Math 533 - Course Project Part a

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  • Topic: 3rd millennium, City, Variable
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  • Published : January 20, 2013
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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:

LOCATION (Rural, Urban, Suburban)
INCOME (in $1,000's – be careful with this)
SIZE (Household Size, meaning number of people living in the household) YEARS (the number of years that the customer has lived in the current location) CREDIT BALANCE (the customers current credit card balance on the store's credit card, in $). The data appears below, and is available in Doc Sharing Course Project Data Set as an EXCEL file:

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
67
4
13
5037

Rural
50
2
11
3605

Urban
67
5
1
5345

Urban
55
6
16
5370

Urban
52
2
11
3890

Urban
62
3
2
4705

Urban
64
2
6
4157

Suburban
22
3
18
3579

Urban
29
4
4
3890

Suburban
39
2
18
2972

Rural
35
1
11
3121

Urban
39
4
15
4183

Suburban
54
3
9
3730

Suburban
23
6
18
4127

Rural
27
2
1
2921

Urban
26
7
17
4603

Suburban
61
2
14
4273

Rural
30
2
14
3067

Rural
22
4
16
3074

Suburban
46
5
13
4820

Suburban
66
4
20
5149

PROJECT PART A: Exploratory Data Analysis

Open the file MATH533 Project Consumer.xls from the Course Project Data Set folder in Doc Sharing. For each of the five variables, process, organize, present and summarize the data. Analyze each variable by itself using graphical and numerical techniques of summarization. Use MINITAB as much as possible, explaining what the printout tells you. You may wish to use some of the following graphs: stem-leaf diagram, frequency/relative frequency table, histogram, boxplot, dotplot, pie chart, bar graph. Caution: not all of these are appropriate for each of these variables, nor are they all necessary. More is not necessarily better. In addition be sure to find the appropriate measures of central tendency, and measures of dispersion for the above data. Where appropriate use the five number summary (the Min, Q1, Median, Q3, Max). Once again, use MINITAB as appropriate, and explain what the results mean. Analyze the connections or relationships between the variables. There are ten pairings here (Location and Income, Location and Size, Location and Years, Location and Credit Balance, income and Size, Income and Years, Income and Balance, Size and Years, Size and Credit Balance, Years and Credit Balance). Use graphical as well as numerical summary measures. Explain what you see. Be sure to consider all 10 pairings. Some variables show clear relationships, while others do not. Prepare your report in Microsoft Word (or some other word processing package), integrating your graphs and tables with text explanations and interpretations. Be sure that you have graphical and numerical back up for your explanations and...
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