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Our statistical analysis software reviews are the result of over 40 hours of research on 40+ statistical analysis software companies from across the web. These reviews and our statistical analysis software guide help small businesses and startups find the best statistical analysis software for their business.
Domo is a cloud-based self-service business intelligence platform that’s designed to provide one central location for all data. It empowers organizations to automate their reporting and to quickly leverage massive amounts of data quicker. Some features include:
Reducing the time it takes to do raw statistical data analysis from weeks to days or even hours
Blending data from multiple sources into useful visualizations
Integrating data in workflows for real-time project and task management
Leveraging algorithms for better predictive data modeling
Domo supports numerous data sources, including Excel and data text file, SQL, Google Analytics, and SalesForce, and its analyzer tool suggests graphs from numerous visualization formats, such as heatmaps and scatter plots, which can be published to the web or to a PDF.
Pricing isn’t provided on the site, but businesses have the opportunity to try it out once they create a free account.
Pros & Cons
Rich visualization features with detailed drill down
Correlate large amounts of data from multiple data sources
Supported by the University of Amsterdam, JASP is an open-source statistical analysis tool that was designed to support scientific work. It gives users the choice to use Frequentist, repeatable random event probabilities, or Bayesian, a bottom-up approach, where probabilities are used to represent uncertainty. In addition to standard statistical modeling, you can use more advanced structural equation modeling (SEM) and reanalyze data with the summary stats module. Other features include:
Easily editing raw data and immediately seeing how changes made affect your analysis
Copying and pasting graphs and tables to your favorite word processor
Ability to transparently reproduce, review, and annotate analysis of collaborators
Results can be immediately published on JASP’s Open Science Framework, which can be viewed by anyone.
JASP is free to use and can be downloaded at the site. Users can request features and get help from the forum.
Pros & Cons
Integrates with popular software tools like R and Stata
Save graph as PNG or immediately add it to a document
JMP is a statistical software tool that’s popular among government sector scientists and engineers as well as companies who need to do targeted customer segmentation and market research. Users get more insight from using JMP to shape and preprocess their data than they would relying on a flat spreadsheet with static graphs. Its features include:
The ability to share analysis with those who don’t have JMP with the help of interactive HTML
Quick-view dashboards with key information for project managers and executive stakeholders
Experiments that provide deeper insights into possible opportunities
Model comparison and average to choose the best cross-validation and fitness
JMP’s platform utilizes neural networks to handle data and learn difficult cases, and with its Time Series platform, it’s able to execute better forecasting and modeling.
JMP is an SAS product, so you can deploy models in SAS as well as C and other languages. It also interfaces with MATLAB and connects with R, with the help of some JSL scripting. For those who need support, they have phone and email along with their knowledge base and education resources for users to wade through.
JMP offers a 30-day trial of its fully functional platform. Once that’s over, users are billed annually at about $125/month. For JMP Pro, Live, or Clinical software, companies must request an evaluation.
MATLAB is used in many industries for predictive analytics and computing. It’s a platform that’s popular in academia, particularly engineering and computer science, but also has prominent applications in economics because it’s very good at real-world simulations. Its features include:
Describes, analyzes, and models data with fit probability distributions and Monte Carlo simulations with random numbers
Tool box of machine learning algorithms
Multidimensional feature extraction
With the MATLAB coder, you can deploy models in C or C++. In addition to integrating with applications, such as Spark and MapReduce, you can build with .NET, Java, and Python.
You can download MATLAB for a 30-day free trial. For primary and secondary students and teachers, it’s as low as $29 for just MATLAB and $55 for the suite, which includes ten of the most popular add-ons and Simulink. For personal use, the one-time price is about $95. For Academia and standard use, opting for the perpetual license provides indefinite use, and the annual license is a little cheaper. Since MATLAB is available worldwide, pricing may change, depending on location and applicable taxes.
Founded in 1972, Minitab Statistical Software helps users discover patterns and hidden relationships between variables from past and present data. With its visualization capabilities, users can take advantage of the program’s data analytics strength to uncover upcoming challenges. Some features include:
Deep dive tools such as CART and factor analysis
Matrix plots, time series plots, and contour 3D plots
Time series and forecasting tools, including ARIMA and exponential smoothing
Minitab’s step-by-step guidance helps you create detailed reports that are easy to understand from analysis to interpretation. It has open-source integration with programs like Python, and the library has convenient macros for automation. The tools kit is comprehensive and provides users with plenty of options to visualize data and make the necessary business decisions.
