Infostat is a statistical analysis software that meets the needs of analysis of a wide range of users. The software has evolved rapidly and is frequently updated. These updates not only have to do with the addition of new functionality but also to increased productivity and algorithms' efficiency. InfoStat also evolve to keep the pulse of new hardware and operating systems, allowing us to maintain the code updated and adapted to the incredibly dynamic computer industry. InfoStat covers a wide range of statistical applications, below is a summary of the techniques implemented:

Exploratory Analysis

Construction of cross-classification tables

Construction of frequency tables and calculation of goodness of fit statistics

Calculate confidence intervals for parametric and nonparametric statistical sampling classic

Calculation of power and sample size for the design of experiment

Analysis of samples obtained under basic sampling designs

Inference in one and two populations using parametric and nonparametric

Multiple comparisons (Fisher LSD, Duncan, Tukey, SNK, DGC, BSS, Scott & Knot, Bonferroni)

Contrasts

Simple

Multiple

Polynomial

Residuals and predicted

Studentized residuals

Jackniffe residuals

Partial residuals

Cook's distance

Leverage

Confidence and prediction bands

Forward

Backward

Stepwise

All possible models

User-specified models

Logistics

Logistics to shift

4P-L (4-parameter logistic

5P-L (logistics 5 parameters)

Gompertz

Gompertz to shift

Exponential

Monomolecular

Richard

Linear installments

General linear and mixed models

Logistic

Poisson

Probit

Pearson correlation coefficients, Spearman correlation,

Partial correlation coefficients

Path analysis

Principal component analysis

Principal coordinates analysis (multidimensional scaling)

Biplots

Generalized Procrustes

Canonical correlations

PLS

Linear discriminant

K nearest neighbors

Filtering attributes

Single linkage

Complete linkage

Aaverage linkage - UPGMA)

Centroid method

Weighted centroid method

Ward

Dendrograms and dendrograms

Kmeans

Kmeans for large samples

Dissimilarity and similarity matrix

Curves of sensitivity and specificity

Curves for positive and negative predictive value

ROC Curves

Survival curves of Kaplan-Meier

Control & chart attributes

Control variables diagrams

Pareto diagrams

Ability to process

Graphics continuous density functions and probability graphing calculator

Confidence Intervals

All possible samples

Sample from the empirical distribution

Resampling