Why Applied Statistics is Important
Applied statistics is a great choice for those with an interest in math, data analysis and problem-solving. What exactly is applied statistics? It is the practice of analyzing data, which includes collecting data, then finding patterns and making actionable decisions based on it. Today, companies have unprecedented access to huge troves of data, meaning that skilled statistics professionals who can take that data and find meaning behind it are in high demand.
Data analysts, biostatisticians, and researchers use applied statistics methods often in their work. There’s also the emerging role of the data scientist: a very in-demand profession with roots in applied statistics and machine learning (a branch of artificial intelligence that uses algorithms and statistical models to teach computer programs to analyze data without being explicitly programmed to do so). Many positions in this field offer engaging day-to-day work and a dynamic, regularly changing environment that stimulates critical
Applied statistics is the foundation of many professions and industries. Interpreting and understanding big data can provide sound statistical thinking and analysis so that companies can improve their business processes and strategies.
Where Do People with Applied Statistics Master’s Degrees work?
Researchers and analysts who choose to study applied statistics at the graduate level often already work in or are looking to pursue a career in a variety of industries, including finance, marketing, science, health, or technology.
Data analysts use applied statistics and data (which can be anything from sales reports to social media statistics) to help companies make better business decisions – cutting transportation costs, deciding which online customers to market to, and more.
From conducting medical studies to creating marketing campaigns, these professionals use advanced statistical methods to gather and collect big data and make inferences from it. Data analysts can help shape public policy, make business decisions, and more.
Data scientists are often data analysts that also have a vast knowledge of applied statistics, software engineering, machine learning, and predictive analytics skills. Data scientists are in huge demand at companies like Facebook, Amazon, and Google.
Biostatisticians are scientific researchers that use applied statistics in the medical and pharmaceutical industries during research studies and medical trials. They’re the people behind medical statements like, “Smoking while pregnant increases your risk of birth defects;” and they’re often involved in testing and monitoring new drugs before they’re released. Biostatisticians also work in health and medical research, creating risk assessment tools to predict outcomes based on patient history. They can even influence public policy: The FDA has its own office of Biostatistics.
Business analysts work in marketing, where they use predictive modeling techniques (an applied statistics method that combines data mining and probability) to target potential customers. Today’s online retailers now have Internet data that not only reveals what users are buying, but what they’re clicking on, how long they’re clicking for, and what they’re putting in their shopping carts. Statisticians working in marketing and data analysis can create algorithms that will suggest certain items to shoppers.
Data analysts and researchers also use their applied statistics skills to work for political campaigns (collecting and analyzing demographic data), as market researchers, and more.
What Skills Do Data Analysts and Data Scientists Need?
Data analysts, data scientists, biostatisticians, and other data researchers must be passionate about applied statistics – able to tackle advanced statistical theories like predictive modeling, data modeling, and linear regression.
The heart of data analysis is being able to find patterns and make sound statistical inferences from huge sets of data, and a solid mastery of applied statistics is the foundation of this skillset. No matter the industry, great data analysts need to know how to derive real answers from large amounts of data.
The data sets most analysts and data scientists are working with are huge (think of everything a company is able to gather from an online user), so statisticians and analysts work to collect and mine data using specialized software programs and programming languages, including SAS, Python, R, and Hadoop.
This software use especially applies to data scientists, who carry out most of their analysis in code – they’re often tasked with solving complex business problems. Most companies are looking for data scientists that have am expert-level knowledge of applied statistics, machine learning, and programming languages.
Applied statistics provides a mastery of the methodologies professional use to find data patterns and make inferences; but beyond identifying important insights in data, data analysts also need to be able to communicate their findings in a way that makes sense to non-statisticians. Just as important as discerning the data is communicating what it means, and how it can be used to shape a company or organization’s future.
Beyond the applied statistics, programming, and communication skills, companies value data analysts – especially business and marketing analysts – that have a strong business acumen. (This is why professionals with a background in management or strategic business analytics are great candidates for pursuing a degree in applied statistics.) Analysts can collect and analyze data all day long, but what makes the difference is when they’re able to take that data and turn it into a solid business decision or plan.
Ultimately, data scientists and high-level analyst and research employers value candidates with master’s degrees and an expertise in applied statistics and programming.
Why Is Applied Statistics in Demand?
Professionals with advanced applied statistics knowledge are in high demand – not only for those who work in research and analytics, but for other fields too.
Businesses, nonprofit organizations, pharmaceutical companies, the government, and more all want analysts, researchers, statisticians, and data scientists who can help make data-driven decisions. Having a gut feeling isn’t how companies do business anymore; with access to so much data, there’s no reason not to harness to the power of it.
The industry supports that notion: According to the U.S. News and World Report, statistician is the No. 2 Best Job in 2019, with a median salary of $84,060. Data scientists can earn an average base pay of nearly $140,000, states job search site Glassdoor. Companies can now collect practically unlimited amounts of data online – transactions, time spent on a website, clicks, search terms, etc. – and they need statisticians and data scientists to collect, analyze, and find patterns in this consumer engagement.
