Is correct interpretation of data important?

To a scientist this is an incomprehensible question. How can it not be important to interpret data correctly?

However, if your intention is to motivate people to take action then it does not matter whether your interpretation of the data is correct so long as people believe it.

A number of my posts over the six months have dealt with the interpretation of data. Why do I think it is so important to interpret data correctly?

1. Incorrect data interpretation allows critics to discount your arguments.
2. Incorrect data interpretation allows critics to re-focus the discussion as an argument about what the data mean.
3. Incorrect data interpretation leaves you running the risk that scarce resources are directed at solving non-existent problems while leaving actual problems unaddressed.
4. The examples of poor data interpretation I have discussed include:

• Making a stronger claim than the data support (Over-interpreted Data 1)
• Failure to distinguish between effect and fluctuation (for example, in appointments statistics, see Myth of Hard Facts)
• Failure to account for confounding variables (Over-interpreted Data 2)
• Failure to rule out alternative hypotheses (Over-interpreted Data 3)

Do we really make the argument for more women in science by demonstrating such basic errors in analysis?

5. I have a pedantic streak.