Lower-Division

Introduction to statistical methods/reasoning, including descriptive methods, data-gathering (experimental design and sample surveys), probability, interval estimation, significance tests, one- and two-sample problems, categorical data analysis, correlation and regression. Emphasis on applications to the natural and social sciences. Students cannot receive credit for this course if they have already received credit for STAT 7. (Formerly AMS 5.)

Case-study-based introduction to statistical methods as practiced in the biological, environmental, and health sciences. Descriptive methods, experimental design, probability, interval estimation, hypothesis testing, one- and two-sample problems, power and sample size calculations, simple correlation and simple linear regression, one-way analysis of variance, categorical data analysis. (Formerly AMS 7.)

Computer-based laboratory course in which students gain hands-on experience in analysis of data sets arising from statistical problem-solving in the biological, environmental, and health sciences. Descriptive methods, interval estimation, hypothesis testing, one-and two-sample problems, correlation and regression, one-way analysis of variance, categorical data analysis. (Formerly AMS 7L.)

Introduction to statistical methods as practiced in business and economics. Topics include descriptive methods, probability, random variables, expected values, sampling, estimation, confidence intervals, hypothesis testing, one- and two-sample problems, power and sample size calculations, correlation, and simple linear regression. Prerequisite(s): concurrent enrollment in STAT 17L; and score of 300 or higher on the mathematics placement examination (MPE), or AM 3 or AM 11A or MATH 3 or MATH 11A. Completion of MATH 19A is strongly recommended.

Overview and basic training in statistical programs used in the economics major.  Introduces students to basic data analysis workflow. A workflow of data analysis is a process for managing all aspects of data analysis. Planning, documenting, and organizing work; cleaning the data; creating, renaming, and verifying variables; creating summary statistics; and archiving what has been done are all integral parts of students' data analysis. This is an online asynchronous lab, with synchronous office hours/question and answer sessions. Prerequisites: concurrent enrollment in STAT 17; and score of 300 or higher on (MPE), or AM 3 or AM 11A. MATH 3 or MATH 11A strongly recommended. See Economics Department to petition for exceptions to concurrent enrollment restriction.

Games of chance and strategy motivated early developments in probability, statistics, and decision theory. Course uses popular games to introduce students to these concepts, which underpin recent scientific developments in economics, genetics, ecology, and physics. (Formerly AMS 80A.)

Introduces the use of complex-data graphical representations to extract information from data. Topics include: summary statistics, boxplots, histograms, dotplots, scatterplots, bubble plots, and map-creation, as well as visualization of trees and hierarchies, networks and graphs, and text. (Formerly AMS 80B.)