...PROJECT PART A Exploratory Data Analysis Keller Graduate School of Management GM533: Managerial Statistics (Downers Grove, IL) Table of Contents I. Introduction & Overview .................................................................................................... 3 II. Individual Variables............................................................................................................. 4 Variable: Location................................................................................................................ 4 Variable: Income.................................................................................................................. 4 Variable: Credit Balance .................................................................................................... 5 III. Relationships.......................................................................................................................... 6 Location and Credit Balance................................................................................................ 7 Credit Balance and Household Size .................................................................................... 8 Income and Credit Balance .................................................................................................. 8 References............................................................................................................................... 9 I. Introduction...
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...Sarah R Klemm GM533 Course Project Part A 7/21/13 Introduction: This report includes a comparision of 50 AJ DAVIS department store credit card customers. The report takes 5 individual variables, location, income ($1000), size, years (the number of years a customer lived in a certain location) and credit balance (the customer’s current credit card balance on the store’s credit card, in dollars) and compares them both graphically and numerically. A. The first variable discussed in location of the customers. The chart below is a bar graph seperating the 50 credit card customers into rural, suburban and urban locations. The bar graph shows that most of the credit card customers are located in urban areas and the least amount of credit card customers are located in rural areas. B. The second variable discussed in the income of the household in thousands based on the histogram and box plot below. The histogram shows the frequency in which credit card customers with household incomes between $20,000 and $65,000 have credit cards. The boxplot shows where the highs and lows of those income categories fall. C. The third variable graphed is the years the credit card customer has lived in their current location. Based on the histogram below most credit card customers have lived in their current location around 15 years. The histogram shows the tallest frequency above the 15 year mark. Whereas the dotplot shows that the highest number of years is at 14 and...
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...PART A- Exploratory Data Analysis Introduction & Overview AJ Davis is a department store chain, which has many credit customers and wants to find out more information about these customers. The total sample set of 50 credit customers is selected with data collected. The below data was provided in order to perform the analysis. 1. Location: a. Urban b. Suburban c. Rural 2. Income 3. Household Size (number of people living in the household) 4. Years (the number of years that the customer has lived in the current location) 5. Credit Balance (the customer’s current credit card balance on the store's credit card) Individual Variables Five individual variables were provided for review: Location, Income, Household Size, Years, and Credit Balance. Below is a statistical analysis summarizing the key points referencing Location, Income and Credit Balance. Variable: Location The location of AJ Davis’ customers is distributed between three classes of urban, suburban and rural areas. Of the total number of customer locations in the sample set of 5; 13 are located in rural, 15 in suburban and 22 in urban locations. The pie chart shows that just less than half of all AJ Davis’ customers live in urban (44%) areas, yet customers that live in rural (26%) and suburban (30%) areas are relatively evenly distributed. The rural and suburban areas combine to compromise 56% of AJ Davis’ credit customer base in which they are interested in. This should be useful information to AJ Davis...
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...Maurice S. Butler Math533—Applied Managerial Statistics Course Project: Part A Introduction This project is based upon statistical data compiled concerning AJ Davis Department Stores, specific to a sample of its customer base. It is with intent of establishing relationship between location, gross income, and credit balances carried by customers that the following statistical analysis has been performed. It is assumed that information obtained as well as the interpretation of statistical analysis will enable credible recommendations in regard to future revenues or continued handling and/or maintenance of its receivables. Variables The first variable is the gross income of the stores’ customers. The data set includes 50 customers with gross income ranging from $20,000 to $79,000 per year. Compilation of the data into a frequency/relative frequency table (see below) reveals that the greatest frequency and relative frequency of the store’s customers is found within the $30,000 to $49,000 range. Fifty-two percent of the store’s customer base gross income is found within this range. First and third quartiles have been calculated to be 33 and 57 respectfully. However, no outliers have been identified within the data set. Income ($1000) | Frequency | Relative Frequency | 20-29 | 5 | 10% | 30-39 | 13 | 26% | 40-49 | 13 | 26% | 50-59 | 8 | 16% | 60-69 | 9 | 18% | 70-79 | 2 | 4% | | 50 | 100% | My second variable is the outstanding credit balances of...
