We statisticians use many words in ways that are slightly different from the way everyone else uses them. This cause lots of problems when we teach or explain what we are doing. I'll start a list (and now I'll add some definitions, per comments):
- Power is the probability of correctly reject a false null hypothesis in a hypothetical situation where the data comes from a specific alternate hypothesis or range of alternates. Usually, this means "our statistical method should succeed" if "something is happening".
- Bias - a statistic is biased if it is systematically different from the population parameter associated with it.
- Significance - results are statistically significant at some percent (often 5%) in the following situation: If the population which the sample comes from has a true effect of 0, a statistic at least as extreme as the one gotten from the sample would only occur 5% of the time.
- Interaction - Two independent variables interact if the relationship between the dependent variable and one independent variable is different at different levels of the other independent variable
But there have to be many others!