EDUC 152
Quantitative Methods in Education: Applied Data Analysis for Policy and Practice
Education · 5 units · Undergraduate upper division (100-199)
Application of tools such as regression to analyze educational data. Students learn to appropriately interpret the results, with consideration to the nature, assumptions, and limitations of these tools; and learn the kinds of questions they can and cannot answer related to association, prediction, and causal inference. Particular attention is given to understanding the use of data to interrogate disparities in educational opportunities and outcomes rather than reify biased assumptions and concepts. Students learn to apply basic regression analysis and related analytical tools using various education datasets.
Letter grading.
When it runs
Checking the Schedule of Classes…
Requisites
Official UCLA wording
Requisite: course 150 or 151. Preparation: basic familiarity with programming language R. Introduction to statistical modeling techniques that go beyond simple correlations among variables to provide better answers to important questions of education policy and practice.
BruinTree reads · Preparation
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Requires
Everything that has to come before this course, not just the courses named in the requisite above.
EDUC 152
- EDUC 150Quantitative Methods in Education: Claims and Evidence
- EDUC 35Introduction to Inquiry and Research in Education
- EDUC 151Quantitative Methods in Education: Principles of Measurement and Testing
2 direct requisites. The whole upstream is here — 4 courses over 2 levels. Every course here opens its own tree.
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
No course in the catalog lists this as a requisite.





