Psych 210 – Basic Statistics for Psychology
Statistics consists of both lecture (handled by the instructor) and laboratory instruction (handled by the TA). Psych 210 meets the Quantitative Reasoning B (QR-B) requirements, which are spelled out in the memo reproduced below:
January 2010
TO: Chairs of departments currently listed as offering Quantitative Reasoning B courses
COURSES FOR THE DEPARTMENT OF: Psychology
210-Basic Statistics for Psychology
280-Honors Basic Statistics for Psychology
FROM: Associate Dean Nancy Westphal-Johnson, College of Letters and Science
RE: Information about Quantitative Reasoning B criteria
I am writing to remind you that Quantitative Reasoning B courses should continue to be taught in a way that meets the established criteria for such courses (the criteria are attached to this memo); please share this information with QR B course instructors in your department. If you have questions about the current QR B listings for your department or resources available to QR B instructors, please visit the UW-Madison General Education web site http://www.ls.wisc.edu/gened/) or contact me (westphal@ls.admin.wisc.edu, 3-2506).
XC: Departmental Administrators of relevant departments.
Professor Gloria Mari-Beffa, QR-liaison
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The General Education requirement in Quantitative Reasoning (QR) consists of two parts:
QR-A: 3 credits in mathematics, computer science, statistics, or formal logic.
QR-B: 3 additional credits in quantitative reasoning.
The QR-B course follows the QR-A course and is expected to make use of skills learned in QR-A for dealing with quantitative information. A very important goal of every QR-A course is to increase the readiness of students to understand, process, and reason with quantitative information and relationships in many different contexts.
The guidelines for a QR-B course are that they must make *significant* use of quantitative tools in the context of other course material, for example:
- the recognition and construction of mathematical models and/or hypotheses that represent quantitative information,
- the evaluation of these models and hypotheses,
- the analysis and manipulation of mathematical models,
- the drawing of conclusions, predictions, or inferences, and
- the assessment of the reasonableness of conclusions.