10 Best Free Statistical Softwares for PhD Candidates, Researchers and Data Scientists

What Are Statistical Software?

Statistical software, often known as statistical analysis software, is a set of tools that aid in the collection and analysis of data using statistics to provide science-based insights into patterns and trends. To undertake data science, they frequently employ statistical analysis theorems and methodologies such as regression analysis and time series analysis.

10 Best Free Statistical Software for PhD Candidates, Researchers and Data Scientists

List of 10 Best Free Statistical Softwares for PhD Candidates, Researchers and Data Scientists

1.     SAS Analytical Software

You can gain quick access to powerful SAS software via the cloud whether you're a professor, instructor, student, or independent learner. It's also simple to set up. After that, all you'll need is a broadband internet connection to run the best analytics software on the planet. Click here to visit official website

2.   Stata: Statistical software for data science

It is a statistical software that is quick, accurate, and simple to use. Stata is a comprehensive data science software suite that includes data manipulation, visualisation, statistics, and automated reporting. Click here to visit official website

3.   IBM SPSS Statistical Analysis Software

IBM SPSS Statistics is a powerful statistical software platform. It offers a user-friendly interface and a robust set of features that lets your organization quickly extract actionable insights from your data. Advanced statistical procedures help ensure high accuracy and quality decision making. All facets of the analytics lifecycle are included, from data preparation and management to analysis and reporting. Click here to visit official website

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4.   Statistical Lab

The Statistical Lab is an explorative and interactive tool designed both to support education in statistics and provide a tool for the simulation and solution of statistical problems. The graphical user interface is designed to make complex statistical relations easy to understand. It connects and displays data frames, frequency tables, random numbers or matrixes in a user-friendly statistical worksheet allowing users to run calculations, conduct analyses and perform multiple simulations and manipulations. The Statistical Lab uses R for statistical computing and visualizing data. Click here to visit official website

5.    Dataplot

Dataplot® is a free, public-domain, multi-platform (Unix/Linux, MacOS, Windows 7/8/10) software system for scientific visualization, statistical analysis, and non-linear modeling. The target Dataplot user is the researcher and analyst engaged in the characterization, modeling, visualization, analysis, monitoring, and optimization of scientific and engineering processes. Click here to visit official website

6.   SCIPY

SciPy is a set of open source (BSD licensed) scientific and numerical tools for Python. It currently supports special functions, integration, ordinary differential equation (ODE) solvers, gradient optimization, parallel programming tools, an expression-to-C++ compiler for fast execution, and others. A good rule of thumb is that if it’s covered in a general textbook on numerical computing (for example, the well-known Numerical Recipes series), it’s probably implemented in SciPy. Click here to visit official website

7.    Zelig

Zelig is an easy-to-use, free, open source, general purpose statistics program for estimating, interpreting, and presenting results from any statistical method. Zelig turns the power of R, with thousands of open source packages — but with free ranging syntax, diverse examples, and documentation written for different audiences — into the same three commands and consistent documentation for every method. Click here to visit official website

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8.   DataMelt

DataMelt is free software for numeric computation, mathematics, statistics, symbolic calculations, and data analysis and data visualization. This multiplatform program combines the simplicity of scripting languages, such as Python, Ruby, Groovy (and others), with the power of hundreds of Java packages. Click here to visit official website

9.   Minitab Statistical Software

Data is everywhere, but are you truly taking advantage of yours? Minitab Statistical Software can look at current and past data to discover trends, find and predict patterns, uncover hidden relationships between variables, and create stunning visualizations to tackle even the most daunting challenges and opportunities. With powerful statistics, industry-leading data analytics, and dynamic visualizations on your side, the possibilities are endless. Click here to visit official website

10.                     GraphPad Prism

It is a versatile statistics tool purpose-built for scientists-not statisticians. Get a head start by entering data into tables that are structured for scientific research and guide you to statistical analyses that streamline your research workflow. No coding required. Click here to visit official website

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