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...Exploratory Data Analysis AJ Davis Project Part A January 18, 2013 Overview of Analysis 3 Individual Variable Analysis 4 Relationship between variables 8 Conclusion 10 Bibliography 11 Overview of Analysis AJ Davis is a department store chain, which has many credit customers and wants to find out more information about these customers. The department store provided a sample of 50 customers. The following data was provided for analysis: 1. Location a. Rural b. Urban c. Suburban 2. Income (measured in $1000’s) 3. Household size 4. Years in current location 5. Store credit balance Individual Variable Analysis Five individual variables were provided for analysis: Location, Income, Household size, Years at location and Credit balance. Below is a summary of the key points on the following individual variables: Location, Size and Credit Balance. Variable: Location The first individual variable summary presented is Location. The variable location has 2 subcategories from which data was reported: Rural, Urban and Suburban. As this is qualitative data only no measures of central tendency or descriptive statistics will be given. Based on the frequency distribution and the pie chart, the maximum number of customers from the sample live in Urban locations, with this variable representing 44% of the sample. Customers in the represented in the Rural areas is 26% and customers in the Suburban area represents 30% of the...
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...Keller graduate school of management | Department Store part B | Week 6 project for AJ Davis | Information from the project for AJ Davis department store. Attached in this report is all information related to the information listed from Excel. | Results from Minitab findings The mean income was less than $50,000. The Null Hypothesis: which states the average annual income was greater than or equal to 50. The number of trials (n) is larger than 30 use ztest to check the hypothesis. With the Critical Value and decision rule: Reject H0 if Z –value is -1.645. By using the z-test the one sample z: results are as follows: z -3.02 p .001 mean 43.74. The p value .999 is larger than .05, so I would not reject the null hypothesis. The p value shows the probability of rejecting null hypothesis. The confidence level of .05 shows there is enough data to support the claim that the average annual income was less than $50,000. The confidence level at 99.5% is 38.41 and since 50 are above the 99.5% confidence level shows support for the claim that the mean income is less than $50,000. The proportion of customers who live in urban areas exceeds 40%. For this 21 out of the 50 people in the data live in an urban area. This equates to .42 so my point estimate would be .42 or 42%. The Ho: p=.40 vs. Ha: p >.40. z= .29. The reject area is z> 1.645; since .29 is less than 1.645 I would not reject Ho. The p value is .386. By not rejecting this is saying there is insufficient...
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...Project Part A Exploratory Data Analysis Keller Graduate School of Management GM533: Managerial Statistics (Downers Grove, IL) Michael Knapp Table of Contents I. Introduction...pg 3 II. Individual Variables a. Location…pg 3 b. Income…pg 3 and 4 c. Size…pg 4 and 5 III. Relationships d. Size and Location…pg 5 and 6 e. Income and Location…pg 7 and 8 f. Size and Income…pg 8 and 9 This analysis is to compare the information presented by AJ DAVIS which is a department store chain, which has many credit customers and wants to find out more information about these customers. A sample of 50 credit customers is selected with data collected on five variables, I have selected 3 to compare side by side to one another and analyze the data provided. The 3 variables are LOCATION (Rural, Urban, Suburban), INCOME (in $1,000ʼs – be careful with this) and SIZE (Household Size, meaning number of people living in the household). After I cover each variable I will compare the relationship between size and location, income and location, and size and income. The first variable is location. The location refers to three categories: rural, suburban and urban. Based off of the information provided I found that 13/50 or 26% of the sample group live in a rural area, 15/50 or 30% of the sample group live in a suburban area and 22/50 or 44% live in a urban area. Tally for Discrete Variables: Location Location Count Percent ...
