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SOFA Statistics VS IBM SPSS Statistics

Compare SOFA Statistics VS IBM SPSS Statistics and see what are their differences


SOFA Statistics Open For All - the user-friendly, open-source statistics, analysis, & reporting software package.

IBM SPSS Statistics is software that provides detailed analysis of statistical data. The company behind the product practically needs no introduction, as it's been a staple of the technology industry for over 100 years.
SOFA Statistics Landing Page
SOFA Statistics Landing Page
IBM SPSS Statistics Landing Page
IBM SPSS Statistics Landing Page

SOFA Statistics details

Categories
Technical Computing Numerical Computation Data Dashboard
Website sofastatistics.com  
Pricing URL-
Details $-
Platforms
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Release Date-

IBM SPSS Statistics details

Categories
Technical Computing Numerical Computation Data Dashboard
Website ibm.com  
Pricing URL-
Details $-
Platforms
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Release Date-

SOFA Statistics videos

SOFA Statistics - the user-friendly statistics, analysis, and reporting program

More videos:

  • - SOFA Statistics
  • - Installing SOFA Statistics in Windows

IBM SPSS Statistics videos

IBM SPSS Statistics Overview

More videos:

  • - What's new in IBM SPSS Statistics 26

Category Popularity beta

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28
28%
72%
72
100
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0
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100

What are some alternatives?

When comparing SOFA Statistics and IBM SPSS Statistics, you can also consider the following products

PSPP - PSPP is a free software application for analysis of sampled data.

RStudio - RStudio™ is a new integrated development environment (IDE) for R.

JASP - JASP, a low fat alternative to SPSS, a delicious alternative to R.

Stata - Stata is a software that combines hundreds of different statistical tools into one user interface. Everything from data management to statistical analysis to publication-quality graphics is supported by Stata. Read more about Stata.

RKWard - RKWard is an easy to use, transparent frontend to the R programming language, a very powerful, yet...

JMP - JMP is a data representation tool that empowers the engineers, mathematicians and scientists to explore the any of data visually.

User comments

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