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Statistical significance

Index Statistical significance

In statistical hypothesis testing, a result has statistical significance when it is very unlikely to have occurred given the null hypothesis. [1]

48 relations: A/B testing, ABX test, Alternative hypothesis, American Statistical Association, Bayesian statistics, Clinical significance, Coefficient of determination, Conditional probability, Confidence interval, Data dredging, Deirdre McCloskey, Effect size, Egon Pearson, Experiment, Fisher's method, Genome-wide association study, Higgs boson, Human sex ratio, Independence (probability theory), Jerzy Neyman, John Arbuthnot, Look-elsewhere effect, Manufacturing, Multiple comparisons problem, Normal distribution, Null hypothesis, Observational study, One- and two-tailed tests, P-value, Particle physics, Pearson correlation coefficient, Philosophical Transactions of the Royal Society, Philosophical Transactions of the Royal Society A, Pierre-Simon Laplace, Power (statistics), Research question, Ronald Fisher, Sample (statistics), Sample size determination, Sampling distribution, Sampling error, Standard deviation, Statistical hypothesis testing, Statistical population, Stephen Ziliak, Texas sharpshooter fallacy, Type I and type II errors, University of Michigan Press.

A/B testing

In web analytics, A/B testing (bucket tests or split-run testing) is a randomized experiment with two variants, A and B. It includes application of statistical hypothesis testing or "two-sample hypothesis testing" as used in the field of statistics.

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ABX test

An ABX test is a method of comparing two choices of sensory stimuli to identify detectable differences between them.

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Alternative hypothesis

In statistical hypothesis testing, the alternative hypothesis (or maintained hypothesis or research hypothesis) and the null hypothesis are the two rival hypotheses which are compared by a statistical hypothesis test.

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American Statistical Association

The American Statistical Association (ASA) is the main professional organization for statisticians and related professionals in the United States.

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Bayesian statistics

Bayesian statistics, named for Thomas Bayes (1701–1761), is a theory in the field of statistics in which the evidence about the true state of the world is expressed in terms of degrees of belief known as Bayesian probabilities.

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Clinical significance

In medicine and psychology, clinical significance is the practical importance of a treatment effect—whether it has a real genuine, palpable, noticeable effect on daily life.

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Coefficient of determination

In statistics, the coefficient of determination, denoted R2 or r2 and pronounced "R squared", is the proportion of the variance in the dependent variable that is predictable from the independent variable(s).

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Conditional probability

In probability theory, conditional probability is a measure of the probability of an event (some particular situation occurring) given that (by assumption, presumption, assertion or evidence) another event has occurred.

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Confidence interval

In statistics, a confidence interval (CI) is a type of interval estimate, computed from the statistics of the observed data, that might contain the true value of an unknown population parameter.

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Data dredging

Data dredging (also data fishing, data snooping, and '''''p'''''-hacking) is the use of data mining to uncover patterns in data that can be presented as statistically significant, without first devising a specific hypothesis as to the underlying causality.

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Deirdre McCloskey

Deirdre Nansen McCloskey (born September 11, 1942), born Donald N. McCloskey, is the Distinguished Professor of Economics, History, English, and Communication at the University of Illinois at Chicago (UIC).

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Effect size

In statistics, an effect size is a quantitative measure of the magnitude of a phenomenon.

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Egon Pearson

Egon Sharpe Pearson, CBE FRS (11 August 1895 – 12 June 1980) was one of three children and the son of Karl Pearson and, like his father, a leading British statistician.

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An experiment is a procedure carried out to support, refute, or validate a hypothesis.

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Fisher's method

In statistics, Fisher's method, also known as Fisher's combined probability test, is a technique for data fusion or "meta-analysis" (analysis of analyses).

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Genome-wide association study

In genetics, a genome-wide association study (GWA study, or GWAS), also known as whole genome association study (WGA study, or WGAS), is an observational study of a genome-wide set of genetic variants in different individuals to see if any variant is associated with a trait.

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Higgs boson

The Higgs boson is an elementary particle in the Standard Model of particle physics.

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Human sex ratio

In anthropology and demography, the human sex ratio is the ratio of males to females in a population.

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Independence (probability theory)

In probability theory, two events are independent, statistically independent, or stochastically independent if the occurrence of one does not affect the probability of occurrence of the other.

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Jerzy Neyman

Jerzy Neyman (April 16, 1894 – August 5, 1981), born Jerzy Spława-Neyman, was a Polish mathematician and statistician who spent the first part of his professional career at various institutions in Warsaw, Poland and then at University College London, and the second part at the University of California, Berkeley.

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John Arbuthnot

John Arbuthnot (baptised 29 April 1667 – 27 February 1735), often known simply as Dr Arbuthnot, was a Scottish physician, satirist and polymath in London.

