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Online Master of Science in Biostatistics

The online Master of Science in Biostatistics (MSBST) is designed for professionals with a bachelor’s degree who aspire to start or advance their career in biostatistics, statistics or data science.

Offered by the School of Public Health & Information Science at the University of Louisville, this program delivers a forward-thinking curriculum that emphasizes medical, dental, nursing and healthcare applications of statistical analysis, with applicability across countless other industries. Through state-of-the-art coursework in designing research studies and applying modern statistical analysis, you’ll be equipped with the expertise needed to meet the growing industry demand for skilled statisticians who can effectively drive evidence-based decisions.

100% ONLINE COURSES

Complete this degree on your own time through fully online coursework and learning tools.

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32 CREDIT HOURS

Only 12 courses are required for graduation. Math Tools prep course also available in summer.

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100% GRADUATE EMPLOYMENT RATE

To-date, all graduates of the MSBST program at UofL have found employment in a biostatistics-related role

Online learning video - Master of Science in Biostatistics

"“Statisticians and individuals who are trained in quantitative methods are going to be the invisible force for doing an impeccable job to advance the [data] industry today "


DR. KB KULASEKEERA
PROGRAM DIRECTOR
MASTER OF SCIENCE IN BIOSTATISTICS

Public Health 2020
MSBST 2018 Healthcare Management Degree Most Affordable
50 best online colleges 2019 2020

How Much Will I Pay?

$764 per credit hour
$250 active duty military rate per credit hour

Tuition & Aid    

Tuition rate does not include costs associated with a specific course or program, such as textbooks. Tuition and fees are subject to change at any time without prior notice.

Highlights

  • Learn rigorous statistical analysis methodology you can apply to any industry.
  • Gain extensive training in statistical computing and data management in the SAS, SPSS and R statistical software programs.
  • Join one of the very few comprehensive biostatistics programs in the nation.
  • Build upon your background—the program is open to individuals with a bachelor’s degree in any field with some exposure to quantitative background (see Apply Now tab for more details).
  • Complete your degree in as few as 3 semesters.
  • Transfer up to 6 credits from a regionally-accredited institution.


Outcomes

Ongoing innovation in a variety of industries creates the need for skilled statisticians and bioinformatics professionals to drive evidence-based decisions in medicine, nursing, public health, commerce and engineering. The field is projected to experience a staggering 34% growth rate from 2014-2024. In 2016, statisticians earned a median annual salary of $80,500 (BLS.gov).

Graduates of our online MSBST program are equipped with the expertise needed to pursue careers with:

  • Pharmaceutical corporations
  • Insurers
  • Medical researchers
  • Government agencies (FDA, NIH, Census Bureau)
  • Universities and research institutions
  • Hospitals and cancer centers

Not quite ready to commit to a master’s program?

Get a feel for the industry with an online Graduate Certificate in Biostatistics—a 12 credit hour (4 course) program that can be the perfect platform to launch your next education achievement.


Application Deadline Term Start Date
July 15 Fall August

Steps to Apply

  1. Complete graduate application
  2. Submit $65 non-refundable application fee
  3. Submit GRE scores
  4. Submit all official transcripts of graduate work in English from all previous institutions

Note: Electronic transcripts are only accepted directly from the institution(s). Please have electronic transcripts sent directly to UofL Graduate Admissions Office.


Admission Requirements

  • Bachelor’s degree in any field from a regionally-accredited institution
  • Minimum undergraduate GPA of 3.0 to be admitted in good standing (applicants with a lower GPA may obtain conditional admission)
  • Mathematics coursework covering differential and integral calculus including multi-variable integration
  • Minimum of two letters of recommendation written within the past twelve months
  • GRE scores – considered in the context of other required components of the application; successful students in our program have a median [Q1, Q3] GRE Quantitative score at the 80th percentile [63, 91]
  • Statement of purpose

Send all materials to:
Graduate Admissions
University of Louisville
2211 S. Brook Street
Louisville, KY 40292
gradadm@louisville.edu


Concerned you don’t have the required mathematics background? Don’t let that hold you back!

