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Playing with Numbers: Bringing Statistics to Life in the Undergraduate Classroom
Unformatted Document Text:  Nordyke, Moulton and Nesbit  Page 4    Finally our third goal is to provide a sense of connectedness throughout the undergraduate statistics course. Many statistics classes can feel a bit disjointed. Important statistical topics are discussed and applied in isolated chapters that often lack continuity to a larger “way of thinking.” Further, the examples given in statistics texts are often completely unrelated, not to mention irrelevant. Can we really expect students to care about the amount of variation in the pages of textbooks, or the probability of drawing a blue sock out of a drawer of multicolored socks? We wanted to find a way to connect all of the topics we covered in class to a larger statistical analysis project, so that at every point along the way the students could see how this particular topic or method was going to help them answer their question of interest. The statistical analysis project provides a practical way to achieve all three of our goals. The Statistical Analysis Project Most undergraduate statistics textbooks approach instruction from a computational lens; a lens that may be necessary, but is not sufficient, particularly for students for whom the introductory statistics course is likely their first and last course in any form of research methods instruction. In more advanced courses in research design and analysis, students are often required to complete a research project, including formulating a research question and collecting data from external data sources to answer that question. The benefits of such an approach are numerous; most critically, students learn a new way of approaching real world questions through an analytic framework. The purpose of the statistical analysis project that we have developed is to bring the “analytic” model often applied in more advanced research methods courses to the introductory level statistics course. Doing this requires a much more structured approach than an open-ended, student-directed research project. We have observed colleagues attempt to include a “research

Authors: Nordyke, Shane., Moulton, Stephanie. and Nesbit, Becky.
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Nordyke, Moulton and Nesbit 
Page 4 
 
Finally our third goal is to provide a sense of connectedness throughout the
undergraduate statistics course. Many statistics classes can feel a bit disjointed. Important
statistical topics are discussed and applied in isolated chapters that often lack continuity to a
larger “way of thinking.” Further, the examples given in statistics texts are often completely
unrelated, not to mention irrelevant. Can we really expect students to care about the amount of
variation in the pages of textbooks, or the probability of drawing a blue sock out of a drawer of
multicolored socks? We wanted to find a way to connect all of the topics we covered in class to
a larger statistical analysis project, so that at every point along the way the students could see
how this particular topic or method was going to help them answer their question of interest.
The statistical analysis project provides a practical way to achieve all three of our goals.
The Statistical Analysis Project
Most undergraduate statistics textbooks approach instruction from a computational lens; a
lens that may be necessary, but is not sufficient, particularly for students for whom the
introductory statistics course is likely their first and last course in any form of research methods
instruction. In more advanced courses in research design and analysis, students are often
required to complete a research project, including formulating a research question and collecting
data from external data sources to answer that question. The benefits of such an approach are
numerous; most critically, students learn a new way of approaching real world questions through
an analytic framework.
The purpose of the statistical analysis project that we have developed is to bring the
“analytic” model often applied in more advanced research methods courses to the introductory
level statistics course. Doing this requires a much more structured approach than an open-ended,
student-directed research project. We have observed colleagues attempt to include a “research


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