Anova & Non Parametric Test Simulation

ANOVA page 1

ANOVA and Nonparametric Test Simulation

University of Phoenix

ANOVA page 2

ANOVA stands for analysis-of-variance, a statistical model meant to analyze data. Generally the variables in an ANOVA analysis are categorical, not continuous. The term main effect is used in the ANOVA context. The main effect of x seems to mean the result of an F test to see if the different categories of x have any detectable effect on the dependent variable on average. (about.com n.d.). In the context of production theory a nonparametric index number would not be derived from a specific functional form of the production function.

After completing the Applying ANOVA and Nonparametric Tests simulation on the student website there were three lessons that I learned. First, I learned how to use the Kruskal-Wallis test in order to compare data on more than two populations. This test analyzes data that has a fluctuation distribution and is not considered the norm. Second, I learned the importance of identifying the right variables. If you fail to do this it can lead to misguided decisions. Third, I learned to take my time in analyzing the tests to make absolute certain it really had a relevance to the outcome of the experiment.

As a result of using this simulation I am now able to better understand the usage of other tolls such as the two-way ANOVA to help me in determining how effective my sales staff is. These tests could really help my company improve upon our sales production as well as schedules and communication.

Based upon my experience, the additional information I would recommend to the key decision maker in the simulation to solve the challenge given is to have more information on the amount of money being invested in each specific project as well as identifying the length of time a project takes from beginning to end. Management also needs to take into consideration the solid knowledge base that they...