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About Action

A statistical software developed for you, easy to use and reliable. The software Action was developed under the R platform, one of the most used statistics systems around the world.

System Action represents a major evolution in relation to statistical softwares:

  •  It allows you to work with Excel in an integrated way;
  •  It is easy to install, creative and covers the main needs of the statistics user;
  •  Is becoming more intuitive, easier to use than ever, with a lot of features;

You can download the System Action without any costs and can use it for any purpose – in private companies with or without profitable endings, schools, government and general public administration. You can pass copies to your relatives, friends, students, employees, etc. Help to disseminate System Action!

 

What is important about the System Action?

System Action is an open and democratic system to use statistics;

  • No business license or software compatibility issues to worry about;
  • No language barrier – is available in Portuguese and English;
  • First system that user statistical platform R and Excel in an integrated manner, all to facilitate and expedite your statistical analysis;

 

Sistem Action is synonymous of quality:

  • Its roots go back about 10 years, resulting in great experience; 
  • All statistical analysis are based on the platform R, the world’s fastest growing statistical system, which is the official system of most statistician and technology companies; 
  • We currently have thousands of users from different branches of industy, government and universities; 
  • With a fully open development process, the system Action has nothing to hide – the product is maintained due to the efforts and reputation of Estatcamp Tean in the scenario of Brazilian statistics; 

 

Action is friendly

  • The program looks and behaves family and can be use immediately by anyone who has used a competing product;
  • It is easy to change to the System Action, it behaves as an Excel add-in and has a detailed manual describing all the features;
  • Action is supported by Estatcamp and a community volunteer with extensive experience in Statiscs and Computing, willing to help both new users as the more experienced;

 

What is in Action?

Basic Statistics: Includes the basic tools of exploratory data analysis, frequency distributions and tests of mean, variance, proportions and rates. Beyond normality tests;

Distributions: For major discrete and continuous distributions of probability, we calculate the quantiles, percentiles, density, and also generate random samples;

ANOVA: This module introduces the main tools for the comparison of factors in the performance of products and services. We have the ANOVA model with fixed, mixed and random effects, the classical methods of multiple comparisons (Tukey, Fisher, Dunnet and HSU tests) and the variance tests (Levene and Bartlet). We also have several charts (Main Effects, Interactions and Confidence Intervals charts) that simplity your analysis and diagnosis. Finally, we have the Welch test, where the do not show honogeneity of variance and nonparametric Kruskal-Wallis test for the case where the assumption of data normality is violated.

Models: The main tools of linear and generalized linear models are covered in this module. In this module, we performed linear regression and nonlinear regression, binomial and multinomial regression. Also, we have several charts to facilitate the analysis.

Nonparametric: The main nonparametric techniques to data analysis are available in this module. Among then, we have the Wilcoxon and Kruskal-Wallis test.

Charts: A variety of charts are available in this module. We have the traditional histogram, boxplot, Pareto, dotplot and 3D charts. Everything to make your presentation dynamic, easy and understandable.

Reliability: The main techniques of reliability and survival analysis are available in this module. From simple techniques such as adjustement of the Weibull distribution and the Kaplan-Meier techniques to accelerated life test and hire scale regression models. We also present a technique for determining the amount of items required to meet specifications of the customer, called determination plan.

Quality Tools: We contemplate the major quality tools such as SPC, process capability analysis, measurement systems analysis (MSA) and quality indicators. The SPC tool has the main type of charts, such as the Xbar and R, Xbar and S, individual values and moving range, among others. We also have the main attribute charts. The MSA tools presents all the techniques for replicable and not replicable (or destructive) systems analysis. We also have a module for attributive systems analysis. Our capability analysis module and capability process is one of the most complete. Initially, we have a module to test what probability distribution fits your data set. If your data set fits the normal distribution, you can apply the traditional techniques. If your data set does not fit the normal distribution, we have a range of possibilities, from data transformation (Box-Cox) and adjusting of other distributions (Weibull, Lognormal, etc.) to nonparametric techniques, as the Kernel method. Moreover, we have a module with indicators of quality (DPU and DPMO) as Ishikawa charts. In summary, a complete module for you to perform and present your analysis in an easy and understandable manner.

DOE: This module has one of the most powerful tools for improving processes, products and services. Here, we make the design of your experiment, the main techniques of analysis and the suitables charts for your presentation to be understood by all. This module also presents a series of techniques that you can perfor an analysis of the response surface of the process and thus, determine the levels of impact factors that maximize the performance of your process, product or service.

Multivariate Analysis: We have simple techniques for data clustering and cluster formation. Also, we have the use of MANOVA that allows you to study the impact factors in the process, products or services with multiple quality characteristics.

Power and Sample Size: Here we use a technique of power function to determine the sample size needed to perform your experiment. In this module, we apply this techniques to simple tests as the t test to more complex tests such as ANOVA and chi-square tests.