...MATH533: Applied Managerial Statistics Course project – part A I. Introduction. AJ DAVIS 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 the following five variables: 1. Location (Rural, Urban, Suburban) 2. Income (in $1,000’s) 3. Size (Household size) 4. Years (the number of years that the customer has lived in the current location) 5. Credit balance (the customers current credit balance on the store’s credit card, in $) II. Individual variables. 1. Location Tally for Discrete Variables: Location Location Count Percent Rural 13 26.00 Suburban 15 30.00 Urban 22 44.00 N= 50 [pic] Interpretation: Look at the table and the pie chart above, we can see the location of AJ Davis’ customers is distributed in 3 areas: rural, urban and suburban. The majority of customer live in urban areas with 44%. Suburban areas with 30% of customers are the second and rural areas have the least amount of customers with 26%. 2. Income. Descriptive Statistics: Income ($1000) Total Variable Count Mean StDev Minimum Q1 Median Q3 Maximum Income ($1000) 50 43.74 14.64 21.00 30.00 43.00 55.00 67.00 Variable Range Income ($1000) 46.00 [pic] Interpretation: Based on the table and histogram, we have some comments as follow. The range of customer’s...
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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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