Courses Catalogue

Engineering Probability And Statistics

COURSE CODE: MAT1204
COURSE CREDIT UNIT: 3
ACADEMIC PROGRAMME: Mechanical Engineering, Bsc
COLLEGE/SCHOOL/FACULTY: School of Engineering and Applied Sciences
STATUS: Core
PROGRAMME TYPE: Undergraduate

Course Description


This course is introduces a student to the fields of Probability and Statistics designed for

engineering fields. Probability Theory is of great use in all branches of Engineering in understanding and modeling phenomena that exhibit random behavior. Probability Theory also provides the theoretical and mathematical basis for statistics. The field of Statistics pertains to the presentation, analysis and interpretation of data. Engineers will be faced with the need to analyze data on a daily basis in the real world, and thus a good grounding in the

basics of statistics is invaluable. Statistics is inherently inductive since inference is made

about a whole population on the basis of information/data obtained from a sample from the population. Unlike Statistics, Probability theory is inherently deductive, and has nothing to do with sample data. Rather it is a field of mathematics from which results and conclusions are derived from propositions and assumptions.

COURSE JUSTIFICATION/RATIONALE

To develop an understanding of the methods of probability and statistics which are used to model engineering problems

COURSE OBEJECTIVES

At the end of this course, the student should be able to:

  •    Analyze samples and present them in tabular or graphical forms.
  •    Become familiar with events that occur with certainty and un-certainty.
  •    Know how to use inferential statistics to analyze data.
  •  Outline regression techniques.
  •    Outline regression techniques.

LEARNING OUTCOMES

A student on completing this course is expected to:

  •    Present data in tabular or graphical forms;
  •  Describe concept of a random event and a random experiment;
  •  Calculate discrete and continuous.
  •   Analyze data obtained from different scientific fields.
  •   Use statistical hypotheses and tests.
  •   Use regression techniques in data analysis.