# Lesson 3 – Cause and Effect Relationships

```MDM4U
Ms. Kueh
Cause and Effect Relationships
Read pg. 195-197 (up to the end of example 1) and fill in the following definitions:
Cause – and – Effect Relationship: A change in 𝑥 produces a change in 𝑦.
Example:
Common Cause Factor: An external variable causes two variables to change in the same way.
Example:
Reverse Cause – and – Effect Relationship: The dependent and independent variables are
reversed in the process of establishing causality.
Example:
Accidental Relationship: A correlation exists without any causal relationship between variables.
Example:
Presumed Relationship: A correlation does not seem to be accidental even through no cause –
and – effect relationship or common-cause factor is apparent.
Example:
Example 1 Identify the most likely type of causal relationship between each of the following
pairs of variables. Assume that a strong positive correlation has been observed with the first
variable as the independent variable.
a) Time spent practicing free-throws, free-throw scoring percent.
b) Aptitude for physics, aptitude for chemistry
c) Amount of traffic congestion, number of accidents
d) Price of milk, crime rate
Example 2 For each pair of variables, identify a possible common- cause factor that could
account for a positive linear correlation.
a) Ice cream sales, corn harvest
b) Number of traffic accidents, number of traffic violations
c) Confidence level facing a final exam, final exam score
d) Endurance on the tennis court, tennis skill