Know the best open-source statistical analysis software and their features that make them stand out!

Data is available everywhere around us and is now traded as a commodity among marketers & researchers for various purposes. However, this data needs to be processed, refined and turned into something useful. The refining & processing is done through different statistical analysis software which further presents the ‘new oil’ in a much more organized manner. There are numerous tools available in the market today but only a handful can produce what we actually need.

The article lists such best open-source statistical analysis tools that are ruling the market and are popular among expert marketers & researchers.

Table of Contents

- Features in Statistical Analysis Software
- What is the statistical analysis package?
- What are the tools of statistics?
- What are the statistical analysis methods?
- What are the uses of statistical packages?
- What is the difference between statistical analysis and data analysis?
- What are the 5 basic methods of statistical analysis?
- List of a top free and open-source statistical analysis software:
- JASP
- SOFA
- GNU PSPP
- SCI LABS
- Jamovi
- MacAnova
- Past
- Develve
- Invivostat
- IBM SPSS
- SPC for Excel
- MATLAB
- Tableau
- Conclusive: How to choose amongst the best Stats software?
- Top FAQs – Best Statistical Analysis Tools

Statistical Analysis is a component of data analytics, collection, and interpretation of data to uncover patterns and trends, gather research interpretations, statistical modelling or designing surveys and studies. Statistical Analysis Software is used to solve complex business problems.

## Features in Statistical Analysis Software

Statistical software comes with expansive libraries of readymade/ready to use statistical procedures. This might include 100’s of prewritten procedures to deliver or amplify the functionality of the program.

These come with a range of robust statistical methods and a set of tools to accomplish various specialized and enterprise wise needs from analysis of variance and linear regression to Bayesian inference and high-performance model selection for massive data.

Statistical Analysis Software is made to be scalable and to run across multiple platforms. They can access nearly any data source, can easily integrate into any computing environment, scaling too address larger or even more complex analytical problems.

These also come with some regular updates, thus delivering the statistical methods and high-performance computational tools along with user-requested enhancements.

## What is the statistical analysis package?

Statistical Analysis Software (SAS) understands the data type; access it from any software and any format and solve complex business problems. It is often used for collection, organization, analysis, interpretation, and presentation of data.

It is a general-purpose statistical package used in academic research for editing, analyzing, and presenting numerical data. It is compatible with various file formats that are commonly used for statistical data such as Excel Spreadsheet Software (EPSS), plain text and relational SQL databases.

## What are the tools of statistics?

F-test, T-tests, regression analysis are the most common and convenient statistical tools to quantify the comparisons.

## What are the statistical analysis methods?

Statistical Analysis makes use of two main methods:

**Descriptive Statistics:**It is the process of summarizing data from a sample using indexes such as the mean or standard deviation.**Inferential Statistics:**It is the process of concluding data that are subject to random variation like the variation in sampling or observational errors etc.

## What are the uses of statistical packages?

Statistical packages allow the users to decide what information they need to collect, else the data goes waste.

## What is the difference between statistical analysis and data analysis?

Statistical analysis can be used to gain an understanding of a larger population by analyzing the information of a sample. Data analysis can be used to inspect, present, report the data in a way that is useful to non-technical people.

## What are the 5 basic methods of statistical analysis?

Basic methods of statistical analysis include: mean, standard deviation, regression, hypothesis, testing, and sample size determination.

## Here is A list of a top free and open-source statistical analysis software:

### JASP

It stands for the Journal of Statistical Software and is a free and open-source graphical program for statistical analysis. It comes with a user-friendly interface and offers standard analysis procedures for Integrated with The Open Science Framework (OSF) and support for APA format (copy graphs and tables directly into Word). It can be used both for Frequentist analyses and Bayesian analyses. It updates all results dynamically. It comes with a spreadsheet layout and an intuitive drag and drop interface. It showcases progressive disclosure for increased understanding. It possesses annotated output for communicating your results.

### SOFA

It stands for statistics open for all. It is a user-friendly, open-source statistics analysis and reporting package, to make users export data into an Excel spreadsheet format by using SOFA Statistics. It also enables users to perform easy data recording using a simple form. The data analytics that is output by SOFA Statistics are easily shareable.

### GNU PSPP

GNU PSPP is a free statistics software compatible with SPSS language to perform descriptive statistics, T-tests, anova, linear and logistic regression, measures of association, cluster analysis, reliability, non-parametric tests, and factor analysis. It currently features high-quality output formatting, a user-friendly interface, a command-line interface to allow users to rapidly perform analysis, data preprocessing, analysis, visualization. It can be built in a wide range of platforms.

