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Pages in category "Statistical paradoxes" The following 18 pages are in this category, out of 18 total. This list may not reflect recent changes. A. Abelson's paradox;
Simpson's paradox is a phenomenon in probability and statistics in which a trend appears in several groups of data but disappears or reverses when the groups are combined. This result is often encountered in social-science and medical-science statistics, [ 1 ] [ 2 ] [ 3 ] and is particularly problematic when frequency data are unduly given ...
Bertrand's box paradox: A paradox of conditional probability closely related to the Boy or Girl paradox. Bertrand's paradox: Different common-sense definitions of randomness give quite different results. Birthday paradox: In a random group of only 23 people, there is a better than 50/50 chance two of them have the same birthday.
Statistical tests are used to test the fit between a hypothesis and the data. [1] [2] Choosing the right statistical test is not a trivial task. [1] The choice of the test depends on many properties of the research question. The vast majority of studies can be addressed by 30 of the 100 or so statistical tests in use. [3] [4] [5]
Also confidence coefficient. A number indicating the probability that the confidence interval (range) captures the true population mean. For example, a confidence interval with a 95% confidence level has a 95% chance of capturing the population mean. Technically, this means that, if the experiment were repeated many times, 95% of the CIs computed at this level would contain the true population ...
Lord's Paradox and associated analyses provide a powerful teaching tool to understand these fundamental statistical concepts. More directly, Lord's Paradox may have implications for both education and health policies that attempt to reward educators or hospitals for the improvements that their children/patients made under their care, which is ...
Lindley's paradox is a counterintuitive situation in statistics in which the Bayesian and frequentist approaches to a hypothesis testing problem give different results for certain choices of the prior distribution.
Further, a foundation can be used to explain statistical paradoxes, provide descriptions of statistical laws, [1] and guide the application of statistics to real-world problems. Different statistical foundations may provide different, contrasting perspectives on the analysis and interpretation of data, and some of these contrasts have been ...