Apply today and kick-off your program with our online Math Tools courses to prepare for the mathematical rigor necessary to complete the M.S. in Biostatistics degree.

While completing your Math Tools courses, you can begin working toward your master’s by earning a Certificate in Biostatistics online. The certificate can be completed in tandem with the Math Tools courses (there is no quantitative requirement for the certificate program)—with all certificate credits applied toward your degree!


International Students

The Master’s in Biostatistics program is open to international students. If you live outside of the United States and intend to complete an online academic program from your home country, be sure to review these additional requirements for international students.

  1. All transcripts not in English must be certified as authentic and translated verbatim in English. A foreign credential evaluation may be required. View the FAQs for more information.
  2. Students whose primary language is not English must show English language proficiency by attaining one of the following:
    • Total score at or above 550 (paper based test and a 5.0 on the TWE test), 213 (computer based test), 79 (internet based test), OR
    • Submitting an IELTS test score of 6.5 or higher, OR
    • Successful completion of the exit examination for the advanced level of the Intensive English as a Second Language Program (IESL) at the University of Louisville, OR
    • Demonstration of a degree award from an acceptable English language institution
  3. International students will not be issued a U.S. visa, since there are no campus attendance requirements. All courses in the program are taught 100% online, allowing you to attain the entire degree from the comfort of your home and at any time convenient for you, regardless of your current location, anywhere in the world.

For more information on the admission and application process, please contact our Online Learning Enrollment Counselor at 800.871.8635 or by email at online@louisville.edu.


Start Your Application

The online M.S. in Biostats degree is a 32 credit hour program that requires 24 credit hours in core courses and 8 credit hours in electives.


Core Courses


Courses Hours
PHST 661 Probability 3
PHST 680 Biostatistical Methods I 3
PHST 624 Clinical Trials I 2
PHPH 523 Public Health in the U.S.1 (2)
PHST 662 Mathematical Statistics 3
PHST 681 Biostatistical Methods II 3
PHST 684 Categorical Data Analysis 3
PHST 625 Clinical Trials II 2
PHST 683 Survival Analysis 3
Electives2 8
Total 30 (32)

  1. PHPH 523 fulfills the accreditation requirement that all graduates from the School of Public Health and Information Science receive foundational instruction in public health. The two credit hours for PHPH 523 do not accrue toward the 30 hours required for the MS degree completion. Students with a prior degree and/or coursework in a public health field or substantial experience in the public health workforce may be relieved of this requirement, per approval of the Associate Dean for Academic Affairs.
  2. Electives are chosen with the approval of a faculty advisor. Students are typically encouraged to select electives from among the following courses offered by the Department of Bioinformatics and Biostatistics:
    • PHST 603 Biostatistics Public Health Practicum I
    • PHST 620 Introduction to Statistical Computing
    • PHST 675 Independent Study in Biostatistics
    • PHST 682 Multivariate Statistics

Students may also choose elective courses outside of the department in fields related to biostatistics, such as Mathematics, Epidemiology, and Computer Science (subject to approval from faculty advisor). Students are responsible for ensuring they have met the prerequisites for these courses.


Course Descriptions


PHST 661 Probability
Prerequisite: Enrolled in BDSCMS BIO or Math major in Graduate School. Introduction to probability theory. Topics include axioms of probability, conditional probability, discrete and continuous random variables, probability distributions and joint distributions, moments, moment generating functions, mathematical expectation and transformation of random variables, limit theorems (Law of Large Numbers and Central Limit Theory).


PHST 680 Biostatistical Methods I
Prerequisite: Enrolled in BDSCMS BIO, PH MPH and PHST 501, Math major in Graduate School. A mathematically sophisticated presentation of statistical principles and methods. Topics include exploratory data analysis, graphical methods, point and interval estimation, hypothesis testing, and categorical data analysis Matrix algebra is required. Data sets drawn from biomedical and public health literature will be analyzed using statistical computer packages.


