WebCab Probability and Stat for. NET V3.6

WebCab Probability and Stat for. NET 3.6

WebCab Probability and Stat for. NET 3.6

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Free Download WebCab Probability and Stat for. NET 3.6

Add Statistics, Discrete Probability, Standard Probability Distributions, Hypothesis Testing, Correlation and Linear Regression functionality to your. NET, COM, and XML Web service Applications. ..

WebCab Probability and Stat for. NET 3.6 Description

" WebCab Probability and Stat for. NET : Add Statistics, Discrete Probability, Standard Probability Distributions, Hypothesis Testing, Correlation and Linear Regression functionality to your. NET, COM, and XML Web service Applications. . "

Edit By 008tools.com Editor: WebCab Probability and Stat for. NET - Add Statistics, Discrete Probability, Standard Probability Distributions, Hypothesis Testing, Correlation and Linear Regression functionality to your. NET, COM, and XML Web service Applications.

Statistics Module
Incorporates topic from data presentation ( incl. standard, relative and cumulative frequency tables ), Basic Statistics ( incl. measure of centrality, dispersion and relative location ) and Grouped Data ( incl. Sample Mean, Variance and Standard Deviation

Discrete Probability Module
Encapsulates the probabilistic study of finite set of events ( i. e. discrete probability ) and experiments with a finite number of outcomes ( i. e. discrete random variables ). Including: probability measures, union / intersection law, conditionals / complementary probability; cumulative distribution functions, mean / variance / expected return of Random Variable.

Correlation and Regression Module
Allows the user to investigate relationships between two variables. These finding can be used to predict one variable from the given values of other variables. We cover linear ( Spearman' s, t-test, z-transform ) and rank ( Spearman' s, Kendall' s ) correlation, linear regression and conditional means.

Standard Probability Distributions Module
This module assists in the development of applications that incorporate the Binomial, Poisson, Normal, Lognormal, Pareto, Uniform, Hypergeometric, Weibull and Exponential probability distributions. The PDF, CPDF and inverse, mean, variance, Skewness and Kurtosis, random number generators are implemented where appropriate and / or their approximations.

Curve Fitting Module The Curve Fitting module offers procedures by which linear and non-linear functions can be fitted in accordance with the least squares approach to a given data set which may or may not exhibit measurement errors. We also include functionality which performs ANNOVA type analysis including goodness-of-fit measures such as the R-Squared measure and T-Test statistic.

Confidence Intervals and Hypothesis

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