Applied Environmental Statistics 1: (Existing registrants only)
Make Sense of Your Data
To get an idea of what my teaching style is like and what this course is about, view the free "Don't Worry About A Normal Distribution Again" or "Which Of These Things Is Not Like The Others?" videos on this site. They are a preview and a small sample of the content of the AES courses.
This course may be bundled with the AES2 course to save money versus enrolling in both. See the AES 1+2 Bundle in the course listings.
- Graphing data for your insight and to present to others.
- Transformations - what are they used for and when to use them.
- Treat outliers like children -- correct them when needed but never throw them out.
- Applying confidence, prediction and tolerance intervals to practical problems.
- Bootstraps and other computer-intensive methods desperately needed in environmental studies.
- Hypothesis Tests -- how they work. Which types (parametric, nonparametric, permutation) to use?
- Testing the mean/median/precision of two groups, more than two groups, matched pairs, and more.
- Comparing data to a numerical standard.
"When I took this course, I finally realized the meaning of 'Applied' Stats. It did not happen in the many academic stat courses I took! Most of the time, scientists are overwhelmed with a plethora of statistical methods that they never know how or what to use for. In other cases, they use incorrect practices, ending in questionable and/or useless outcomes and interpretations. If you are interested in learning about applied stats and how to make sense of your data, either to write papers, to make sound decisions, or to meet your work goals, I recommend that you take this course. Do not hesitate! What you think is made for pure statisticians, Dr. Helsel makes friendly-to-use every time you get environmental data on your hands! The methods I learned have helped me greatly to interpret data for my PhD dissertation -- investigating how rainfall characteristics are related to agricultural NO3 concentrations -- and am using stat methods that I learned from Dr. Helsel’s course. I recently published the article “Seasonal water quality changes in on-farm water storage systems in a south-central U.S. agricultural watershed” using stats methods from the AES course with Dr. Helsel."
Juan D. Pérez-Gutiérrez, PhD. Candidate (Biological Eng.), Mississippi State Univ.
Your Instructor
Dennis Helsel (Ph.D. Environmental Science and Engineering):
"I'm a translator of statistical methods for scientists. My firm's name, Practical Stats, says it all. I've written/co-authored two textbooks. Statistics for Censored Environmental Data using Minitab and R (2012) pioneered statistical methods for data below detection limits. Statistical Methods in Water Resources (2020) has been cited by scientists throughout the world. I've taught webinars for the National Water Quality Monitoring Council and others; workshops for the American Statistical Association and others; courses such as AES and NADA for scientists in North America, Europe and Singapore since 1990. I worked for 30 years at the US Geological Survey before starting Practical Stats.
In 2003 I received the Distinguished Achievement Award from the American Statistical Association’s Section on Statistics and the Environment for my training courses in applied statistics.
In 2018 I received the Lifetime Achievement Award from the California Groundwater Resources Association for my communication of statistical methods to scientists. My courses provide up-to-date procedures communicated in clear language using video examples of data analysis of 'real data'."
"Best practices in statistics evolve. So much of what many of us were taught in college is not currently the best methods for environmental data. With lots of well-written handouts/slides and good hands-on exercises, everyone who attended the Region 1 EPA-sponsored Applied Environmental Statistics class for Indian Nations learned a lot, both on statistics applied to environmental sampling, and how to use the free R software for data analysis. Representatives from Penobscot Indian Nation, located in central/northern Maine, have attended this and two other classes taught by Practical Stats. These classes have also provided insight into how to improve a program’s study design to better answer the questions Indian Nations ask of their data. What I learned helped us decide which site was the best location for a continuous monitoring platform that would give us the earliest detection of Harmful Algal Blooms (HABs), saving us scarce monitoring dollars."
- Angie Reed, Penobscot Indian Nation