Tag: applied statistics degree online

How to Become a Medical Statistician

Medical statisticians analyze data to prevent and predict diseases.

Accurate measurements and data analyses are invaluable throughout healthcare systems. That is, sound statistical methods in clinical trials, university research, and hospital operations are crucial to better patient outcomes. Medical statisticians – also known as biostatisticians – are key to setting the foundations of medical research and to clinical decision-making.

Medical statisticians regularly require both applied statistics expertise and healthcare industry knowledge. Merging these knowledge areas is possible with a graduate-level education. If this career intrigues you, read on about the responsibilities in this role.

A Medical Statistician’s Job Responsibilities

Medical statisticians design clinical studies and quality improvement projects. They also perform other data-gathering methods in healthcare settings. That is, they are involved in every step of a project’s development from study design through publication of research results.

Typical employers for medical statisticians include the following:

  • Integrated healthcare systems
  • Pharmaceutical and medical equipment companies
  • Public health departments
  • University research institutes and medical schools

Statisticians in healthcare settings may simultaneously oversee studies and projects in different stages. For instance, take the example of a medical statistician employed by a pharmaceutical company. This statistics professional might work on one of more of the following tasks in a day:

  • Optimizing sample sizes for upcoming clinical trials of new medications and products
  • Updating case report forms with data from ongoing trials
  • Modeling trial results for data on positive and negative impacts
  • Writing the methods section for an application to a regulatory body like the FDA

Because health statisticians are involved with many aspects of healthcare, their careers are highly collaborative. Medical statisticians might team up with physician-scientists, medical writers, clinical managers, and regulatory affairs specialists. They may also work with statisticians at other organizations as part of large-scale research projects.

Preparing For a Medical Statistician Career

An undergraduate degree with a mathematics focus is a good starting point for a career in medical statistics. Professionals pursuing nursing or other care-focused degrees may also leave statistics career options open by taking a few college courses. Truly, successful coursework in calculus, linear algebra, and statistics is helpful no matter your college degree.

However, the most common entry point into a medical statistician career is a master’s degree in applied statistics. Students in this graduate program learn how to use statistical methods to analyze and to solve real-world challenges. Medical statisticians typically build advanced skills in the following areas during their graduate education:

  • Designing and evaluating experiments
  • Communicating research results to stakeholders
  • Employing programming languages, such as R and Python to solve problems
  • Using SAS software for data mining and analysis

Success as a medical statistician, however, extends beyond fluency in statistics and data analytics. That is, medical statisticians also need project management skills to oversee junior staff members and balance research responsibilities. They also require a rich understanding of medical ethics and professional standards.

Looking Ahead: Career Prospects and Salary for Medical Statisticians

A graphic of a bar chart and a trend line.

Increasing complexity in clinical research and health services means there is a high demand for medical statisticians. Overall, the U.S. Bureau of Labor Statistics (BLS) projects a 30% growth in jobs for all statisticians from 2022 to 2032.

This projection far exceeds the estimated 3% growth in jobs for all occupations during the same period. What this growth comes down to is a need for about 10,600 statisticians.

And this long-term demand for statistics professionals in health fields translates into above-average salaries. The BLS found a median salary of $104,860 for mathematicians and statisticians in 2023. Experience and specialized knowledge may lead to higher salaries, with the top 10% of earners reporting salaries of at least $161,300.

Aspiring medical statisticians can boost their career prospects by studying at a leading university. A graduate education focused on the latest methods and tools prepares statisticians for future opportunities. Michigan Tech University offers a Master of Science in Applied Statistics that achieves these goals.

Acquiring Medical Statistician Skills at Michigan Tech

Michigan Tech’s innovative Online MS in Applied Statistics Degree provides entryways into in-demand fields such as medical statistics and others. This program is also flexible. It offers seven-week courses for accelerated learning opportunities as well as three possible start dates. And Michigan Tech does not require GRE or GMAT scores in its free graduate application process.

Applied statistics students work with experienced faculty members on several subjects including the following:

  • Computational Statistics
  • Design and Analysis of Experiments
  • Regression Analysis
  • Time Series Analysis and Forecasting

Prospective students with undergraduate calculus, linear algebra, and statistics coursework are well-positioned for admission into the program. Also, a ten-week bridge course is available for incoming students who need to brush up on their linear algebra skills.

Join Us to Learn More About Applied Statistics.

But a medical statistician is just one example of a possible data-driven career made possible by advanced education in Applied Statistics. Want to learn more about the courses and the program structure in Michigan Tech’s online MSAS program? Explore other career trajectories?

Then attend our virtual interest session on Tuesday, November 12, 2024, at 11:30 AM ET.

Linear Algebra Bridge Course Returns for Fall 2024

 A 3-D representation of Linear Algebra equations.

