Department of Mathematics Syllabus
This syllabus is advisory only. For details on a particular instructor's syllabus (including books), consult the instructor's course page. For a list of what courses are being taught each quarter, refer to the Courses page.
MAT 19A: Calculus for Data-Driven Applications
Approved: 2023-03-21, J. De Loera and R. Thomas
Suggested Textbook: (actual textbook varies by instructor; check your instructor)
“Finite Mathematics & Applied Calculus,” 8th edition, by Waner & Costenoble (Cengage)
Two years of high school algebra, plane geometry, plane trigonometry, and analytical geometry, and satisfying the Mathematics Placement Requirement.
Calculus and other mathematical methods necessary in data driven analysis in the sciences, technology and the humanities.
|1||1.1-1.2||Review of functions (including linear, power, polynomial, rational);|
functions and models
|1||1.3-1.4||Linear models & linear regression|
|1||2.2-2.3||Exponential & logarithmic functions|
|1.5||10.1-10.3||Limits and continuity|
|0.5||10.4||Average rate of change|
|1||11.3||Product & quotient rules|
|1||11.5||Derivatives of exponential & logarithmic functions|
|1||12.3||Higher-order derivatives, concavity|
|1||8.1-8.3||Events, sample spaces, probability|
|1||8.5||Conditional probability, independence|
This course includes weekly 2-hour lab meetings in which students will use R to analyze real data in order to deepen their understanding of course material.
Upon completion of this course, students will be able to
- model data using functions,
- calculate derivatives,
- interpret derivatives in an economic or financial context,
- solve related rates and optimization problems,
- use calculus to sketch curves,
- calculate basic probabilities,
- determine whether events are independent, and
- use Bayes’ Theorem to calculate conditional probabilities.