2005 Fall STA 101-002
Bulletin Course Description First principles of quantitative arguments in the social and behavioral sciences and public policy. Topics include descriptive statistics, graphical methods, elementary probability, point and interval estimation, frequentist and Bayesian statistical inference and historical and philosophical developments of statistics. Applications in education, sports, law, environment, government, discrimination, psychology, sociology, and public policy. Instructor: Staff
(Instructor named in bulletin description above may not be current. For current instructor, see listing below.)
Title DATA ANALY/STAT INFER Department STA Course Number 2005 Fall 101 Section Number 002 Primary Instructor Jang,Woncheol Prerequisites Prerequisite: STA 10, STA 19, placed in STA 101 by the statistics placement test, or have declared a major by March 29, 2007. Not open to students who
Prerequisites
Comfort with high-school algebra, including square roots.
Synopsis of course content
Statistics 101 introduces principles in the construction and critique of quantitative arguments for research questions in the social and behavioral sciences and public policy.
Topics include: descriptive statistics, graphical methods for exploring distributions and relationships between variables, elementary probability, point and interval estimation in one-, two- and multi-sample problems, and statistical inference from frequentist and Bayesian perspectives. Historical and philosophical developments of classical and Bayesian statistics are discussed.
Textbooks
Freedman, Pisani, and Purves. "Statistics: Third Edition." W. W. Norton, 1998.
Assignments
This course will have quizzes, exams, labs, and projects. In the computing labs, students analyze datasets using statistical software.
Additional Information
This course assumes students have only a high-school algebra background. Mathematical notation is minimized in favor of conceptual understanding. As such, the course does not cover many topics needed for further study in statistical methods, for example random variables and calculation of arbitrary expectations and variances. Therefore, students preparing for econometrics and finance courses in Economics are better served by taking Statistics 103. Students interested in a mathematically rigorous introduction to statistics should take Statistics 114.
