Business

Analysis of Variance (ANOVA) is primarily an extremely useful anthology of statistical models used for the sole purpose of comparing the means of three or more samples. ANOVA testing is based upon the fundamental principle of breaking down a particular observed variance into various subsidiary elements in accordance with different explanatory variables. Principally, the ANOVA test determines, through statistical procedures, whether the mean of various comparable population samples is equal or not. Consequently, we can state with utmost certainty that the ANOVA test provides a much better and comprehensive approach than the Two-Sample t-test.

During the simulation, the application of ANOVA as well as subsequent statistical non-parametric procedures provided me with three extremely valuable lessons which I will mentioned collectively because they inherently complement each other. ANOVA testing primarily assumes that the condition of normality in regards to the residuals holds under all situations, however, since that assumption cannot really be applied always therefore during such an event, the Kruskal-Wallis test is a much better alternative. Therefore, it is extremely important that one should have be significantly clear on what test should be applied under different situations. Consequently, it is also of great importance to correctly monitor the situation under consideration, provision of adequate data through proper measurement techniques as well as providing solutions for improvements. Since ANOVA testing primarily helps in reducing Type I errors, it is important to check for the significance and accuracy of the assumptions being used.

In regards to the field of business, the main purpose of ANOVA testing is focused solely around Operational Research as well as the field of Total Quality management. For a restaurant manager, both previously mentioned fields are of extreme importance. The application of ANOVA and non-parametric testing techniques upon daily operations as well as in regards to the determination and improvement of quality management primarily aids an organization such as a restaurant in making accurate decisions in the sense that it helps identify areas which need improvement, augment the quality of the management at work as well as the provision of solutions in regards to the potential problems that that particular organization is facing.

As a restaurant manager, it would be of extreme importance to utilize techniques such as Kruskal-Wallis test, factorial ANOVA and multivariate analysis of variance (MANOVA). Such analytical tools would essentially enable the restaurant management to determine exactly, with mathematical certainty, what the situation of the business and the areas which are suffering from deficiency. Moreover, such analytical tools would also allow the management to combine various impact variables in accordance with mathematical logic thereby increasing the accuracy of the decisions being made.

In regards to additional information that would have been beneficial during the period of simulation, it is important to note the fact that the Liker Scale is primarily an acceptable data set format. One must also take note of the fact that the restaurant business is also heavily dependent upon consumer preferences and perceptions thus any additional information from customers such as surveys and interviews concerning food preferences and habits should be conducted in order to enhance the data set. It is also important that data be collected through appropriate sampling techniques with due consideration given to measurement errors.