What is Applied Statistics?

Let’s start with a definition of applied statistics: applied statistics is the root of data analysis. The practice of applied statistics involves analyzing data to help define and determine an organization's needs. Because modern workplaces are overwhelmed with big data, many are seeking statisticians, data analysts, data scientists, and other professionals with applied statistics knowledge who can organize, analyze, and use data to solve real-world problems.

Properly analyzing company data can lead to marked increases in efficiency and profitability. For instance, studies show that companies employing data-driven marketing strategies experience up to 20% increases in revenue and 30% decreases in spending.

Beyond businesses, government agencies, nonprofits, and other organizations might use data to help prevent disease, collect important demographic information, steer political campaigns, and test potential life-saving pharmaceutical products. As the power of data continues to be revealed, the demand for statisticians and other professionals with advanced applied statistics skills will likewise increase.

Applied Statistics Vs. Data Science

As the root of data analysis, the study of applied statistics prepares professionals for careers as statisticians, data scientists, data analysts, and more. In other words, applied statistics is a foundation upon which data science is built. Through statistical methods, analysis, and an emphasis on real-world data, applied statisticians seek concrete solutions to tangible problems.

Individuals with a strong background in applied statistics may then become data scientists, but the relationship doesn’t work inversely. That is, those who study data science exclusively would not necessarily be prepared for careers as applied statisticians. And depending on a company’s approach to statistics and data, they may position a data scientist and applied statistician on the same team or delegate their job responsibilities in overlapping ways.

Applied statistics is anchored by the statistics themselves. Data scientists, on the other hand, employ complex computing techniques, statistical inference, and machine learning (the science of teaching computers to analyze data as humans do) to extract information from large data sets. As data scientists observe trends and patterns, they can equip their companies to forecast potential problems, focus on areas ripe with growth potential, and make strategic, data-driven business decisions.

You may find eight different job postings for data scientists and discover that all of them ask for slightly different skills. A background in applied statistics can set you up for success as a data scientist.

Applied Statistics Vs. Statistics

Pure statistics focuses primarily on the numbers, math, and problems themselves. Applied statistics, on the other hand, can be thought of as “statistics-in-action” or using statistics with an eye toward real-world problems and what their solutions might be. Of course, statistics alone can be used pragmatically. However, in general, the emphasis of applied statistics tends to oriented more toward practical benefits.

What Do Statisticians Do?

Statisticians use applied statistics to solve practical problems in today’s data-centric world. They decide what data they need to collect, determine how to collect that data, and then analyze and interpret the data by using statistical tools, algorithms, and software. In short, statisticians take data and turn it into action. Statisticians, data analysts, and other data professionals use applied statistics across a myriad of industries including business, marketing, media, finance, insurance, government, healthcare, manufacturing, and engineering.

How Professionals Use Applied Stats In Various Industries

• studying the effectiveness of new pharmaceutical products
• affecting decisions about public policy
• understanding risks and returns in financial investments
• predicting the potential outcomes of political campaigns
• collecting market study research on online shopping habits
• determining stock market trends
• improving manufacturing processes

 

Here are some notable concrete examples. Google once used applied statistics to predict flu outbreaks based on search data; statistician Nate Silver analyzed data to come up with his election forecasts; and Netflix and Hulu analysts use viewership data to create algorithms that generate recommended content. From engineering to entertainment, then, applied statistics make an impact.

What Are the Career Opportunities for Applied Statistics Experts?

A wide variety of professional opportunities exist for students with applied statistics master’s degrees. The following list is just a selection of the many career paths available.

Why Are People With Applied Statistics Degrees in High Demand?

The Bureau of Labor Statistics (BLS) explains that, as business, healthcare, and governments turn to statistical analysis to inform their decision making, statistics professionals will be in high demand. Also, the increase in data collection from online consumers also creates a need for applied statistics professionals to make sense of that data, helping companies leverage it in useful ways. To put it simply, the world has access to more data than we ever have had before. Now, we need professionals who can put that data to work.

Take a look at the U.S. News & World Report rankings for applied statistics careers:

• Data Scientist: #4 in Best Technology Jobs, #7 in Best Stem Jobs, and #8 in 100 Best Jobs overall.
• Statistician: #4 in Best Business Jobs, #9 in Best STEM Jobs, and #12 in 100 Best Jobs
• Operations Research Analyst: #6 in Best Business Jobs, #10 in Best STEM Jobs, #15 in 100 Best Jobs
• Computer Systems Analyst: #6 in Best Technology Jobs, #18 in Best STEM Jobs, #61 in 100 Best Jobs

The 2023 median salary for mathematicians and statisticians is $104,860. And the predicted growth for these posit according to the Bureau of Labor Statistics (2023). 

If you’re not quite sure whether or not an applied statistics degree is worth it for you, know that many companies look for candidates with graduate-level degrees. Studying applied statistics, then, is a marketable way to gain the skills needed to transition into a more advanced data analysis role in your desired industry.

Is Studying Applied Statistics Right For You?

You’re a good fit for applied statistics if you’re seeking a career in a data-related field, or you already deal with data at your job and want to increase your skills and knowledge. You should also consider a master’s degree in applied statistics if you fall into one of the following groups:

• You have a background in mathematics. Mathematicians, math teachers, and those who have studied math in an undergraduate degree program are excellent candidates for transitioning into careers as statisticians.
• Your background is in research and analytics. Data analysts are in demand in marketing, research, finance, and more. Scientific researchers can also segue into a career as a biostatistician, and market research analysts can increase their applied statistics skills.
• You’re interested in becoming a data scientist. Students with a background in computer science or software programming often need to advance their applied statistics skills in order to enter the world of data science.
• You work as an engineer. Software and electrical engineers use applied statistics with a high degree of regularity. An applied statistics degree can be helpful when pursuing advanced statistical engineer positions.

How Do You Become a Statistician or Data Scientist?

Studying applied statistics, then, is a great first step. Most applied statistics degree programs cover the essentials of data analysis: probability testing, statistical testing, hypothesis testing, parameter estimation, regression analysis, computational statistics, time series analysis, and forecasting, data mining, predictive modeling, and more.

Beyond learning applied statistics theories and methods, you’ll also need the following skills to become a statistician or data scientist:

• skills in data visualization 
• knowledge of programming languages like R and Python
• experience with the SAS software suite
• familiarity with SQL database languages.

An advanced applied statistics program focuses on developing a strategic mindset, technical aptitude, quantitative methods, business acumen, and connective communication. Prerequisites often require pre-calculus and calculus courses, and fundamental math proficiency.

Why Study Applied Statistics at Michigan Tech?

The Masters in Applied Statistics online program at Michigan Technological University prepares students to meet today’s surging demand for data experts. This innovative program, which combines statistics theory and methodologies with emerging technologies, teaches students how to take data, interpret it in an efficient manner, and apply it to the real-world. Coursework includes statistical theory and inference, probability theory, data mining and visualization, and programming languages.

MTU's 100% online, 30-credit, accelerated, and math-focused graduate degree program also gives students the flexibility to complete coursework in a way that works best for their schedules.

For instance, many students study while working full-time, which provides them with the opportunity to apply new knowledge and skills immediately while setting their sites on career advancement or transitioning into a new field. 

Michigan Tech offers three start dates per year to accommodate busy professional schedules. And our accelerated semesters are just seven weeks long.

To take the next step, reach out to Amanda, our graduate admissions advisor. You can call her at 906-487-1000, email her at globalcampus@mtu.edu, or make an appointment in her calendar.

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