Misunderstanding statistical distribution

I start to think that a statistical misunderstanding is the source for certain types of interpretations of the controversial memo published by a Google engineer about the company’s diversity efforts.

When investigating the distribution of traits and noting that certain traits are more prevalent in one group compared to another (whatever type of group we are talking about), this by no means allows for the conclusion that the group with the smaller prevalence does not have any members who feature strong combination of the traits in question. It only means that if you look at a sufficiently large number of members of each group and eliminate for external factors, you would see more of certain characteristics in one group than the other, seen on average over the complete group.

Even if one would hold the position of the memo’s author that in an environment which artificially has been cleared from all cultural and social norms, fewer girls/women than boys/men would develop an interest in programming, then this does not say anything about the quality and skill of those girls/women who do. In fact, hypothetical it is even possible that an objective assessment might reveal that the girls/women who choose (or would be interested in choosing) an engineering profession actually are better at it than the men who do, featuring on average a stronger combination of these traits (and in that case, companies should actually hire only women as engineers :P). I’m not saying this is the case, but I want to point it out as a possibility to illustrate why the statements about the statistical distribution across the whole population of a group do not allow for conclusions about the quality and skill level of the individual.

I am by far not an expert in statistics, but I try to implement some basic principles into my judgements of our time’s heated debates. It helps a lot and I’d wish basic statistical principles would be internalized by more people .

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