Course Brief
Unit abstract
This unit enables learners to develop previous mathematical knowledge obtained at school or college and use fundamental algebra,trigonometry, calculus, statistics and probability for the
analysis, modelling and solution of realistic engineering problems.
Learning outcome 1 looks at algebraic methods, including polynomial division, exponential,trigonometric and hyperbolic functions, arithmetic and geometric progressions in an engineering context and expressing variables as power series.
The second learning outcome will develop learners’ understanding of sinusoidal functions in an engineering concept such as AC waveforms, together with the use of trigonometric identities.
The calculus is introduced in learning outcome 3, both differentiation and integration with rules and various applications.
Finally, learning outcome 4 should extend learners’ knowledge of statistics and probability by looking at tabular and graphical representation of data; measures of mean, median, mode and
standard deviation; the use of linear regression in engineering situations, probability and the Normal distribution.
- This course is offered in 45 hours.
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Unit abstract
This unit enables learners to develop previous mathematical knowledge obtained at school or college and use fundamental algebra,trigonometry, calculus, statistics and probability for the
analysis, modelling and solution of realistic engineering problems.Learning outcome 1 looks at algebraic methods, including polynomial division, exponential,trigonometric and hyperbolic functions, arithmetic and geometric progressions in an engineering context and expressing variables as power series.
The second learning outcome will develop learners’ understanding of sinusoidal functions in an engineering concept such as AC waveforms, together with the use of trigonometric identities.
The calculus is introduced in learning outcome 3, both differentiation and integration with rules and various applications.
Finally, learning outcome 4 should extend learners’ knowledge of statistics and probability by looking at tabular and graphical representation of data; measures of mean, median, mode and
standard deviation; the use of linear regression in engineering situations, probability and the Normal distribution.