Beware when we decide to make a Correlation Graphs:
1. Make sure the input DATA are correct!!! –> “Garbage in, Garbage out”
2. Even for the same data, 2 Graphs can look like different if we use DIFFERENT SCALE –> “Different Scale can be Different Interpretation“!!!
3. Beware of COMPARISON Graphs!!! –> is there really any relation between them?
CORRELATION doesn’t always imply CAUSATION (cause relation)
ex. a study concludes that young children who sleep with the light on are much more likely to develop myopia (short-sightedness) in later life. When we draw this finding on a graph we will find a graph with the longer sleeping with light on the higher level potential to have myopia. So…further can we concludes that the sleeping light on is one of the causes of myopia.
Answer: Not so simple!!! remember again “correlation does not always mean causation”
in fact of this case, further research found….the development of child myopia does not have any link with its sleep habits but it has strong relation with parental myopia and the myopic parents were more likely to leave a light on in their children’s bedroom.
Again Do not easily to draw a correlation graph since reader can misinterpret it as cause relation !!!