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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.
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Is it true some normal probability distributions are positively skewed?
No. The Normal distribution is symmetric: skewness = 0.
What is the math definition of experimental?
The word "experimental" is usually used to describe data that have come from an actual test or experiment. These data are opposite to "theoretical" data, which are only educated guesses at what the data should look like. In statistics, theoretical probability is used a lot. For example, if I flip a coin, in theory, it would land on each side half of the time. Perform some trials, however, and this percentage may be skewed. The experimental data that you collect probably wouldn't exactly match the theoretical probability.
All graphs must have what?
Some data.
When some arithmetic or logical operations are performed on data it is called?
I believe the term "data processing" is appropriate in this case.
Mode is 100 and mean is less than the median?
Oh, dude, it's like when you have a group of numbers and the mode, which is the most common one, is 100, but the mean, which is the average, is lower than the median, which is like the middle number when they're all lined up. So basically, it's just a funky little math situation where the numbers are playing musical chairs and the mean ends up being the odd one out below the median.
