What Is Statistical Analysis Software?

Key takeaways

• Statistical analysis software is a computer program containing built-in tools for analyzing data using statistical methods.

• By using software for statistical analysis, you can analyze market performance, find opportunities through data trends, make informed decisions based on forecasts, and optimize business processes.

• Free statistical analysis software programs, such as R, offer full access to their statistical computing environment, where you can analyze data and visualize it in different ways.

When choosing the best statistical analysis software for you, consider the cost and subscription options, whether you need coding integrations, and what tools the software offers. Read on to explore different statistical analysis software, how to use them, the careers and industries that find it helpful, and how to start learning about statistical analysis.

If you’re ready to get your start building expertise in data analysis, consider enrolling in the Google Data Analytics Professional Certificate, where you will have the opportunity to learn key analytical skills, like data cleaning, analysis, and visualization, and how to use tools like spreadsheets, SQL, Python, and Tableau in as little as six months. Upon completion, you’ll also earn a shareable certificate for your resume.

What is statistical analysis software?

Statistical analysis software programs have built-in tools to help you analyze and visualize data to spot trends and patterns. They help you and any stakeholders make informed decisions using the data collected from a survey or other forms of research. Statistical analysis is a part of data analysis. It allows you to collect data through research, use statistical methods to model data, and design further studies to collect better or different data. Statistical computing opens up various possibilities for statisticians and data scientists to process data and make informed decisions.

Types of software for statistical analysis

Many different types of statistical analysis software exist, from open-source solutions like R to enterprise solutions like IBM SPSS Statistics. Learn more about some of these below.

SPSS

SPSS Statistics is a statistical analysis software developed by IBM. It has a suite of tools aimed at different experience levels. SPSS Statistics includes various features and an intuitive interface to organize large data sets, use statistical techniques, make predictions, and produce research. Other benefits of SPSS include:

• A user interface with drag-and-drop functions that bypass the need for coding

• Tools for data management, cleanup, and manipulation

• Analytics tools to perform both descriptive and predictive modeling

• A suite of data visualization tools

• Open-source integration of packages using R and Python

Cost: Starts at an online subscription of $109 per month with additional add-ons [1]

SAS

SAS/STAT (Statistical Analysis System) is a high-performing enterprise statistical analysis software with constant updates, providing the newest models and best methods. Other features of SAS include:

• A detailed library of more than 100 statistical analysis procedures with pre-written code

• A range of statistical methods for specialized needs in enterprise-level analysis

• Scalability and a wide range of support on many major computing systems

• Regular updates with high-performing tools and a system to process user requests

Cost: Request pricing directly from SAS [2].

R

R is a programming language developed for statistical computing and graphics. It is an open-source alternative to the S programming language. R is both a programming language and an environment with a fully functional system around the language to support statistical computing. Other features of the R environment include:

• Ways to handle data and the storage of data

• Many kinds of mathematical operators for arrays and matrices

• A fully functional programming language with loops, conditionals, and the ability for users to create their own functions

• Various ways to display graphics; you may view them within the integrated development environment (IDE) or print a physical copy, and you can use R with RStudio, an IDE that helps you write R code

• Tools available to perform data analysis

Cost: Both the R programming language and RStudio are free software.

Minitab

Minitab Statistical Software allows you to find patterns in data, make predictions, and visualize your data to find relationships. Minitab integrates data analytics and data visualizations to help you discover, predict, and achieve your statistical goals. Other features of Minitab include:

• A combination of software and cloud resources to power your business

• A series of statistical modeling, correlation, and time series analysis tools

• The ability to integrate Python and R languages to make predictions using more intensive machine learning algorithms

• Real-time integration of graphics that allows you to change your visualization without running your analysis over and over

Cost: Free trial option available, with basic yearly subscriptions starting at $2,394 for a single user [3]

Stata

Stata is a fast and accurate integrated software with data manipulation, visualization, and statistical tools, including automated reporting. Some features of Stata include:

• An extensive suite of statistical tools and modeling

• Full Python integration that allows you to use any Python package

• Continual updates that provide you with the most recent models and data tools

• A complete graphical user interface (GUI), so coding isn't needed to make use of its features

• A suite of resources, including tutorial videos, training, webinars, and blogs

Cost: A business single-user yearly subscription is $1,015 [4]

What is statistical analysis software used for?

