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The Logic of Congressional Elections part of Examples
A variety of quantitative approaches to Congressional elections in which students learn the causes of electoral outcomes, the predictability of those outcomes, and intervening variables that produce unexpected outcomes.
Assessing the Measurement and Validity of Ambiguous Concepts in Ethnic Conflict Datasets part of Examples
This assignment introduces students to commonly used datasets in ethnic conflict studies. It also encourages them to think critically about data quality and measurement challenges when using large datasets.
Quantitative Review of an Article part of Examples
Students will read an academic article critically and write a review of the article.
Building an Electoral Dataset and Testing Hypotheses with the Data part of Examples
Undergraduate student project for building datasets and analyzing the electoral, party system, and mass behavioral characteristics for a set of countries.
What is the main issue we face as a society? part of Examples
Final Quantitative Reasoning Project: Planning a Sesquicentennial Celebration part of Examples
This final project gives students the opportunity to apply unit conversions, geometry, estimation, and personal finance modeling in one cohesive, real world analysis.
How to Teach to be Statistically Literate part of Examples
Finding Your 'Perfect Partner': Evaluating matchmaker profiles usings ratings and cutoff methods part of Examples
In this activity, students informally explore how the rating systems might be set up in a simple setting which uses the "profile" of eight candidates who have responded to an online dating service. The activity also employs the cut-off method as another decision making method on the same problem.
The Science of Sugaring part of Examples
Comparing Journalistic Reports to Primary Sources of Research part of Examples
A set of three short writing assignments were designed to encourage students to think critically about the way that scientific research is reported by the popular media and the reasons that research may or may not be reported in a way that could be construed as misleading.