Critical thinking for the layman

Chapter 0 : Intro

Hey there, hope you're doing well. I want to talk about thinking today, specifically about critical thinking. Let's start by defining thinking.

Think : Have a particular opinion, belief, or idea about someone or something.

It would be fair to say our decisions in life are based on how we think.  And making good decisions can a lot difference in life.

Therefore it is important to be good at thinking.
But how do we define good thinking?

Good thinking : Being able to think creatively, strategically, and  critically to solve problems.(Yep, this article is about critical thinking, so I'll address that in depth in this article.)

Alright, so we can imagine good thinking like a three legged stool. 

Creative thinking : Being able to see a problem from multiple perspectives and come up with new ideas and solutions.

Strategic thinking : Analyzing trends over time, and breaking down a problem to find it's root cause.

Critical thinking : The objective analysis and evaluation of an issue in order to form a judgement.

Two things that we need to get straight about critical thinking:

1) Being critical is to be skeptical, not cynical.

2) Critical thinking lays a foundation for creative and strategic thinking.

Chapter 1 : Critical thinking from an analytical perspective

Let's start this section by defining critical thinking (again)

Critical thinking : Assessing information quality and relevance.

Let's make this a little more objective, we can assess information quality by measuring the reliability, relevance, and validity of the data.

You know how we can visualize critical thinking ? 

Yep, a three legged stool (again)

Reliability : Checking if the data is consistent.

Relevance : Checks if the data help us in the current context of the problem.

Validity : Checking the accuracy of the measure.

 

Determining the reliability of evidence :  

There are three things that can hamper the reliability of data:

1) Bad data : We can say that we are dealing with bad data if the sample size is small or unrepresentative of the population.

2) Biases : inclination or prejudice for someone or something, especially in a way considered to be unfair.

3) Mistaking accuracy for reliability : A model can be accurately wrong, and we should not confuse this with an accurate or good model.

Weighing the relevance of evidence :

 There are two factors to be considered while weighing the relevance:

1) Check for logical fallacies.

2) Ask "how" questions. (example : How does this information help?)

Determining Validity of information :

The information can be called valid if it is both reliable and relevant.