Undergraduate Course: Mathematics for Chem Eng 4 (MATH08020)
Course Outline
School  School of Mathematics 
College  College of Science and Engineering 
Course type  Standard 
Availability  Available to all students 
Credit level (Normal year taken)  SCQF Level 8 (Year 2 Undergraduate) 
Credits  10 
Home subject area  Mathematics 
Other subject area  Mathematics for Physical Science & Engineering 
Course website 
https://info.maths.ed.ac.uk/teaching.html 
Taught in Gaelic?  No 
Course description  THIS COURSE IS FOR STUDENTS RETAKING THE EXAMINATION ONLY AND NOT OPEN TO NEW STUDENTS
Integration in two and three variables. Scalar and vector fields, gradient, divergence and curl, divergence theorem. Diffusion equation in one dimension, separation of variables, error function. Laplace's equation in two dimensions, separation of variables, analytic functions. Revision of basic probability and discrete and continuous random variables. Sampling distributions, in particular in large samples. Hypothesis testing on one and two Normal expectations, including matches pairs design, and goodnessoffit tests on tables of frequency counts. Simple linear regression calculations. 
Information for Visiting Students
Prerequisites  None 
Displayed in Visiting Students Prospectus?  No 
Course Delivery Information

Delivery period: 2013/14 Semester 2, Available to all students (SV1)

Learn enabled: No 
Quota: 6 
Web Timetable 
Web Timetable 
Course Start Date 
13/01/2014 
Breakdown of Learning and Teaching activities (Further Info) 
Total Hours:
100
(
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
96 )

Additional Notes 

Breakdown of Assessment Methods (Further Info) 
Written Exam
100 %,
Coursework
0 %,
Practical Exam
0 %

Exam Information 
Exam Diet 
Paper Name 
Hours:Minutes 


Main Exam Diet S2 (April/May)  Mathematics for Chem Eng 4  1:30   
Summary of Intended Learning Outcomes
1. An ability to evaluate surface and volume integrals.
2. An ability to apply div, grad and curl.
3. An ability to solve Partial Differential Equations using separation of variables, similarity variables and the complexvariable method.
4. An ability to perform elementary probability calculations, and work with discrete and continuous random variables.
5. An ability to recognise when binomial, Poisson, Normal probability distributions are appropriate models.
6. Understanding what a sampling distribution is.
7. An ability to recognise when large sample approximations (eg Central Limit Theorem) are useful.
8. An ability to carry out simple hypothesis tests on binomials, Poissons, and Normals  this includes distinguishing between a twosample problem and a matched pairs design  and chisquared goodnessoffit tests on tables of frequency counts.
9. An ability to construct a least squares fitting of a straight line regression. 
Assessment Information
See 'Breakdown of Assessment Methods' and 'Additional Notes' above. 
Special Arrangements
None 
Additional Information
Academic description 
Not entered 
Syllabus 
Not entered 
Transferable skills 
Not entered 
Reading list 
Not entered 
Study Abroad 
Not entered 
Study Pattern 
Not entered 
Keywords  mc4 
Contacts
Course organiser  Dr Tom Mackay
Tel: (0131 6)50 5058
Email: T.Mackay@ed.ac.uk 
Course secretary  Mrs Gillian Law
Tel: (0131 6)50 5085
Email: G.Law@ed.ac.uk 