Am I a Good Fit for Studying Applied Statistics?
If you’re interested in applied statistics, you may agree with one of the following statements about your educational or professional background:
You want to level up your applied statistics knowledge and sharpen your data or research analysis skills. You may already work as a marketing analyst or a data researcher, but your applied statistics knowledge may not be as advanced as you’d like. This is especially true if you’re looking to move into the field of data science, where your statistics, machine learning, and programming skills will need to be top notch.
Studying applied statistics can help you learn how to better manage data, understand that data, and use it to analyze and make inferences with high-level statistical methodologies.
You’ve got the strategic mindset and business acumen, and you’re interested in data analyst or data scientist role. You want to be able to evaluate a scenario or identify a problem, and then use data to determine a course of action for solving that problem.
You also believe that solving complex business problems can be done with data, and that data is the solution for sound decision-making and business success. You want to learn how to define a company’s key metrics for success based on data analysis.
You’re a scientist interested in more statistical-driven research. You want to design and develop studies in a specific field of scientific research, or learn know how to communicate your research findings in a way stakeholders will understand. Studying applied statistics gives you advanced knowledge of statistics and software technologies.
What’s Covered in an Applied Statistics Master’s Degree Program?
Most applied statistics programs are, naturally, a deep dive into the field of modern statistics: linear regression, predictive modeling, machine learning, regression analysis, computational statistics, time series analysis, and statistical data mining are a few of the topics covered. Students will use modern statistical theories and data mining techniques to understand giant sets of data that are collected via experiments, surveys, and more.
High-level applied statistics coursework will help students learn how to perform statistical analysis on data, through statistical theories and models and real-world statistical programming languages like SQL and R. Students will learn how to communicate the results of their data analysis through an array of data visualization techniques. They’ll document relevant findings, and then deliver, report, and visualize them with clarity in a way that non-statistics stakeholders can understand.
What Are the Current Job Opportunities for Data Analysts and Scientists?
Those with a master’s degree in applied statistics may be solid candidates for an array of data analyst, research, and data science jobs. These are a few of the most common job opportunities that may be relevant to you, based on recent postings.
This is still a bit of a complex and somewhat undefined job title because the title of “data scientist” is still relatively new. (It was only first coined in 2008.) A data scientist can mean one thing at one company and one very different thing somewhere else, from developing statistical learning models to conducting end-to-end deep data analysis.
Generally, data scientists need a mix of computer science and applied statistics skills, with some solid business acumen thrown in there. Current job listings for data scientists seek employees with strong backgrounds in applied statistics, database systems, and many programming languages like Python, Java, and C++.
Data Analyst/Senior Data Analyst
Data analysts organize, review, and interpret large sets of data and determine how these numbers can help affect positive business decisions. Great data analysts have solid analytical, critical thinking, applied statistics, and communication skills.
Recent job listing for data analysts seek candidates who can use data to generate revenue management insights and recommendations at a mortgage company, and analyze media and social media data to identity trends and improve marketing performance.
Marketing Research Analyst
This professional helps a company decide which goods and services to sell, what audiences to target, where to advertise, and other marketing strategies – by using solid consumer data analysis. These professionals help marketing research teams carry out experiments, and then use applied statistics to analyze the data.
A quantitative skill-set is valued here, as well as a programming background in R, which a number of marketing firms use for market research and insight analysis. In a recent marketing research analyst job listing, the company wanted a candidate with a background in marketing and data visualization.
These analysts typically work for banks, securities firms, mutual funds, and insurance companies, using analytics skills to help companies make sound investment decisions. They keep on top of industry trends but also dig into applied statistics software to analyze financial data and trends to determine solid forecasts. An applied statistics background is key, along with economics and business knowledge.
These statisticians are found in the fields of agriculture and medical sciences – working to plan experiments, collect data, and analyze results. Rather than drive business decisions, biostatisticians typically work in more research-driven fields, and their experiments contribute to groundbreaking studies and reports. They help pharmaceutical companies tests new drugs and work with government agencies to shape public policy.
Companies Currently Hiring Data Analysts
- The New York Times
- Sun Life Financial
Applied Statistics at Michigan Technological University
Michigan Technological University’s online MS degree in Applied Statistics teaches students how to use high-level applied statistics methods and theories to collect data, make inferences from it, and translate those findings into meaningful and practical business decisions. Students not only learn how to tap into big data, but how to visualize and communicate it too – a skill companies in practically every industry are looking for.
The accelerated program consists of ten online courses with a deep focus on high-level applied statistics techniques, plus data visualization and programming. Throughout this program, students will combine tested statistical techniques with emerging technologies, become familiar with industry software tools, work with real data, and build the skills needed to communicate data analysis with consistency and clarity. Study takes place in a flexible online learning environment, meaning students can make room for their applied statistics education in a way that works best for their schedules and lives.