Incorporating > and < Values in Data Analysis
Using interval censored methods
A free-to-stream video that is a taste of our course Nondetects And Data Analysis.
One way of representing censored data in a database is the "interval endpoints" format. Two columns are used with the first being the low end of possible values for the variable (often 0 for censored chemical data) and the second column holding the highest possible values (often the detection limits). One benefit of storing data this way is that it allows 'greater thans' to also be stored in the same two columns. Most censored methods for data analysis can incorporate both 'less thans' and 'greater thans' as interval-censored data and compute everything from means to hypothesis tests and regression. This video will introduce you to how these types of methods can be performed.
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'."