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JASP
JASP (Harold Jeffreys, Jeffreys’s Amazing Statistics Program) is a free and open-source program for Statistics, statistical analysis supported by the University of Amsterdam. It is designed to be easy to use, and familiar to users of SPSS. It offers standard analysis procedures in both their classical and Bayesian statistics, Bayesian form. JASP generally produces APA style results tables and plots to ease publication. It promotes open science via integration with the Open Science Framework and reproducibility by integrating the analysis settings into the results. The development of JASP is financially supported by sponsors several universities and research funds. Analyses JASP offers frequentist inference and Bayesian inference on the same statistical models. Frequentist inference uses p-values and confidence intervals to control error rates in the limit of infinite perfect replications. Bayesian inference uses credible intervals and Bayes factors to estimate credible parame ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
JASP 0
JASP (Jeffreys’s Amazing Statistics Program) is a free and open-source program for statistical analysis supported by the University of Amsterdam. It is designed to be easy to use, and familiar to users of SPSS. It offers standard analysis procedures in both their classical and Bayesian form. JASP generally produces APA style results tables and plots to ease publication. It promotes open science via integration with the Open Science Framework and reproducibility by integrating the analysis settings into the results. The development of JASP is financially supported by sponsors several universities and research funds. Analyses JASP offers frequentist inference and Bayesian inference on the same statistical models. Frequentist inference uses p-values and confidence intervals to control error rates in the limit of infinite perfect replications. Bayesian inference uses credible intervals and Bayes factors to estimate credible parameter values and model evidence given the availabl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
R (programming Language)
R is a programming language for statistical computing and Data and information visualization, data visualization. It has been widely adopted in the fields of data mining, bioinformatics, data analysis, and data science. The core R language is extended by a large number of R package, software packages, which contain Reusability, reusable code, documentation, and sample data. Some of the most popular R packages are in the tidyverse collection, which enhances functionality for visualizing, transforming, and modelling data, as well as improves the ease of programming (according to the authors and users). R is free and open-source software distributed under the GNU General Public License. The language is implemented primarily in C (programming language), C, Fortran, and Self-hosting (compilers), R itself. Preprocessor, Precompiled executables are available for the major operating systems (including Linux, MacOS, and Microsoft Windows). Its core is an interpreted language with a na ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
SPSS
SPSS Statistics is a statistical software suite developed by IBM for data management, advanced analytics, multivariate analysis, business intelligence, and criminal investigation. Long produced by SPSS Inc., it was acquired by IBM in 2009. Versions of the software released since 2015 have the brand name IBM SPSS Statistics. The software name originally stood for Statistical Package for the Social Sciences (SPSS), reflecting the original market, then later changed to Statistical Product and Service Solutions. Overview SPSS is a widely used program for statistics, statistical analysis in social science. It is also used by market researchers, health researchers, survey companies, government, education researchers, industries, marketing organizations, data miners, and others. The original SPSS manual (Nie, Bent & Hull, 1970) has been described as one of "sociology's most influential books" for allowing ordinary researchers to do their own statistical analysis. In addition to statist ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
LaTeX
Latex is an emulsion (stable dispersion) of polymer microparticles in water. Latices are found in nature, but synthetic latices are common as well. In nature, latex is found as a wikt:milky, milky fluid, which is present in 10% of all flowering plants (angiosperms) and in some Mushroom, mushrooms (especially species of ''Lactarius''). It is a complex emulsion that coagulation, coagulates on exposure to air, consisting of proteins, alkaloids, starches, sugars, Vegetable oil, oils, tannins, resins, and Natural gum, gums. It is usually exuded after tissue injury. In most plants, latex is white, but some have yellow, orange, or scarlet latex. Since the 17th century, latex has been used as a term for the fluid substance in plants, deriving from the Latin word for "liquid". It serves mainly as Antipredator adaptation, defense against Herbivore, herbivores and Fungivore, fungivores.Taskirawati, I. and Tuno, N., 2016Fungal defense against mycophagy in milk caps ''Science Report Kanazaw ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Levene's Test
