Suppose X has a distribution that is not normal. The Central Limit Theorem is important in this case because:.a) it says the sampling distribution of is approximately normal for any sample size. b) it says the sampling distribution of is approximately normal if n is large enough. c) it says the sampling distribution of is exactly normal, for any sample size. d) none of these choices.

For a science project, a high school research team conducted a survey of local air temperatures. based on the results of the survey, the found that the average temperatures were around 10 degrees higher than expected. this result was wrong. the trouble with the survey was that most of the locations were exposed to direct sunlight and located over asphalt or sand, which resulted in higher temperatures than normal. this is a classic example of an error in which phase of inferential statistics?