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jamovi (stylised in all lower-case) is a free and open-source computer program for data analysis and performing statistical tests. The core developers of jamovi are Jonathon Love, Damian Dropmann, and Ravi Selker, who were developers for the JASP project.
MedCalc includes basic parametric and non-parametric statistical procedures and graphs such as descriptive statistics, ANOVA, Mann–Whitney test, Wilcoxon test, χ 2 test, correlation, linear as well as non-linear regression, logistic regression, and multivariate statistics. [5]
A simple arithmetic calculator was first included with Windows 1.0. [6]In Windows 3.0, a scientific mode was added, which included exponents and roots, logarithms, factorial-based functions, trigonometry (supports radian, degree and gradians angles), base conversions (2, 8, 10, 16), logic operations, statistical functions such as single variable statistics and linear regression.
In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the outcome or response variable, or a label in machine learning parlance) and one or more error-free independent variables (often called regressors, predictors, covariates, explanatory ...
Fityk – nonlinear regression software (GUI and command line) GNU Octave – programming language very similar to MATLAB with statistical features; gretl – gnu regression, econometrics and time-series library; intrinsic Noise Analyzer (iNA) – For analyzing intrinsic fluctuations in biochemical systems
G*Power is a free-to use software used to calculate statistical power. The program offers the ability to calculate power for a wide variety of statistical tests including t-tests , F-tests , and chi-square-tests , among others.
Vowpal Wabbit (VW) is an open-source fast online interactive machine learning system library and program developed originally at Yahoo! Research, and currently at Microsoft Research.
R 2 L is given by Cohen: [1] =. This is the most analogous index to the squared multiple correlations in linear regression. [3] It represents the proportional reduction in the deviance wherein the deviance is treated as a measure of variation analogous but not identical to the variance in linear regression analysis. [3]