PHST 624 Clinical Trials I
Prerequisite: Enrolled in BDSCMS BIO, CISCCCI, CISCMSC, MD/MSc. Phases of Trials, Ethical Issues, Basic Design, Inclusion and Exclusion criteria, Randomization and Blinding, Sample Size, Monitoring Response Variables, and Issues in Data Analysis


PHST 662 Mathematical Statistics
Prerequisite: Enrolled in BDSCMS BIO, Math major in Graduate School and PHST 661. A first course in statistical theory. Topics include limiting distributions, maximum likelihood estimation, least squares, sufficiency and completeness, confidence intervals, Bayesian estimation, Neyman-Pearson Lemma, uniformly most powerful tests, likelihood ratio tests and asymptotic distributions.


PHST 681 Biostatistical Methods II
Prerequisite: Enrolled in BDSCMS BIO, PH MPH, Math major in Graduate School and PHST 680. This course offers a mathematically sophisticated introduction to simple regression models and analysis of variance. Matrix algebra is required and data analysis will be illustrated drawing examples from biomedical and public health literature.


PHST 684 Categorical Data Analysis
Prerequisite: Enrolled in BDSCMS BIO, PH MPH and PHST 501. Topics include inference for two-way contingency tables, models for binary response variables, log-linear models, models for ordinal data, multinomial response data, Poisson regression and analysis of repeated categorical response data. Emphasis will be placed on methods and models most useful in biomedical and public health research.


PHST 625 Clinical Trials II
Prerequisite: PHST 624 and enrolled in BDSCMS BIO, CISCCCI, CISMSC, MD/MSc. Sample Size and Power Analysis, Survival Analysis, Sequential Design, Meta Analysis, Reporting and Interpreting of Results, Multicenter Trails. SPSS will be used.


PHST 683 Survival Analysis
Prerequisite: Enrolled in BDSCMS BIO, PH MPH and PHST 681. Statistical methods for analyzing survival data. Parametric and nonparametric methods for complete and incomplete data, life-table, KM estimator, accelerated lifetime models, proportional hazard models, log-rank tests, and goodness-of-fit tests.


PHST 620 Introduction to Statistical Computing
Prerequisite: Enrolled in PH MPH and PHST 500. This course provides an introduction to SAS. It will give students an overview of the SAS system under MS Windows and provide fundamental grounding in the environment for accessing, structuring, formatting and manipulating data. Students will learn how to summarize and display data, and the inference between data steps and procedures to get information out of data.


PHST 682 Multivariate Statistics
Prerequisite: Enrolled in BDSCMS BIO, Math major in Graduate School and PHST 681. The topics covered in this course include the multivariate normal distribution, inference for mean vectors, inference for covariance and correlation matrices, analysis of covariance structure, analysis of serial measurements, factor analysis, and discriminant analysis. Statistical methods and models that are most useful in multivariate data analysis will be introduced. Instruction will also be given in the proper use of R to carry out these analyses.



    Featured Faculty


    Jeremy Gaskins, Ph.D., Assistant Professor

    Jeremy received in his Ph.D. in Statistics from the University of Florida in 2013. His areas of research include Bayesian statistics, longitudinal data, variable selection, and missing data models. He is the instructor for the PHST 661 Probability and PHST 662 Mathematical Statistics sequence of courses.

    Bakee Gunaratnam, Ph.D., Assistant Professor

    Bakee earned his Ph.D. from Case Western University in 2013. His primary research interests include stable and Linnik processes, logistic regression and clinical trials. He teaches PHST 620 - Introduction to Statistical Computing (SAS), PHST 624 - Clinical Trials I, PHST 625 - Clinical Trials II and PHST 640 - Statistical Methods for Research Design in Health Studies.

