5+ Statistical Software Which You Have to Master in 2018

Statistics as a discipline involves handling a large number of data that needs conversion into a meaningful form. It is very uncomfortable for both students and professionals who manage large data in statistics since they take a lot of time with little progress recorded. The age of computers that we live now has made strides to simplify the techniques we use to handle statistics and save time.





Statistical Software is a computer program that is tailored by professional software developers to help in managing statistical data. The Software is designed to perform tasks such as collection, analyzing and interpreting data. There exists more acknowledgment by many participants in the field of handling statistical data that the software such SPSS statistics help in making handling data to be efficient and fun.

There exists more than fifty statistical software that has been developed to be used, and more continuously generated each year. Statistical software is either commercial or has a free to use license by any one.

 The following are statistical software that is critical to being mastered;

1.         SPSS Software
The SPSS (Statistical Software for Social Sciences) is relatively common software to most people in the field of statistics since it performs several functions and its free for use. The software is used on the window operating system and handles entry, analysis, and presentation of data in graphs and tables help with SPSS applications. 

The software can handle large data and complex data calculations and maintain simplicity in its instructions through graphic visualizations that show how to read SPSS output.

2.         SAS Software
The SAS software stands for Statistical Analysis System, and it was developed by the SAS Institute to serve in handling major data analytics such as regression. The software work in different platforms of operating systems; Windows, Linux, and IBM computers. The software is freely available in most university institutions and serves the purpose of handling modeling and analyzing large data banks of businesses.

3.         MATLAB Software
The MATLAB (Matrix Laboratory) software is relatively easy to use and is well suited for use by scientists and engineers from the results it produces in numerical computations. The software work under both operating systems of Windows and Macintosh to handle complex operations of matrices and algorithms contained in the large data community of mathematics.

MATLAB has obtained a license and is relatively easy to use if you are conversant with mathematics and statistics.

4.         Stata software
Stata is statistical software that is developed by the Stata corporation to integrate all the concepts that are in statistics and related disciplines such as economics and medical research. The Stata software can perform under operating systems including Windows, Linux, and Macintosh with access to the license to use the software. 

The applications of Stata range from management and analysis of data, simulations and the production of graphical images to explain calculations.

5.         JMP Software
The JMP statistical software is closely related to the SAS software since they are developed from the same institute to integrate the significant advantage of advanced graphics and statistical analysis. The JMP software has extensively used for analysis by most engineers and scientist who would want to analyze data that is graphical.

The software is developed to work with operating systems of Windows and Macintosh to perform data analysis and mining on exploratory data.

6.         Analytica Software
Analytica software was designed to stand alone and handle the analysis and interpretation of visual quantitative data. The software works well in Windows and Macintosh operating systems and available to the public on a free license.

Although Analytica is not well known, it works well to analyze the density functions and modeling of data from various sources such as environment financial services and health.

Conclusion
The introduction of the programming language in into statistics has helped to reduce the time spent on analyzing data and the errors that occur when handling data using human mind. There is much software that is developed to manage statistics data, and it is a common trend that the aim of the developers to reduce the constraints of handling big data through alternative methods such as help with SPSS.

It is important to recognize that software has changed the blunt dimension used to approach and manage data to a practical approach.

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