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Look-elsewhere effect

The look-elsewhere effect is a phenomenon in the statistical analysis of scientific experiments, particularly in complex particle physics experiments, where an apparently statistically significant observation may have actually arisen by chance because of the size of the parameter space to be searched.

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Manufacturing is the production of merchandise for use or sale using labour and machines, tools, chemical and biological processing, or formulation.

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Multiple comparisons problem

In statistics, the multiple comparisons, multiplicity or multiple testing problem occurs when one considers a set of statistical inferences simultaneously or infers a subset of parameters selected based on the observed values.

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Normal distribution

In probability theory, the normal (or Gaussian or Gauss or Laplace–Gauss) distribution is a very common continuous probability distribution.

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Null hypothesis

In inferential statistics, the term "null hypothesis" is a general statement or default position that there is no relationship between two measured phenomena, or no association among groups.

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Observational study

In fields such as epidemiology, social sciences, psychology and statistics, an observational study draws inferences from a sample to a population where the independent variable is not under the control of the researcher because of ethical concerns or logistical constraints.

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One- and two-tailed tests

In statistical significance testing, a one-tailed test and a two-tailed test are alternative ways of computing the statistical significance of a parameter inferred from a data set, in terms of a test statistic.

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In statistical hypothesis testing, the p-value or probability value or asymptotic significance is the probability for a given statistical model that, when the null hypothesis is true, the statistical summary (such as the sample mean difference between two compared groups) would be the same as or of greater magnitude than the actual observed results.

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Particle physics

Particle physics (also high energy physics) is the branch of physics that studies the nature of the particles that constitute matter and radiation.

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Pearson correlation coefficient

In statistics, the Pearson correlation coefficient (PCC, pronounced), also referred to as Pearson's r, the Pearson product-moment correlation coefficient (PPMCC) or the bivariate correlation, is a measure of the linear correlation between two variables X and Y. It has a value between +1 and −1, where 1 is total positive linear correlation, 0 is no linear correlation, and −1 is total negative linear correlation.

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Philosophical Transactions of the Royal Society

Philosophical Transactions, titled Philosophical Transactions of the Royal Society (often abbreviated as Phil. Trans.) from 1776, is a scientific journal published by the Royal Society.

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Philosophical Transactions of the Royal Society A

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences is a fortnightly peer-reviewed scientific journal published by the Royal Society.

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Pierre-Simon Laplace

Pierre-Simon, marquis de Laplace (23 March 1749 – 5 March 1827) was a French scholar whose work was important to the development of mathematics, statistics, physics and astronomy.

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Power (statistics)

The power of a binary hypothesis test is the probability that the test correctly rejects the null hypothesis (H0) when a specific alternative hypothesis (H1) is true.

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Research question

Specifying the research question is the methodological point of departure of scholarly research in both the natural and social sciences.

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Ronald Fisher

Sir Ronald Aylmer Fisher (17 February 1890 – 29 July 1962), who published as R. A. Fisher, was a British statistician and geneticist.

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Sample (statistics)

In statistics and quantitative research methodology, a data sample is a set of data collected and/or selected from a statistical population by a defined procedure.

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Sample size determination

Sample size determination is the act of choosing the number of observations or replicates to include in a statistical sample.

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Sampling distribution

In statistics, a sampling distribution or finite-sample distribution is the probability distribution of a given random-sample-based statistic.

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Sampling error

In statistics, sampling error is incurred when the statistical characteristics of a population are estimated from a subset, or sample, of that population.

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Standard deviation

In statistics, the standard deviation (SD, also represented by the Greek letter sigma σ or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values.

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Statistical hypothesis testing

A statistical hypothesis, sometimes called confirmatory data analysis, is a hypothesis that is testable on the basis of observing a process that is modeled via a set of random variables.

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Statistical population

In statistics, a population is a set of similar items or events which is of interest for some question or experiment.

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Stephen Ziliak

Stephen T. Ziliak (born October 17, 1963) is an American professor of economics whose research and essays span disciplines from statistics and beer brewing to medicine and poetry.

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Texas sharpshooter fallacy

The Texas sharpshooter fallacy is an informal fallacy which is committed when differences in data are ignored, but similarities are stressed.

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Type I and type II errors

In statistical hypothesis testing, a type I error is the rejection of a true null hypothesis (also known as a "false positive" finding), while a type II error is failing to reject a false null hypothesis (also known as a "false negative" finding).

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University of Michigan Press

The University of Michigan Press is part of Michigan Publishing at the University of Michigan Library.

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[1] https://en.wikipedia.org/wiki/Statistical_significance

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