MATH 23
Engineering Statistics
Course Description
This course provides a comprehensive introduction to probabilistic and statistical modeling for students in engineering, economics, finance and related disciplines in the mathematical sciences. It exposes students to a variety of applications requiring decision making in the face of uncertainty. Topics covered include the collection and analysis of information, making use of graphical and numerical techniques, discrete, continuous, cumulative, and joint probability distribution functions and use of statistical inference, experimental design, and equation fitting, when appropriate. Many of the applications require the use of technology (computers and graphic calculators). Computer simulations are used to illustrate difficult topics and provide visualization of advanced theoretical results (e.g. the Central Limit Theorem).
Class Details
| CRN | Course | Section | Days | Times | Instructor | Loc |
|---|---|---|---|---|---|---|
| 39140 | MATH 23 | 50Z | ······· | TBA-TBA | Fatemeh Yarahmadi | ONLINE |
Class Materials: View textbook and/or other materials for this course available at the Bookstore.
Class Dates: This class runs from 2025-01-06 to 2025-03-28.
Footnote:
MATH 23.50Z: Fully ONLINE. This is an online class that does not have scheduled meetings. Students can log in anytime to do the required weekly course work. Students must have access to a computer, the internet and an individual email address. We recommend a laptop or desktop computer to successfully complete the course; a tablet or phone may not be adequate for all assignments and tests. Most De Anza classes will use the Canvas course management system. Information about Canvas and Online Education Orientation can be found in Canvas on the Student Resources page: https://deanza.instructure.com/courses/3382. The Student Online Resources hub with extensive information and tips can be found at deanza.edu/online-ed/students/remotelearning .
Course Details
- Units
- 5 Units
- Hours
- Weekly Lecture Hours: 5
- Weekly Lab Hours: 0
- Gen Ed
- Non-GE Class
- Program Status
- Program Applicable
- Credit
- Credit - Degree Applicable
- Grading Method
- Letter Grading
General Course Statement
- General Statement
- See general education pages for the requirements this course meets.
Requisite and Advisory
- Advisory
- ESL 272. and ESL 273., or ESL 472. and ESL 473., or eligibility for EWRT 1A or EWRT 1AH or ESL 5.
- Prerequisite
- MATH 1C or MATH 1CH (with a grade of C or better)
