As statistics educators, we should be preparing our students to interpret maps and identify their associated strengths, weaknesses, and potential biases. This will encourage statistics faculty to discuss maps in their courses. Further, we would encourage authors of introductory statistics texts to infuse examples of the use of maps in their text. Given their frequency of use, the authors of this article believe that maps should be discussed in introductory statistics courses. Statistics educators should cultivate in our students the skills of inquiry and reflection, encouraging our students to employ statistical science to be creative and productive citizens.Īs we demonstrate in this article, maps are extensively used to articulate arguments related to geographic data. As such, the practice of statistics is an application of QL. Statistics can be described as the science of collecting, organizing, and interpreting data.
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Steen ( 2001) presented a characterization of QL as an “aggregate of skills, knowledge, beliefs, dispositions, habits of mind, communication capabilities, and problem-solving skills that people need to engage effectively in quantitative situations arising in life and work.” Universities place a high priority on improving the QL of all of their baccalaureate students, as there is a consensus that QL skills are invaluable to an individual’s academic career and professional life. Introductory statistics courses serve as General Education requirements for many students, in which the emphasis is QL. We provide concluding remarks in Section 4. Section 3 describes how the topic and maps might fit into the introductory statistics curriculum and provides an example activity that examines the obesity and poverty rate by U.S.
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Section 2 provides definitions and examples of different types of thematic maps (including the commonly used choropleth map), as well as how to interpret these maps. John Snow making his case for cholera as a water-borne disease through his cholera map of London, which revolutionized the field of epidemiology. In Section 1.3, we introduce the compelling historical example of Dr. Section 1.2 describes how teaching maps aligns with the Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report, which contains widely cited recommendations on what should be taught in undergraduate introductory statistics courses and how these courses should be taught. In Section 1.1, we argue that the ability to read maps is an essential quantitative literacy (QL) skill. Few statistical texts explicitly present maps, so we offer examples, definitions, and an activity related to them. In this article, we argue that maps must be part of the introductory statistics curriculum. Maps have great visual power and are capable of conveying information with incredible authority, whether real or illusory.
Like all well-done statistical visualizations, maps are “worth a thousand words” in that they can convey a dataset’s primary message much more easily than tabulations or verbal descriptions of the same data. Every day we are bombarded with maps used by advertisers, governments, journalists, academics, and everyday people for a myriad of reasons. Maps present all types of information: political, historical, topographic, ethnic, religious, economic, and military information, to name but a few. Maps are not only navigational tools they are also important visualizations of data.
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