1. Describe an interesting question that you might answer with this data set? Wh
ID: 3057494 • Letter: 1
Question
1. Describe an interesting question that you might answer with this data set? What do you anticipate finding as you study your variables and their relationships? (This should be 2-3 sentences.)
2. Identify the population used in this data set. What is the sample size?
3. Identify all the variables. Label each as either categorical (qualitative) or quantitative.
this is the data
Row Items Sales Card Type Gender Country Age Martial Status 1 19 $50.61 visa-electron Male China 35 2 2 14 $105.37 mastercard Female China 22 2 3 11 $90.21 maestro Female Russia 52 2 4 20 $280.84 visa Male China 38 1 5 18 $265.68 jcb Male China 44 1 6 19 $103.63 americanexpress Female Indonesia 56 2 7 17 $215.00 jcb Male Dominican Republic 51 1 8 20 $168.06 laser Male Czech Republic 25 1 9 3 $181.42 maestro Female China 41 1 10 11 $240.51 mastercard Female China 44 1 11 17 $260.56 jcb Male China 58 1 12 17 $170.56 jcb Female Belarus 28 2 13 14 $71.42 diners-club-carte-blanche Male Sweden 41 1 14 3 $242.23 diners-club-carte-blanche Female Indonesia 58 2 15 15 $250.44 visa-electron Male Latvia 41 2 16 4 $71.80 jcb Male New Zealand 20 2 17 6 $33.62 diners-club-us-ca Male United States 48 2 18 17 $81.35 diners-club-enroute Female Colombia 44 2 19 13 $67.09 maestro Male China 53 1 20 3 $262.41 jcb Female Lithuania 22 1 21 16 $204.28 jcb Female Indonesia 23 2 22 2 $289.74 jcb Female Vietnam 28 2 23 1 $33.45 china-unionpay Male China 29 2 24 19 $154.19 jcb Female Botswana 46 2 25 20 $43.29 diners-club-enroute Male Argentina 58 2 26 5 $96.97 jcb Male Russia 42 2 27 1 $46.62 jcb Male Ecuador 21 2 28 17 $241.04 jcb Male China 41 1 29 6 $251.64 switch Female Sudan 58 1 30 1 $115.24 visa-electron Female Canada 52 1 31 10 $263.42 jcb Male France 44 2 32 10 $274.67 jcb Female Italy 32 2 33 1 $69.59 jcb Female Switzerland 48 2 34 17 $136.30 china-unionpay Male China 44 2 35 7 $201.52 jcb Male Macedonia 26 2 36 8 $51.44 switch Female Papua New Guinea 51 1 37 11 $52.95 jcb Male Czech Republic 48 2 38 19 $162.89 china-unionpay Female China 36 2 39 5 $160.09 jcb Female China 38 1 40 6 $91.28 jcb Female Brazil 39 1 41 4 $140.53 mastercard Female Indonesia 26 2 42 15 $190.36 visa Male Greece 57 1 43 10 $181.57 americanexpress Male Philippines 46 2 44 1 $65.59 jcb Female China 31 1 45 3 $49.01 laser Female United States 49 2 46 16 $88.05 jcb Female France 54 2 47 9 $193.79 jcb Male Indonesia 38 1 48 5 $39.55 mastercard Female Indonesia 24 2 49 1 $32.56 jcb Male Japan 23 1 50 2 $54.52 china-unionpay Male Ireland 43 1 51 19 $161.89 jcb Male China 57 1 52 2 $59.63 maestro Male Cyprus 35 1 53 13 $257.81 bankcard Male China 38 1 54 15 $166.53 laser Male South Africa 50 1 55 15 $253.02 diners-club-carte-blanche Female Canada 39 2 56 16 $193.56 americanexpress Female China 30 2 57 18 $80.57 china-unionpay Male Brazil 30 1 58 18 $250.29 jcb Male Yemen 41 1 59 15 $46.79 jcb Female Japan 42 1 60 18 $276.56 laser Male Slovenia 32 2 61 14 $135.13 jcb Male Tanzania 31 1 62 14 $195.58 jcb Female China 42 1 63 15 $182.98 visa Female China 52 2 64 8 $221.03 jcb Male Zimbabwe 29 1 65 3 $128.11 jcb Female China 40 1 66 19 $76.60 diners-club-carte-blanche Female Indonesia 38 1 67 13 $27.07 jcb Female China 59 2 68 4 $109.20 diners-club-carte-blanche Male Russia 48 2 69 4 $276.85 jcb Male Uruguay 57 2 70 19 $195.10 jcb Male Sao Tome and Principe 25 1 71 5 $112.23 instapayment Male Zambia 41 1 72 15 $61.94 jcb Female Nigeria 41 1 73 4 $35.08 jcb Female China 35 2 74 20 $60.13 switch Male China 23 2 75 6 $277.11 visa-electron Female Portugal 54 2 76 5 $220.47 jcb Female Russia 37 2 77 14 $185.57 laser Male Russia 53 2 78 19 $295.96 diners-club-enroute Male Greece 51 1 79 12 $238.86 visa Female Indonesia 45 2 80 3 $275.81 visa-electron Female Indonesia 26 2 81 7 $77.07 visa Female Portugal 57 1 82 2 $252.58 mastercard Female Russia 45 2 83 4 $134.78 jcb Male Japan 29 1 84 3 $43.49 americanexpress Male Indonesia 48 2 85 1 $223.78 jcb Male Mexico 53 2 86 8 $238.74 jcb Female China 28 2 87 9 $291.30 americanexpress Male Togo 44 1 88 14 $79.46 jcb Female Finland 54 2 89 16 $193.73 jcb Male Indonesia 57 1 90 13 $224.23 visa-electron Female Pakistan 23 2 91 16 $247.43 mastercard Female Honduras 27 1 92 9 $186.11 jcb Male China 56 2 93 17 $58.48 jcb Male China 53 2 94 1 $281.40 jcb Female Philippines 46 2 95 10 $254.37 bankcard Male Brazil 42 1 96 8 $145.00 jcb Female Indonesia 50 2 97 20 $122.35 jcb Female Sweden 25 2 98 1 $210.77 jcb Male Portugal 50 1 99 7 $225.37 diners-club-carte-blanche Female South Africa 43 2 100 18 $87.98 maestro Male China 37 2 Note: Marital Status 1 = Married Marital Status 2 = SingleExplanation / Answer
Answer to question# 1)
This data consists of the credit card details of the consumers. It shows us what type of card they have and the amount of sales made and the number of items purchased on that card. Then this data also contains some demographic details like: the age and marital status of the consumers. An interesting question can be based on : Does the card usage depend on the card type , the gender of the consumer, the age of the consumer and the marital status of the consumer.
In this the dependent variable would be : sales , and all the other variables would be considered as independent variables.
.
Answer to question# 2)
The population set for this data is: the card owners. All the card owners are observed and interviewed. The data related to the purchases done on the card, the card type he owns, age and marital status are recorded and that is how the complete sample data is compiled.
.
Answer to question# 3)
The “type” of variable is discussed as shown below:
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