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    Standard and Average Deviation, Non parametric Statistics

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    1- What is more useful for computing and understanding a measure of something, the average deviation or the standard deviation? Why?

    2- Why would you use a nonparametric statistic?

    3- If two things are correlated, does that mean one thing is causing the other to happen?

    4- Describe an experiment requiring the statistic ANOVA for analysis. Describe the Dependent Variable, the Independent Variable, the Levels of the Independent variable, and make sure you are using the correct types of data for each variable.

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    1. In general, standard deviation is considered more useful for computing and understanding a measure of something. Standard deviation is used more commonly compared to average deviation as it is easy to compute for data that is normally distributed. By simply reporting a data point as 1, 2 or 3 standard deviations away from the mean we can easily relate to others where one point within a data set is located in reference to the mean. Standard deviation is more useful because it is a simple calculation; it is used for normally distributed data, and conveys information easily with the use of simple numbers.

    The average deviation statistic requires the use of absolute values in its calculation, which is not as simple to compute as standard deviation. The average deviation does not provide as much information as it cannot be applied to a standard distribution in the way that the standard deviation can be applied (see 68-95-99.7 rule for standard deviation http://en.wikipedia.org/wiki/68-95-99.7_rule).

    2. A nonparametric statistic can be ...

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