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The mean and standard deviation. If the data really are normally distributed, all other statistics are redundant.
The means of repeated samples from any population.
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The z score is (1650-1500)/150 = 150/150 = 1
The cause of skewed data distributions are extreme values, also know as outliers. For example imagine taking the weights of people you see on the street. If you have 9 cheerleaders' weights and then the weight of a sumo wrestler mixed into the averages this skews the data. This makes the mean much higher because of the one extreme value. Instead of the data being distributed normally, it is distributed with a positive skew. If there is a really small extreme value instead of a really large one, then the data has a negative skew. This could be the heights of people on the street, but one of them would be a midget. The mean is made lower by that one extreme value. Perhaps, little person is a more politically correct term in our day.