Question
Introduction: Use the same scenario you submitted for the Part 1 with modifications using your instructor's feedback, if needed. Include Table 1 : Variables Selected
Introduction:
Use the same scenario you submitted for the Part 1 with modifications using your instructor's feedback, if needed. Include Table 1: Variables Selected for the Analysis you used in Part 1 to show the variables you selected for analysis.
Table 1. Variables Selected for the Analysis
Variable Name in data set | Description | Type of Variable (Qualitative or Quantitative) |
Variable 1: "Income" | Annual household income in USD. | Quantitative |
Variable 2: "Marital Status" | Married or Not Married | Qualitative |
Variable 3: "Family" | Total number of people within the family(Represents adults and children respectively) | Quantitative |
Variable 4: "Housing" | Total amount of annual expenditure on housing | Quantitative |
Variable 5: "Food" | Total amount of annual expenditure on food | Quantitative |
Data Set Description and Method Used for Analysis:
Briefly describe the data set, using information provided in the data set file. Also describe what method(s) (i.e., TI Calculator, free web applets, Excel) you used to analyze the data.
Results:
Variable 1:Income
Numerical Summary.
Table 2. Descriptive Analysis for Variable 1
Variable | n | Measure(s) of Central Tendency | Measure(s) of Dispersion |
Variable: Income | Median = | SD = |
Graph and/or Table: Histogram of Income
(Place Histogram here)
Description of Findings.
Variable 2: (Fill in name of variable)
Numerical Summary.
Table 3. Descriptive Analysis for Variable 2
Variable | n | Measure(s) of Central Tendency | Measure(s) of Dispersion |
Variable: |
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Variable 3:(Fill in name of variable)
Numerical Summary.
Table 4. Descriptive Analysis for Variable 3
Variable | n | Measure(s) of Central Tendency | Measure(s) of Dispersion |
Variable: |
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Variable 4:(Fill in name of variable)
Numerical Summary.
Table 5. Descriptive Analysis for Variable 4
Variable | n | Measure(s) of Central Tendency | Measure(s) of Dispersion |
Variable 4: |
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Variable 5:(Fill in name of variable)
Numerical Summary.
Table 6. Descriptive Analysis for Variable 5
Variable | n | Measure(s) of Central Tendency | Measure(s) of Dispersion |
Variable: |
Graph and/or Table.
(Place Graph or Table Here)
Description of Findings.
Discussion and Conclusion.
Briefly discuss each variable in the same sequence as presented in the results. What has the highest expenditure? What variable has the lowest expenditure? If you were to recommend a place to save money, which expenditure would it be and why?
STAT200 Introduction to Statistics
Dataset for Written Assignments
Description of Dataset:
The data is a random sample from the US Department of Labor's 2016 Consumer Expenditure Surveys (CE) and provides information about the composition of households and their annual expenditures (https://www.bls.gov/cex/). It contains information from 31 households, where a survey responder provided the requested information; it is all self-reported information. This dataset contains four socioeconomic variables (whose names start with SE) and four expenditure variables (whose names start with USD).
Description of Variables/Data Dictionary:
The following table is a data dictionary that describes the variables and their locations in this dataset (Note: Dataset is on second page of this document):
Variable Name | Location in Dataset | Variable Description | Coding |
UniqueID# | First Column | Unique number used to identify each survey responder | Each responder has a unique number from 1-30 |
SE-MaritalStatus | Second Column | Marital Status of Head of Household | Not Married/Married |
SE-Income | Third Column | Annual Household Income | Amount in US Dollars |
SE-AgeHeadHousehold | Fourth Column | Age of the Head of Household | Age in Years |
SE-FamilySize | Fifth Column | Total Number of People in Family (Both Adults and Children) | Number of People in Family |
USD-AnnualExpenditures | Sixth Column | Total Amount of Annual Expenditures | Amount in US Dollars |
USD-Food | Seventh Column | Total Amount of Annual Expenditure on Food | Amount in US Dollars |
USD-Housing | Eighth Column | Total Amount of Annual Expenditure on Housing | Amount in US Dollars |
USD-Transport | Ninth Column | Total Amount of Annual Expenditure on Transportation | Amount in US Dollars |
How to read the data set:Each row contains information from one household. For instance, the first row of the dataset starting on the next page shows us that for the first household in the sample: the head of household is not married and is 35 years old, has an annual household income is $97,469, has a family size of 4, annual expenditures of $54,929, and spends $6,900 on food, $18,514 on housing, and $145 on transportation.
