
The Pearson-Fisher chi-squared test can be used to evaluate the goodnessof-fit of categorized continuous data with known bin endpoints compared to a continuous distribution, in the presence of unknown (nuisance) distribution parameters. Rayner and McAlevey [11] and Rayner and Best [9],[10] demonstrate that in this case, component tests of the Pearson-Fisher chi-squared test statistic can be obt...
متن کاملPearson-Fisher Chi-Square Statistic Revisited
The Chi-Square test (χ 2 test) is a family of tests based on a series of assumptions and is frequently used in the statistical analysis of experimental data. The aim of our paper was to present solutions to common problems when applying the Chi-square tests for testing goodness-of-fit, homogeneity and independence. The main characteristics of these three tests are presented along with various p...
متن کاملKarl Pearson and the Chi - squared Test
Karl Pearson was a man of many parts: the applied mathematician who completed Todhunter's History of the Theory of Elasticity; the philosopher of science whom Lenin described as 'this conscientious and honest opponent of materialism' (1970, p. 170); the statistician who espoused the cause of evolution and edited Biometrika for 35 years; the innovator and administrator whose Department became fa...
متن کاملJoint Bayesian Treatment of Poisson and Gaussian Experiments in a Chi-squared Statistic
Bayesian Poisson probability distributions for n̄ can be analytically converted into equivalent chi-squared distributions. These can then be combined with other Gaussian or Bayesian Poisson distributions to make a total chi-squared distribution. This allows the usual treatment of chi-squared contours but now with both Poisson and Gaussian statistics experiments. This is illustrated with the case...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Applied Mathematics and Decision Sciences
سال: 2002
ISSN: 1173-9126
DOI: 10.1155/s1173912602000172