...Keller Graduate School of Management Applied Managerial Statistics (GM533) Course Project Case Study: Grocery Bags data gathered and written by ME Applied Managerial Statistics GM533 Instructor: XX I. Executive Summary For this research I decided to develop my own case study and collect all the data myself. The data file named “Grocery Bag Study” (separate attachment), contains observations on 33 sample groups with a variation of 8 different characteristics (see table below). These characteristics include ethnicity, number of adults and minors in household, the number of bags collected weekly, the number of bags they recycle or reuse, the use of reusable fabric shopping bags, how many they throw away and the sex of the adults in the household. The totals for the bags are shown in the table below (Table A.1). For the sake of this study, I am going to combine the paper and plastic together because I want my dependent variable to be the number of bags recycled each week. I want to determine if the independent variables affect the recycle rate and which ones affect it the most, which can be eliminated and what my conclusions will be. II. Calculations This file was used to prepare a report on the influence of various options on grocery bags collected each week and to relay how this information could be used to determine the recycle rates (y). Statistical analysis by Hypothesis Testing and Multiple Regression Analysis was performed on the collection of grocery...
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...A Statistical Analysis of Case 32 Michael A. Wilson GM533 02/12/2012 INTRODUCTION The purpose of this analysis is to analyze the QSCA in determining if the amount or size of a bill is directly correlated to the number of days the bill is past due. In order to support the validity of this relationship, a statistical analysis of the data provided will support the relationship within 95% confidence levels. These findings should give a better understanding of the QSCA’s business and provide vital insight on the relationship between the data being evaluated. SUMMARY The focal point of this analysis is to determine whether or not the amount of the bill has an effect on the number of days the bill is late. This information will be extremely valuable for the business to develop higher efficiency and profitability within the account services team. In addition, the final output of the analysis can be applied to several situations, such as insights into customer trends like bill payments, financing, and the current economic impact on the bill collection business. This analysis will help confirm the importance of paying a bill on time and should be supported by the client services team in the management of bill collection. We are currently face with challenging economic times and the support of motivating clients to expedite their bill payments will help businesses and customer’s personal and internal finances. In order to validate the relationship between the amount of a bill...
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...Running Head: Case 49 Property Crimes Andrea K. Wallace GM533 Professor Beintema Keller Graduate School of Management October 16, 2011 Executive Summary After examining the eight variables that attribute to property crimes, the three variables that effect crime are density, dropout and urban. When density increases by 1%, this would cause a decrease in crime rate. When the dropout rate increases by 1%, this would cause an increase in property crimes. When urban area crimes increase by 1%, the property crime rate increases. The more crowded the urban areas are, the more property crimes will be committed. Introduction Crime is an act of violence that is carried out by an individual or multiple individuals. A crime can be toward another person or property of a person or company. Property Crimes often occurs when someone tries to steal something that is not the property of their own and in other scenarios, the destruction of someone else’s property also. There are many different types of property crimes. Burglary, theft, motor vehicle theft, larceny & arson are few that can fall under that category. This research is going to examine the cause of property crime based on the income, dropout, precipitation, public aid recipients, density, kids, unemployment, urban area, and state. The information that was provided was given by variety of United States government sources. ANALYSIS AND METHOD: Minitab was used to analyze the given data and test the various facts. Crime...
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...Case Study 49: Property Crimes First M Last (firstlast@mail.com) For Professor Beintema Managerial Statistics (GM533) Keller School of Management August 2010 I. Executive summary Our study examined data provided by various U.S. government agencies on property crime rates in the fifty U.S. states and eight possible contributing factors such as per capita income, high school dropout rate, average precipitation, population density, and urbanization. Our analysis revealed that of the eight possible contributing factors, only three variables (namely, urbanization rate, high school dropout rate, and population density) affected property crime rates. Our data analysis model accounted for approximately 66% of the factors contributing to property crimes. The model is generally considered to be statistically strong, however, if we need to account for the remaining 34% of factors contributing to property crime rates in the U.S., further data and evaluation of other possible factors would be necessary. II. Introduction According to the US Department of Justice (2006), property crime includes several criminal offenses such as burglary; car and motorcycle theft, larceny theft and arson. Property crimes involve “taking of money or property, but there is no force or threat of force against the victims.” One exception to the basic rule, however, is arson which does not involve the taking of property and does involve force against the victims. The purpose of this case...
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...HOUSE PRICES II CASE: 28 Olusegun Abebayo TAKSAMAI TANAPAISANKIT STACEYANN BARTON GM533 Applied Managerial Statistics Abstract Pricing your home competitively is an important factor in determining your selling price. As a seller, the aim is to get the best asking price. To prevent losing money, one has to be careful not to underprice their home. As mentioned in the article Selling Your Home – The Importance of Pricing Correctly, the most important factor when selling your home is not what your home is listed for, but rather what similar homes have recently sold for. This is the statistic that will properly tell you what buyers are willing to pay for a similar home, in a comparable neighborhood. In the article entitled Pricing Houses-Pricing Houses to Sell, Elizabeth Weintraub provided a few guidelines that can be effective in pricing one’s home. She suggested that a seller looks at every similar home that was or is listed in the same neighborhood over the past six months. Compare similar square footage, within 10% up or down from the subject property, if possible. Compare apples to apples. The objective of this study is to use the data given in Case 28 – Housing Prices 11 to determine the selling price for a house in Eastville, Oregon and prepare and establish the description of how the findings might be used as a general method for estimating the selling price of any house in my neighborhood. In doing so, we had to figure out what factors determine the selling...
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