Applied Math   Math Home

The Applied Mathematics 10 / 20 / 30 sequence is designed for students who require a less algebraic mathematics program. Applied Mathematics emphasises the a application of math with the use of measurement, geometry, technology, and laboratory approaches to solve problems. This program should prepare students for colleges and technical institutes and some university programs. As per Alberta Learning's requirements, anyone wishing to receive a grade 12 diploma must obtain at least 10 credits in mathematics.
 

Applied Mathematics 10 - 5 credits
Prerequisite: Mathematics 9 (50%-65% recommended) Course Guide

Applied Mathematics is defined more by approach than by content. It should be noted that students will experience mathematics by experimentation and a laboratory approach and will make mathematical conclusions that are useful in careers and everyday life from these activities and projects. Topics include measurement, number patterns in tables, relations and functions, sampling, line segments, linear functions, and trigonometry. Computer technology and graphing calculators are used throughout this course. Applied Math 10 is not a prerequisite course for Pure Math 10. The next course in the sequence is Applied Math 20 or Pure Math 10 if a student wishes to change from Applied to Pure Mathematics.
 

Applied Mathematics 20 - 5 credits
Prerequisite: Applied Math 10 (50%+) Course Guide

Topics include number of operations an concepts to solve consumer problems, patterns and relations that involve expressions, equations and inequalities, analyzing functions using technology, circles and polygons, linear programming, scale factors re shape and space, statistics and probability analyzing graphs and charts.  The content of this course will again be taught by an experimental and a laboratory approach to learning mathematics.
 

Applied Mathematics 30 - 5 credits
Prerequisite: Applied Math 20 (50%+) Course Guide

Topics include matrices; consumer math; financial decisions using spreadsheets; analysis of cyclic, recursive and fractal patterns; sinusoidal curves; analysis of objects, shapes and processes that solve cost and design problems; vectors that contain 2D and 3D applications; normal binomial probability. This course will include laboratory and project approaches.

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Web Author: Philip Kaatz
Revised: February 24, 2001