Free Webinars Trend Analysis for Data With Nondetects
Nov 19, 2019 10 am Pacific, 1 pm Eastern.Webinar Registration
Concentrations of trace contaminants often have a significant percentage of nondetects, data below the detection or quantitation limits of the laboratory used. Are those concentrations at a site changing over time? This webinar will show you what NOT to do, as well as methods for answering this question. You'll see demonstrations of the equivalents of the Mann-Kendall test, Seasonal Kendall test, and regression methods for data with nondetects. Methods for data with multiple detection limits are included. This is one of the topics in our Nondetects And Data Analysis (NADA) course now available at practicalstats.teachable.com ..
Free webinars for your viewing at our Online Training Center
. Click the "View All Courses" button to see more than the top 3. The webinars will be listed as free courses.
1. Intro to Nondetects and Data Analysis An introduction to data analysis for variables with nondetects.
Free. 50 mins.
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.
Free. 50 mins.
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.
Free. 55 mins.
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 Free. 60 mins.
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.
Free. About 1 hour. Q&A file and pdf of slides also available for download on our Downloads page.
Correlation and regression form the backbone of much of the data analysis in the environmental sciences. Computing coefficients, evaluating the quality of the regression and determining which variables produce the best equations are standard procedures. However, what can be done when data include values below detection or quantitation limits? This webinar will show you what is possible for these objectives, as well as for determining whether the methods’ assumptions are met (Q-Q plots) and to plot predicted values. You can do all of the tasks you are used to in correlation and regression, using parametric and nonparametric methods, all without substituting fabricated numbers for nondetects. This is anoher topic from our new online course Nondetects And Data Analysis, available on our Training Site -- http://practicalstats.teachable.com
6. Seven Perilous Errors in Environmental Statistics Seven common errors to avoid!
Free. About 1 hour.
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.
7. Statistics For Managers What your employees need to know to stay current with statistical methods today
Free. About 1 hour.
People requested this 2015 webinar be made available for listening. And here it is!
1. Permutation Tests -- what they are and why they are important.
2. Free Software for Environmental Statistics
3. Better Methods for Handling Nondetects
4. Analysis of "real-time", frequently collected data
8. Intro to R Break down the barrier of how to get started using R!
Free. About 1 hour.
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? Free. 60 mins.
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?
Materials from the webinar (including slides and info) can be downloaded on the webinar site.
10. Never Worry About A Normal Distribution Again! Free. 65 mins.
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.
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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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