In business today, People can all appreciate customer satisfaction, employee involvement, and continuous improvement. In order to ensure quality, they are able to utilize a statistical tool in Operations Research and Total Quality Management, known as Analysis of Variance (ANOVA) or The Kruskal-Wallis Test. ANOVA assumes that each population being studied has a normal distribution, that the errors are random and independent of each other, and that all populations have the same variance. However, another nonparametric test Kruskal-Wallis assumes the data does not have a normal distribution and the data is ordinal and not quantitative.

In Applying ANOVA and Nonparametric Tests Simulation, I learned:

1. Defining characteristics of ANOVA Test and Kruskal-Wallis Test 2. If the data does not have normal distribution, use Kruskal-Wallis Test 3. One-way and two-way ANOVA analysis is a technique used to compare means of two or more groups; variables like client satisfaction and core competency

At the workplace, I would like to increase productivity, customer satisfaction, and continued education among sales and service representatives. In order to do this, I can apply the concepts of ANOVA analysis or Kruskal-Wallis. My recommendation to the key decision maker would be to double check if that is the best solution and that we might not over look the rest of variables. Proficiency is a necessity in insurance and financial industry. Your job depends on your competency.

References
University of Phoenix. (2011). Applying ANOVA and Nonparametric Tests Simulation. In Applying ANOVA and Nonparametric Tests Simulation. Retrieved January 25, 2011, from https://ecampus.phoenix.edu/secure/aapd/vendors/tata/UBAMsims/research2/res

...ApplyingANOVA and Nonparametric test
In the simulation, I selected the Kruskal-Wallis test which is used when it is difficult to meet all of the assumptions of ANOVA. The Kruskal-Wallis test is a nonparametric alternative to one way ANOVA. This test is used to compare three or more samples, to test the null hypothesis that the different samples in the comparison drawn from the same distribution or from distributions with the same median. Interpretation of the Kruskal-Wallis test is basically similar to that of the parametric one way ANOVA however; nonparametric tests are usually simpler to calculate. We use ANOVA and Nonparametric tests in everyday situations, we rely on statistical techniques whether to determine a baseball score or to find out why a crop is failing.
Being able to apply the concepts and analytical tools in the workplace should not be a difficult one. In the simulation, I made suggestions to review project plans and effort estimation, review testing procedures and increase channels for effective communication. I should have set up a two-way ANOVA with a schedule variance as factor A and number of defects as factor B which I then would have been able to conclude that there was a difference in the means due...

...Running Head: ApplyingANOVA and Nonparametric TestsSimulationApplyingANOVA and Nonparametric TestsSimulation
<Name>
RES 342
University of Phoenix
<Date>
<Instructor>
ApplyingANOVA and Nonparametric TestsSimulation
Nonparametric tests are used in business research when data does not fit a normal distribution, require less stringent assumptions about data, and allow for the analysis of categorical and ranked data (Plonsky, 2009). When statisticians want to compare the means of two samples, an analysis of variance, or ANOVA, is often employed. According to Choudhury (2009), there are “four basic assumptions used in ANOVA: the expected values of the errors are zero, the variances of all errors are equal to each other, the errors are independent, and they are normally distributed” (n.p.).
The ANOVA and Nonparametric TestsSimulation provided by University of Phoenix yielded three lessons. The first is that a nonparametric test is used for tests of differences between groups (independent samples). The second lesson is that the nonparametric test is used to test differences between variables (dependant samples). And the third...

...NON-PARAMETRICTESTS AND ITS APPLICATION IN MANAGEMENT.
SUBMITTED BY :
SHARDA HARYANI
NON-PARAMETRICTESTS AND ITS APPLICATION IN MANAGEMENT
INTRODUCTION
Everything that we have done up until now in statistics has relied heavily on one major fact: that our data is normally distributed. Wehave beenable to make inferences about population means (one-sample, two-sample z and t tests and analysis of variance), but in each case weassumed that our population was normal. What happens when we want to performa test on our data, but we have no idea what its true distribution is, and therefore can’t assumethat our data are normally distributed? In this case, we use what are called nonparametric tests. These tests do not require any specific form for the distribution of the population. s non-parametric methods make fewer assumptions, their applicability is much wider than the corresponding parametric methods. In particular, they may be applied in situations where less is known about the application in question. Also, due to the reliance on fewer assumptions, non-parametric methods are more robust. Another justification for the use of...

