...Descriptive Statistics Project A Baron J Hamilton Jr. D00743033 Keller Graduate School of Management Math 533-65352 Applied Managerial Statistics Introduction Data was collected from a sample of credit customers in the department chain store of AJ Davis using statistical analysis. The analysis below consists of 4 quantitative methods which are income, size, years and credit balance and one qualitative method, location. Descriptive statistics can explain some of the relationships of the data collected. LOCATION | INCOME($1000) | SIZE | YEARS | CREDIT BALANCE($) | Urban | 54 | 3 | 12 | 4016 | Rural | 30 | 2 | 12 | 3159 | Suburban | 32 | 4 | 17 | 5100 | Suburban | 50 | 5 | 14 | 4742 | Rural | 31 | 2 | 4 | 1864 | Urban | 55 | 2 | 9 | 4070 | Rural | 37 | 1 | 20 | 2731 | Urban | 40 | 2 | 7 | 3348 | Suburban | 66 | 4 | 10 | 4764 | Urban | 51 | 3 | 16 | 4110 | Urban | 25 | 3 | 11 | 4208 | Urban | 48 | 4 | 16 | 4219 | Rural | 27 | 1 | 19 | 2477 | Rural | 33 | 2 | 12 | 2514 | Urban | 65 | 3 | 12 | 4214 | Suburban | 63 | 4 | 13 | 4965 | Urban | 42 | 6 | 15 | 4412 | Urban | 21 | 2 | 18 | 2448 | Rural | 44 | 1 | 7 | 2995 | Urban | 37 | 5 | 5 | 4171 | Suburban | 62 | 6 | 13 | 5678 | Urban | 21 | 3 | 16 | 3623 | Suburban | 55 | 7 | 15 | 5301 | Rural | 42 | 2 | 19 | 3020 | Urban | 41 | 7 | 18 | 4828 | Suburban | 54 | 6 | 14 | 5573 | Rural | 30 | 1 | 14 | 2583 | Rural | 48 | 2 | 8 | 3866 | Urban | 34 | 5 | 5 | 3586 | Suburban...
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...TQM and Reinventing Government on the web-site for teachers and learners of English as a secondary language from a German point of view. [pic] Table of contents |Total Quality Management and Reinventing Government |HOME[pic]PAGE |[pic] |back to An introduction to QM |go on to: Committee:TQM Information |[pic] | |[pic] TOTAL QUALITY MANAGEMENT AND REINVENTING GOVERNMENT I. What is TQM? TQM is a new paradigm of management! TQM is both a philosophy and methodology for managing organizations. TQM includes a set of principles, tools, and procedures that provide guidance in the practical affairs of running an organization. TQM involves all members of the organization in controlling and continuously improving how work is done. Government agencies that use TQM agree that it is fundamentally different from traditional management. II. History of TQM! TQM Japanese Management? Yes and No! The American Walter A. Shewhart of Bell Laboratories developed a system of measuring variance in production systems known as statistical process control (SPC). Statistical process control is one of the major tools that TQM uses to monitor consistency, as well as to diagnose problems in work processes. His student W. Edwards Deming, a mathematical physicist and U.S Department of Agriculture and Census Bureau research scientist, was hired to teach SPC and quality control to the U.S. Defense industry. These methods were considered so important to the war effort that they were classified as military...
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...1. The graph below shows a slight positive relationship between having a higher credit balance with a larger household size. 2. The equation of best fit, also known as the regression equation, is Credit Balance($) = 2591 + 403 Size. This means that for each 1 increase in household size that that credit balance increase by $403. 3. The coefficient of correlation is the square root of .566 which is .7523. This value being closer to one than to zero and being positive implies strong linear relationship between credit balance and size. It confirms that as credit balance increases, household size will also increase. 4. The coefficient of determination is .566. This value represents the proportion of the total sample variation of y, measured by the total sum of squares of deviations in the sample from the mean, can be explained by using credit balance to predict household size. This means that 56.6% of the sample variation credit balance (y) can be explained by using household size (x) in this straight line model. 5. The null hypothesis is that Beta1equals 0 and the alternative hypothesis is that Beta1 does not equal 0. The p-value is 0.000, which is less than 0.05. Therefore, the null hypothesis that Beta1 equals zero can be rejected. There is sufficient evidence that Beta1 does not equal zero. This shows that our regression model is useful, in that credit balance does depend on household size. 6. Based on my findings, credit balance will increase by $403 per 1...
