Data Distribution & Decision-Making
The idea that the Gaussian Distribution is so frequently found in everyday life that it is also called Normal Distribution can also be misleading. If one assumes normality where it does not exist, data-driven decisions will be in jeopardy. For instance, making decisions that will affect a region with high unemployment rates under the assumption that the average salary is the most common salary, and that there’s an equal number of people who are well-off as there is people struggling to make ends meet, would be catastrophic.
For your initial post, find one type of data that tends to be normally distributed, and one type of data that does not. Make sure that you present relevant data/sources to support your claims. Then, discuss how assumptions about the normality of your “not normal” data can result in bad decision-making.