Open Stats Online has been developed as hub for free and open-source statistical tools starting with Open UCL.
How Many Samples is Enough (Part 2: Using Max Probable Error)
Contributed by Marc Salmon The following table shows the estimated number of analytical samples required to estimate the arithmetic mean at a 95% confidence level, based on the maximum probable error (MPE) method for various MPEs and relative standard deviations (RSDs). The estimates were developed using ProUCL statistical software[1]. As described in Background, as the variability of the…
How Many Samples is Enough (Part 1: Background)
Contributed by Marc Salmon The maximum probable error (MPE) method can be used to determine the number of analytical samples[1] required to estimate the arithmetic mean of a population (µ). This method has been referred to in the assessment of site contamination (ASC) literature since the mid-1980s (Provost 1984, USEPA 1985, and Gilbert 1987). As noted by…
Which Statistical Test to Use?
An easy flow chart for selecting the appropriate statistical test.
Excel Statistics
The use of Excel for statistics is wide spread but is it correct?
Open UCL Github Release
he Shiny R code for Open UCL is now available for forking, copying or distribution.
Student’s t-test in R and by hand: How to compare two groups under different scenarios
These are a set of links to a blog and app by Antoine Soetewey that explain the procedure to conduct t-tests by hand, and with R. He steps through the calculations and includes the code for R. But if you don’t know R, he also includes a Shiny application to help with the calculations and…