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Exploratory Data Analysis: Visualizing and Examining Relationships in Data

Learn how exploratory data analysis techniques provide insights through visual representations and how cross-tabulation helps in examining relationships and making data-driven decisions.

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Exploratory Data Analysis: Visualizing and Examining Relationships in Data

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  1. Chapter 17 Exploring, Displaying, and Examining Data

  2. Learning Objectives Understand . . . • exploratory data analysis techniques provide insights and data diagnostics by emphasizing visual representations of the data • how cross-tabulation is used to examine relationships involving categorical variables, serves as a framework for later statistical testing, and makes an efficient tool for data visualization and later decision-making

  3. Exploratory Data Analysis • This Booth Research Services ad suggests that the researcher’s role is to make sense of data displays • Great data exploration and analysis delivers insight from data

  4. Data Analysis Exploratory Confirmatory

  5. Exhibit 17-1 Data Exploration, Examination, and Analysis in the Research Process

  6. Value Label Value Frequency Percent Valid Cumulative Percent Percent Exhibit 17-2 Frequency of Ad Recall

  7. Exhibit 17-3 Pie Chart

  8. Exhibit 17-3 Bar Chart

  9. Exhibit 17-4 Frequency Table

  10. Exhibit 17-5 Histogram

  11. Exhibit 17-6 Stem-and-Leaf Display

  12. Exhibit 17-7 Pareto Diagram

  13. Exhibit 17-8 Boxplot Components

  14. Exhibit 17-9 Diagnostics with Boxplots

  15. Exhibit 17-10 Boxplot Comparison

  16. Mapping

  17. Digital Camera Map

  18. Exhibit 17-11 SPSS Cross-Tabulation

  19. Exhibit 17-12 Percentages in Cross-Tabulation

  20. Guidelines for Using Percentages Averaging percentages Use of too large percentages Using too small a base Percentage decreases can never exceed 100%

  21. Exhibit 17-13 Cross-Tabulation with Control and Nested Variables

  22. Exhibit 17-14 AID Example

  23. Automatic interaction detection (AID) Boxplot Cell Confirmatory data analysis Contingency table Control variable Cross-tabulation Exploratory data analysis (EDA) Five-number summary Frequency table Histogram Interquartile range (IQR) Marginals Nonresistant statistics Outliers Pareto diagram Resistant statistics Stem-and-leaf display Key Terms

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