Listed in: Mathematics and Statistics, as MATH-135 | Mathematics and Statistics, as STAT-135
Moodle site: Section 01 (Login required)
Brittney E. Bailey (Sections 01 and 02)
Ryan P. McShane (Sections 03 and 04)
(Offered as STAT 135 and MATH 135) This course is an introductory statistics course that uses modeling as a unifying framework. The course provides a basic foundation in statistics with a major emphasis on constructing models from data. Students learn important concepts of statistics by mastering powerful and relatively advanced statistical techniques using computational tools. Topics include descriptive and inferential statistics, visualization, probability, study design, and multiple regression.
Students who have taken a semester of calculus (MATH 111 or higher, or equivalent placement) or who are majoring or planning to major in mathematics and/or statistics should take this course instead of STAT 111/111E. (Students who have taken STAT 111/111E or PSYC 122 may not also receive credit for STAT/MATH 135. Students who have taken ECON 360/361 will be admitted only with consent of the instructor.) No prior experience with statistical software is expected.
Fall 2020 Sections 01 and 02, January 2021 Section 01 and 02, and Spring 2021 Sections 01, 02, 04, and 05 will be online only. Methods and tools will vary by instructor, but all online only sections will include small group work and interactive labs to foster student engagement. We will conduct synchronous activities over Zoom and use platforms such as Moodle to structure asynchronous interactions and host course material.
Requisite: MATH 111 or equivalent. Limited to 24 students per section. Fall semester: Professors Bailey and McShane. January 2021: Professors Horton and McShane. Spring semester: Professors Bailey, Donges, Matheson, and Wagaman.
If Overenrolled: If Overenrolled: For the Fall, priority for rising sophomores. For the Spring, priority for first-year students, then sophomores.