STAT 200 Assignment 1 PDF

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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: Date: May 31, 2019 Scenario: Please write a few lines describing your scenario and the four variables (in addition to income) you have selected. I’m 35 year hold single parent with a high school diploma and one child. My income is $25000. Addition to income variable: SE- marital status , SE- Family size , USD- Food and USD- Education Use Table 1 to report the variables selected for this assignment. Note: The information for the required variable, “Income,” has already been completed and can be used as a guide for completing information on the remaining variables. 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: “Income”

Annual household income in USD.

Quantitative

Variable 2: SE-Marital

Marital Status of Head of Household

Quantitative

Variable 3: SE-Family size

Total Number of People in Family ( Both Adults and Children)

Quantitative

Variable 4: USD-Food

Total Amount of Annual Expenditure on Food

Quantitative

Variable 5: USDEducation

Total Annual of Expenditure on Education

Quantitative

Reason(s) for Selecting the Variables and Expected Outcome(s): 1. Variable 1: “Income” -

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2. Variable 2: “ “ - SE Marital Status . I choose this variable because it one of the important variables when it comes to socioeconomic problem. The outcome for this variable will be quality of life. 3. Variable 3: “ “ - SE Family size. I choose this variable because family size predicts parents ‘ investment in children’s education. So, to me this is a good variable to work on it. The outcome for Family size will be children’s schooling. 4. Variable 4: “ “ - USD Food. I choose this variable because it indispensable to our life we eat every day , it important to analyze and understand this variable. The outcome for this variable will be malnutrition, negative effects on health and quality of life. 5. Variable 5: USD Education. I choose education variable because Education has many benefits and has positive impact in our life. The outcome for Education variable will be illiteracy.

Data Set Description: Proposed Data Analysis: Measures of Central Tendency and Dispersion Complete Table 2. Numerical Summaries of the Selected Variables and briefly explain why you choose those measurements. Note: The information for the required variable, “Income,” has already been completed and can be used as a guide for completing information on the remaining variables.

Table 2. Numerical Summaries of the Selected Variables Variable Name Variable 1: “Income”

Measures of Central Tendency and Dispersion ● ● ●

Number of Observations Median Sample Standard Deviation

Rationale for Why Appropriate

I am using median for two reasons: 1. If there are any outliers or the data is not normally distributed, the median is the best measure of central tendency. 2. The variable is quantitative. I am using sample standard deviation for three reasons: 1. The data is a sample from a larger data set. 2. It is the most commonly used measure of dispersion. 3. The variable is quantitative.

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 

Number of married and single by sex Mean Mean deviation

I’m using mean to see the distribution of married people and single. The mean will help us to calculate the mean deviation since we have a quantitative variable. I’m using standard deviation because the data from a large population. And the data is quantitative.

Variable 3: Family size

   

Number of people Mean Variance Standard deviation

I’m using mean to see the average deviation of my data. I think the mean is the appropriate measure of central tendency. It will help me to calculate the variance. I am using standard deviation because the data from a large population. And the data is quantitative.

Variable 4: Food



Amount spends on food Mode Mean and Median Variance Standard deviation

I’m using mode to identify the amount spent on food by most people. As the data is quantitative, the median will be using to calculate the variance and then deduct the standard deviation.

Annual expenditure Mean Sample variance Standard deviation

I’m using to determine the average deviation of the data. The mean will help me understand the set of my data and to calculate the variance of my data. Sample variance and Standard deviation will be use because I have a large population data.

Variable 2: Marital Status



    Variable 5: Education

   

Graphs and/or Tables Complete Table 3. Type of Graphs and/or Table for Selected Variables and briefly explain why you choose those graphs and/or tables. Note: The information for the required variable, “Income,” has already been completed and can be used as a guide for completing information on the remaining variables. 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 plots to show the normal distribution of quantitative level data .

Variable 2:

Graph: I will use scatter to

I think scatter is the best chart to see the

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Marital Status

compare number of married people and single people.

difference between two different set of data.

Variable 3: Family size

Graph: I will use column chart to see the number of people in different family.

I think column bar is one of the most and clear charts uses to show quantitative data.

Variable 4: Food

Graph: I will use line chart to show the total amount of annual expenditure on food .

The line chart will show us the evolution of expenditure on food during the year. The line chart will allow us to give a good analyze of the data.

Variable 5: Education

Graph: I will use a pie chart to chow the proportion of annual expenditure on education.

I think with the pie chart we are seeing clary the different value of the data and the proportion of each element of the variable.

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