ANOVA and Nonparametric Simulation
For this assignment students are tasked with completing an online simulation and applying statistical research. To complete this paper we as students need to answer three basic questions. What are three lessons you learned relative to ANOVA and nonparametric tests? As a result of using this simulation, what concepts and analytic tools will you be able to use in your workplace (i.e., how do you expect to apply what you learned)? Based on your experience, what additional information would you recommend to the key decision maker in the simulation to solve the challenge given?
For the first question relating to lessons learned; ANOVA is a test to compare the means of several populations. ANOVA doesn’t answer which population might have a larger or smaller mean: it only answers whether all the means are equal. This is done by evaluating the variances within the groups and between the groups being compared (Doane & Seward, 2007).
ANOVA can be used to evaluate if different factors have a different effect on a variable. The factors are categorical variables with different levels. For instance, the context of the simulation is a software development company that wants to know if factors like project difficulty, experience, or requirement changes affect the productivity of the software engineers. Productivity is measured by the average number of lines of code written per day by a programmer. An ANOVA test can shed light as to whether productivity is affected by a project’s difficulty (Doane & Seward, 2007).
In the ANOVA test the dependent variable is numerical. If the dependent variable is ranked, we can do an analysis of variance with nonparametric techniques like the Kruskal-Wallis test (Doane & Seward, 2007).
Upon graduation of this course I plan to own and operate my own business. With a statistical back ground it will make analyzing customer flow, advertising needs, and the need for inventory control an understandable process. Having the ability to research multiple levels of data pertaining to a targeted area gives business a formidable edge on almost predicting the future.
Based upon my experience in management, what I would endorse to the simulation’s decision maker is to remember the impact on productivity that originates from management styles. It is common knowledge that employees are more apt to be productive when they have a pleasant relationship with team members and supervision. Since managers are to have a working knowledge of the tasks of his or her employees they too must possess people skills in dealing with the staff or team to keep any business running smoothly.