2024 Statistics Summer Courses
STAT 5 [In Person]
Session 1
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.) Antirequisite: Students cannot enroll in STAT 5 after receiving a C or better in STAT 7.
General Education Code SR
Proposed Instructor: Dee MartinSTAT 7 [In Person]
Session 2
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.) Prerequisite(s): score of 300 or higher on the mathematics placement examination (MPE), or AM 3 or AM 6 or AM 11A or AM 15A or MATH 3 or MATH 11A or MATH 19A. Concurrent enrollment in STAT 7L is required.
General Education Code SR
Proposed Instructor: Dee MartinSTAT 7L [In Person]
Session 2
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.) Prerequisite(s): score of 300 or higher on the mathematics placement examination (MPE), AM 3 or AM 6 or AM 11A or AM 15A or MATH 3 or MATH 11A or MATH 19A. Concurrent enrollment in STAT 7 is required.
Proposed Instructor: TBASTAT 17 [Online]
Session 2
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. Prerequisite(s): A score of 300 or higher on the mathematics placement examination (MPE), or completion of AM 3 or AM 11A or MATH 3 or MATH 11A or MATH 19A. Concurrent enrollment in STAT 17L is required.
General Education Code SR
Proposed Instructor: David DraperSTAT 17L [Online]*
Session 2
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. Prerequisites: A score of 300 or higher on (MPE), or completion of AM 3 or AM 11A or MATH 3 or MATH 11A or MATH 19A. Concurrent enrollment in STAT 17 is required. Declared and proposed majors in one of the economics programs who are transferring in a course equivalent to STAT 17, should contact the Economics Department to petition for an exception to the concurrent enrollment requirement.
General Education Code IM
Proposed Instructor: Subhra Saha
*Pending CCI ApprovalSTAT 131 [Online]
Session 1
Introduction to probability theory and its applications. Combinatorial analysis, axioms of probability and independence, random variables (discrete and continuous), joint probability distributions, properties of expectation, Central Limit Theorem, Law of Large Numbers, Markov chains. Students cannot receive credit for this course and STAT 203 and CMPE 107. (Formerly AMS 131.) Prerequisite(s): AM 11B or ECON 11B or MATH 11B or MATH 19B or MATH 20B.
General Education Code SR
Proposed Instructor: David Draper
Statistics (5 credits)
Statistical Methods for the Biological, Environmental, and Health Sciences (5 credits)
Statistical Methods for the Biological, Environmental, and Health Sciences Laboratory (2 credits)
Statistical Methods for Business and Economics (5 credits)
Statistical Methods for Business and Economics Laboratory (2 credits)
Introduction to Probability Theory (5 credits)