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...| Course Project: AJ DAVIS DEPARTMENT STORES | | | | | | This is a report presenting detailed statistical analysis of the data collected from a sample of fifty credit customers in the department chain store AJ DAVIS. Data was collected on five variables, which were location, income, size, years at current location and credit balance. The first variable analyzed was that of Location. The location data is a categorical variable. Which was further broken down into three subcategories? These subcategories are Urban, Suburban and Rural. A frequency distribution and pie chart are given as follows: Frequency Distribution: | Location | Frequency | Urban | 21 | Suburban | 15 | Rural | 14 | The pie chart and frequency distribution, proves that the largest number of customers are those in the rural category (42%), followed by those in the suburban category (30%). There are only 28% of the customers falling into the urban category. The next variable analyzed was Size. It is a quantitative variable. Central tendency, variation and a bar graph were calculated for the Size variable. The mean household size of the customers is 3.42. And the median of the data collected is 3, the mode is 2. The standard deviation is rounded to the nearest one hundredth and is 1.74. Upon reviewing the frequency distribution chart and the bar graph, the largest number of customer household size is 2. Size | Mean | 3.42 | Median | 3 | Mode | 2 | Standard...
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...GM533 PROJECT PART C: Regression and Correlation Analysis 1. 2. The equation of the ‘best fit’ line which describes the relationship between credit balance(y) vs size(X) is given as follows: y = 404.13x + 2581.9 3. The coefficient of correlation = 0.752483 Correlation coefficient, r is a measure of the degree of correlation or interdependence between two variables. The value of the correlation coefficient can range between -1 and +1. A negative value of r indicates an inverse relationship; a positive value of r indicates a direct relationship; a zero value of r indicates that the two variables are independent of each other. The closer r is to +1 or -1, the stronger is the relationship between the two variables. For the given regression model, the correlation coefficient is very close to its ideal value of +1, thus indicating a strong positive correlation among the variables credit balance(y) vs size(X). 4. The coefficient of determination = 0.566773. Coefficient of determination, r2, is a measure of the amount of possible variability in the dependent variable that can be explained by its relationship to the independent variable. It is the square of the coefficient of correlation. The value of r2 ranges from 0 to 1 and higher the value, the better the fit. For the given regression model, about 94.81% of the variability in the dependent variable credit balance (Y) can be explained by the variability in the independent...
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...1) Mean: The mean of a set of numbers is the average. The mean is calculated by finding the sum of all the values and dividing by the number of values. 11+12+12+13+14+16+18+19+20 = 135 There are 9 numbers in the series, so the mean is: Mean = 135/9 = 15 Median: The median of a series of numbers is the number that appears in the middle of the list when arranged from smallest to largest. For a list with an odd number of members, the way to find the middle number is to take the number of members and add one. Then divide that value by two. In our case, there are 9 numbers in the series. 9+1 = 10 and half of 10 is 5. The fifth number in the series is the median or 14. If the number of members of the series was even, the average of the two middle numbers would be the median. Mode: The mode is the number in the series that appears the most often. If there is no single number that appears more than any other number in the series, there is no value for the mode. The number 12 appears twice in the series. The mode of this series is 12. Quintile: The first quartile of a group of values is the value such the 25% of the values fall at or below this value. The third quartile of a group of values is the value such that 75% of the values fall at or below this value. The first quartile may be approximately calculated by placing a group of values in ascending order and determining the median of the values below the true median, and the third quartile is approximately calculated by determining...
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...Course Project A – AJ Davis Department Store Keller Graduate School In reviewing the data for AJ Davis Department Store, the below diagrams represents the detailed statistical analysis of the data collected from a sample of 50 credit consumers. The data collected was based on the following five variables: location, income, size, years and credit balances. The first individual variable considered was Location. The three subcategories are Rural, Suburban, and Urban. Shown below is the frequency distribution and pie chart, the maximum number of customer belonging to the Urban category were 42%, followed by the Suburban of 30% and Rural at 28%. Since this is a categorical variable, the measure of central tendency and descriptive statistics was not calculated. Frequency Distribution Location Frequency Rural 14 Suburban 15 Urban 21 The second variable is Credit Balances, displayed in the histogram below in the frequency of how many consumers and their credit balances at department store. Descriptive Statistics: Credit Balances ($) Variable N N* Mean SE Mean StDev Minimum Q1 Median Q3 Credit Balance ($) 50 6 3964 132 933 1864 3109 4090 4748 Variable Maximum ...
