Response to: Great example of "Lying with Statistics"
My view is closer to Rip's. Deceiving people is not alleviated by being "truthful" but misleading. As with many things where you draw the border is often challenging. I do like putting the claims of lying on a person - not on data. Data can be wrong. It can't lie. People can lie. People can also mislead. And very often people can be mislead (by those intending to mislead them and those that failed to understand the data in the first place and then used the data in a faulty way to support their mistaken notion).
Those of us reading the messages in this group (statistics group on LinkedIn) are not likely to fall into the being mislead camp often. But my experience is that is by far the biggest problem. People not having numeracy and being mislead all the time do to their lack of understanding (either intentionally, or through ignorance of theirs [or the person presenting the info to them]).
Related: Bigger Impact: 15 to 18 mpg or 50 to 100 mpg? - Understanding Data -
