By Dr. Jerome Roehm, Assistant Professor of Mathematics and Data Analytics

If you are a post-baccalaureate student preparing for graduate or professional school, you are likely thinking carefully about what will make your application stronger and your transition into advanced study smoother.

Maybe you are aiming for medical school, PA school, public health, or nursing.

Or perhaps your path leads toward business school, data analytics, education, social sciences, or another professional program where evidence and decision-making matter.

Across all of these fields, one expectation is becoming increasingly universal: You must be able to understand, interpret, and communicate with data.

That is where MTH-120: Introduction to Data Through Visualization can play a valuable role.

This course is designed to help students develop confidence with data through visual thinking, real-world applications, and modern tools—without requiring an extensive mathematical background.

Building Confidence With Data—Without the Heavy Math

Many returning students worry that working with data means jumping into advanced statistics or complicated math. For some, it has been years since they last took a quantitative course. Others may have avoided statistics altogether during undergrad.

This course is built specifically to remove that barrier.

MTH-120 is an introductory course that assumes no specialized background. Instead of focusing on memorizing formulas, students learn to think statistically by exploring data visually and asking meaningful questions:

  • What is this dataset actually measuring?
  • What patterns or relationships stand out?
  • What conclusions are supported by evidence—and what conclusions are not?
  • How can results be communicated clearly to others?

These are the kinds of skills that matter in graduate and professional environments. Whether you are reading academic research, evaluating business trends, interpreting healthcare outcomes, or analyzing policy data, the ability to reason carefully from information is essential.

Skills That Translate Directly Into Graduate-Level Expectations

By the end of the course, students develop practical, transferable abilities, including:

  • cleaning and organizing raw data
  • creating clear and effective visualizations
  • interpreting patterns and relationships
  • communicating results in a meaningful way
  • explaining key characteristics of datasets

These are foundational skills for success in nearly any graduate or professional program, where students are expected to move beyond computation and toward analysis, interpretation and communication.

From Research Questions to Dashboards: Learning the Real Workflow

Another strength of the course is that it mirrors how data is actually used in professional settings.

Students progress through the full arc of applied data work:

  • defining variables and forming research questions
  • understanding how data is collected and what can go wrong
  • cleaning and organizing information in spreadsheets
  • creating summaries and pivot tables
  • designing thoughtful visualizations
  • building dashboards that communicate a cohesive story

This workflow prepares students not just to “do an assignment,” but to think the way graduate students and professionals are expected to think when working with evidence.

A Final Project That Strengthens Your Portfolio and Your Voice

The course culminates in a final project that is especially valuable for students preparing for their next step.

Rather than a traditional exam, students choose their own dataset—often connected to their interests or intended field—and create a visualization-based presentation.

This experience provides something graduate programs increasingly value: evidence that you can work independently with real information and communicate what you find.

A strong final project can demonstrate:

  • analytical maturity and intellectual curiosity
  • comfort working with open-ended questions
  • the ability to present findings clearly and professionally
  • a concrete example of applied skill beyond coursework

For post-bacc students, this can become a meaningful portfolio artifact—something you can reference in applications, interviews, or future academic work as proof that you can engage with data thoughtfully and effectively.

It is not just a class project. It is practice in professional communication.

Why Choose MTH-120 Through Doane’s Online Learning Academy?

Doane’s Online Learning Academy offers flexible, high-quality online courses designed for adult learners, career changers, and graduate-bound students.

MTH-120 is:

  • fully online and asynchronous
  • approachable for beginners
  • focused on real-world, transferable skills

If you are preparing for the next stage of your education, learning to think clearly with data is one of the smartest investments you can make now.

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