Applied Managerial Decision Making MGMT600-1301B-03 Phase 3 individual project Rocklyn Kee Colorado Technical University Online Professor Donald Pratl March 11, 2013 There are 500 employees in the sales force of Company W that are spread out over Southeast, Northeast, West, and Central regions. The company has recently incorporated a new software program in and attempt to monitor how many sales are generated by each employee. It is expected that each month each region should sell the same aamount of products.
It has been noted that over the last three months however that this expectation has only been reached by half of the employees in each region. Before a decision can be made on possible theories as to why this is, some statistical testing must be done. Company W knows that there are different techniques that can be used to statistically analyze this issue. The one that we will be discussing here will be non-parametic statistics and hypoyhesis testing along with chi-square distribution testing of data. Let us begin by first defining these terms for a better understanding. Hypothesis Testing This is a technique that is applied sequentially by businesses in order to obyain concluions in regard to population utilizing information obtained from a sample. This information is gathered so as to enable a decision to be made as to the acceptance or rejection of the hypothesis by the researcher. The researcher makes a decision on two types of hypotheses the null (Ho) and the alternative (H1). The research is actually done on the null hypothesis, as this is the one that trys to reject the hypothesis statement by proving it to be untrue.
The researchers testing end result will do one of two things accept or reject the null hypothesis statement. Should the statement be proving to be untrue and rejected, the alternative hypothesis would in turn then be accepted. CTU Online, (2013) * Non-parametric Statistics This is what is known as an assessment to categorically apply information. The informationcan be ordinal or nominal. The researcher will be allocated to classify information that is presented as qualitative for variables that are nominal, while the researcher will be allocated by ordinal variables th categorize the presented information so it can be ranked.
There will be no formulated statements from non-parametric analysis in regard to the information that is presented by the researcher. The ANOVA, (analysis of variation) is a commomlly used method of non-parametric. The researcher does an analysis with the ANOVA to see if there is a differentation among groups, and if the mean of them are the same. With a null hypothesis the ANOVA will determine if the information that has been presented has the same means, while with the alternative hypothesis it will determine if the information has defferent means.
CTU Online, (2013) There is a one way method and a two way method for an ANOVA analysis that can be used by the researcher. There is only one factor for the researcher to test for equality of the presented information in the one way method, and the two way mwthod allows for distinguishing if there may be another factor. * Chi-Square Distribution Use Two types of information can typically be generarted when variables have no pattern, categorical or numerical. Researchers’ employ using the chi-square distribution in order to unmask the distinctions and to see if they are independent.
Categorical variables are specific variables with no fixed numerical value, and numerical type variables are numerical. In this regard there are question asked like, what type of work do you do, or do you own a vehicle? These types of questions are categorical variables because of the answers which would be for example, construction and yes or no, which are different responses from that of other questions like, what is your weight or what is your GPA? , that are numerical variables. These can be continious or discrete, for instance; how many homes do you own? This is discrete.
What is you height? This is continious. The counting of particular things is where the discrete data comes, and measuring a particular thing is where the continious data comes. CTU Online, (2013) * Using Chi-Square Analysis There can be a fluctuating in the testin using of the chi-square analysis based on the collected information, such as in this case of the representatives that reached the quotas and those who did not. In relation to the null hypothesis the statement would be, the sales representatives using the new sales software were able to meet their sales quotas vs. he sales representative not using the new sales software where not able to meet their quotas. The null in this statement cannot be proven to be true, because there is no proof that the sales representatives that used the new software were the ones to meet their quotas and the ones not using it where the ones who did not. Theory here is that the null hypothesis is false, and the alternative hypothesis is accepted. This means that the same amounts of products were not sold by representatives using the new sales software.
To develop statements of truth in regard to issues and problems in order to accurately classify is why researchers do hypothesis testing. The researcher has to have a complete understanding of the question or issue in odere to collect, analyize, and interpret data. A researcher has to analyze different theories statistically in order to be useful in educated business decisions making. Voelz, V. , (2006) References: . CTU Online. (2013). Applied Managerial Decision Making www. ctuonline. edu Voelz, V. , (2006). Hypothesis testing www. standford. edu