Specialist Methods (T)

students at Gungahlin College

Course information

Specialist Methods covers all the content of the Mathematical Methods course with more depth and difficulty. As such it also focuses on the development of the use of calculus, probability and statistical analysis but is designed to extend students with exposure to higher level mathematics. Students who were successful in Australian Curriculum 10A would be suitable to study this course.

Post-school pathways

This course is designed to thoroughly prepare students for study at university in courses which require a high level of mathematical knowledge and skills. This course includes calculus which is often required knowledge for science and engineering degrees. Other areas might include architecture, computer science, business or economics.

Do you enjoy or are you good at Mathematics? (pdf, 110kb)

Workload expectation

Specialist Methods requires commitment and a positive work ethic to complete the required study in class and at home. Students are expected to be completing at least four hours of study per week and more in preparation for examinations.

Course pattern

Available as a Minor or Major

Suggested Minor course

Semester

Unit

1

Unit 1: Specialist Methods

2

Unit 2: Specialist Methods

Suggested Major course

Semester

Unit

1

Unit 1: Specialist Methods

2

Unit 2: Specialist Methods

3

Unit 3: Specialist Methods

4

Unit 4: Specialist Methods

Unit descriptions

Unit 1: Specialist Methods

Review of Basic Algebraic concepts, Introduction of Functions and their Graphs, review the Fundamentals of Probability and Introduction of Conditional Probability and Independence.

Unit 2: Specialist Methods

Exponentials and Logarithms, Rates of Change, Average and Instantaneous, Calculus introduced through study of the Derivative

Unit 3: Specialist Methods

Calculus continues, Derivatives of Exponential and Trigonometric Functions, Integration and the Fundamental Theorem of Calculus

Unit 4: Specialist Methods

Statistics and Probability continued through Discrete and Continuous Random Variables and the Normal Distribution.