NAME OF COURSE/MODULE: ENGINEERING STATISTICS
COURSE CODE: KEH2412
NAME(S) OF ACADEMIC STAFF: Assoc. Prof. Dr. Janatul Islah Binti Mohammad
RATIONALE FOR THE INCLUSION OF THE COURSE/MODULE IN THE PROGRAMME: This course provides students with an opportunity to develop their skills in the use of the literature and in quantitative methods. Students will learn how to evaluate and contribute to the scientific literature, to assess the kinds of scientific data and tests of hypotheses, as well as to use and interpret advanced methods of experimental design and statistical analysis.
SEMESTER AND YEAR OFFERED: SEM 4 / YEAR 2
TOTAL STUDENT LEARNING TIME (SLT) FACE TO FACE TOTAL GUIDED AND INDEPENDENT LEARNING
L = Lecture

T = Tutorial

P = Practical

O= Others

L

28

T

 

12

P

 

0

O

0

 

Guided: 40 hours

Independent Learning: 40 hours

Total: 80 hours

CREDIT VALUE: 2
PREREQUISITE (IF ANY): NONE
OBJECTIVES: To learn and acquire the knowledge of designing of experiment with respect to engineering statistics.
LEARNING OUTCOMES (LO): Upon successful completion of this course, students should be able to:

CLO1: Analyse and solve the problems using related essential concepts, principles and theories (C4)

CLO2: Display the ability to solve the problems related to engineering statistics (P4 – PO4)

CLO3: Demonstrate the ability to communicate and explain the concepts of engineering statistics (A3 – PO9)

TRANSFERABLE SKILLS: Students should be able to develop and apply characteristic of good engineering skills and interpersonal communication, teamwork and leadership, problem solving, planning and organisational skills through a process of lectures and tutorials.
TEACHING-LEARNING AND ASSESSMENT STRATEGY:

 

Teaching-learning strategy:

•               Problem Based Learning

•               Outcome Based Learning

Assessment strategy:

•               Formative

•               Summative

SYNOPSIS:

 

This course will introduce the basic requirement in the theory of probability and statistics. The approach will be axiomatic and with numerous examples. The topics to be discussed are: the three concepts of probability measurement, axioms of probability; sample space and events, mutually exclusive events and addition rule; conditional probability, independent events, multiplication rule. The concept of random variable, its probability distribution and its expectation will also be introduced. Examples on the probability distributions will include the binomial and Poisson for the discrete random variable, and the uniform, normal, and exponential for the continuous probability distributions. The topics on statistical inference cover estimation of parameters, the construction of confidence interval, and the concept of hypothesis testing involving the use of the z, t and the χ2 tables.
MODE OF DELIVERY: Lectures and Tutorials
ASSESSMENT METHODS AND TYPES:
A. Continuous Assessment (50%)
Category Percentage
·    Test (s)

·    Assignment (Written report & group presentation)

20%

30%

B. Final Examination (0%)
i.          Examination 50% ·    Structured and essay type questions
MAIN REFERENCES SUPPORTING THE COURSE
  1. Montgomery, D.C., Runger, G. C. and Hubele, N. F. 2012. Engineering Statistics. 5th edition. John Wiley & Sons (Asia) Pte. Ltd.
ADDITIONAL REFERENCES SUPPORTING THE COURSE
  1. Devore, J.L. 2004. Probability and Statistics for Engineering and the Sciences. 6th edition. Thomson Brooks.
  2. Mason, R.L.,Gunst, R.F. and Hess, J.L. 2003. Statistical Design and Analysis of Experiments: with Applications to Engineering and Science. John Wiley.
  3. Johnson, N.L. and Leone, F.C. 1964. Statistics and Experimental Design in Engineering and the Physical Sciences. John Wiley