SIMPLE OPEN-SOURCE STATISTICAL APPLICATIONS USED FOR DATA ANALYSIS

Abstract

Software, applications, or APPs are nowadays essentials for doing work on mobile, computers, tabs, etc. In a statistical framework, statistical analysis software integrates, analyses, and interprets vast amounts of data. Various types of statistical tests are required software to compare, analyze, and create models, graphs, etc. Open-source statistical software (OSSS) accelerates the ability and performance of learner or program runner who is not able to buy paid software. On the other hand, the use of statistical applications is mandatory to calculate big data flawlessly. Statistics is a field that uses a wide range of methods to analyze data and draw conclusions. Information is gathered, catalogued, summarised, interpreted, and reported as part of the statistical process. This branch of mathematics is typically broken down into "descriptive" and "inferential" subfields. Data representation in numerical form is the focus of descriptive statistics. In contrast, inferential statistics is concerned with drawing conclusions from the data. Statisticians and researchers used different Open-source statistical software like Microsoft XL, JASP, IBM-SPSS, Invivostat, OpenStat, G*Power, MacAnova, SOFA, PAST, TIMi, XLSTAT, Zelig, etc. The purpose of this paper is to serve as a resource for readers in making informed decisions on open-source or free software for use in performing statistical analysis. The summarized information will help readers to select the appropriate application(s) to perform statistical analysis. It is also helpful to the readers that what type of OS and data format requires for successfully running an application.