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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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...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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...MATH 533 WEEK 6 COURSE PROJECT PART B To purchase this, Click here http://www.activitymode.com/product/math-533-week-6-course-project-part-b/ Contact us at: SUPPORT@ACTIVITYMODE.COM MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 Week 6 Course Project Part B MATH 533 WEEK 6 COURSE PROJECT PART B To purchase this, Click here http://www.activitymode.com/product/math-533-week-6-course-project-part-b/ ...
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...Data File 2 Chapter Three (Show all your work) 1) A teacher asked each of her students how many novels they had read in the previous six months. The results are shown below. 0 1 5 4 2 1 3 2 2 7 2 5 0 1 0 1 1 2 6 0 2 3 1 2 7 1 4 2 3 1 7 0 0 2 1 1 0 6 1 7 Construct a frequency table for the number of novels read. |Number |Frequency | |of novels | | |0 |7 | |1 |11 | |2 |9 | |3 |3 | |4 |2 | |5 |2 | |6 |2 | |7 |4 | 2) The frequency table shows the weights in ounces of 30 stones Weight (oz) Number of Stones 1.2-1.6 5 1.7-2.1 2 2.2-2.6 5 2.7-3.1 5 6. 13 Use the above information to construct a cumulative frequency table for the data. |Weight (oz) |Cumulative | | |Frequency | |1.2 - 1.6 |5 | |1.7 - 2.1 |7 | |2.2 - 2.6 |12 | |2.7 - 3.1 |17 | |3.2 - 3.6 |30 | 3) Use the following data to construct a bar chart. Job categories Clerical Management Maintenance Professional...
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...Data Visually and Through Numbers Data File 2 - Chapter Three (Show all your work) 1) A teacher asked each of her students how many novels they had read in the previous six months. The results are shown below. 0 1 5 4 2 1 3 2 2 7 2 5 0 1 0 1 1 2 6 0 2 3 1 2 7 1 4 2 3 1 7 0 0 2 1 1 0 6 1 7 Construct a frequency table for the number of novels read. Solution: Number of novels read | Frequency | 0 | 7 | 1 | 11 | 2 | 9 | 3 | 3 | 4 | 2 | 5 | 2 | 6 | 2 | 7 | 4 | 2) The frequency table shows the weights in ounces of 30 stones Weight (oz) Number of Stones 1.2-1.6 5 1.7-2.1 2 2.2-2.6 5 2.7-3.1 5 3.2-3.6.1.1 13 Use the above information to construct a cumulative frequency table for the data. Solution: Weight oz | Number of stones | Relative Frequency | Cumulative Frequency | 1.2-1.6 | 5 | 5/30 = 16 2/3% | 5 | 1.7-2.1 | 7 | 2/30 = 6 2/3% | 2 + 5 = 7 | 2.2-2.6 | 12 | 5/30 = 16 2/3% | 5 + 2 + 5 = 12 | 2.7-3.1 | 17 | 5/30 = 16 2/3% | 5 + 5 + 2 + 5 = 17 | 3.2-3.6.1.1 | 30 | 13/30 = 43 1/3% | 13 + 5 + 5 + 2 + 5 = 30 | | | 100% | 30 | 3) Use the following data to construct a bar chart. Job categories Clerical Management Maintenance Professional Unemployed 5 4 6 2 1 Create a bar graph and place the above data in a bar graph. Solution: Okay, but the categories should be plotted on the x-axis and frequency should be plotted on the y-axis. 4) The data below are...
