The document discusses the complexity of modeling social phenomena and highlights George E. P. Box's assertion that while all models are flawed, they still provide valuable insights into understanding relationships within social systems. It emphasizes the importance for researchers to recognize and mitigate errors in quantitative research and to critically evaluate the work of others. Graduate students are encouraged to select a relevant quantitative article with social change implications and analyze its usefulness and potential errors.

1. 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

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