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Extension > Environment > Water Resources > Stormwater Education Program > Environmental Statistics Workshop Series

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Environmental Statistics Workshop Series

Statistical educational programs for natural resource managers and technicians, scientists, technical managers, reviewers and others who want to build statistical strengths.

Environmental Statistics Workshops teach natural resources professionals how to apply statistics to extract basic information from a vast pool of data to make data relationships visible.

The University of Minnesota Extension Stormwater team partners with industry professionals to teach statistical concepts such as mean, average, standard deviation, outlier, skewed distribution, and bootstrapping. Participants learn how to interpret the results of water quality computer models and how to set up an effective sampling program.

The introductory one-day class is designed for anyone who desires a basic statistics review and an introduction to the open-source statistical program "R."

Those who already have basic statistics knowledge or who complete the introductory class may move on to the 4 1/2-day Applied Environmental Statistics workshop, the Statistical Trend Analysis workshop, and the R Coding Intensive.

Upcoming workshops:

Introductory Environmental Statistics Workshop

Thursday, November 10, 2016

8:00 a.m.—3:30 p.m.

Bunker Hills Activities Center, Oak Room, 550 Bunker Lake Blvd NW, Andover, MN 55304

Pre- and post-class webinars on October 27 and November 29, 2016 at 11:00 a.m.

Course information (PDF 287 K)

Register

Statistical assessment tool

Build statistics strength and make sure you're up to speed before the workshop with a free online course that includes an overview of statistical terms, definitions, and basic calculations. The Statistical Assessment Tool includes a welcome video, presentations, exercises, sample files, and a quiz to check your learning.

To access the statistical assessment tool:

Introductory Environmental Statistics Workshop

This workshop offers participants to gain a solid understanding of basic statistic concepts, and learn basic operations with R statistical software. This one-day class is designed for natural resource managers and technicians, statistic, technical managers, reviewers, and others who simply desire a basic statistic review and an introduction to the open-source statistical program "R." Through three modules of lectures, examples, and hands-on exercises, attendees will gain a solid understanding of basic statistical concepts, learn how to access, setup, configure, and perform basis operations with R statistical software and use R to load and assess an environmental data set.

Applied Environmental Statistics Workshop

This workshop offers participants to learn:

This 4 1/2-day course provides hands-on expertise for environmental scientists who interpret data and present their findings to others. Through lectures, examples, and hands-on exercises assessing environmental data with the open-source program R, attendees develop a complete understanding of statistical methods through applications to field-oriented problems in water quality, air quality, and biocontaminants.

Statistical methods is be explained in the light of data with non-detects, outliers, and skewed distributions. Methods for estimation and prediction will be illustrated along with their common pitfalls. Class emphasizes nonparametric methods, including permutation tests and bootstrapping.

Topics covered will include data description, comparing two groups of data, linear regression and multiple regression, analysis of covariance, trend analysis, and logistic regression. Attendees will leave with electronic datasets, course books, and additional resources. Instructor is Dr. Dennis Helsel of Practical Stats and classes are limited to 40 students.



Contact

For more information on these workshops, contact Shahram Missaghi,

miss0035@umn.edu, 651-480-7759

or Larisa Jenrich

jenri001@umn.edu, 651-480-7732

Calendar

Check the Water Resources Calendar of Events for a schedule of community and professional courses.

Class resources

Statistics course series resources (PDF 213 KB)

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