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...حربيت اصالييت 12 May - 16 May GRADE 5 نغت عربيت اجخًاعياث English Math Sceince ICT Art Sunday حم اَشطت انطانب درس انٓجرة انُبٕيت انى انًذيُت انًُٕرة ٍحم ٔرلت حًاري To study for quiz on Wednesday : Sequence of events. Exercise on p157 of practice book. 1 Monday حم يٍ يهزيت احكاو 10انخالٔة صفحت To study for quiz on Quiz Material: 8-1/ 8Wednesday : Adverbs 3/ 13-2/ 13-3 exercise on p199 and 200 2 Tuesday ٌ" انًادة انًطهٕبت في االيخحا صذيمُا حضيٍ - انُحٕ كم ياحى ّ" دراصخ To study for quiz on Wednesday : vocabulary words on Tucker's Travels. In copybook and in the reader 3 Wednesday ٔرلت حذريباث Study for Quiz: 1. How Does Matter Change?(booklet) 2. What is Sound?(booklet) related sheets 4 Thursday w.b. pg. 94 ex 1 to 16 +18 + 5 Comments Al ARABIA FOR EDUCATION DEVELOPMENT AL ITTIHAD PRIVATE SCHOOL- Mamzar العربيـــــــــــــــة لتطويــــــــــــر التعليـــــــــــــم الممزر - مذرســـــة االتحــــــاد الخاصــــــة Boys Section Weekly Homework S R DAYS حربيت اصالييت 12 May - 16 May GRADE 6 نغت عربيت اجخًاعياث English Math Sceince ICT Art Sunday حم اَشطت انطانب درس ٍانًٕاخاِ بيٍ انًٓاجري ٔاالَصار 1 Quiz Syllabus: 1. Fact&Opinion 2. ٍ حم ٔرلت حًاريMain idea with supporting details 3. 'Robotics' Vocabulary list (10 Revision sheet for facts & opinions worksheet Solve H.w p. 533 # 3 and 5 Monday حم يٍ يهزيت انخالٔة صفحت 13 QuizI: 11.1 ; 11...
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...Keller University Math 533 Prof Ron Deluca Project Part C AJ Davis Inc., Regression Analysis June 18, 2016 Abstract: This is the final project C from Keller University math 533 using AJ Davis company data base provided in our doc sharing student portal. The bold questions are taken from Part C in the Project outline. My answer is underneath each of 14 questions. *Please note the formatting was difficult because Minitab fonts output is different than my desired Arial 12 point font. From AJ Davis database from our class. 1. Generate a scatterplot for income ($1,000) versus credit balance($), including the graph of the best fit line. Interpret. note y=income, x=credit balance Interpretation: The scatter plot of Income Vs Credit balance ($) show that the slope of the ‘best fit’ line is upward (positive); this indicates that Income varies directly with Credit Balance. As Income increases, Credit Balance also increases vice versa. 2. Determine the equation of the best fit line, which describes the relationship between income and credit balance. Y= -3.516 + 0.01193(x) 3. Determine the coefficient of correlation. Interpret. Correlations: Income ($1,000), Credit Balance($) Pearson correlation of Income ($1,000) and Credit Balance($) = 0.801 P-Value = 0.000 The coefficient of correlation is given as r = 0.801. The correlation coefficients between the variables show a positive sign OR direct relationship. The correlation coefficient is far from the P-Value...
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...MATH-533 Applied Managerial Statistics Course Project Part A Introduction It is so interesting to choose sections location, an income and size as representative of my course project. From the list, it really makes me an interest of trend of people who is living in urban, has how many of family members and how much they earn. Basically I would like to categorize the direction of cluster of people and their desires to live which area of country. First, I am going to analyze the locations versus family size, and then family size versus to income. Then I will analyze further how many of family and location has how much income which helps us to reveal to pay back the credits. 1st Individual Variable (Location) Table 1 and graph 1 Location | Number of houses | Rural | 14 | Suburban | 15 | Urban | 21 | From the table 1 and graph 1 shows the number of houses and number of locations. Based on the information customers from AJ Davis tend to live in the Urban area rather than the suburban and rural area. 2nd individual variable (Size) Size (family members) | number of objects | 1 | 5 | 2 | 15 | 3 | 8 | 4 | 9 | 5 | 5 | 6 | 5 | 7 | 3 | Graph 2 and table 2 Based on table 2 information following data comes out. (Numbers of customers) Minimum: 3 Median:5 Q3:8.5 Maximum:15 Based on the graph 2 and table 2, most of the customers intend to have less than 5 family members. The majority of customers have 2 family members and only 3 of them...
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