Statistical analysis software can aid you in improving the efficiency of statistical analysis for your business. Although this process could be done without the help of software, using statistical analysis software allows you to enjoy a more streamlined approach to statistical analysis and reduces the risk of error. You may use statistical software for many tasks, such as:

• Analyzing marketing performance to improve strategies and efficiency

• Using data analysis to find opportunities in patterns you could not see otherwise

• Making decisions based on models and forecasting to improve planning

• Optimizing business processes by finding inefficiencies through modeling and prediction

Read more: 7 Statistical Analysis Methods Beginners Should Know

Statistical analysis is a key component that can be used to perform data analysis and make informed decisions. It’s an integral part of business intelligence, a field that uses data to learn about your business’s function in the market and gain an advantage over its competitors.

Who uses statistical analysis software?

You can find uses of statistical analysis software in many industries, such as psychology, data science, economics, education, epidemiology, business, marketing, medicine, public health, and politics. Due to the rise in big data implementations, statistics is an in-demand skill as companies analyze this data. Explore how a few key industries use statistical and data analysis:

• Manufacturing: Statistics can be used to make informed decisions and predictions about market futures using a business's various data sources.

• Health care: If you work in the health care or pharmaceutical industries, you can use statistics to improve patient treatments, drug therapies, and efficiency in the overall patient experience.

• Government: Statistics can be used in many different fields of government, whether to improve services, make economic forecasts, enhance environmental protections, or strengthen public health outcomes.

Careers in statistical analysis

According to the US Bureau of Labor Statistics, the job outlook for mathematicians and statisticians from 2025 to 2035 is 10 percent, and the outlook for data scientists over the same period is 35 percent [5, 6]. Both of these figures are much faster than the average for all jobs in the US. Below is a list of many different kinds of jobs that use statistical analysis and their median annual salary:

• Data scientist: $158,000

• Market researcher: $74,000

• Statistician: $109,000

• Financial analyst: $107,000

• Actuary: $211,000

• Biostatistician: $128,000

• Machine learning engineer: $165,000

• Economist: $189,000

*All salary information represents the median total pay from Glassdoor as of September 2026. These figures include base salary and additional pay, which may represent profit-sharing, commissions, bonuses, or other compensation.

Advantages of using statistical analysis software

Statistical analysis software helps you produce efficient statistical calculations more quickly than by hand. It can help provide you and your business with other benefits:

• Creating data visualizations in the software, making them easy to analyze by many stakeholders

• Allowing for the processing of much larger, faster data sets

• Leading to informed data-driven decision-making (DDDM) in an organization

Things to consider when choosing the best statistical analysis software for you

When choosing statistical analysis software, you must consider various factors, including price, subscription, and coding requirements. Consider the following factors when you compare statistical analysis software:

• Cost: Enterprise software like SAS and Minitab costs much more than IBM SPSS and free software like RStudio.

• Coding: Consider whether each software has coding integrations from R, Python, or C++ sources. If you need a fully custom environment, consider RStudio, which has many package integrations.

• Tools: Research the kinds of statistical tools and models each software offers and whether you interact with them through a GUI or code.

• Subscription: Many paid statistical analysis software programs have a monthly or yearly subscription for a certain number of seats. Determine your needs and those of your organization as you examine each one.

How to get started in statistical analysis

To start using statistical analysis software, many companies provide free trials that you can use to see if a specific software fits your needs. If you’re new to statistical analysis, you may need to learn some of the basics of statistics before using statistical analysis software. Explore some of the educational paths and skills you’ll need for statistical analysis.

Educational paths

To become a mathematician or statistician, you’ll want at least a bachelor’s degree, but most jobs require a master’s degree in either mathematics or statistics. Becoming a data scientist requires a similar level of education, with a bachelor’s degree in math, statistics, or computer science being the most common path. However, many employers in this field prefer candidates with a master’s or doctoral degree.

Developing skills and expertise

While earning a degree is the formal educational path to learning statistical analysis methods, you can develop skills or hone your expertise through self-study or online courses. To self-study statistics, focus on the essential concepts in statistics, such as:

• Descriptive statistics

• Probability distribution

• Hypothesis testing

• Regression analysis

Exploring statistics can help you build upon the statistical analysis skills you use in data science. If you want to develop skills in statistics through online learning, consider the Introduction to Statistics course from Stanford on Coursera.

Explore learning tools that fit your goals and pace

Subscribe to our weekly LinkedIn newsletter, Career Chat, for updates on popular skills, tools, certifications, and more. Then, check out some of our other free resources to keep learning more about extracting insights from data:

• Read an insider story: Meet the Statistics Teacher Who's Going Back to School for Data Science

• Take the quiz: R Programming Quiz: Assess Your Skill Level

• Watch on YouTube: BI vs Data Analytics: What’s the Difference?

Whether you want to develop a new skill, get comfortable with an in-demand technology, or advance your abilities, keep growing with a Coursera Plus subscription. You’ll get access to over 10,000 flexible courses.