...
QoS Techniques: MPLS
CET 2486C – Network Technologies
Professor:
November 27, 2012
Abstract
MPLS or Multi Protocol Label Switching is a networking technology that functions between layers 2 and 3 of the OSI model. MPLS constitutes of adding a label (sometimes called “Shim” because of their placement between layer 3 and layer 2 headers.) to the data package, this label contains special addressing and sometimes prioritization information. Because the MPLS label contains all the information necessary for the router to forward the package to the next hop, the router does not have to spend time analyzing the entire package thus improving network latency or bottlenecks. Due to its multi protocol capabilities MPLS can be integrated with different networking technologies from ATM to native IP environments; in addition, this multi protocol capability also provides a way to converge different types of traffic such as data, voice and video onto one network. MPLS technology also provides some other advantageous features like Traffic Engineering (TE), VPN, Any Transport over MPLS (AToM) and Quality of Service (QoS). This paper will help provide an understanding of how MPLS works and the QoS capabilities it can provide.
History of MPLS
In 1996 a group from Ipsilon Networks introduced a “flow management protocol”, this technology only worked with ATM transmissions and did not become very popular in the market. Not long after Cisco...

...Non-ParametricTests
In contrast to parametrictests, non-parametrictests do not require any assumptions about the parameters or about the nature of population. It is because of this that these methods are sometimes referred to as the distribution free methods. Most of these methods, however, are based upon the weaker assumptions that observations are independent and that the variable under study is continuous with approximately symmetrical distribution. In addition to this, these methods do not require measurements as strong as that required by parametric methods. Most of the non-parametrictests are applicable to data measured in an ordinal or nominal scale.
As opposed to this, the parametrictests are based on data measured at least in an interval scale. The measurements obtained on interval and ratio scale are also known as high level measurements.
Level of measurement
1. Nominal scale: This scale uses numbers or other symbols to identify the groups or classes to which various objects belong. These numbers or symbols constitute a nominal or classifying scale. For example, classification of individuals on the basis of sex (male, female) or on the basis of level of education (matric, senior secondary, graduate, post graduate), etc. This scale is the weakest of all the...

...Delos Santos
Members
Anna Lyn P. Jaime
Parametric and Non-ParametricTest
Topics
I. Introduction
II. Summary of the major points and how they might affect statistical analysis
III. What is the Parametric and Non- ParametricTests?
A. Parametric
a. Definition
b. Parametric Assumption
B.Non-Parametric
a. Definition
b. NonParametric Assumption
c. Two Different Meaning of ParametricTest
IV. Measurement
A. What are the 4 levels of measurement discussed in Siegel’s Chapter?
a. Nominal or Classificatory Scale
b. Ordinal or Ranking Scale
c. Interval Scale
d. Ratio Scale
V. When do we use the Parametric and Non-ParametricTest?
A. ParametricTest
a. Nominal or Ordinal
B. NonParametricTest
b. Interval or Ratio
VI. Kinds of Tests
A. ParametricTest
a. ANOVA- Analysis of Variance
i. Assumptions
ii. Inventor
1. Sir R. A. Fisher (1935)
iii. Formula
b. Test of Test
i. Inventor
1. Satterthwaite’s...

...ApplyingANOVA and NonParametricTests
a. What are three lessons you learned relative ANOVA and Nonparametric tests?
While doing the simulation; the three lessons learned are as follows:
Monitor – the situation
Measure – provide measurements, accumulate data
Improve – provide solutions for improvement.
b. 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)?
As a result of using this simulation the writer thinks he can apply numerous concepts to the workplace. A favorite of the writer is the chi-squared test for ANOVA. The writer feels that he can make competent decision in his business model by consistently utilizing the appropriate test on particular dataset. When attempting to solve the dilemma associated with the lack of productivity in the first part of the scenario, using the information given, the writer noticed that not enough people were competent enough to complete the tasks assigned to them, and as a result, the writer the Praxidike Systems provide training to increase competency. This is a vital component of the competency issues that the writer has in his business. Training the customer service and technical support staff is a vital component of the measure...

...Parametric and Nonparametric Data Identification
It is not always easy deciding whether data should be treated as parametric or nonparametric. A parametrictest is a test that requires a parametric assumption, such as normality. A nonparametric test does not rely on parametric assumptions like normality (Simon, 2005). Whichever test a researcher decides to use, one must have a basic understanding of both parametric and nonparametric data.
Parametric data is data that can be measured. For example, heights, weight, depth, amount of money, square footage are all forms of parametric data. These are all data with parameters. Interval and ratio measurements are considered parametric.
Data is considered parametric if it has the following three assumptions: normality, equal variances, and independence. First, is the data obtained from a population that is considered normal? Second, the populations from which the data is obtained should have equal variances. The F-test can be used to test the hypothesis that the samples have been drawn from populations with the equal variances. And, third, the data should be measured on an interval scale (Eachus, 2000).
Nonparametric data, on the other hand, does not have parameters and allows one to analyze...

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