Users get access to the full Minitab suite during their 30-day trial, after which they can opt for the single-user annual license for $1,400, which includes all software updates, upgrades, and tech support.
OpenText Magellan is a platform that leverages the power of machine learning and advanced analytics to give context to already accumulated structured and unstructured Big Data and Big Content. This helps businesses to answer all sorts of questions about their next steps. Some features include:
Understanding text, numbers, and IoT to turn information into actionable steps
Drag-and-drop functionality to create custom dashboards
OpenText Magellan uses NLP to interpret unstructured data to create emotion analysis tools. This helps businesses to better serve customers by finding upsell and cross-sell opportunities and improving customer retention.
There is a free trial upon request, but pricing isn’t provided.
Pros & Cons
AI is easier to integrate and helps business to scale
Use scripts to extend analytical and report functionality
Headquartered in Massachusetts, OriginLab has been publishing its graphing and analysis software for use by academics, scientists, and engineers for projects in both the commercial and business sectors since 1992. It started with Origin, but now with OriginPro, it offers far more features including:
Tools for cross-tabulation, distribution, and calculation of correlation and partial correlation coefficients
Easily bringing your data into the software and allowing you to click a few buttons to get the graphs needed and interactively explore them
Over 150 graph templates and a graph maker app with drag-and-drop columns
Three-way ANOVA as well as support for unbalanced data and mixed experiment design
Non-parametric tests are only available in OriginPro, including one and pair samples and multiple independent and related samples. There are five exclusive multivariate analysis tools, including K-Means and Hierarchical Cluster analyses, along with three survival analysis tools, including the Kaplan-Meier estimator. Users can also extend their graphing and analysis capabilities by installing free apps from File Exchange.
OriginPro comes with a 21-day free trial. From there, students can get an annual user license for $69, and those in academia can get it for $255. Business users pay a one-time individual user fee of $435, and government agencies and nonprofits can get a perpetual license for $1,500+.
Qlik Sense is an AI-powered data analytics platform that helps organizations make data-driven decisions. It allows users to go through any use-case scenario to gather business intelligence. Some of its features include:
Ability to build smart visualizations and drag-and-drop apps
Natural language and real-time analytics that enable better insights and analyses
Better ability to highlight certain data relationships
Fully interactive mobile analytics whether you’re online or offline
Qlik Sense’s Associative Engine lets users explore the associations across all of their data sources in a way that goes beyond the standard query-based tools like SQL. This proprietary engine unifies all tables and data sources while managing the relationships between every piece of information. It’s an extremely visual program that makes it easy for anyone to glean insight from the data, which can be imported through its array of web connectors.
Qlik Sense offers a free trial and is available for a monthly cost of $30/user. For Enterprise, there’s a base price of $70/ month, with analyzer add-ons costing more. Both tiers are billed annually.
Pros & Cons
Better data modeling with the associative engine
Easy to use and quick to learn
Integrates with many data sources through Qlik Connectors
SAS’s cloud-based platform has several product lines that take full advantage of its statistical and analysis capabilities. Users can perform multiple operations simultaneously and easily create hundreds of custom charts and graphs for repeated use. Some if its features include:
Predictive modeling on mined data to calculate probable and possible outcomes
More than 100 built-in statistical analysis procedures that can provide specialized needs
Tailored data analysis based on type and size, including filling in missing values
Centralized repository that makes integration of models easier
SAS uses AI and machine learning techniques to create a modern statistical processing environment that reduces millions of IoT data events to manageable sizes that are analyzed and visualized. Users can access the platform from Python, R, Java, and other coding environments.
Those considering SAS can request a demo. They are also offering a 30-day free trial with the potential for extension, if needed. Contact the company to request a custom quote.
First released in 1994, Scilab is a free open-source computation software that’s used by scientists and engineers for numerical analysis, visualizing data, developing algorithms, and deploying applications. Its features include:
Approximately 1,700 math functions for use in data analysis
Supervised and unsupervised machine learning tools for performing predictive analysis
Signals filtering and processing in time and frequency domains
When it comes to developing an app, Scilab can work with Excel files as well as MATLAB binary files for data management. Its modules, called toolboxes, are handled through ATOMS and include image processing, GUI builders, and IPT3 for pattern classification.
Scilab is free to use and has several tutorials for self-learning. It takes support requests from 9 a.m. to 5 p.m. during central European summer time, and has a response window of two business days. Otherwise, they have paid live 3-day training seminars.
