Data analytics, statistics, and more
Dixon’s test is simple, easy to understand, and is widely used in the scientific community. Data recorded to some specific measurement increment can become a problem for outlier tests, such as Dixon’s test. Dixon’s test assumes that the data values (aside from those being tested as potential outliers) are normally distributed. Most sample distributions are not normally distributed.
Detection of temporal trends is one of the most important objectives of environmental monitoring. This post examines nonparametric temporal trend analysis using the Mann-Kendall test and the Theil-Sen regression estimator.
The most common activity in research is the comparison of two groups. The t-test is robust to departures from normally for moderate tailed, symmetric distributions. When the data come from a heavy tailed distribution, even one that is symmetric, the two-sample t-test may not perform as designed.
Management decisions are affected by left-censored observations because they impact not only the estimation of statistical parameters but also inferential statistics. This post presents statistically robust procedures to analyze censored data that make no assumptions or use of arbitrary values.