Item talk:Q56399

Statistical methods in water resources

This text began as a collection of class notes for a course on applied statistical methods for hydrologists taught at the U.S. Geological Survey (USGS) National Training Center. Course material was formalized and organized into a textbook, first published in 1992 by Elsevier as part of their Studies in Environmental Science series. In 2002, the work was made available online as a USGS report.

The text has now been updated as a USGS Techniques and Methods Report. It is intended to be a text in applied statistics for hydrology, environmental science, environmental engineering, geology, or biology that addresses distinctive features of environmental data. For example, water resources data tend to have many variables with a lower bound of zero, tend to be more skewed than data from many other disciplines, commonly contain censored data (less than values), and assumptions that the data are normally distributed are not appropriate. Computer-intensive methods (bootstrapping and permutation tests) now improve upon and replace the dependence on t-intervals, t-tests, and analysis of variance. A new chapter on sampling design addresses questions such as “How many observations do I need?” The chapter also presents distribution-free methods to help plan sampling efforts. The trends chapter has been updated to include the WRTDS (Weighted Regressions on Time, Discharge, and Season) method for analysis of water-quality data. This new version contains updated graphics and updated guidance on the use of statistical techniques. The text utilizes R, a programming language and open-source software environment, for all exercises and most graphics, and the R code used to generate figures and examples is provided for download.

Table of Contents

• Chapter 1 Summarizing Univariate Data
• Chapter 2 Graphical Data Analysis
• Chapter 3 Describing Uncertainty
• Chapter 4 Hypothesis Tests
• Chapter 5 Testing Differences Between Two Independent Groups
• Chapter 6 Paired Difference Tests of the Center
• Chapter 7 Comparing Centers of Several Independent Groups
• Chapter 8 Correlation
• Chapter 9 Simple Linear Regression
• Chapter 10 Alternative Methods for Regression
• Chapter 11 Multiple Linear Regression
• Chapter 12 Trend Analysis
• Chapter 13 How Many Observations Do I Need?
• Chapter 14 Discrete Relations
• Chapter 15 Regression for Discrete Responses
• Chapter 16 Presentation Graphics
• References Cited
• Index