Free Webinars

How Many Observations Do I Need?
Feb 4, 2020 10 am Pacific, 1 pm Eastern.
Webinar Registration link

See our Videos page for less-technical videos on environmental statistics. They are free to stream and watch.

Our Online Training Center streams the free recordings of our 'technical' webinars, listed below. .
The webinars will be listed as free courses. Each takes about 60 minutes.
Q&A files as an Excel document, and slides as a pdf document, can be downloaded from our Downloads page.

Webinars on Stats for Data with Nondetects:
1. Intro to Nondetects and Data Analysis
An introduction to data analysis for variables with nondetects.
Materials from the webinar (including slides and info) can also be downloaded as a zip file:
Download here

2. Fitting Distributions to Data with Nondetects
Making the most of small datasets with nondetects.
Recorded 2/19/2019. Q&A file and pdf of slides also available for download on our
Downloads page.

3. Testing Groups of Data With Multiple DLs
“ANOVA-type” tests and multiple comparison tests with nondetects.
Recorded 3/19/2019. Q&A file and pdf of slides also available for download on our
Downloads page.

4. The Mystery of Nondetects: How Censored Data Methods Work
Recorded 5/21/2019 Q&A file and pdf of slides also available for download on our Downloads page.

5. Correlation and Regression for Data with Nondetects
You can do it all, without substituting fabricated values.
Q&A file and pdf of slides also available for download on our Downloads page.

6. Trend Analysis for Data with Nondetects
Are concentrations changing over time? Can I tell even when there are multiple detection limits used?
Parametric and nonparametric methods for data with nondetects, including the Seasonal Kendall test for trend.
Q&A file and pdf of slides also available for download on our Downloads page.

Webinars related to our Applied Environmental Statistics courses:
7. Seven Perilous Errors in Environmental Statistics
Seven common errors to avoid!
Seven common errors in statistical analysis by environmental scientists all stem from an outdated understanding of statistics. I'll define the seven 'perilous errors' and how each can be avoided. They revolve around old ideas about hypothesis tests, p-values, using logarithms of data, evaluating what is a good regression equation, evaluating outliers and dealing with nondetects. Understanding why each error is perilous can save the scientist from publishing incorrect statements, using inefficient analysis methods, and wasting scarce financial resources. These errors have persisted through the years -- break the cycle and step into the 21st Century.

8. Intro to R
Break down the barrier of how to get started using R!
R is one of the most widely used statistics software packages in the world. Its versatility as a programming language and its interconnectivity with email, web page generation and other computer processes make it a bit daunting for people just starting to use it for data analysis. It need not be that way. This webinar introduces you to R software and its use for data analysis. You'll learn how to type commands, install and load packages, and use the pull-down menus of R Commander (Rcmdr) to compute confidence intervals and a test for whether the mean exceeds a numerical standard.

9. Forty Years of Water Quality Statistics: What's Changed, What Hasn't?
Some folks are still using methods from the era of black rotary-dial phones. You've upgraded your phone. How about updating your statistical methods? (this is also available on our Videos page)
Materials from the webinar (including slides and info) can be downloaded from our Downloads page.

10. Never Worry About A Normal Distribution Again!
Permutation Tests and Bootstrapping
Traditional parametric tests for differences in means (Analysis of Variance, t-tests and more) as well as t-intervals require data within groups to follow a normal distribution. If this isn't so, p-values may be inflated so that differences in means are not detected, and confidence intervals are often too wide. Permutation tests and bootstrap intervals avoid the normality assumption, returning accurate p-values and interval widths while being distribution-free. These methods are widely used in a variety of applied statistics fields including environmental science, but have not been sufficiently used in water quality, air quality and soils applications. This webinar will describe how these methods work, where you can find them, and demonstrate their benefits over older traditional methods.

11. Which of These Things is Not Like the Others?
How Multiple Comparison Tests Work
Multiple comparison tests determine which groups differ from others. Why are they needed following an ANOVA or Kruskal-Wallis test? How do they work? There are familiar types such as Tukey's test, and a newish version called the False Discovery Rate. Learn why the False Discovery Rate is a method you should probably be using.

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Past attendees said this about our webinars:
"A great introduction to stuff I need to know, and a great review of things I once knew. You have an uncanny ability to convey things most people avoid into a language people can understand."
……………………… -- State agency staff

"Thanks Dennis, we really enjoyed the seminars and feel they will be very helpful in future data analyses."
………………………-- Environmental consultant
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