What Is Statistical Analysis? Definition, Types, and Jobs

Written by Coursera • Updated on

Statistical analytics is a high demand career with great benefits. Learn how you can apply your statistical and data science skills to this growing field.

[Featured image] Analysts study sheets of paper containing statistical harts and graphs

Statistical analysis is the process of collecting large volumes of data and then using statistics and other data analysis techniques to identify trends, patterns, and insights. If you're a whiz at data and statistics, statistical analysis could be a great career match for you. The rise of big data, machine learning, and technology in our society has created a high demand for statistical analysts, and it's an exciting time to develop these skills and find a job you love. In this article, you'll learn more about statistical analysis, including its definition, different types of it, how it's done, and jobs that use it. At the end, you'll also explore suggested cost-effective courses than can help you gain greater knowledge of both statistical and data analytics.

Statistical analysis definition

Statistical analysis is the process of collecting and analyzing large volumes of data in order to identify trends and develop valuable insights.

In the professional world, statistical analysts take raw data and find correlations between variables to reveal patterns and trends to relevant stakeholders. Working in a wide range of different fields, statistical analysts are responsible for new scientific discoveries, improving the health of our communities, and guiding business decisions.

Types of statistical analysis

There are two main types of statistical analysis: descriptive and inferential. As a statistical analyst, you'll likely use both types in your daily work to ensure that data is both clearly communicated to others and that it's used effectively to develop actionable insights. At a glance, here's what you need to know about both types of statistical analysis:

Descriptive statistical analysis

Descriptive statistics summarizes the information within a data set without drawing conclusions about its contents. For example, if a business gave you a book of its expenses and you summarized the percentage of money it spent on different categories of items, then you would be performing a form of descriptive statistics.

When performing descriptive statistics, you will often use data visualization to present information in the form of graphs, tables, and charts to clearly convey it to others in an understandable format. Typically, leaders in a company or organization will then use this data to guide their decision making going forward.

Inferential statistical analysis

Inferential statistics takes the results of descriptive statistics one step further by drawing conclusions from the data and then making recommendations. For example, instead of only summarizing the business's expenses, you might go on to recommend in which areas to reduce spending and suggest an alternative budget.

Inferential statistical analysis is often used by businesses to inform company decisions and in scientific research to find new relationships between variables. 

Statistical analyst duties

Statistical analysts focus on making large sets of data understandable to a more general audience. In effect, you'll use your math and data skills to translate big numbers into easily digestible graphs, charts, and summaries for key decision makers within businesses and other organizations. Typical job responsibilities of statistical analysts include:

  • Extracting and organizing large sets of raw data

  • Determining which data is relevant and which should be excluded

  • Developing new data collection strategies

  • Meeting with clients and professionals to review data analysis plans

  • Creating data reports and easily understandable representations of the data

  • Presenting data

  • Interpreting data results

  • Creating recommendations for a company or other organizations

Your job responsibilities will differ depending on whether you work for a federal agency, a private company, or another business sector. Many industries need statistical analysts, so exploring your passions and seeing how you can best apply your data skills can be exciting. 

Statistical analysis skills

Because most of your job responsibilities will likely focus on data and statistical analysis, mathematical skills are crucial. High-level math skills can help you fact-check your work and create strategies to analyze the data, even if you use software for many computations. When honing in on your mathematical skills, focusing on statistics—specifically statistics with large data sets—can help set you apart when searching for job opportunities. Competency with computer software and learning new platforms will also help you excel in more advanced positions and put you in high demand.

Data analytics, problem-solving, and critical thinking are vital skills to help you determine the data set’s true meaning and bigger picture. Often, large data sets may not represent what they appear on the surface. To get to the bottom of things, you'll need to think critically about factors that may influence the data set, create an informed analysis plan, and parse out bias to identify insightful trends. 

To excel in the workplace, you'll need to hone your database management skills, keep up to date on statistical methodology, and continually improve your research skills. These skills take time to build, so starting with introductory courses and having patience while you build skills is important.

Common software used in statistical analytics jobs

Statistical analysis often involves computations using big data that is too large to compute by hand. The good news is that many kinds of statistical software have been developed to help analyze data effectively and efficiently. Gaining mastery over this statistical software can make you look attractive to employers and allow you to work on more complex projects. 

Statistical software is beneficial for both descriptive and inferential statistics. You can use it to generate charts and graphs or perform computations to draw conclusions and inferences from the data. While the type of statistical software you will use will depend on your employer, common software used include:

  • SAS

  • R

  • SPSS

  • Minitab

  • Stata

Read more: The 7 Data Analysis Software You Need to Know

Pathways to a career in statistical analytics

Many paths to becoming a statistical analyst exist, but most jobs in this field require a bachelor’s degree. Employers will typically look for a degree in an area that focuses on math, computer science, statistics, or data science to ensure you have the skills needed for the job. If your bachelor’s degree is in another field, gaining experience through entry-level data entry jobs can help get your foot in the door. Many employers look for work experience in related careers such as being a research assistant, data manager, or intern in the field.

Earning a graduate degree in statistical analytics or a related field can also help you stand out on your resume and demonstrate a deep knowledge of the skills needed to perform the job successfully. Generally, employers focus more on making sure you have the mathematical and data analysis skills required to perform complex statistical analytics on its data. After all, you will be helping them to make decisions, so they want to feel confident in your ability to advise them in the right direction.

Read more: Your Guide to a Career as a Statistician—What to Expect

How much do statistical analytics professionals earn? 

Statistical analysts earn well above the national average and enjoy many benefits on the job. There are many careers utilizing statistical analytics, so comparing salaries can help determine if the job benefits align with your expectations.


Median annual salary: $105,900

Job outlook for 2020 to 2030: 24% [1]

Data scientist

Median annual salary: $108,660

Job outlook for 2020 to 2030: 22% [2]

Financial risk analyst

Median annual salary: $81,410

Job outlook for 2020 to 2030: 6% [3]

Investment analyst

Median annual salary: $81,410

Job outlook for 2020 to 2030: 6% [3]

Operational research analyst

Median annual salary: $82,360

Job outlook for 2020 to 2030: 25% [4]

Market researcher

Median annual salary: $63,920

Job outlook for 2020 to 2030: 22% [5]


Median annual salary: $92,280

Job outlook for 2020 to 2030: 33% [6]

Read more: How Much Do Statisticians Make? Your 2022 Statistician Salary Guide

Statistical analysis job outlook

Jobs that use statistical analysis have a positive outlook for the foreseeable future.

According to the US Bureau of Labor Statistics (BLS), the number of jobs for mathematicians and statisticians is projected to grow by 31 percent between 2021 and 2031, adding approximately 4,100 new jobs a year throughout the decade [6].

As we create more ways to collect data worldwide, there will be an increased need for people able to analyze and make sense of the data.

Ready to take the next step in your career?

Statistical analytics could be an excellent career match for those with an affinity for math, data, and problem-solving. If you want to prepare for a career using statistical analysis, then you might consider taking a cost-effective, online course through Coursera. In Google's Data Analytics Professional Certificate, you'll learn how to process and analyze data, use key analysis tools, apply R programming, and create visualizations that can inform key business decisions.


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Google Data Analytics

This is your path to a career in data analytics. In this program, you’ll learn in-demand skills that will have you job-ready in less than 6 months. No degree or experience required.


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Article sources


US BLS. "Actuaries, https://www.bls.gov/ooh/math/actuaries.htm." Accessed December 14, 2022.

Written by Coursera • Updated on

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