## VisualStat Features

VisualStat is a comprehensive and versatile desktop statistics package that is simple for beginners, yet powerful enough for experts. It is designed for business, science, marketing, and education, with fully functional spreadsheet.

VisualStat is a major integrated development environment for R, allowing users to run R scripts and commands directly inside VisualStat. R output can be retrieved as native VisualStat output, and managed via highly flexible VisualStat containers. All VisualStat DataBook are manipulated as the R DataFrame, without any import/export procedure. Provides a platform-independent basic-statistics GUI (graphical user interface) for R, based on the many package.

VisualStat has a well-designed user interface with all its statistical and charting procedures easily selected from ribbon. Basic and frequently used commands can be shown continuously for instant access. With VisualStat DataBook, you can develop feature-rich database with an object-oriented, extensible set of classes to incorporate spreadsheet functionality into your set of data. VisualStat supports ODBC database connections.

As always with VisualStat, your reports are produced visually, and all details are commented. And you’ll be able to easily communicate them with others. All test results have an associated report which provides a short conclusion and other descriptions to assist in the interpretation.

### R Integration

- Full R Integration
- Support for R Cammands and Scripts
- Provides a GUI for the R programming language
- R users can access superior data management capabilities, which enable them to handle much larger data sets.
- VisualStat users gain access to many more statistical functions without learning the R programming language.

### Core Features

- Exceptionally easy to use
- Microsoft Office look and feel using Ribbon
- Project Manager, organizes analysis
- Includes all common statistical methods
- Clear, comprehensive Help system
- DataReport, report generator
- Full academic references and validation of functions
- Glossary of statistical terms
- Multiple language versions, English and French
- Methods and formulas used in calculations

### Data Import and Export

- DataBook (similar to Excel spreadsheet)
- Maximum DataSheet capacity is 1M columns by 1M rows
- Read and write Microsoft Excel files (2013/2010/2007 or 97-2003)
- Read and write XML files
- Import any common spreadsheet data
- Import text based data (formatted or plain)
- Read/write reports in portable rich text format (RTF) or HTML
- Read SPSS, Minitab; DBF, Stata, EpiInfo files
- Query databases with ODBC

### Data Management

- DataBook, multiple sheets, allows calculation like in Excel spreadsheet
- Headers with multiple columns and rows
- Multiple column types, including Currency, Date/Time, Number, Percent and Factor
- Over than 300 built-in functions
- Full localization support, with all regional options
- Auto DragAndDrop, Easy copy/paste with Microsoft Excel and others applications
- Categorization of continuous data
- Assign formulas to columns; columns update when data change
- Multiple Undo/Redo in the DataBook
- Data manipulation: merge, subset, sort, transpose, split, stack, unstack, code
- On-line algebraic calculator
- Apply user-defined functions/formulae to data in worksheet
- Sort in worksheet (like Excel) or as separate function
- Rotate/transpose blocks of data in worksheet
- Ranks and normal scores (van der Waerden, Blom and expected normal order)
- Combine or split data by group identifier or separate columns
- Transformations (many, including ladder of powers)
- Convert text to numbers, factors, ...

Categorise a continuous variable - Extract a subset of data by search rules

### Descriptive Statistics

- Univariate descriptive statistics (count, mean, standard deviation, standard error, confidence interval, skewness, kurtosis, median, quartiles, range and a user defined quantile, ...)
- Frequencies
- Tabulations and CrossTabs

### Chi-square Contingency Tables

- 2 by 2 with confidence interval for odds ratio or relative risk
- Pearson's Test
- Bowker's Test of Symmetry
- McNemar matched pairs (and k by k extension)
- Likelihood-Ratio Test
- Maxwell (agreement, equivalence)
- Mantel-Haenszel and Woolf with plots
- Generalised Cohrane-Mantel-Haenszel for R by C by K tables
- Goodness of fit

### Exact Tests on Counts

- Exact Binomial Test
- Proportions Test
- Fisher’s Exact Test
- Sign test
- Poisson rate or count confidence interval

### Distribution Functions

- Normal
- t
- Chi-Square
- Poisson
- Gamma
- Logistic
- F
- Beta
- Binomial
- Negative Binomial
- ... many other distribution functions

### Random Data

- Normal
- Uniform
- Gamma
- Pareto
- Exponential
- Poisson
- Binomial
- Lognormal
- Triangular
- ... many other random functions

### Parametric Methods

- Student's t tests for single, paired and unpaired samples
- Normal distribution (Z) tests
- Sign test for a single median and two medians (paired observations)
- F test, variance ratio test
- Shapiro-Wilk, Shapiro-Francia and Royston tests for (non) normality

### Regression and Correlation

- Simple linear regression and Pearson's correlation
- Multiple and General linear regression
- Influential data identification, residual diagnostics and plots
- Probit analysis (probit or logit)
- Logistic regression with confidence intervals
- Poisson regression, relative risk, incidence rate ratio
- Cox regression, proportional hazards, hazard ratio
- Confidence intervals for Kendall's and Spearman's rank correlations
- Repeated measures linear regression

### Analysis of Variance

- One way, Two way, Two way with repeats
- Multiple comparisons: Tukey(-Kramer), Dunnett, Neuman-Keuls, Scheffé and Bonferroni
- Homogeneity of variance
- Randomized Block
- Analysis of means

### Non-parametric Methods

- Mann-Whitney U-test for Independent-Samples
- Wilcoxon Signed Rank Test for Paired-Samples
- Kruskal-Wallis Rank Sum Test for Independent-Samples
- Kolmogorov-Smirnov Test, One and Two Sample
- Paired-Samples Sign Test
- Signed rank test, mean, two mean (paired observations)
- Wilcoxon's matched pairs
- Median test, and Extension
- Median test, two and k populations

### Multivariate Analysis

- Principal components analysis
- Cluster analysis
- Correspondence analysis
- Biplot for principal components and correspondence analysis