Applying ANOVA and Nonparametric Tests Simulation This week’s assignment was to take a simulation called Applying ANOVA and
Nonparametric Tests. After carefully reviewing the simulation it became easier to answer the questions for the assignment. Researchers sometimes have difficult decisions to make. Applying the analysis of variance (ANOVA) helps businesses to recognize the challenges and opportunities of making a business decision. ANOVA testing is a statistical tool that test each population calculated with a normal distribution (University of Phoenix, 2011). The benefit of this test is it can narrow down the errors of an incorrect test method as long as there is statistical proof (University of Phoenix, 2011). On the other hand, other tests are required because sometimes there are inaccurate assumptions that come with the testing process and businesses than acquire the nonparametric test known as the Kruskal-Wallis test for further analysis
(University of Phoenix, 2011). The three lessons learned related to the ANOVA and Nonparametric tests include how businesses can learn how to better monitor, measure and improve their business processes
(University of Phoenix, 2011). A successful business is faced with many challenges daily. The goal is to provide quality products and excellent services to their customer’s, employees and shareholders. After reviewing the simulation, some concepts and analytic tools came to mine, which this would be helpful to take back to the workplace (University of Phoenix, 2011). For instance, the company I previously worked for the AVOVA testing would have been an excellent tool to use. Working for a transportation company hiring and firing takes a large amount of patience. The
ANOVA test would have assembled the range of customer service needs and benefits. Applying questionnaires to new hires, as well as applicants not hired or decided not to accept the position would have solve several issues in communication as well as other strengths and weaknesses with the company. Based on the experience from the simulation here is some additional information, which should have been provided to the key maker of the simulation to help solve the challenge given (University of Phoenix, 2011). For example, increasing the knowledge of the software engineers and providing additional training would boost their competency and productivity (University of Phoenix, 2011). The results of the simulation pointed-out factors that would help businesses increase their achievement goals. Productivity and Client satisfaction were the two most important variables recognized in this simulation (University of Phoenix). Knowing these tools and addressing them properly can make a difficult situation less difficult to handle.

Reference
University of Phoenix. (2011). Applying Analysis of Variance (ANOVA) Nonparametric Tests Simulation. Retrieved from University of Phoenix, Simulation, RES342-Research and Evaluation course website.