On Monday, September 16, 2024, Teresa Woods is once again teaching her ten-week, noncredit, asynchronous, online course: Linear Algebra: A Bridge Course for Prospective Applied Statistics Students.

If you’re unfamiliar with the term bridge course, it is a short, intensive, preparatory course. Bridge courses help learners acquire the necessary knowledge and skills to enter advanced study, which might mean an undergraduate program, graduate degree, or graduate certificate. Often, these courses are meant for students who have been provisionally accepted into a program.

Woods’ course is an effective, low-cost option for prospective students who need the linear algebra requirement to enroll in MTU’s Online Master of Science in Applied Statistics program. However, those interested in brushing up on their linear algebra, so that they can later apply to the MSAS program could also take it.

The course’s very practical curriculum covers the fundamentals of linear algebra as they are used in applied statistics. Some of the topics include, but are not limited to, the following:

  • systems of equations
  • vectors
  • matrices
  • orthogonality
  • subspaces
  • the eigenvalue problem

Students will benefit from an interactive learning experience that will make the concepts stick. That is, the course involves helpful instructor-led videos, extensive auto-graded exercises in Pearson’s MyLab Math, periodic review assignments, and regular instructor feedback.

What is Linear Algebra?

Algebra is a broad field encompassing the study of mathematical symbols and the rules for manipulating them. It includes various sub fields, such as elementary algebra, abstract algebra, and number theory.

Linear algebra, a specialized branch of algebra, focuses on the study of vectors, vector spaces (or linear spaces), matrices, eigenvalues and eigenvectors, linear transformations, and systems of linear equations. This foundational area of mathematics has applications in several fields, such as physics, computer science, engineering, economics, and applied statistics.

  • In physics, experts use linear algebra to describe physical systems, including quantum mechanics, classical mechanics, and relativity.
  • In engineering, those working in control theory, signal processing, and structural analysis recruit linear algebra tools.
  • Computer scientists use this branch of algebra in computer graphic creation, machine learning, data mining, and optimization problems.
  • Also, those in the field of economics apply linear algebra when modeling economic systems, analyzing input-output models, and optimizing resource allocation.

What is the Relationship Between Linear Algebra and Applied Statistics?

And, of course, linear algebra plays a key role in applied statistics.

Applied statistics is the implementation of statistical methods, techniques, and theories to real-world problems and situations in science, engineering, business, medicine, social sciences, and more.

It involves collecting, summarizing, analyzing, interpreting, and presenting data to make informed decisions, analyze scenarios, solve problems, and answer questions.

Applied statisticians often use linear algebra to analyze and then visualize data.

Applied statisticians also use advanced techniques, such as machine learning algorithms, to extract insights and patterns from large datasets. They work in a wide range of places: research institutions, the government, business and finance, universities, healthcare systems, and more.

These experts regularly apply linear algebra, primarily because of its ability to handle large datasets and complex calculations efficiently. 

What Are Some Real-World Examples of Linear Algebra and Applied Statistics?

Here are a few scenarios in which linear algebra and applied statistics work together:

  • A statistician working for Netflix might collect and then simplify data on user ratings for various movies. Next, they would represent that data as a matrix and train the model. By uncovering patterns in the ratings, they could then use the model to generate an effective recommendation system. This approach is also widely used in e-commerce sites and music streaming services.
  • Furthermore, a real estate agent might use linear regression, a common method for determining outcomes, to predict how housing prices will increase or decrease in the next year. This information would help them price houses in their portfolio, estimate their commission, and so on.
  • In the healthcare sector, professionals use linear algebra and applied statistics. Principal Component Analysis (PCA) helps reduce the complexity of a large dataset by identifying key patterns and relationships between variables. Through this approach, health officials can then predict and intervene on disease outbreaks more effectively.
  • And, of course, linear algebra and applied statistics work together in several processes involving elections. These include voter segmentation and targeting, predictive modeling, analyzing voting patterns, polling analysis, and redistricting and gerrymandering.

About Your Instructor

Teresa Woods, associate teaching professor in Mathematical Sciences, is helming this course. Woods also advises students and serves as assistant to the department chair.

Woods’ received her Master’s of Science in Mathematical Sciences from Michigan Tech in 2017. Her master’s report “ANALYSIS OF ALEKS MATHEMATICS PLACEMENT TEST DATA” combined her two areas of expertise (and passions): mathematics and educational assessment. That is, she holds both an MS in Mathematical Sciences and an MS in Education (with a focus on adult learning.)

If you take this course, you’ll benefit from an instructor who has considerable experience in teaching, a wealth of enthusiasm for elementary linear algebra, and a rich history in designing and delivering online courses. 

Reach Out if You’d Like to Learn More.

Need advice on whether this course is right for you? If so, please contact Teresa Woods at tmthomps@mtu.edu. Or if you have questions about our online MSAS program, contact Amanda at globalcampus@mtu.edu.