Simon Fraser University
Engaging the World

Course Outlines

Summer 2018 - ENSC 280 E100

Engineering Measurement and Data Analysis (4)

Class Number: 1101

Delivery Method: In Person

Overview

  • Course Times + Location:

    May 7 – Aug 3, 2018: Mon, 4:30–6:20 p.m.
    Burnaby

    May 7 – Aug 3, 2018: Wed, 4:30–6:20 p.m.
    Burnaby

  • Exam Times + Location:

    Aug 14, 2018
    Tue, 7:00–10:00 p.m.
    Burnaby

  • Prerequisites:

    ((PHYS 121 and ENSC 120) or PHYS 141) and (MATH 251 and MATH 232). MATH 251 and/or MATH 232 may be taken concurrently with ENSC 280. Engineering Science Majors and Honours students are requires to take ENSC 280 (no course substitutions will be accepted).

Description

CALENDAR DESCRIPTION:

Methods to collect and analyze engineering data. Topics include: engineering data representation, discrete and continuous probability density functions, engineering measurements, error analysis, test of hypotheses, linear and nonlinear regression, and design of experiments. This course includes a significant laboratory component comprising: laboratory measurements and statistical analysis of electronic circuits, introduction to electronic device behaviour, instrument noise. Students with credit for STAT 270, MSE 210, or PHYS 231 cannot take this course for further credit.

COURSE DETAILS:

Important Dates:
Midterm: Wednesday June 27, 2017. Lecture Time.
Final: Tuesday August 14, 2017, 7–10 PM, Room TBA

Course Outline:

(1) Introduction and Data representation
Introduction to engineering measurements, Dot plots, Stem-and-Leaf diagrams, Histograms, Box plots, Time
series plots, Scatter plots
(2) Introduction to probability
Population and sample, Random variables, Mean and variance, Functions of random variables
(3) Probability distribution functions, Discrete distributions: Binomial, Poisson Continuous distributions: Normal, Lognormal, Exponential, Weibull, Gamma
Normal approximations to Binomial and Poisson distributions
(4) Error analysis Reporting and using uncertainties, Error propagation, Random and systematic errors
(5) Engineering measurement Sensitivity, Accuracy, Precision, Resolution, Quantization, Noise
(6) Hypothesis testing, Point estimation, z-test, t-test, χ2 test, F-test, Testing for the goodness of a fit
(7) Empirical models, Simple linear regression, Multiple regression, Least-square fitting to polynomial models
(8) Design of experiments Factorial analysis (Tentative)

Laboratory:

There will be 3 laboratory exercises for this course. Labs are not in session every week. Lab assignment
handouts and dates will be announced in advance of each session. Students will work in groups. Lab reports are
usually due about one week after each lab session. One report per lab group is required.
Term-Long Project:
This is a group project performed by the same groups formed for the lab assignments. More information about
this project is given in Canvas.

Note: There will be no makeup exams for any of the midterms, regardless of the reason for missing the exam.
Midterm exam missed for non-legitimate reason will be given a zero mark. The weight of a midterm missed
for a legitimate reason will be added to the final.

Academic Integrity
Simon Fraser University is committed to creating a scholarly community characterized by honesty, civility,
diversity, free inquiry, mutual respect, individual safety and freedom from harassment and discrimination. Any
form of academic dishonesty or cheating will not be tolerated. For further information, please review SFU’s
policies on academic integrity:
http://www.sfu.ca/policies/Students/
Copying of others’ work is referred to as plagiarism and will not be tolerated. For more information, please
visit:
http://www.sfu.ca/students/academicintegrity.html

Grading

  • Assignments 5%
  • Term-Long Project 10%
  • Labs 15%
  • Midterm - 30% or 35% 30%
  • Final - 40% or 35% 40%

Materials

REQUIRED READING:

Engineering Statistics, 5th Edition, Montgomery, Runger, and Hubele, Wiley. (Printed or E-book)

RECOMMENDED READING:

An Introduction to Error Analysis, 2nd Edition Taylor, University Science Books, 1997

Applied Statistics and Probability for Engineers, 5th Edition Montgomery and Runger, Wiley, 2011

Registrar Notes:

SFU’s Academic Integrity web site http://students.sfu.ca/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS