The relationship between a commercial district and the concentration of consumers in a specific generation mostly is not by causal effectSimultaneity oftern requires instrumental variablesReal cases also end up with mis-specification due to endogeneity When working on data science-related projects, causality errors are common issues. There are quite a few cases where the variable thought…
With high variance, 0/1 hardly yields a decent model, let alone with new set of dataWhat is known as ‘interpretable’ AI is no more than basic statistics’AI’=’Advanced’=’Perfect’ is nothing more than mis-perception, if not myth 5 years ago. Just not long after an introduction of simple ‘artificial intelligence’ learning material that uses data related to…
One-variable analysis can lead to big errors, so you must always understand complex relationships between various variables. Data science is a model research project that finds complex relationships between various variables. Obsessing with one variable is a past way of thinking, and you need to improve your way of thinking in line with the era…