Measurements should also be valid - that is, they really should measure what you think they measure. If so, the intelligence test might be invalid if it is used in a culture for which it was not designed. You need not be statisticians to understand the implications of some important statistical issues. Statistical testing allows you to compare two groups to see if they are the same or different. Often a test will have an associated p-value that indicates the likelihood that the difference seen between the two groups could be due to chance alone.
Larger groups make differences easier to detect - that is, the power of the study is increased.
A confidence interval is a way of stating how unsure you are about an effect. The two statements tell you similar, but not identical things, and the confidence interval may be more useful to you. If this difference might reasonably have affected the study results, then the study is potentially biased. Often a study is well done and technically sound, but may not apply to patients you deal with. That is, the study findings cannot be generalized to your population.