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Submitted By smartinez2

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Words 334

Pages 2

February 1, 2012

Victor Ornelas

Most recent concepts are ANOVA and nonparametric tests. ANOVA, also known as analysis of variance is a concept that allows you to “compare more than two means simultaneously and how to trace sources of variation to potential explanatory factors”. One of the biggest take away from this concept is that the ANOVA tests can take on many factors or “treatments. This can be very beneficial when dealing with many factors. Although this does not mean that it is the norm to have many factors. Most researchers focus on a limited amount of factors. Another big lesson is with nonparametric tests. Working for a company that requires that we learn how comfortable our users are with their technology it is very important to use ordinal data for informative decision making. In our data sets there is a large majority of information that does not come in with a normal distribution. This is where it comes into play that a parametric test can aid due to the ability to examine information without normal distribution. One of the largest lessons in terms of these concepts is the data size that it takes to utilize these tests. Unfortunately as with any questionnaire my department usually gets only a small amount back. When working with parametric testing a small sample size would only go to hurt the result of the testing. When working with these tests it is possible to extrapolate the data and generalize for the mass amount. Unfortunately when working with parametric data it is not beneficial to use smaller data sets due to the fact that the results cannot reach normalcy. Working with this information, I feel that it is more possible for our department to better utilize the limited data sets that we receive and better inform our department director.…...

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