Quantitative Reasoning – Finding Quantitative Article and Brief Explanation

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Discussion: The Logic of Inference: The Science of Uncertainty

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All models are wrong. Some models are useful.”

—George E. P. Box (1919–2013) Statistician

Describing and explaining social phenomena is a complex task. Box’s quote speaks to the point that it is a near impossible undertaking to fully explain such systems—physical or social—using a set of models. Yet even though these models contain some error, the models nevertheless assist with illuminating how the world works and advancing social change.

The competent quantitative researcher understands the balance between making statements related to theoretical understanding of relationships and recognizing that our social systems are of such complexity that we will always have some error. The key, for the rigorous researcher, is recognizing and mitigating the error as much as possible.

As a graduate student and consumer of research, you must recognize the error that might be present within your research and the research of others.

To prepare for this Discussion:

  • Use the Walden Library Course Guide and Assignment Help found in this week’s Learning Resources to search for and select a quantitative article that interests you and that has social change implications.
  • As you read the article, reflect on George Box’s quote in the introduction for this Discussion.
  • For additional support, review the Skill Builder: Independent and Dependent Variables, which you can find by navigating back to your Blackboard Course Home Page. From there, locate the Skill Builder link in the left navigation pane.

By Day 3

Post a very brief description (1–3 sentences) of the article you found and address the following:

  1. Describe how you think the research in the article is useful (e.g., what population is it helping? What problem is it solving?).
  2. Using Y=f(X) +E notation, identify the independent and dependent variables.
  3. How might the research models presented be wrong? What types of error might be present in the reported research?
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