Biometry is the development and application of statistical methods to biological problems. At the University of Wisconsin, biometry refers to this application to problems from plant, animal and agricultural biology. (Biostatistics denotes this application to human biology.) The biometry program is an M.S. degree program in the field of biometry.
The program is interdisciplinary, providing formal course work in statistics and biology, consulting experience, and supervised research combining the two areas. Students completing the program will understand biological processes and have the ability to apply and extend a broad range of statistical concepts and techniques to biological problems. This integration of statistics and biology is the distinguishing feature of the program. The biometry program is distinct from the M.S. statistics program in its interdisciplinary emphasis and corresponding reduced depth in statistics. (Students interested in training with statistical consulting as the primary focus should apply for the M.S. in statistics through the statistics department.)
The biometry program is intended for two groups of students:
- students simultaneously working toward or intending to work toward a Ph.D. in a biological discipline and
- non-Ph.D. students.
Students who complete the M.S. in biometry and the Ph.D. in a biological science should be at the forefront of quantitative biological research. Students who stop with the M.S. in biometry, possibly obtaining another M.S. in a biological science concurrently, will be well suited for positions with industry or government focused on quantitative biological research.
Minimum Degree Requirements and Satisfactory Progress
To make progress toward a graduate degree, students must meet the Graduate School Minimum Degree Requirements and Satisfactory Progress in addition to the requirements of the program.
Minimum Graduate Degree Credit Requirement
Minimum Graduate Residence Credit Requirement
Minimum Graduate Coursework (50%) Requirement
At least half of degree coursework (15 credits out of 30 total credits) must be completed in statistics courses numbered 600 or above (which the statistics department considers to be graduate courses).
Prior Coursework Requirements: Graduate Work from Other Institutions
With program approval, students are allowed to count no more than 9 credits of graduate coursework from other institutions towards the graduate degree credit and graduate coursework (50%) requirements. Coursework earned five or more years prior to admission to the master’s degree is not allowed to satisfy requirements.
Prior Coursework Requirements: UW–Madison Undergraduate
No credits from a UW–Madison undergraduate degree are allowed to count toward the degree.
Prior Coursework Requirements: UW–Madison University Special
No credits earned while a UW–Madison University Special student are allowed to count toward the degree.
Credits per Term Allowed
Program-Specific Courses Required
Yes—see the program website for a list of required courses.
Overall Graduate GPA Requirement
Other Grade Requirements
A grade of B or better must be received in any course used to fulfill the required and elective course requirements.
Candidates who fail to meet satisfactory progress criteria in two consecutive reviews will be dropped from the program.
Advisor / Committee
Students are required to meet with their advisor near the beginning of each semester to discuss course selection and progress.
Assessment and Examinations
Candidates must complete a project with an emphasis on the integration of statistics and science. A final oral examination is also required upon completion of the coursework and project.
The student should make application for both the master's and Ph.D. degrees during the semester in which they defend. In other words, the biometry degree should be completed by the semester in which a concurrent Ph.D. degree is completed. It is expected that all enrolled students will complete the program within three years.
No language requirements.
Prospective students may apply for admission to the biometry program without application to any other program. Prospective students may also apply simultaneously with application to another program or after admission into another program. It is anticipated that most students enrolled in the biometry program will be enrolled concurrently in another program.
Acceptance of a prospective student by a statistical and biological co-advisor, who should be identified at the time of application, is necessary for admission into the Program and input from prospective co-advisors will be sought in the admissions process. It is expected that most students will be supported through a biological department or program or with their own funds. Opportunity for financial support through the program is extremely limited.
Applicants to the M.S. program should have completed the following prerequisites:
- undergraduate calculus (MATH 221 Calculus and Analytic Geometry 1, MATH 222 Calculus and Analytic Geometry 2, and MATH 234 Calculus--Functions of Several Variables or equivalent);
- a course in statistics (HORT/F&W ECOL/STAT 571 Statistical Methods for Bioscience I and STAT/F&W ECOL/HORT 572 Statistical Methods for Bioscience II or equivalent one year sequence);
- background courses in biology (e.g., BOTANY/BIOLOGY 130 General Botany, ZOOLOGY/BIOLOGY 101 Animal Biology & ZOOLOGY/BIOLOGY 102 Animal Biology Laboratory, BIOLOGY/BOTANY/ZOOLOGY 151 Introductory Biology & BIOLOGY/BOTANY/ZOOLOGY 152 Introductory Biology).
The background courses in biology are a bare minimum; it is anticipated that almost all successful applicants will have a strong background in some area of biological science. Under extenuating circumstances, students may appeal to the Biometry Executive Committee for exemptions to prerequisites or requirements.
Knowledge and Skills
- Demonstrates understanding and critical evaluation of statistical methods selected for applications in scientific inquiries.
- Identifies data sources and study design, and assembles appropriate statistical approaches to data analysis, in a particular scientific field of study.
- Evaluates and synthesizes data information pertaining to questions in the field of study.
- Communicates data concepts and analysis results clearly.
- Recognizes and applies principles of ethical and professional conduct.