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...12 Course Project AJ DAVIS DEPARTMENT STORES PROJECT PART A In this course project, my aim is to present the statistical analysis of the data for Aj Davis departmental store chain, which has many credit customers and wants to find out more information about these customers. In analyzing the individual variable, using graphical illustrations I would be using histogram, bar chart and a pie chart because there are useful when using numerical comparison. The 3 individual variables 1) The 1st individual variable, I choose is the credit balance of the customers. Credit Balance Numerical Summary: | Credit Balance($) | Mean | 3970 | Median | 4090 | Mode | 3890 | Standard Deviation | 932 | Skewness | -0.15 | Range | 3814 | Minimum | 1864 | Sum | 198523 | Maximum | 5678 | Interpretation The mean credit balance of the customers is given as $3970. The standard deviation is given approximately as 932. The credit balance of the customers is more or less normally distributed with the peak of the bell shaped distribution lying in the range 3814. 2) The 2nd individual variable, I choose is the household size. Thus the number of people living in the households. SIZE Frequency Distribution | Size | Frequency | 1 | 5 | 2 | 15 | 3 | 8 | 4 | 9 | 5 | 5 | 6 | 5 | 7 | 3 | Interpretation The mean of the household size is known as 3 approximately as seen on Minitab. The median of the household size 3 and the mode would be 2. As...
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...What to Never Eat After Your Workout By Cassandra Forsythe-Pribanic, PhD, RD, CSCS & Jayson Hunter, RD, CSCS Introduction Nutrition: To some people, it's just a nine-letter word synonymous with food and dieting. To others - people who know the secrets behind a better workout and a leaner body nutrition means so much more than just filling their plates. These people know that with proper nutrition, your body can experience beneficial results that out-compete any fancy pill or expensive surgical intervention. It's true! And, to take it even a step further, the timing of your nutrition with correct food choices will turn your body into an energetic, elated, lean, fat-burning machine! And who doesn't want that? We sure do! Not that being lean means you'll be automatically happier, but, if you eat the right foods at the right times, you'll feel less grumpy, you'll have more energy to exercise hard the next time you hit the gym, and you'll be pleasant for others to be around! Plus, you'll look good too! You probably already know that eating small, balanced meals every few hours is one of the keys to a healthy physique, but that's not what we're talking about here. In this special report, we're going to show you how eating the right foods at the right times following your workout will make a huge difference in how you feel when you're working out, and how you feel for the 23 hours that you're not working out. Eating correctly after your workout will also help you be able...
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...Table of Contents |Topic |Page No. | |Executive Summary |3 | |Introduction |4 | |History |5 | |Brands |11 | |Values |14 | |Vision Statement |15 | |Mission Statement |16 | |Aspiration Statement |18 | |Situation Analysis |19 | |Competitive Analysis |20 ...
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...GLOBAL MARKET ASSESSMENT FOR HANDICRAFTS VOLUME I FINAL DRAFT JULY 2006 This publication was produced for review by the United States Agency for International Development. It was prepared by Ted Barber and Marina Krivoshlykova of Development Alternatives, Inc. GLOBAL MARKET ASSESSMENT FOR HANDICRAFTS VOLUME I FINAL DRAFT The authors’ views expressed in this publication do not necessarily reflect the views of the United States Agency for International Development or the United States Government. FOREWORD This paper was written as part of the Accelerated Microenterprise Advancement Project (AMAP) Business Development Services Knowledge and Practice (BDS K&P) research initiative. The AMAP BDS initiative’s major objective is “integrating micro and small enterprises into productive value chains to create wealth in poor communities.” The research draws on experience and insights from: • Interviews with leading handicraft buyers in the United States, the European Union, and the Caribbean, including importers and retailers currently sourcing from Haiti, those who have done so in the past, and those who source handmade products from other destinations; • Interviews with market experts, such as product development consultants, designers, enterprise development consultants, and marketing specialists who work with handicraft producers in developing countries; • Discussions with market experts and USAID at a roundtable conducted in Washington...
