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Mann-Kendall Power Analysis Revisited

Detection of a long-term, temporal trend in environmental data is affected by a number of factors, including the size of the trend to be detected, the time span of the data, and the magnitude of variability and autocorrelation of the noise in the data. This post evaluates the power of the Mann-Kendall test to identify a trend for various combinations of trend, variability, and sample size using Monte Carlo simulation.

April 5, 2022

Sample Size Requirement for One-Sample t-Test

This post computes the sample size necessary to achieve a specified power for a one-sample t-test, given the ratio of means, coefficient of variation, and significance level. Calculations are based on the USEPA’s 1996 Soil Screening Guidance Document that discusses sample size calculations to determine whether soil at a potentially contaminated site needs to be investigated for possible remedial action.

April 2, 2022

Plume Moment Analysis Using Thiessen Polygons

Mass-based analyses of groundwater contaminants provide complementary information not readily quantified using single-well analytics. This post describes methods that can be used to evaluate contaminant concentrations measured in wells to determine how plume mass and plume center-of-mass change through time.

April 2, 2022

How to Calculate Summary Statistics for Left-Censored Data

Left-censored environmental data are problematic because censored (nondetect) values are known only to range between zero and the detection or reporting limit. Fortunately, methods are available for analyzing data containing a mixture of detects and nondetects that make few or no assumptions about the data, or that substitute arbitrary values for the nondetects.

March 28, 2022