Visualization is often used for evil - twisting insignificant data changes and making them look meaningful. Don't do that crap if you want to be my friend. Present results clearly and honestly. If something isn't working - those reviewing results need to know.

When communicating results to non-technical types there is nothing better than a clear visualization to make your point.

Far better an approximate answer to the right question, which is often vague, than the exact answer to the wrong question, which can always be made precise.

The best thing about being a statistician is that you get to play in everyone's backyard.

Numerical quantities focus on expected values, graphical summaries on unexpected values.

In a single sentence the moral is: admit that complexity always increases, first from the model you fit to the data, thence to the model you use to think about and plan about the experiment and its analysis, and thence to the true situation.

All we know about the world teaches us that the effects of A and B are always different-in some decimal place-for any A and B. Thus asking "are the effects different?" is foolish.