### SCI LABS

Scilab is an open-source statistical tool that performs data analysis and modelling. It is better known for Descriptive statistics, Probability distributions, Linear and nonlinear modelling, Machine learning, Regression and Classification. It as well calculates Central tendency, Data with missing values, Descriptive statistics, Measures of dispersion and Measures of shape.

### Jamovi

Jamovi is one of the best free statistical software to bridge the gap between the researcher and statistician. It makes the statistics easy, it is based on R statistical language and is open-source and free for the scientific community where it finds its purpose.

### MacAnova

It is interactive, free, and open-source statistical software for MAC, Linus and Windows. It comes up with features like descriptive statistics, variables and operations, linear and generalized linear models, time series, matrix algebra, design of experiments, multivariate analysis etc.

### Past

It is free statistical software for scientific data analysis with functions for data manipulation, univariate, plotting, ecological analysis, multivariate statistics, time series and spatial analysis, stratigraphy and morphometrics. It might also help users with a spreadsheet-type data entry form; it comes with an interactive user interface and scripting. It comes with kernel density estimation, 3D scatter, percentile, ternary, Graph, bubble, matrix, spindle, survivorship, box, histogram, scatter, surface, and normal probability plots and curve fitting.

### Develve

It is a free statistical analysis tool used for research in science and R&D (Six Sigma) in a technical environment. It is used for fast analysis, design of experiments, basic statistics, Gauge R&R and Sample size calculations. It comes along with a couple of basic statistics like Anderson Darling normality test, Wilcoxon–Mann–Whitney-test, Compare with, Mean, Correlation test, Sample size calculations, Variation F-test, Difference, Min/Max, STDEV, Regression, Multiple linear regression, Kutosis, Cp Cpk % out of tolerance, Sample counting, t-test, Skewness, Generate distribution, Proportion calculation, Chi-Square test, filter, Multiple linear regression, One-way Anova, Distribution fitting, Graphs, Kruskal-Wallis Test, Nested Gauge R&R (destructive), Gauge, Design of experiments (DOE), Response Surface Methodology (RSM), Reliability Weibull analysis and Weibayes.

### Invivostat

It is a powerful, free, and open-source statistical analysis software package that combines complex and statistical tools (within R) with a user interface that is user-friendly and intuitive. It comes with requisite dataset checks to invalidate the results of the analysis are identified before analysis.

### IBM SPSS

It is one of the leading free and open-source statistical software that is designed to solve business and research problems by random analysis, geospatial analysis, hypothesis testing and predictive analytics.

### SPC for Excel

SPC for Excel Software streamlines statistical analysis and charting, assisting you in identifying problem areas, gaining insights into your data, spotting trends, solving issues, and improving processes. The platforms come with several tools for users including Histograms, Control charts, distribution fitting, Pareto diagrams, process capability, DOE, regression, DOE, hypothesis testing, and much more!

### MATLAB

With the help of the programming and numerical computing platform MATLAB, companies and academic institutions can build models, develop algorithms, examine data sets, and do a lot more. Experts may add headings, hyperlinks, and graphics to code and write scripts using the live editor.

Data visualization, signal processing, a drag-and-drop interface, and application sharing are some of MATLAB’s key features.

### Tableau

Tableau is a comprehensive analytics and business intelligence (BI) tool that facilitates the analysis of important company data and the production of insightful reports. In order to construct a collective dataset, the solution assists organizations in gathering data from many sources, including spreadsheets, cloud programs like Google Analytics and Salesforce, and SQL databases.

Users can analyze data across areas, territories, demographics, and more by creating interactive maps.

#### Conclusive: How to choose amongst the best Stats software?

Hope you get some clarity about the reason why statistical tools are used, which tools are currently topping the charts and how do they differ from each other. There is many other free stats software that works on the similar lines besides the above-mentioned software like Atom, Brackets, Bluefish, Visual Studio Code, Notepad++, Cuda text, Emacs, ConText, Editpadlite and Komodo IDE. If you wish to discuss or know something about statistical/analytical tools or want us to add something to this list, reach out to us.

## Top FAQs – Best Statistical Analysis Tools

### What is statistical analysis software?

Statistical analysis tools help in collecting, analyzing, interpreting, and organizing large databases for researchers & analysts. The software uses several statistical techniques, including hypothesis technique, descriptive statistics, analysis of variance, regression analysis, and time series analysis.

### What are the benefits of statistical analysis software?

Statistical analysis software handles databases of multiple formats efficiently and in an organized way. Some of the benefits of the tool include –

- Minimum Manual Errors
- Identifying Trends Earlier
- Visualizing Data Interpretation
- Manage Large Datasets

### What are the top features in statistical analysis software?

Some of the common features to look in a statistical analysis tool include –

- Reporting & Statistics
- Data Clustering
- Regression Analysis
- Data Visualization