Pros & Cons
Great at crunching numbers for complex math problems
Many free-to-install toolboxes for customization
Strong community of peers to help answer questions
SigmaPlot is a data visualization software tool that’s all about giving you the perfect graph for whatever data you want to represent. Some features include:
More than 100 2D and 3D graphs from simple scatter plots to radar density plots
Interactive wizard for step-by-step creation and easy fitting
Built-in templates or the WYSIWYG layouts that let you customize your own pages
Creation of macros to automate repetitive tasks and use VB to create SigmaPlot-based apps
Industry-specific modules, such as Electrophysiology and Enzyme Kinetics
SigmaPlot works with Microsoft Office, so you can seamlessly integrate your graph in a slide or an active spreadsheet. You can even share your data on the web by embedding the graph in your HTML to generate interactive reports.
Businesses can get a 30-day free trial. The serial numbers are available in the support section of the site. All of the licenses are one-time fees: $599 for academic users, $799 for each government user and $899 for commercial users.
IBM’s SPSS statistical software platform helps organizations crunch large data sets to get actionable insights. Its features include:
Ability to build visualizations and reports with simple point-and-click actions without the need for coding
Quick identification of invalid and missing data for more efficient conditioning and preparation
Use of a library for R and Python to enhance syntax
Improvement of predictive modeling with neural networks
SPSS is scalable and agile, giving businesses the opportunity to perform advanced simulations. Data can come from different spreadsheets and databases, and users have the option of automating recurring tasks to save time and improve productivity. When you’re ready to share your data, you can use a variety of formats, including .xls, .pdf, and HTML.
After a 14-day free trial, companies can access SPSS for just $99/user/month for the base subscription. Optional add-ons can be purchased.
Stata is statistical software used by data scientists in a variety of fields, such as marketing, medical research, and sociology. Users can customize certain aspects of the graphs, such as the texts and margins. Other features include:
Thousands of built-in Bayesian models, in addition to extended regression, generalized, and choice models
Ability to study the time-invariant features and any other extra information from panel/longitudinal data
User-friendly interface with logical menu layout
Invokes Python packages, such as TensorFlow, Seaborn, and Pandas for passing data and visualization
There are four Stata packages: Stata/MP, Stata/SE, and Stata/IC, which depend on data set size and CPU configuration, and Numerics by Stat,for embedded and web apps. For times when users need to perform quick matrix calculations, Mata is the programming language within Stata that’s automatically compiled, making it fast. It looks similar to C/C++ and Java, and it can convert Stata datasets with matrices with up to 2 billion rows and columns. Stata has more than 15,000 pages of documentation to help you navigate the programs.
Stata has a 7-day free trial, if requested. Otherwise, it’s individual user licenses are $94/year for students and $125/year for education faculty and staff. Government, nonprofit and business users have to pay $765/year.
Tableau is a popular statistical analysis software that turns data into actionable insights with the help of advanced visual analytics presented in bold interactive dashboards. Some of its features include:
Intuitive drag-and-drop interactive interfaces with no coding required
Feature-rich multiview dashboards
Numerous native and partner connectors, including SAP Sybase, QuickBooks, and Google Analytics
Extension of calculations ability with data science tools, including R, Python, and MATLAB
There are different tiers including Tableau Prep, which prepares the data and manages flows along with monitoring and scheduling. Tableau has a wide range of products as well as data management and server management add-ons for teams and organizations.
There is a free trial of Tableau Desktop, with the option to extend that to include Prep Builder and Server. Individual users can only get Tableau Creator individual licenses for $70/month, but teams and organizations can opt for Tableau Explorer for $42/month or a Viewer license for $15/month. All tiers are billed annually. Tableau Public is a great way for data enthusiasts to show off their creations of public data. The company also gives students and nonprofits opportunities to obtain free licenses.
For those who want to extend the functionality of MS Excel, XLSTAT is an add-on that can perform in-depth statistical analysis, from modeling to forecasting and machine learning. Some if its features include:
Calculation of price sensitivity and elasticity for marketing research
Text mining and latent semantic analysis
Classification and regression trees for machine learning
ANOVA and ANCOVA modeling
XLSTAT also has a 3D Plot option that can help users get more context and latent class analysis for better segmentation.
The free edition of XLSTAT includes access to 13 of its features. After the 14-day free trial, users can opt for the Basic, Basic+, Applied and Premium tiers of the software depending on if they are Students, Academics or Commercial entities. Student licenses start at $50/year, Academic Basic starts at $165/year and Corporate or individual users start at $295/year.
