This chapter presents the use of charts to present data and the initial exploration of data using tools like cross-tabulation. After reading this chapter, you should understand: That 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. | Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved. This chapter presents the use of charts to present data and the initial exploration of data using tools like cross-tabulation. 16- Learning Objectives Understand . . . That 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. 16- Research as Competitive Advantage “As data availability continues to increase, the importance of identifying/filtering and analyzing relevant data can be a powerful way to gain an information advantage over our competition.” Tom . Anderson founder & managing partner Anderson Analytics, LLC 16- PulsePoint: . | Chapter 16 Exploring, Displaying, and Examining Data McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All Rights Reserved. This chapter presents the use of charts to present data and the initial exploration of data using tools like cross-tabulation. 16- Learning Objectives Understand . . . That 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. 16- Research as Competitive Advantage “As data availability continues to increase, the importance of identifying/filtering and analyzing relevant data can be a powerful way to gain an information advantage over our competition.” Tom . Anderson founder & managing partner Anderson Analytics, LLC 16- PulsePoint: Research Revelation 65 The percent boost in company revenue created by best practices in data quality. See the text Instructors Manual (downloadable from the text website) for ideas for using this research-generated statistic. 16- Researcher Skill Improves Data Discovery DDW is a global player in research services. As this ad proclaims, you can “push data into a template and get the job done,” but you are unlikely to make discoveries using a template process. 16- Exploratory Data Analysis Confirmatory Exploratory In exploratory data analysis, the researcher has the flexibility to respond to the patterns revealed in the preliminary analysis of the data. Patterns in the collected data guide the data analysis or suggest revisions to the preliminary data analysis plan. This flexibility is an important attribute of this approach. When the researcher is attempting to show causation, confirmatory data analysis is required. Confirmatory data analysis is an analytical process .
