03_Statistical methods and inference (Part 1)

Event A causes outcome B. There is a cause and effect relationship.

Event A and event B are related but one does not necessarily causes the other

• determinining whether there is causality between two data sets -> otherwise could lead to false conclusions

• often causality is assumed because our brains construct causal stories

• to understand how a third variable is influencing the relationship between two variables

• mediator variable mediates: the causal realtionship between variable X & Y exists due to an intermediate third variable Me

Example

• also to understand how a third variable is influencing the relationship between two variables

• Mo has an influence on the strength of

  the relationship between X and Y

Example

In order to test hypothesis one often divides a population into control and experimental groups

Idea: Separate two groups of people so that they only differ by one variable

Example:

• Group 1: Random subset of the whole population who gets medication X

• Group 2: Random subset of the whole population who doesn’t get medication X

A variable that causes both variables X and Y independently, making them look related

Example: