Statistics are worse than lies.

Statistics can easily be misused or misinterpreted.

Lurking Variables
When examining the relationship between variables, there are often other variables influencing that relationship that can lead us astray. These are called lurking variables.

For example, we might see statistics that say kids with mobile phones have better test scores. This is in reality due to the fact that kids with mobile phones generally have more wealthy parents, ones who can afford to spend more money on their kids education. The parents wealth is a lurking variable.

Association does not imply causation.
Just because there is an association between having a mobile and getting good test scores, doesn't mean the good test scores are caused by the mobile. Giving someone a mobile isn't going to improve their test scores.

Extrapolation
When predicting a value using a regression line you should stick to values within the range of the data you have collected. Just because the data follows a pattern in the range you've examined, doesn't mean that pattern is universal.

For example, if we make a regression line for the relationship between age and number of teeth for people from the age of 0-10, we might see that the number of teeth a person has is double their age. But if we try to extend that out of the range of data we examined, we get very inaccurate predictions. A 50 year old doesn't have 100 teeth. Our regression line only makes valid predictions for people aged 0-10.