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Categorical Data Visualization and Analysis

Learn about displaying categorical data using pie charts and bar graphs, and interpreting two-way tables and marginal distributions. Explore the effects of age on education levels through data analysis.

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Categorical Data Visualization and Analysis

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Presentation Transcript

  1. Chapter 3 Displaying Categorical Data

  2. Categorical Data • Variables with labels as values. • Gender (Male, Female) • Marital Status (Single, Married, Widowed, Divorced)

  3. Describing Categorical Data • Pie Chart • Displays percentage of whole for each category. • Must include all possible categories.

  4. Example of Pie Chart • Marital Status • 61% Married • 7% Widowed • 23% Never Married • 9% Divorced

  5. Describing Categorical Data • Bar Charts • Displays either number or percentage for each category. • Do not need to include all possible categories.

  6. Example of a Bar Graph • Number of students enrolled in certain majors. • 2,105 Engineering • 1,550 Business • 1,025 Biological Sciences

  7. Two-Way Tables • Summarizes the relationship between two categorical variables. • Row = values for one categorical variable • Column = values for other categorical variable • Table entries = number in row by column class.

  8. Two-Way Table

  9. Marginal Distribution • Look at each variable separately • Age • 25 to 34: 41,388 of 166,438 = 24.87% • 35 to 54: 73,028 of 166,438 = 43.88% • 55+: 52,022 of 166,438 = 31.26%

  10. Marginal Distribution • Education • No HS: 30,512 of 166,438 = 18.3% • HS: 56,451 of 166,438 = 33.9% • C. 1-3: 41,247 of 166,438 = 24.8% • C. 4+: 38,225 of 166,438 = 23.0%

  11. Effect of Age on College • Look at number of people with college degree (Total = 38,225) • Age 25 to 34: 10,342 out of 38,225 = 27.06% • Age 35 to 54: 19,878 out of 38,225 = 52.00% • Age 55+: 8,005 out of 38,225 = 20.94% • Age 55+ is 31.26% of population, but only makes up 20.94% of people with college degree.

  12. Effect of Age on Education • Look at each level of education. • Break up each level by age. • Make bar graph for each level of education.

  13. Education Levels by Age

  14. Conclusions • Older people make up a large percentage of people without HS education.

  15. Conclusions • Younger people make up a small percentage of people without HS education.

  16. Conclusions • Older people make up a small percentage of people with college education.

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