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Understanding the Relationship Between Econometrics and Data Science in Today’s Economic Landscape

The current landscape of the labor market is seeing an increased demand for professionals who understand the intricacies of interpreting, analyzing, and utilizing economic data. Comprehending the critical relationship between econometrics and data science is essential for businesses seeking to succeed, and they are eager to partner with candidates who can connect the fundamentals that link statistics, quantitative analysis, and policy.

By combining the principles, theories, and methodologies of economics, both the Valpo Certificate of Applied Econometrics and Data Science Foundations Using SAS and the Master of International Economics and Finance degree provide pathwayw for individuals to gain hands-on experience and sharpen their skills.

If you're ready to open exciting new doors, schedule a time to visit our innovative campus or apply today.

What is Econometrics? What is a Data Science Degree?

Both the word and the science of econometrics breaks down into two parts: “econo,” which refers to the study of economics, and “metrics,” which delves into the measures of quantitative assessment. As such, econometrics provides the necessary methods to understand and learn from data. By applying mathematical principles to economic theories, econometricians use statistical models to develop economic theories, test hypotheses, and forecast future trends.

Obtaining a data science degree allows students to understand the integration between statistics, mathematics, computer science, and the data they are examining. Graduates then enter the job market with the skills needed to evaluate and interpret data, solve multidimensional problems, and offer insightful recommendations.

What is Applied Econometrics?

Applied econometrics pertains to understanding theories through the use of applications and problem solving, rather than through mathematical formulas.

5 Ways Econometrics and Data Science Work Together

Econometrics and data science are similar in that they both rely on linear regression and require an exceptional knowledge of statistics. They differ, however, in their aims, with econometrics seeking to comprehend more and test assumptions, while data science leans more towards making informed predictions and information to discover relationships. Even with these differences, the two sciences work incredibly well together, uniquely blending theories with applications.

Interpret Real World Data

Econometrics and data science challenge individuals to think critically about how data works in the real world. From examining how individuals behave to dissecting how markets operate, both methods interpret evidence and analyze outcomes.

Hypothesis Development

Both econometrics and data science are rooted in the understanding of theoretical frameworks, and fusing them together allows for further hypothesis development, as well as determining techniques for selecting appropriate models.

Forecast Growth

Working together, econometrics and data science examine patterns in sequential data, allowing them to forecast values of series, probable trends, and future growth.

Detect Hidden Patterns

Through the use of statistical methodologies such as mixture models and compositional data, econometrics and data science work collaboratively to investigate and detect hidden patterns.

Inform Better Decision Making

Through employing the findings of patterns, trends, and forecasted growth, econometrics and data science provide the foundation for businesses to make the most informed decisions about their economic futures.

Econometrics Jobs and Salaries for Forward-Thinking Data Professionals

Professionals who pursue a career in the econometrics and data science fields will find nearly unlimited possibilities for growth. Leveraging their extensive knowledge and analytical expertise, these roles provide the insights that directly impact some of the largest and most influential businesses in the world.

Econometric Modeler

Econometric modelers translate business ideas into analytical models, resulting in significant contributions. Through machine learning, natural language processing, and image processing, this role innovates results with diverse data sets and cross-functional solutions.

Data Miner

Data miners are responsible for cleaning and preparing data, creating models, testing those models against hypotheses, and publishing those models for analytics or business intelligence projects. Using statistical methods, this role analyzes data, disseminates information, and develops appropriate solutions.

Data Analyst

Found in a wide-ranging array of positions in both the private and public sectors, data analysts contribute to the examination and production of statistical data. The responsibilities of these roles vary, depending on the industry, but often include establishing statistical methodology, market forecasting, creating data archive systems, and developing reports.


Relying on their expertise, statisticians fulfill data analysis needs for complex and unusual problems. These roles are proficient in manipulating and analyzing data, machine learning methods, mixed and generalized linear models, and implementing state-of-the-art data analysis algorithms.

Quantitative Analyst

Quantitative analysts are responsible for developing, implementing, and calibrating various analytical models. Individuals in this role often perform highly complex activities related to analysis, along with providing insights and recommendations.

Job Outlook and Salaries

The fields of econometrics and data science continue to expand rapidly, and the U.S. Bureau of Labor Statistics is projecting that job opportunities will rise nearly 35% by 2030.

The amount of digitally stored data will increase over the next decade as more companies conduct business online through the use of social media, smartphones, and other mobile devices. As a result, businesses will steadily need qualified candidates to analyze the large amount of information and data collected. Statistical analyses will help companies improve their business processes, inform policy decisions, and design and develop new products.

Many of the new jobs for econometricians and data scientists are expected to be in research and development, consulting, and computer systems design. Looking at national averages, the median salaries in these fields range from $90,970 to $167,040.

An Inside Look at Valpo’s Graduate Certificate in Applied Econometrics and Data Science Foundations Using SAS

By providing practical, hands-on learning experiences, the Valparaiso Certificate in Applied Econometrics and Data Science Foundations Using SAS prepares students with an understanding of data manipulation, segmentation, econometric modeling, and forecasting. Students master the use of SAS statistical software in order to perform complicated data analysis, critically evaluate problems, and promote the development of business solutions.

Why Learn SAS?

Statistical Analysis System (SAS) is the software suite developed for advanced analytics, business intelligence, data management, and predictive analytics. Proficiency in SAS is highly valued in the job market, as it allows users to manage and manipulate existing data, analyze data using statistical techniques, and present analysis results in meaningful reports.

SAS skills are always in demand, and having that certification listed on a resume will immediately set you apart from the competition. As a pioneer in programming languages, SAS features the innovative principles and techniques that top companies rely on for their data analytics.

Valpo Graduate Admission Requirements

To qualify for an admission recommendation into a Valparaiso Graduate School program, all applicants must:

  • Have graduated from an accredited college or university with a 3.0 GPA in all undergraduate and/or graduate coursework.
  • Submit all required, official documents outlined under the Domestic or International instructions

Applicants who do not meet these requirements but have reason to believe that they can succeed in and benefit from graduate study will be considered on an individual basis and, if appropriate, may be admitted under certain conditions.

Challenge the Status Quo with Valpo’s Unique Graduate Certificate in Econometrics and Data Science

Students who earn the Valpo Graduate Certificate in Econometrics and Data Science will exit the program equipped with the skills and expertise needed to launch a new path in one of many exciting, interdisciplinary fields. Using the foundations of mathematics, statistics, computer science, and machine learning, graduates will be prepared to enhance their current career trajectory or begin pursuing new opportunities.

Request information about this dynamic program, schedule a time to visit, or apply today to begin building your future tomorrow.


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