# How to Lie With Statistics?

Categories: Statistic

The Post– hoc analysis which is the cause and impact issue. Techniques of providing cause and impact: 1) provide a result without a significance value 2) utilize untestable assumptions 3) use precision and precision interchangeably 4) carry out nonsensical test that sound excellent. Bear in mind that a fact is just rewarding when it pleases the presumptions on the test. Knowing whether the presumptions are satisfied depends on the proficiency of the person running the test. Just since 2 things seem to have a relationship, could it have been by pure possibility? It can not be identified by causation and impact.

The two variables have no impact on each other at all.

Chapter 9– How to Statisticulate is the procedure of misleading individuals using statistics. It is also misinforming with figures, or statistical adjustment may not be a mathematician purpose. Lying with statistics– is this dishonesty or incompetence? Primarily dishonesty. The author list different tricks– things like determining earnings on expense rate, showing a graph with a finer Y-axis scale simply to reveal the steep development is, how income calculations deceive by including kids in the family as individuals for the average amongst a couple of.

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Chapter 10 – How to Talk Back to a Statistic In how we talk back to a statistic one should ask themselves to find out if the statistic that you are reading being presented is it genuine or not. There are 5 simple steps, in Huff’s own words, “how to look a phoney statistic in the eye and face it down”. (page **)

Question 1 – Who says so? Find the bias before trusting.

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