In statistics, Levene's test is an inferential statistic used to assess the equality of variances for a variable calculated for two or more groups. This test is used because some common statistical procedures assume that variances of the populations from which different samples are drawn are equal. Levene's test assesses this assumption. It tests the null hypothesis that the population variances are equal (called ''homogeneity of variance'' or ''homoscedasticity''). If the resulting ''p''-value of Levene's test is less than some significance level (typically 0.05), the obtained differences in sample variances are unlikely to have occurred based on random sampling from a population with equal variances. Thus, the null hypothesis of equal variances is rejected and it is concluded that there is a difference between the variances in the population. Levene's test has been used in the past before a comparison of means to inform the decision on whether to use a pooled t-test or the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bayes Factors
The Bayes factor is a ratio of two competing statistical models represented by their marginal likelihood, evidence, and is used to quantify the support for one model over the other. The models in question can have a common set of parameters, such as a null hypothesis and an alternative, but this is not necessary; for instance, it could also be a non-linear model compared to its linear approximation. The Bayes factor can be thought of as a Bayesian analog to the likelihood-ratio test, although it uses the integrated (i.e., marginal) likelihood rather than the maximized likelihood. As such, both quantities only coincide under simple hypotheses (e.g., two specific parameter values). Also, in contrast with null hypothesis significance testing, Bayes factors support evaluation of evidence ''in favor'' of a null hypothesis, rather than only allowing the null to be rejected or not rejected. Although conceptually simple, the computation of the Bayes factor can be challenging depending on ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Credible Intervals
In Bayesian statistics, a credible interval is an interval used to characterize a probability distribution. It is defined such that an unobserved parameter value has a particular probability \gamma to fall within it. For example, in an experiment that determines the distribution of possible values of the parameter \mu, if the probability that \mu lies between 35 and 45 is \gamma=0.95, then 35 \le \mu \le 45 is a 95% credible interval. Credible intervals are typically used to characterize posterior probability distributions or predictive probability distributions. Their generalization to disconnected or multivariate sets is called credible set or credible region. Credible intervals are a Bayesian analog to confidence intervals in frequentist statistics. The two concepts arise from different philosophies: Bayesian intervals treat their bounds as fixed and the estimated parameter as a random variable, whereas frequentist confidence intervals treat their bounds as random varia ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Reproducibility
Reproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method. For the findings of a study to be reproducible means that results obtained by an experiment or an observational study or in a statistical analysis of a data set should be achieved again with a high degree of reliability when the study is replicated. There are different kinds of replication but typically replication studies involve different researchers using the same methodology. Only after one or several such successful replications should a result be recognized as scientific knowledge. History The first to stress the importance of reproducibility in science was the Anglo-Irish chemist Robert Boyle, in England in the 17th century. Boyle's air pump was designed to generate and study vacuum, which at the time was a very controversial concept. Indeed, distinguished philosophers such as René Descartes and Thomas Hobbes denied the very possibility of vacuum ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Shapiro–Wilk Test
The Shapiro–Wilk test is a Normality test, test of normality. It was published in 1965 by Samuel Sanford Shapiro and Martin Wilk. Theory The Shapiro–Wilk test tests the null hypothesis that a statistical sample, sample ''x''1, ..., ''x''''n'' came from a normal distribution, normally distributed population. The test statistic is W = \frac, where * x_ with parentheses enclosing the subscript index ''i'' is the ''i''th order statistic, i.e., the ''i''th-smallest number in the sample (not to be confused with x_i). * \overline = \left( x_1 + \cdots + x_n \right) / n is the sample mean. The coefficients a_i are given by: p. 593 (a_1,\dots,a_n) = , where ''C'' is a vector norm: C = \left\, V^ m \right\, = ^ and the vector ''m'', m = (m_1,\dots,m_n)^ is made of the expected values of the order statistics of independent and identically distributed random variables sampled from the standard normal distribution; finally, V is the covariance matrix of those normal order statis ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
