Course syllabus

DESCRIPTION: This course provides students in Natural Resources Conservation (NRC) and Organismic and Evolutionary Biology (OEB) with an understanding of basic statistical concepts critical to the proper use and understanding of statistics in ecology and conservation science and prepares students for subsequent NRC courses in ecological modeling.

The lecture covers foundational concepts in statistical modeling, basic study design concepts, and lays out the “landscape” of statistical methods for ecological modeling. Specifically, lecture focuses on the following:

• Foundational concepts in statistics.–Understanding the conceptual foundations of statistics in ecological research; emphasis is on conceptual underpinnings of statistics not methodology, with a focus on defining statistical models and the major inference paradigms in use today.
• Study design concepts.–Understanding major study design concepts and common issues that arise in ecological studies; emphasis is on confronting practical issues associated with real-world ecological study designs and statistical modeling.
• Landscape of statistical methods.–Understanding the complex “landscape” of statistical methods and choosing the “right” method(s) for the problem; emphasis is on laying down a road map to help students determine the method or class of methods most applicable to a particular problem, not on the actual methods themselves.

The lab introduces the statistical computing language R and provides hands-on experience using R to screen and adjust data, examine deterministic functions and probability distributions, conduct classic one- and two-sample tests, utilize bootstrapping and Monte Carlo randomization procedures, and conduct stochastic simulations for ecological modeling. Specifically, lab focuses on the following:

• R programming language and statistical computing environment.–Learning the R language and statistical computing environment, which serves as the computing platform for all NRC statistics courses; emphasis is on learning fundamental R skills that will allow students to grow and expand their expertise in subsequent courses or on their own.
• Basic statistical methods.–Using R to conduct basic statistic procedures, including data screening and adjustments, classic one and two sample tests, resampling methods and stochastic simulations.
  

WHO SHOULD TAKE THIS COURSE: This course is required for all Master's level graduate students in Natural Resources Conservation Department (NRC) and is likely to be of equal interest to graduate studenets in Organismic and Evolutionary Biology (OEB). Lecture is required for all NRC Master’s level graduate students. Lab is optional, but is highly recommended for all thesis degree students and is prerequisite for all higher level NRC stats courses. Students are not expected to have a strong background in math and statistics.

TEXT: There is no required text for this course. Readings consist mainly of lecture notes prepared by the instructor and occasional assigned journal articles (see course syllabus).

PREREQUISITES: Graduate standing in NRC or OEB, or permission from instructor.