Nondetects And Data Analysis (NADA)
Statistical analysis of censored data (data with nondetects)
Substitution of a constant times the reporting/detection limit (for example 1/2 DL) introduces bias into estimates of mean, standard deviation and upper confidence limits, and corrupts the results of hypothesis tests and regression. The better alternative is to use methods for censored data. How these methods work is not widely understood by the environmental science community. The most frequent question I am asked about them is "But what number do I put in for the nondetects?" The answer is "you don't". This course explains the reasons why this is so, how these methods work, and demonstrates how to compute a mean and confidence limits through hypothesis tests and regression, all without substituting values for nondetects. You will work exercises using the R software system. After completing the course you will be able to apply all of these methods directly to your own data.
To experience my teaching style and get a taste of what this course is about, view one of the many free videos on this site labeled with the purple "<" logo.
This is an excellent statistics course for anyone that understands basic statistics. It includes theory, implementation, as well as demonstrations in R. Beginner R users will learn new tricks and tips. All course materials are well-made and easy to understand (even for non-native English speakers). This course complements the textbook and gives all the information you need to run your own analyses.
- Erin Symonds, Ph.D., 2019 attendee
I took this self-paced online class in 2020. This is one of the best statistical classes I have ever taken and I highly recommend this class to my peers.
The class talks about a very important topic in Environmental Science, non-detects, and introduces a series of tools to handle non-detect data for meaningful statistical analysis, including summary statistics, comparisons, correlation, regression, and briefly, multivariate analysis. Unlike a few other statistical classes that are either too theoretical or less systematic, the class is offered with actual examples that are explained then employed in a step-by-step fashion. The class is very practical, which gives the attendees an opportunity to think how you can use these methods to solve your own real-world problems.
Besides presentations, this class offered a package of materials that are very helpful, including class notes, R codes, practices as well as exams. The instructor, Dr. Helsel, is very responsive, knowledgeable and patient. My questions were always answered in a timely fashion.
- Weiying Jiang, state agency toxicologist
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 (2nd edition coming this year) is 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 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'."