ESBPDF Analysis - Probability Software 2.4.1

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ESBPDF Analysis - Probability Software Review

ESBPDF Analysis is Probability Analysis Software that provides everything needed for using Discrete and Continuous Probability Distributions in a single Windows application. Most Tables and supplied functions (such as in MS Excel) give P(X less than A) and using algebra other results can be found whereas ESBPDF Analysis is Probability Analysis Software that handles all the combinations for you.

Features include Binomial, Poisson, Hypergeometric, Normal, Exponential, Student t, Chi Squared, F, Beta and Lognormal Distributions; Inverses of Normal, Student t, Chi Squared, F, Beta and Lognormal Distributions; Lists of Binomial Coefficients, Factorials and Permutations; Calculations of Gamma and Beta Functions; Printing of Standard Normal Tables and Critical t Values; Fully Customisable; Integrated Help System which includes a Tutorial. We also plan on adding many more Distributions and features.

Also includes Graphing of Distributions, additional Information on Distributions and registered users also get Electronic Documentation and a PDF version of the documentation designed for printing.

Ideal for the Maths/Stats Student who wishes to understand Probability Distributions better, as well as the Maths Buff who wants a well designed calculating tool.

Designed for Windows and optimised for Windows XP.

ESBPDF Analysis - Probability Software 2.4.1 Information
ESBPDF Analysis - Probability Software Website	Download ESBPDF Analysis - Probability Software Sponsored Links
Version: 2.4.1
Size: 3.92 MB
Downloads: 60
Price: $29
Licence: Shareware
ESBPDF Analysis - Probability Software Screenshot
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OS: Win 95/98/Me/NT/2000/XP
Usage Info: 20 Executions
Un/Install: Install and Uninstall
Requirements: Win32 platform
Reference Keywords: analysis provides everything discrete continuous probability distributions application supplied functions analysis probability analysis software combinations features binomial hypergeometric exponential lognormal distributions inverses lognormal distribut

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