Scenario
The scenario involves a father aged 40 with two children with a university degree. Income, which is critical among the variables in the proposed analysis, comprises of a joint income from him and his spouse. Other identified variables include Marital Status, Family Size, Food, and Housing.
Variables Selected for the Analysis
Table 1 . Variables
Variable Name in the Data Set |
Description |
Type of Variables |
| Variable 1: “Income” | Annual household income in USD | Quantitative |
| Variable 2: “MaritalStatus” | Marital Status of the Head of the Household | Qualitative |
| Variable 3: “FamilySize” | Sum of the adults and children in the family | Quantitative |
| Variable 4: “Food” | Total expenditure on food annually | Quantitative |
| Variable 5: “Housing” | Total expenditure on housing annually | Qualitative |
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Reasons for Selecting the Variables and the Expected Outcome(s)
Variable 1: “Income” – The variable was selected as it a vital determinant of the daily livelihood and quality of life projected by various households.
Variable 2: “MaritalStatus” – It is vitally necessary to comprehend the variance between the living standards of households based on their marital status.
Variable 3: “FamilySize” – The size of the family determines the distribution of the joint income of the parents.
Variable 4: “Food” – As a necessity, the knowledge of the affordability of food is a crucial concern to various stakeholders.
Variable 5: “Housing” – Housing is also a necessary aspect of sustainable and improved living standards.
Dataset Description
Proposed Data Analysis: Measure of Central Tendency and Dispersion
Table 2 . Numerical Summaries of the Selected Variables
|
Variable Name |
Measure of Central Tendency and Dispersion |
Rationale for Why Appropriate |
| Variable 1: “Income” |
Number of Observations Median Sample Standard Deviation |
I am using the median for two reasons: If there are any outliers or the data is not normally distributed, the median is the best measure of central tendency. The variable is quantitative. I am using the sample standard deviation for three reasons: The data is a sample from a broader data set. It is the most commonly used measure of dispersion. The variable is quantitative. |
| Variable 2: “MaritalStatus” | Number of Observations | The count of the three subcategories of marital status (single, married, divorced) will help discern the behavior of each group distinctively. |
| Variable 3: “FamilySize” |
Median Mean |
I will employ the median given the asymmetrical nature of the data. The mean will be useful in giving the overall depiction of the identified variable. |
| Variable 4: “Food” |
Mean Median Number of Observation |
The mean will be useful in averaging the total annual spending on food. The median will be useful in estimating the average amount of expenditure on food by households. Also, the median will minimize the risk of the effects outliers may have on the dataset. It is also crucial to determine the total amount of expenditure on food annually. |
| Variable 5: “Housing” |
Number of Observations Mean Variance |
It is vital to estimate the total expenditure on housing annually. The mean will help determine the average amount of money in USD spend on housing |
Graphs and Tables
Table 3 . Type of Graphs and Tables for Selected Variables
|
Variable Name |
Graphs/Table |
Rationale for Why Appropriate |
| Variable 1: “Income” | Graph: I will use the histogram to show the normal distribution of data. | A histogram is one of the best plot to show the normal distribution of quantitative level data |
| Variable 2: “MaritalStatus” | Table: Frequency Table | A frequency table will adequately summarize the data pertaining to marital status. |
| Variable 3: “FamilySize” | Graph: Bar Chart | A bar chart is useful in displaying a comparison of metric values by relating the family size categories based on the size of their respective bars. |
| Variable 4: “Food” | Graph: Histogram | Tabulating the data values in the food variable could be difficult, and a histogram will be more effective in identifying the frequency of data within the dataset. |
| Variable 5: “Housing” | Graph: Bar Chart | A bar chart will be appropriate in comparing various measures of the categorical data within the housing and other variables. |
Reference
Consumer Expenditure Survey . (2016). Bls.gov . Retrieved 25 January 2020, from https://www.bls.gov/cex/
