Biometrics: info for students

Information for students
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Graduate Students

Why should you choose biometrics?

Biometricians are popular people, even if sometimes for the wrong reasons! Statistical and mathematical analysis forms a critical part of most basic and applied scientific research in forestry and environmental science. Biometrics is about applying t-tests, ANOVA, regression analysis and sampling design correctly. Applied biometrics includes simulation modelling and resource management tool-set development. Biometricians are usually quite busy assisting others with technical aspects of their analysis, if not analyses of their own. And there aren't many biometricians around ... thus, though biometrics can be small but critical part of science and management, there are very few biometricians available to meet this demand. When a job posting for a forest or environmental science biometrician is available, there are usually very few qualified candidates. If you like numbers, precision, and quantitative analysis, and have experience in forestry or ecology, you will find a rewarding career.

Typical course of study: M.Sc. and Ph.D.

At MTU, biometrics can involve applied ecology, silviculture, plant biotechnology or forest forest management. What ties these disciplines together is an emphasis on quantitative, mathematical or statistical analysis. Typically, graduate students will take two three-credit courses in mathematical statistics (MA4760 and MA4770) and at least one graduate-level class in a specialized statistical methodology, such as regression (FW5411), multivariate statistics (MA5741), analysis of natural resources data (FW5410), categorical data analysis (MA5790) or geographic information systems (FW5550). Graduate programs do not emphasize coursework over research, academic and teaching experience; a program is crafted that provides an appropriate package for each individual tailored to their previous experience, skills, and future goals. For more information, and specific requirements, see: http://forest.mtu.edu/gradstudies/.

Graduate Research Assistantships

Regretfully, there are no assistantships open at this time. Please check back in the future. Other opportunities at the School of Forest Resources and Environmental Science may be listed on the main assistantship page at SFRES: http://forest.mtu.edu/gradstudies/openings.htm.

Graduate Classes

FW5411 - Applied Regression Analysis

Regression as a tool for the analysis of forest and environmental science data. Topics include multiple linear, curvilinear and non-linear regression, hierarchial and grouped data and mixed-effects models. Emphasis is placed on application of tools to real-world data. Credits: 3.0 Lec-Rec-Lab: (3-0-0). Restrictions: Must be enrolled in one of the following Level(s): Graduate

FW5412 - Regression with the R Environment for Statistical Computing

Use of R for basic data manipulation, statistical summary and regression. Topics include installing R, data import and export, basic statistics, graphics and fitting of linear, non-linear and mixed-effects models. Credits: 1.0 Lec-Rec-Lab: (0-1-0). Restrictions: Must be enrolled in one of the following Level(s): Graduate. Co-Requisite(s): FW5411.

Undergraduate Students

Why exactly is "sadistics" so important?

Statistics, sometimes affectionately called "sadistics", is pervasive in natural resources management and research. At least a basic working knowledge of simple descriptive and inferential statistics is assumed by most industrial, non-governmental and government employers. Love it, hate it, or just don't care about it, but when it comes to statistics you must know something about it.

Biometrics is more than statistics

The fancy definition for “biometrics” is the field of development and application of statistical techniques to data analysis problems in the biological sciences. A simple description of undergraduate biometrics is “data analysis”. This is so much more than z-tables, t-tests and p-values; it's about using raw data to answer questions in an efficient and effective way. This can be as straightforward as a t-test to compare means, but more likely it's about determining the current population of breeding birds, quantifying the factors that can predict land fragmentation, modelling taper of tree boles, and estimating stored carbon in managed forests. Underneath silviculture, wildlife ecology, conservation biology, entomology and nearly any discipline in natural resources is data analysis. Biometrics is the core tool that enables research and management.

Careers in quantitative forestry and environmental science

Biometricians, or just plain resource managers who aren't afraid of numbers and computers, are in short supply. When a job is posted, it usually isn't filled. Thus, if you master your biometrics skills, when good jobs come around you don't have to compete. Better yet, if you can master even simple statistics you can use these skills to prove other people are wrong!

Undergraduate Classes

FW3200 - Inventory, Monitoring and Data Analysis

Sampling design, implementation and analysis for inventory and monitoring of attributes of stands, forests and landscapes. Includes computing skills for data entry, storage and analysis and application of statistical techniques to answer questions about ecological data. Credits: 4.0. Lec-Rec-Lab: (3-0-3). Semesters Offered: Spring. Pre-Requisite(s): (FW 2050 or FW 2051) and (MA 2710 or MA 2720 or MA 3710).

FW4140 - Vegetation Modelling

FW 4140 - Vegetation Modeling
Use of models in research and management of terrestrial ecosystems. Teaches application with emphasis on philosophy; models as tools, design goals and approaches, and interpreting the meaning and significance of model outputs. Credits: 2.0. Lec-Rec-Lab: (1-0-2). Semesters Offered: Spring.
Restrictions: May not be enrolled in one of the following Class(es): Freshman. Pre-Requisite(s): FW 3010 or FW 3012.