Statistics and Modeling Courses

These courses build skills in population modeling, biological monitoring, and quantitative assessments needed to support conservation decisions. Participants learn about the modeling process including how to think like a modeler, run popular modeling software, and interpret results from models.

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Target Audience: 

Biologists and others with little or no prior experience with R or statistics who need to collect and analyze data for purposes such as impact assessment and biological monitoring.  

Summary and Objectives:

 This course, along with Field Data...

Target Audience:  

Biologists who are responsible for monitoring or conservation design projects and other population-habitat related studies.  

Summary and Objectives:  

Statistical models are used to understand the mechanisms behind the patterns we see in...

Target Audience:  

Those working on constructing models for the development of Species Status Assessments, updating range maps of endangered species, or other conservation applications.  

Summary and Objectives:  

This course provides participants with skills...

Target Audience:  

Anyone interested in expanding their modeling skillset for the benefit of species conservation.  

Summary and Objectives:  

This course will provide participants with the skills needed to build species distribution models (SDMs) and habitat...

 

Target Audience:  

Biologists and resource managers who are seeking to gain model-building skills to inform research and decision-making in natural resource management. Participants are not required to be highly skilled in mathematics or computing, although familiarity with...

Target Audience:

Biologists and resource managers who are seeking to gain model-building skills to inform research and decision-making in natural resource management. Participants are not required to be highly skilled in mathematics or computing, although familiarity with spreadsheets and how the...

Target Audience:

Target Audience: Biologists and others with little or no prior experience with R or statistics who need to collect and analyze data for purposes such as impact assessment and biological monitoring.

Summary and Objectives:

This course, along with Field Data Management using...

Target Audience:

Biologists who collect and analyze data.

Summary and Objectives:

R is a free software environment for statistical computing and graphics. R is an ever-expanding set of analytical packages that has become the primary tool for data analysis in the broadly defined fields of...

Target Audience:

Target Audience: Biologists and resource managers who are seeking to gain experience developing and running occupancy models. All modeling will be done in R, so a working knowledge of R is required.

Summary and Objectives:

Documenting the presence or absence of species...

Target Audience:

Biologists, technicians, researchers, and natural resource managers involved in data collection and dissemination of biological data results.

Summary and Objectives:

Data management is an integral part of natural resource management. Qualitative, quantitative, and...

Target Audience:

Biologists, technicians, researchers, and natural resource managers involved in data collection and dissemination of biological data results.

Summary and Objectives:

Data management is an integral part of natural resource management. Qualitative, quantitative, and...

Target Audience:

Biologists who:

Make status assessments for reasons such as evaluating the influences of management actions or potential changes in the environment. Monitor species or habitat changes over space or time.

 

Summary and Objectives:

This...

Target Audience:

Anyone who wants to learn R to manipulate data and communicate analysis.

Summary and Objectives:

Participants with no prior experience in R will learn how to transform messy field data into purposeful information for analysis and decision making. Computer programming is a...

Target Audience:

Anyone who wants to learn R to manipulate data and communicate analysis.

Summary and Objectives:

Participants with no prior experience in R will learn how to transform messy field data into purposeful information for analysis and decision making. Computer programming is a...