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Course
Pro-forma
Bachelor of Engineering (Computer Aided Design & Manufacturing)
Code
KCEP2105
Title
Numerical Methods and Statistics
Pre-requisite
None
Student Learning Time (SLT)
120 hours
Credit
3
Learning Outcomes
1.
Define the basic theory of numerical methods and apply them
in engineering application.
2.
Classify the errors in computations.
3.
Solve problems concerning elementary probability,
probability distributions and random processes under
practical situations.
4.
Calculate confidence limits for data sample, perform
hypotheses tests concerning mean, variance, goodness of fit
and contingency tables.
5.
Translate numerical methods into step-by-step algorithms
Synopsis
This course will introduce the student to General Numeric
Methods and explain the uses of numeric methods in engineering.
Linear Equations will be introduced by drawing linear graphs and
calculating the gradient and intercept. Numeric Methods in Linear
Algebra will allow the student to draw linear graphs and calculates
the roots of equations. Gaussian elimination will enable to student
to solve for variables when there is a system of linear equations.
Numeric Interpolation will use the method of interpolation for
functions of linear equations. Newtons interpolation method will
facilitate Newtons method of interpolation. Numeric
Differentiation method will allow the student to use
differentiation methods for linear equations. Numeric Integration
method will demonstrate integration methods for functions of
linear equations. Rungge-Kutta method will be used for advanced
systems of linear equations. Weibull, Binomial and Normal
distributions will enable the students to use these dis
Assessment
40 % Continuous Assessments
60 % Final Examination
References
1.
Statistics for Engineers and Scientists William Navidi
(McGraw), 2008.
2.
Applied Numerical Methods with Matlab for Engineers and
Scientists – Steven C. Chapra (McGraw), 2008.
3.
Peter A. Stark, Introduction to Numerical Methods, MacMillan
Publishing Co., LCN 77-85773.
4.
Richard A., Probability and Statistics for Engineer, Prentice
Hall.
5.
Applied Probability and Statistics for Engineers by D. C.
Montgomery and G. C. Runger (John Wiley & Sons, 1999).
Soft Skills
Critical Thinking & Problem Solving Skills (CT1, CT2, CT3)