Statistically speaking, people are highly likely to misinterpret statistics!

Statistics are not easy to understand. They speak broadly of a whole population but say nothing about individual cases. I was watching a show on TV recently that reported that a study has found that in 70% of households women do more of the domestic duties (cleaning, cooking, ironing etc.) than men. A male commentator then rubbished the study, saying that he did nearly all of the housework, so it was obviously wrong!
But 70% means 70%, not 100%. If the study surveyed 1000 households and found that in 700 of them, women do more of the work, then that equates to 70%. In 300 households, men do more of the work (or do the same amount of work). Finding an exception to a majority doesn’t change the underlying statistics.
Statistics say nothing about individual cases, only about whole populations. So assuming that a set of statistics accurately reflects what’s going on in society (which is an assumption that you should always be careful of making), individual cases will vary.
However, politics (including societal politics and work-place politics) is not necessarily about accurate statistics. Politics is about winning people over, so people will often argue about what a set of statistics tells us about our society and what we should do. The interpretation of the statistics is often far more important than the statistics themselves.
So in commenting on the above statistics, some might say that “woman do more housework than men, so things could be better in terms of equality between the sexes”, or more emphatically, “woman are burdened with far more of the housework in society. This is unacceptable…” However, others might say that “the reason that woman do more household work is that they are more likely to be home due to children-related reasons which is completely their choice…”
General statistics are important, but the biggest arguments in society involve why something is the way it is and statistics don’t necessarily have the answers. So, always be careful about not just the statistics themselves but how they are interpreted!

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