The online Certificate in Biostatistics is perfect for those working with statistical data who want to supplement their skills or are seeking a career transition.
Offered by the School of Public Health and Information Sciences at the University of Louisville (UofL), this 5-course (15 credit hour) biostats certificate prepares students to apply fundamental methods for analysis and management of data across various public health industries. Acquire the analytical background and informatics tools you need to meet your professional goals and advance your career in this evolving area.
$764 per credit hour
$250 active duty military rate per credit hour
Students only enrolled in a non-degree certificate program are not eligible to receive federal aid. Tuition rate does not include costs associated with a specific course or program, such as textbooks.
The Certificate in Biostatistics from UofL prepares students for a wide variety of career paths in quantitative data analysis. They can choose to pursue biostats jobs within:
Although admission and enrollment for the certificate program is processed year-round, we encourage all candidates to apply as soon as possible in order to be considered for the next start available.
Send all materials to:
University of Louisville
2211 S. Brook Street
Louisville, KY 40292
International students will not be issued a U.S. visa if admitted to an online program, since there are no campus attendance requirements. All courses in the program are taught 100% online, allowing you to complete the certificate coursework 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 firstname.lastname@example.org.
The online Biostats certificate at UofL is a 15-16 credit hour program that requires 12 credit hours in core courses and 3-4 credit hours in electives (depending on the chosen courses).
|PHST 680 Biostatistical Methods I||3|
|PHST 681 Biostatistical Methods II||3|
|PHST 620 Introduction to Statistical Computing (SAS)||3|
|PHST 684 Categorical Data Analysis||3|
Note: PHST 680 and 681 are prerequisites for PHST 640 and 684.
*Electives can be either PHST 624 Clinical Trials I (2 Hours) and PHST 625 Clinical Trials II (2 hours) or PHST 640 Statistical Methods for Research Design in Health Sciences (3 hours).
PHST 680 Biostatistical Methods I
A mathematically sophisticated presentation of principles and methods of: exploratory data analysis; statistical graphics; point estimation; interval estimation; hypothesis testing of means, proportions and counts; chi-square analysis; rate ratio; and Mantel-Haensel analysis. Matrix algebra is required. Data sets will be analyzed using statistical computer packages; examples will be drawn from the biomedical and public health literature. Emphasis will be placed on methods and models most useful in clinical research.
PHST 681 Biostatistical Methods II
A mathematically sophisticated introduction to: general linear models; regression; correlation; analysis of covariance; one and two-way analysis of variance; and multiple comparisons. Matrix algebra is required. Data sets will be analyzed using statistical computer packages; examples will be drawn from the biomedical and public health literature. Emphasis will be placed on methods and models most useful in clinical research.
PHST 620 Introduction to Statistical Computing (SAS)
This course addresses fundamentals of statistical computing with special emphasis on software tools employed most often in biostatistics.
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 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 684 Categorical Data Analysis
Focuses on statistical methods for analyzing categorical data; topics include inference for two-way contingency tables; models for binary response variables, including logistic and logit models; models for ordinal data; mutinominal response data; and analysis of repeated categorical response data. Emphasis will be placed on methods and models most useful in clinical research.
PHST 640 Statistical Methods for Research Design in Health Sciences
Statistical methods for clinical research and interpretation for the literature.