Syllabus for Statistics for Engineers

Learning outcomes

On completion of the course, the student should be able to:

• use a number of methods and techniques for visualisation of data sets;
• compute probabilities in simple cases;
• give an account of the concept random variable and be able to use some common probability distributions;
• understand the meaning of the central limit theorem;
• use point and interval estimates for some typical statistical problems;
• apply elementary regression for fitting measured data;
• give an account of some typical engineering applications of probability and statistics, e.g. reliability and quality control.

Content

Descriptive statistics: measures of location and variation, frequency tables, bar diagrams, histograms, other diagrams and tools for visualisation. Introductory combinatorics and probability theory. Probability distributions: binomial, Poisson, normal, exponential. Central limit theorem. Point and interval estimation. The method of regression. Engineering applications, selected examples.

Instruction

Lectures, lessons, computer exercises and problem solving sessions.

Assessment

Written examination at the end of the course combined with discussions tasks and written assignments.

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.