    Riten Mitra, Ph.D., Assistant Professor

    Riten earned his Ph.D. in Biostatistics from the University of North Carolina at Chapel Hill in 2010. His methodological research centers on Bayesian models and their applications in genomics and proteomics. He is an instructor for PHST 682 - multivariate statistical analysis.

    Rebekah Robinson, Ph.D., Assistant Professor

    Rebekah received her Ph.D. in Applied and Industrial Mathematics from the University of Louisville in 2012 with her research primarily focused on segmented regression models. She joined the Biostatistics Department in the fall of 2016 and is the instructor for PHST 680 & 681 (Biostatistical Methods I & II) for the online Master of Science in Biostatistics.

    Qi Zheng, Ph.D., Assistant Professor

    Qi earned his Ph.D. from, Clemson University in 2013. His areas of research include high dimensional data, nonparametric modeling and survival data analysis. He teaches PHST 684 - Categorical Data Analysis.



    The set of questions and answers outlined below can help you learn more about our program, delivery method, application and admission process, financial aid options and how to succeed as an online student at UofL. 


    • Is there a specific undergraduate degree required for admission into the Master of Science in Biostatistics?
      No. Admission to the program requires an exposure to statistics -- preferably via a course at a sophomore level or above -- and a background in differential and integral calculus including multi-variable integration. Coursework in linear algebra could be required for some electives.
    • Is the Graduate Records Exam (GRE) required for admission?
      Yes, we require scores from the general GRE as part of the application. While there is no lower bound for GRE scores to gain admission, we look at this as a component of a comprehensive review of the application for admission. Waivers may be granted for students with sufficient mathematics/statistics background.
    • Is a foreign credential evaluation of transcripts from international institutions required?
      Not necessarily. English-language copies of all post-secondary official transcripts must be included as part of the application materials. After review of these transcripts, the department’s admissions committee may require submission of a foreign credential evaluation in addition to the originally submitted transcript.
    • What are the English language proficiency requirements for admission?
      Students must achieve a minimum score on the TOEFL exam (550 on the paper-based TOEFL, 213 on the computer-based TOEFL, 79 on the Internet-based TOEFL), a score of 6.5 or better on the IELTS examination, successful passing of an exit examination for the advanced level of an Intensive English as a Second Language Program, or demonstration of a degree awarded from an institution with instruction primarily in English, as formally documented by an appropriate institutional official.
    • What type of information should be included in the statement of purpose?
      The statement of purpose should cover your background, experiences, and motivations and reason for undertaking graduate work in biostatistics. It is important that this statement describe both your strengths and weaknesses so that the admission committee can make an informed decision regarding admission.
    • What are possible career outcomes?
      There is a very high demand for biostatistical training in many industrial sectors including the insurance, pharmaceutical, and chemical industries, as well as at research institutions and various government agencies (NIH, FDA, Census Bureau, Bureau of Labor Statistics etc.). Job growth data from the Bureau of Labor Statistics predict that there will be a 34% increase in the need for statisticians in the labor market from 2014-2024 (https://www.bls.gov/ooh/). Another study by McKinsey Global Institute predicts that the United States will need over 150,000 professionals with expertise in statistical methods by 2018 (www.mckinsey.com). Our graduates have secured employment at Humana, Google, UPS, NIH, Texas Children’s Hospital, and several other major employers in the United States.
    • What are the advantages of an MS in Biostatistics over a Bachelor’s degree in statistics or mathematics?
      Graduates with Master’s degrees in Biostatistics tend to be more attractive to employers in the industrial market than graduates with Bachelor ’s degrees are and generally better compensated, too. The 2015 Salary Survey of Business, Industry, and Government Statisticians published by the American Statistical Survey shows that the median salary for an entry-level employee in industry with a Master’s degree in statistics, biostatistics, or mathematical statistics was $83,700
    • Can the MS degree be completed part-time?
      Yes. Our advisors work with part-time students to develop course plans for completion of the degree.