It is nearly impossible to live in the world today without being inundated with data. Even the most popular newspapers feature statistics to catch the eye of the passerby, and sports broadcasters overwhelm the listener with arcane statistics. How do we learn to recognize dishonest or even unintentionally distorted representations of quantitative information? How are we to reconcile two medical studies with seemingly contradictory conclusions? How many observations do we need in order to make a decision? It is the purpose of this course to develop an appreciation for and an understanding of the interpretation of data. We will become familiar with the standard tools of statistical inference including the t-test, the analysis of variance, and regression, as well as exploratory data techniques. Applications will come from the real world that we all live in. Format: lecture. Evaluation will be based primarily on performances on quizzes and exams. Prerequisites: Mathematics 100/101/102 (or demonstrated proficiency on a diagnostic test; see Mathematics 100). Students who have had calculus, and potential Mathematics majors should consider taking Statistics 201 instead. Enrollment limit: 50 (expected: 40). Not open for major credit to junior or senior Mathematics majors.

Hour: KLINGENBERG