Evaluating the distribution of your data variables with Python in just a few lines of codes — Descriptive statistics can provide a good sensing of the data. For instance, if the median of your data differs by the mean by a lot, you can infer that your data is skewed. On the hand, if you detect that your dataset has high variance or standard deviation, you can…

A useful book for data scientists to interpret errors and variations in experiments — A measurement without error is meaningless. Indeed, scientific errors are critical in our understanding of variation in experiments. However, the math involved in the calculation of errors, as well as the interpretation of errors can be difficult for researchers to understand. …

Calculating the best estimate for population statistics based on sample data — A measurement without error is meaningless. Let’s imagine you measure that the gene expression of the interferon gene is increased from an intensity of 50 to 200 after a treatment. Looking at these 2 numbers, you conclude that the intensity is increased by 4-fold, but is this really the result…

Deconvoluting the dilemma of tile discard during riichi — In some situations, there could be multiple possibilities of discards before calling riichi. At this point, there will be several factors to consider before deciding on the best tile to discard: Which tile discard will net you the best value? As calling riichi is a risky, you want to make…

Featuring a collection of scenarios that can make one lose a game — In the quest to sharpen my skills for riichi mahjong, I have committed a lot of mistakes, some of which resulted in game loss especially in higher level games. …