UniqueID# | SE-MaritalStatus | SE-Income | SE-AgeHeadHousehold | SE-FamilySize | USD-AnnualExpenditures | USD-Food | USD-Housing | USD-Transport |
1 | Not Married | 97469 | 35 | 4 | 54929 | 6900 | 18514 | 145 |
2 | Not Married | 97912 | 49 | 1 | 55704 | 6937 | 18619 | 152 |
3 | Not Married | 96697 | 49 | 2 | 56453 | 6971 | 18520 | 136 |
4 | Not Married | 96653 | 51 | 4 | 56488 | 6943 | 18838 | 124 |
5 | Not Married | 96664 | 53 | 3 | 55558 | 7051 | 18502 | 168 |
6 | Not Married | 95744 | 52 | 4 | 55963 | 7040 | 18435 | 146 |
7 | Not Married | 94929 | 59 | 2 | 55247 | 6948 | 18483 | 133 |
8 | Not Married | 96928 | 43 | 3 | 55932 | 6953 | 18701 | 145 |
9 | Not Married | 97681 | 53 | 4 | 56124 | 7097 | 18676 | 134 |
10 | Not Married | 96244 | 56 | 4 | 56051 | 7073 | 18484 | 141 |
11 | Not Married | 96886 | 44 | 2 | 55321 | 6982 | 18312 | 153 |
12 | Not Married | 96727 | 39 | 2 | 56440 | 7051 | 18376 | 120 |
13 | Not Married | 96690 | 57 | 2 | 56097 | 6822 | 18334 | 135 |
14 | Not Married | 96572 | 59 | 2 | 56515 | 7179 | 18648 | 123 |
15 | Not Married | 98717 | 40 | 3 | 56393 | 7036 | 18389 | 114 |
16 | Married | 106292 | 57 | 4 | 82299 | 10983 | 23063 | 132 |
17 | Married | 95801 | 54 | 3 | 73798 | 9395 | 23155 | 151 |
18 | Married | 95385 | 50 | 4 | 74110 | 9101 | 22847 | 211 |
19 | Married | 95865 | 46 | 1 | 74789 | 9321 | 22621 | 168 |
20 | Married | 109312 | 37 | 6 | 80801 | 10564 | 25392 | 58 |
21 | Married | 114051 | 42 | 5 | 84486 | 10820 | 25728 | 167 |
22 | Married | 110651 | 58 | 4 | 83766 | 11226 | 22899 | 113 |
23 | Married | 107338 | 67 | 2 | 83651 | 11710 | 21893 | 47 |
24 | Married | 101829 | 45 | 4 | 82385 | 10821 | 22409 | 121 |
25 | Married | 102244 | 34 | 4 | 74687 | 8735 | 27964 | 60 |
26 | Married | 113558 | 31 | 5 | 79861 | 10346 | 25006 | 141 |
27 | Married | 100947 | 35 | 4 | 73973 | 8455 | 26783 | 36 |
28 | Married | 107369 | 66 | 2 | 83441 | 11724 | 23174 | 82 |
29 | Married | 106894 | 51 | 5 | 81585 | 11360 | 22396 | 162 |
30 | Married | 97769 | 47 | 5 | 73950 | 9035 | 22867 | 202 |
31 | Married | 98885 | 45 | 4 | 57795 | 9653 | 23400 | 152 |
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