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...TENNIS RECOVERY A Comprehensive Review of the Research Editors: Mark S. Kovacs, PhD Todd S. Ellenbecker, DPT W. Ben Kibler, MD A United States Tennis Association Sport Science Committee Project Tennis Recovery: A Comprehensive Review of the Research Copyright © 2010 United States Tennis Association Inc. ISBN 978-0-692-00528-6 Editors: Mark S. Kovacs, Todd S. Ellenbecker, W. Ben Kibler TENNIS RECOVERY A Comprehensive Review of the Research A United States Tennis Association Sport Science Committee Project Editors: Mark S. Kovacs, PhD Todd S. Ellenbecker, DPT W. Ben Kibler, MD Introduction In the last two decades, physical training and competitive opportunities have increased dramatically in junior, collegiate and professional tennis. This arose due to a multitude of factors, but much of it has stemmed from an increase in knowledge and understanding of scientifically based training programs focused on improving performance. As this focus on performance has increased, the area of recovery has received relatively limited focus. Recovery is a multi-faceted paradigm focusing on recovery from training—session to session, day to day and week to week. Recovery is also vitally important during training as well as in competition between matches and between days during multi-day tournaments. As more information is needed in the area of tennis specific recovery, the Sport Science Committee of the United States Tennis Association (USTA) sponsored an extensive evidence-based...
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...CHAPTER ONE INTRODUCTION 1. Background to the Study Films, generally, serve as a tool for national integration and development. Major types of film are home video, which develop, until now, from what is formerly known as cinema or stage play/drama. As part of mass media, home videos play the important roles of informing, educating, entertaining and transmitting social heritage. Through their educational role, however, home videos concern themselves with evolving a better society by exposing societal ill and wrongs. Since the emergence of home videos, at the turn of the twenty-first century the films industries, and both male and female actors in Nigeria, Nollywood, have considerably influenced the habits, belief systems, style of dressing and other behavioural idiosyncrasies on many Nigerian youths. Thus, one can say, however, that the emergence of home videos have helped to promote the Nigerian cultural heritage; aside this, it has awaken in many youths the Nigerian culture that was once lost during the colonial period. There are also negative effects of home videos on audiences. However, there have been cases where home videos are criticized to the cause for some societal ills. Social critics, who believes in this school of thought says that some antisocial behaviours like violence and extravagant life that many films portrays in their content perceptibly affect the behavior of the audience. Nonetheless, all these sum up to mean that home videos have both positive...
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...the lives of 5000 people. With the sincere hope and plea that some findings and thoughts of this dissertation will contribute to reducing tuberculosis and poverty. “The appalling global burden of tuberculosis at the turn of the millennium, despite the availability of effective control measures, is a blot on the conscience of humankind. For developing countries, the situation has become desperate and the "cursed duet" of tuberculosis and AIDS is having a devastating impact on large sections of the global community. The vital question is, can despair be turned to hope early in the next millennium?” John Grange and Almuddin Zumla, 1999 TABLE OF CONTENTS Acknowledgements Summary Zusammenfassung Abbreviations i iii vii xi PART I: Introduction and overview Page Chapter 1: Background 1.1. Motivation for the thesis and overview ………………………………………………….….. 1.2. The burden of tuberculosis ………………………………………………………………..… 1.2.1. Public health indicators …………………………………………….……………….. 1.2.2. Economic indicators …………………………………………….…………….…….. 1.2.3. The burden of illness ……………………………………………….…………….….. 1.3. The control of...
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...for dealing with major disasters like earthquake of 2005 and floods of 2010 and 2011 partially due to limited resources, economic instability and partially due to absence of well trained and equipped disaster management infrastructure. We also lack proper system for disaster prevention and preparedness that could ensure effective mitigation to reduce the loss of life and property damage in the face of a natural disaster. 2. Disaster management is unfortunately seen as provision of relief rather than the management of all of its phases and long term management of risk. We therefore need a comprehensive preparedness, prevention and mitigation strategy with a view to better manage and coordinate activities of various line ministries, departments and civil society. Pakistan has a traditional relief and response oriented disaster management system, however over a short period of time it is experiencing constructive changes. Present system to respond to medium level disasters is fairly structured and it is quite in place to handle disasters. Nevertheless, our disaster management system to respond small to large scale disasters needs capacity building and...
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