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10 Elements of Clear Thinking Cheat Sheet (DRAFT) by [deleted]

10 Elements of Clear Thinking

This is a draft cheat sheet. It is a work in progress and is not finished yet.

Introd­uction

Much learning in business and life occurs simply by observ­ation. Automatic learning (knowledge gained without awareness) underlies habitu­ation and classical condit­ioning. Automatic learning process can entice people into biased learning. Good statis­tical thinking can improve our logical and problem solving skills. Statistics is the art of making numerical guesses about puzzling questions (Wheelan, 2013).

1. Solving the right problem

The hardest part of a problem solving is the unders­tanding precisely what is the problem. Problem has to be actionable (e.g., being stuck in a wrong job or relati­ons­hip). If it’s not action­able, then, it’s a gravity problem (Burnett & Evans, 2016). Gravity problem is a situation (a circum­stance) or a fact of life (e.g., growing old). It is not a problem that can be solved. The only response to a gravity problem is acceptance

2. Form a hypothesis

The first step in statis­tical thinking is the formation of a hypothesis (an educated guess). For example, we hypoth­esize the following relati­onship: children who grew up with lots of books in their home tend to do better in school. The aim is to falsify the initial hypothesis by observ­ations and experi­ments. If we fail to reject the null hypoth­esis, we accept it by default.3

3. The underlying theory

Every observ­ation has more than one interp­ret­ation. Observ­ations do not usually announce their meaning and often invite an incorrect interp­ret­ation. So we need a few guiding theory that permit selection of one account over another. For example, research shows that the education and income of a student’s parents have a signif­icant impact on student achiev­ement.

4. Associ­ation is not the same as causation

A cause is something that produces an effect. For example, surrou­nding children with many books does not necess­arily make them to read. The two variables are positively correl­ated.

5. Confou­nding factor

A confounder is a third variable that you did not account for it. These variables distort the true causal link. In the previous example, both variables (the presence of books and academic perfor­mance) are likely caused by a third variable, which is parental education.
 

6. Reversion to the mean

Past perfor­mance is no guarantee of future perfor­mance. Statis­tical thinking tells us that any outlier is likely to be followed by outcomes that are more consistent with the long-term average. This phenomenon is known as reversion to the mean or what is normal. This explains why the baseball rookie of the year so often is a disapp­oin­tment the second year. If we consider the perfor­mance as a continuous variable subject to mean and variance, we will experience distri­buted perfor­mances with extreme values. Any number of other things could be operating to push perfor­mance level up or down.

7. Probab­ility is not determ­inistic

Our intuition does not grasp the nature of random­ness. We see patterns where none may really exist. For example, if a coin comes up heads five times in a row, people will have a powerful sense that the next flip is more likely to come up tails than heads. Each flip is an indepe­ndent event. Similarly, a flood this year says nothing about whether a flood will happen next year.

8. Prepare for the worst-case scenario

The greatest risks are the ones that we can hardly imagine they could happen. The philos­opher Taleb (2012) recommends that in order to make decision you need to focus on the conseq­uences (which you can know) rather than the probab­ility (which you can’t know). The more uncert­ainty you face in the future, you will do well by having options. Chance favors the prepar­edness. An important strategy for the military is to invest in prepar­edness, not in prediction

9. Belief updating

We seem to use perception (the way things appear) to guide our actions (Siegel, 2017). Consider this prejud­icial thinking. A teacher perceives female students being weak in math. Conseq­uently, he will expect and demand less of her, and he will perceive her perfor­mance as being worse than a male student. Perceptual judgment is a form of belief. If our prior beliefs influence our experi­ence, our experience can go on to strengthen those very beliefs. Failure to update prior beliefs explains wishful thinking.

10. Genera­liz­ation

Much of scientific research is aimed at uncovering the causes of illness at the population level. Ultima­tely, we want to understand why illness occurs in indivi­duals (why individual A became unheal­thy?). One cannot necess­arily conclude the same relati­onship from the group level to the individual level. Statistics never delivers absolute certainty. Instead, facts are known with degrees of confid­ence.