- Reworked engine for complicated interactive reports
- New objects for custom designs of all types of documents
- Even more exports that approach WYSIWYG in export of complicated objects
- Easier template design: guidelines and extended script debugger in designer
WebCab Probability and Stat for .NET v.3.3
By Ben Fairfax.18 Feb 2005
DescriptionThis suite consists of five packages: Statistics, Discrete Probability, Standard Probability Distributions, Hypothesis Testing, and Correlation & Regression which offer the following functionality.
- The 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).
- The 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.
- 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.
- This module assists in the development of applications that incorporate the Binomial, Poisson, Normal, Lognormal, Pareto, Uniform, Hypergeometric, Weibull and Exponential probability distributions. The probability density function, cumulative distribution function and inverse, mean, variance, Skewness and Kurtosis are implemented where appropriate and/or their approximations for each distribution. We also offer methods which randomly generate numbers from a given distribution.
- Within this component we present two aspects of inferential statistics known as confidence intervals and hypothesis testing. Confidence intervals determine the level of confidence in pointwise statistics (e.g. mean, variance) of the sample in relation to the statistics for the entire population. With hypothesis testing the user can judge which of several hypotheses sampled evidence best supports.
- Status: Evaluation (time-limit)
- Source: N/A
- price: $179
- Exe demo: included
- Size: 6 039kB
Platforms: C#, VC++