STAT200 SIU Correlation Does Not Mean Causation & Linear Regression Discussion

Description

Please answer one of the two following questions:

1. Correlation: Correlation Does Not Mean Causation

One
of the major misconceptions about correlation is that a relationship
between two variables means causation; that is, one variable causes
changes in the other variable. There is a particular tendency to make
this causal error, when the two variables seem to be related to each
other.

What is one instance where you have seen correlation misinterpreted as causation? Please describe.

OR

2. Linear Regression

Linear
regression is used to predict the value of one variable from another
variable. Since it is based on correlation, it cannot provide causation.
In addition, the strength of the relationship between the two variables
affects the ability to predict one variable from the other variable;
that is, the stronger the relationship between the two variables, the
better the ability to do prediction.

What
is one instance where you think linear regression would be useful to
you in your workplace or chosen major? Please describe including why and
how it would be used.