Statistics can be viewed as the art and science of turning data into information. Real world decision-making, whether in business or science is often based on data and the perceived information it contains. Sherlock Holmes, when prematurely asked the merits of a case by Dr. Watson, snapped back, “Data, data, data! I can’t make bricks without clay.” In this course, we will study the basic methods by which statisticians attempt to extract information from data. These will include many of the standard tools of statistical inference such as hypothesis testing, confidence intervals, and linear regression as well as exploratory and graphical data analysis techniques. This is an accelerated introductory statistics course that involves computational programming and incorporates modern statistical techniques.
Format: lecture; Hybrid format: lecture material will be prerecorded, and you will be asked to attend (in person or virtually) one class session a week, during which we will briefly review lecture materials, allow time for questions, and work through a lab in RStudio to practice using the techniques discussed during that week's lectures.
Grading: yes pass/fail option,
yes fifth course option
weekly homework; quizzes and exams
MATH 150 or equivalent; not open to students who have completed STAT 101 or STAT 161 or equivalent
Prospective Statistics majors, students for whom the course is a major prerequisite, and seniors
Students with AP Stat 4/5 or STAT 101/161 should enroll in STAT 202 (if no calc background) or 302 (MATH 140 prereq). Students with no calc or stats background should enroll in STAT 101. Students with MATH 140 but no statistics should enroll in STAT 161.
Students will learn to interpret, choose, carry out, and communicate analyses of data.
COGS Related Courses
EVST Methods Courses
PHLH Statistics Courses