Sep 30, 2020
MATH 115A - Mathematical Ideas
Intended primarily for students who need only one mathematics foundation course with an emphasis on quantitative reasoning. This course includes support content from intermediate algebra as needed to study major topics selected from (but not limited to) graph theory, voting and apportionment, geometry, growth and symmetry, number theory, and descriptive statistics. Emphasis is on contemporary applications to real-life problems. Credit may not be earned in both MATH 115A and MATH 117A Not intended for students with a grade of C or better in MATH 092 , MATH 093 or MATH 096 . PREREQUISITE(S): A grade of C or better in MATH 080 , appropriate score on the mathematics placement test, or consent of department. Assessment Level(s): ENGL 101 /ENGL 101A or AELW 940 /ELAI 990 , READ 120 or AELR 930 /ELAR 980 . For computation of tuition, this course is equivalent to five semester hours. Five hours each week. Formerly MA 115A.
3 semester hours
Upon course completion, a student will be able to:
- Given a table of values, a verbal, algebraic or graphical representation, identify whether a function is linear, quadratic, or exponential.
- Interpret, in context, the key features of linear, quadratic, and exponential functions.
- Use linear, quadratic, and exponential models to evaluate and make predictions.
- Use numerical, verbal, algebraic or graphical strategies to do all of the above.
- Solve linear, quadratic, and exponential equations by applying algebraic, numerical, and/or graphing techniques.
- Understand, translate, and solve linear, quadratic, and exponential application problems.
- Collect and organize quantitative information and then model a societal, cultural or management system.
- Select an appropriate mathematical model for a given quantitatively based system and then analyze properties of the system.
- Compare, contrast and discuss the limitations of alternate methods of analyzing a given quantitatively based system.
- Use technology to develop and analyze mathematical models for quantitatively based systems.
- Explain the difference between exact and approximate algorithms.
- Explain the difference between efficient and inefficient algorithms.
- Select an appropriate algorithm to use on a quantitatively based system.
Click here for the Summer I 2020 Class Schedule
Click here for the Summer II 2020 Class Schedule
Click here for the Fall 2020 Class Schedule
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