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Becoming a Psychology Scholar part of Examples
This assignment takes indtroductory psychology students step-by-step through the research process.
GSS based data analysis part of Examples
Students will write and present a paper which consists of a review of literature and an empirical/statistical test of the relation between specific variables in the field of social stratification.
Exploring an Architectural Remodel part of Examples
An assignment that requires students to explore a remodeled architectural site, to update the original blueprints with accurate new plans based on their own measurements, and to propose viable possibilities for future reuses of the structure.
Utilizing Numbers in Reading and Writing about Socially-Conscious Literature part of Examples
This activity introduces the students to the usefulness of quantitative material in studying and writing about socially-conscious literature.
Counting Grizzly Bears: An Exercise in Historical Reasoning part of Examples
This assignment engages students in an environmental history class in the use of quantitative data, and raises questions about the nature and meaning of that data, and how it might be utilized.
Comparison of GDP and the Human Development Index (HDI). part of Examples
This assignment exposes students to data on economic growth anddevelopment as commonly measured by per capita GDP and the HumanDevelopment Index (HDI) for 100 countries of the world. There is a bigdebate about how good an indicator HDI is compared to GDP per capita asa measure of development.
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.