Description
Researchers, Scientists, Engineers, Students, Politicians, Economists, Political Analysts, Financial Analysts, Statisticians, and most of us the practitioners use statistics to answer questions or to support decision making that require data analysis. Statistics help to describe the results of, among others, investigations, experiments, and observations.
When data about the subject or object of interest is somewhat comprehensive, data analysis using descriptive statistics may be what is needed.
Unfortunately, in the world of statistics, things may not be that straightforward. The population of interest may not be fully observable or accessible. Hence, the statistician will have to make inference or, in statistics terms, appeal to inferential statistics. Inferential statistics involve statistical tests. One of the major issues facing statisticians and researchers is to choose which test to use. The choice involves first a decision between two families of test statistics: parametric and nonparametric. Then, a choice of specific statistical test must be made.
AroniSmartStat™ intends to help beginners, practitioners and most advanced statisticians and researchers to navigate this tricky step in learning, research, and interpretation and application of or action on results. To achieve these goals, AroniSmartStat™ is built around four modules that provide the four main benefits:
- The specific module of AroniSmartStat™ dedicated to Statistical tests offers an in-depth, user friendly and intuitive reference and selection tool that will facilitate the task, save time, while being rigorously thought out.
- The module dedicated to Probability Distribution is a user-friendly interface with most of the usual statistical distributions, their properties and their graphical representations.
- For researchers, advanced statisticians, students, and other users, the two remaining modules: Descriptive analysis and Statistical testing, help conduct descriptive analyses, conduct statistical analyses and test hypotheses on real or empirical data provided by the users themselves.
- .The graphing capability included in the tool will help to easily simulate distributions and to create histograms and scattergrams.
- Statisticians and users of statistics need a tool that can help refresh their memories and eventually provide the link needed to connect statistical concepts, while using it to solve real life problems. AroniSmartStat™ implements an approach to quickly understand statistical methods and at the same time conduct rigorous statistical researches, without writing any code.
- AroniSmartStat™ is self-contained. AroniSmartStat™ is a statistical software destined to be used by researchers, students, and practitioners.
AroniSmartStat™ is a cost effective tool, either in time, ease of use, access, or price. It is the best statistical reference and research tool for the busiest and savvy statistician and statistical practitioner and researcher.
Enjoy the world of Statistics with AroniSmartStat™
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What's New in Version 3.0.7
AroniSmartStat™ Version 3.0.7 is a major revision of one the most advanced statistical tools in the AroniSmart ™ series that includes AroniStat™, AroniSmartStat™ and AroniSmartIntelligence™.
AroniSmartStat ™ now addresses the needs of the most advanced researchers, business analysts, econometricians, students, teachers, political analysts, statisticians, and data miners and decision makers.
1) Descriptive Analysis, with ability to use own data, in CSV or the most versatile Aroni format; Consult the manual to see how Aroni format accommodates categorical, ordinal, and interval data, in string, date, and other formats.
2) Regression Analysis, including Mixed Effects models and multilevel modeling of hierarchical and longitudinal data model, generalized linear models, and the following Econometrics models:
- Count data: Poisson & Negative Binomial
- Tobit Regression
- Probit Regression
- Interval Regression
- Logit Regression
- Logistic Regression
- Weighted Least Squares Models
- Ordinal Least Squares Models
3) Segmentation, Clustering, Discriminant Analysis and Classification with Finite Mixture and General Mixture models;
4) Graphing capabilities (histograms, scattergrams, pie charts;
5) Editable Analysis outputs.
6) Improvement in several areas including stability, convergence algorithm, and optimization of statistical models
