# Stat200 - Assignment #1: Descriptive Statistics Data Analysis Plan

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University of Maryland University College

STAT200 - Assignment #1: Descriptive Statistics Data Analysis Plan

Identifying Information

Student (Full Name):

Class: STAT 200

Instructor: Dr. D.

Date: 10/11/18

Scenario:

I’m a 40 year old single working parent with 3 children. I’m looking to balance my family’s budget expenditure on meat and fruits. I hope to do so by analyzing trends in other households.

Table 1. Variables Selected for the Analysis

 Variable Name in the Data Set Description (See the data dictionary for describing the variables.) Type of Variable (Qualitative or Quantitative) Variable 1: “SE-Income” Annual household income in USD. Quantitative Variable 2: “SE-Marital Status” Marital Status of Head of Household Qualitative Variable 3:”SE-AgeHeadHousehold” Age of the Head of Household (in years) Quantitative Variable 4:”USD-Meat” Annual Expenditure on Meat (in USD) Quantitative Variable 5:”USD-Fruits” Annual Expenditure on Fruits (in USD) Quantitative

Reason(s) for Selecting the Variables and Expected Outcome(s):

1. Variable 1: “SE-Income” – Budget expenditure obviously depends on household income. Budget is expected to increase as household income increases.
2. Variable 2: “SE-Marital Status “– Marital status not only changes family size but also affects expenditure planning. Single parents are expected to be more economical.
3. Variable 3: “SE-Age Head Household “- Age of head of household relates to budgeting prudence. Young head of households might be spending more.
4. Variable 4: “USD-Meat“- It’s required for analyzing trends in other households. I expect younger and married head of households to spend more on meat.
5. Variable 5: “USD-Fruits“- Needed for analysis of trends. I expect older and single head of household to spend more on fruits.

Data Set Description:

Proposed Data Analysis:

Measures of Central Tendency and Dispersion

Table 2. Numerical Summaries of the Selected Variables

 Variable Name Measures of Central Tendency and Dispersion Rationale for Why Appropriate Variable 1: “Income” Number of Observations Median Sample Standard Deviation I am using 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 sample standard deviation for three reasons: The data is a sample from a larger data set. It is the most commonly used measure of dispersion. The variable is quantitative. Variable 2: “SE-Marital Status” Mode Mode is used because variable is qualitative. Mean and median can’t be calculated. Variable 3: SE-Age Head Household Mean Sample standard deviation Mean is used because Mean is most common measure of central tendency for quantitative variable. Age data isn’t expected to have extreme outliers. Sample standard deviation is used because Data is sampled from larger data set. It’s most common measure of quantitative variable. Variable 4: USD-Meat Median Sample standard deviation Median is used because Variable is quantitative Data may have extreme outliers on lower end (e.g. vegetarians) Sample standard deviation is used because Data is sampled from larger data set Variable is quantitative Variable 5: USD-Fruits Median Sample standard deviation Median is used because Variable is quantitative Data may have extreme outliers on higher end (e.g. vegetarians) Sample standard deviation is used because Data is sampled from larger data set Variable is quantitative

Graphs and/or Tables

Table 3. Type of Graphs and/or Tables for Selected Variables

 Variable Name Graph and/or Table Rationale for why Appropriate? Variable 1: “Income” Graph: I will use the histogram to show the normal distribution of data. Histogram is one of the best plot to show the normal distribution of quantitative level data. Variable 2: SE-Marital Status Graph: I’ll use a pie chart. Pie chart is good for showing the proportional distribution of qualitative data. Variable 3: SE-Age Head Household Graph: I will use the histogram. Histogram would show the normal distribution of quantitative data. Variable 4: USD-Meat Graph: I will use the Box Plot. Box plot doesn’t presume normal/any other distribution of data. It’s good for data expected to have outliers. Variable 5: USD-Fruits Graph: I will use the Box Plot. Box plot doesn’t presume normal/any other distribution of data. It’s good for data expected to have outliers.
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