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RiskQ 4.2 for Mathematica

Available packages for statistics typically limit your flexibility. Many types of analyses are based on the "normality assumption" of data, yielding results that are comprehensive and easy to manage, but do not reflect realistic data characteristics. RiskQ puts you in control. Using theoretical distributions to represent your inputs, or input distributions based on your own empirical data—or combinations of theoretical and empirical inputs—you can build and manipulate probability distributions reflecting those inputs. You can also generate the corresponding distribution(s) representing uncertainty/variability in any arbitrary output function of random input variates, each represented by a corresponding input distribution that you specify or design. You can conduct and a range of customized parametric and nonparametric statistical tests. For field and experimental data that do not meet simple distributional assumptions (which you can test using RiskQ), the added capabilities RiskQ offers are critical to performing realistic data characterization and statistical analysis.

While RiskQ is a general tool for the analysis of probability and distributions, it can be applied in a variety of areas:
bulletExperimental Data Analysis
bulletPerform standard or weighted ANOVA, MANOVA, ANCOVA, and general linear-regression analysis
bulletAdjust p-values from multiple tests
bulletApply common parametric and nonparametric statistical tests
bulletCompare correlation matrices
bulletetc.
bulletToxicology & Environmental Chemistry
bulletConduct statistical tests on experimental toxicity or chemistry data
bulletCharacterize data variation graphically and analytically
bulletEpidemiology & Clinical Trials
bulletAnalyze associations exhibited by epidemiological data (counts, person-years, continuous variates), e.g., to test drug effectiveness or hypotheses concerning suspected environmental agents
bulletPerform adjusted chi-square tests of homogeneity and association
bulletObtain the approximate or exact likelihood of observed contingency-table data
bulletRisk and Uncertainty Analysis
bulletCharacterize distributions reflecting uncertainty or inter-individual variability of system inputs and/or output(s)
bulletPerform parametric and nonparametric sensitivity analysis
bulletAutomatically characterize the Monte-Carlo estimation error of any simulated output.

RiskQ supports numerous continuous and discontinuous probability distributions, including user-supplied empirical ones, which may be operated on by RiskQ functions. Additional RiskQ functions facilitate the characterization of uncertainty and discrete probability calculus. RiskQ also contains a variety of parametric and nonparametric statistical functions. Simulations can be done using Monte-Carlo, Latin-Hypercube, or Systematic Latin-Hypercube approaches to generating pseudorandom variates with any feasible, user-specified rank-correlation matrix. Graphical functions specifically designed to assist quantitative uncertainty analysis are also being developed. RiskQ’s “Data” function (unlike common “spreadsheet” applications) makes it easy to manipulate tabular data, using efficient, symbolic commands to sort data, merge data sets, merge dataset columns or rows, transform or add new data, and bin or classify data (i.e., combine data rows having unique values of one or more specified column variates, using user-specified rules to combine column data). Importantly, symbolically driven data manipulation using the RiskQ Data function can very easily draw on all of Mathematica’s high-powered mathematical functionality. A set of convenient plotting functions for data-fits and probability distribution functions is also included, as is online information about all RiskQ objects and functions.

Cost: RiskQ package for distributional statistics $300. Available for WIN, MAC, and Unix/Linux.

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e-mail: sales@exetersoftware.com
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1-631 339 4764, Toll-free within USA: 1-888-695-0285
FAX: 1-713-422-2361
47 Route 25A, Suite 2, Setauket, NY 11733-2870 USA
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