How We Chose the Best Statistical Analysis Software
Business intelligence, BI, is the ability to leverage software to interpret data and provide actionable insights, which is why statistical analysis software is extremely important. With the growing volume of data, businesses need to be able to load in their information, specify parameters and visualize it in a way that makes sense. We chose the best statistical analysis software based on analysis tools, visualizations, and integrations.
Statistical analysis isn’t just one feature, and that’s why we recommend software that allows users to manipulate the data in a way that best suits their objectives. Whether you need to execute a multivariate analysis that observes and analyzes statistical outcomes or take a look at a specific relationship you see between points in customer data, users need to have access to many analytical tools.
Just because you’ve collected all that data, doesn’t mean you know their story. The best statistical analysis software reinterprets that data on a visual landscape, providing actionable insight. Robust visualization capability allows users to discover and interpret trends in their data sets that they may not have recognized otherwise.
Getting the data into the software requires integration with other applications. Great statistical analysis software has pre-built integrations that make the process smooth but also allows for even more expansion. Whether you’re pulling in data from forms or from a proprietary database, these applications should offer you a hassle-free way to organize the data for use.
What Is Statistical Analysis Software?
Statistical analysis software is a programming application that is used to efficiently solve complex scientific problems. It’s a component of the business intelligence sector that uses data analysis to glean insight into business functions and potential opportunities. It’s also a primary research tool that’s used by academics, scientists and engineers. Users input the dataset they want to analyze. The software takes that information and runs it through a set of protocols, outputting distilled, understandable information that is more useful and actionable than what was input.
There are two basic types of analyses that this software does. Descriptive statistical analysis describes the simplest features of a data set, including its distribution and variability. This provides a summary of the data for easy interpretation.
Inferential statistical analysis involves testing a hypothesis about the data sample and coming to certain conclusions about the future outcomes. This is what we see when scientists use a sample of people to represent a larger segment of the population. Both types make up the bulk of the analysis these software applications do to solve problems and gain insight in business and science.
With the right type of statistical analysis software, users can get the benefit of both and may even be able to predict certain outcomes and behaviors. This is what makes many applications more powerful beyond their ability to crunch numbers.
Benefits of Statistical Analysis Software
As someone looking for answers, you recognize the need to get as much insight as possible from the data you have. This is one of the reasons why choosing a good statistical analysis software is vital. With possibly millions of data points and events, it’s hard for you to get all that you need from looking at the raw data. Statistical software helps in these ways:
Reduces errors in samples: Your data is not perfect, and chances are, it’s going to have some errors. Taking a look at all of that information at once, the application can tell you what the errors are and how they’re handled. This ensures that the results are as accurate as they can be.
Shows users cause and effect: The tendency to overgeneralize results is a danger, especially when dealing with manual analysis. Something as simple as changing an element on a website may be assumed to cause an increase in web traffic. Statistical analysis software uses algorithms and machine learning to repeatedly test an idea in order to understand the difference between correlation and causation. Understanding the link between different variables leads to more accurate decision-making.
Is easy to understand: With all the data you have to interpret, you need to be able to present it to staff, colleagues, or stakeholders in a way that gets their buy-in. Some of the best statistical management software applications have numerous graphical interpretations and features that make it easy to visualize the relationship at a glance, even for someone who may not be a data expert.
Saves time: Statistical analysis software saves time because no business owner or scientist wants to spend hours trying to figure out the numbers. These applications free up your time, so that you can focus on more important business, such as capitalizing on opportunities.
Must-Have Features of Statistical Analysis Software
For someone who understands the value of data in making informed decisions, there are some must-have features for statistical analysis software:
Great visualization: Being able to see the data in different ways helps you understand what it’s telling you. With a rich array of graphs and models, this application can give you more insight into your data..
Key integrations: Easily grabbing your data from wherever it’s stored means having to spend less time preparing it for analysis. If it can be safely moved from its current location or combined with data in a separate location, this saves time and provides a level of flexibility that extends usability.
Easy to use: Not everyone is familiar with the discipline of statistical analysis. In those cases every piece of software is a learning curve, but an application that is intuitive enough to show its value to someone who isn’t an expert is more valuable.
The Cost of Statistical Analysis Software
Statistical analysis software is likely to be subscription-based, billed annually or monthly. The prices vary from free with limited features to hundreds of dollars a month, with the option of a free trial to showcase the value it’ll bring to your organization.
Whatever the price point, the best software will show its value early and pay for itself in the actionable analysis it provides. Ensure that the free trial you’re using includes enough of the software’s features to get a full idea of what it can contribute to your decision-making.