ENSC263: Engineering Measurement Techniques and Statistics
Instructor:
Dr Behraad Bahreyni
Lectures:
Mondays 8:30 to 10:20 (SUR 3090)
Wednesdays 8:30 to 9:20 (SUR 3090) TutorialsWednesdays 11:30 to 12:20 (SUR 3090)
Labs:
LA1: Wednesdays 12:30 to 15:30 at SUR4290
LA2: Wednesdays 15:30 to 18:30 at SUR4290
Syllabus:
Data representation
Dot plots, Stem-and-Leaf diagrams, Histograms, Box plots, Time series plots, Scatter plots
Introduction to probability
Population and sample, Random variables, Mean and variance, Functions of random variables, Independence
Probability distribution functions
Discrete distributions: Binomial, Poisson
Continuous distributions: Normal, Lognormal, Exponential, Weibull, Gamma
Normal approximations to binomial and Poisson distributions
Error analysis
Reporting and using uncertainties, Error propagation, Random and systematic errors
Engineering measurement
Sensitivity, Accuracy, Precision, Resolution, Quantization, Noise
Point estimation
Unbiasedness, Minimum Variance Unbiased Estimators
Hypothesis testing
z-test, t-test, χ2 test, F-test, Analysis of variance, Testing for the goodness of a fit
Empirical models
Simple linear regression, Multiple regression, Least-square fitting to polynomial models
Design of experiments
Factorial experiments
Statistical process control
X_bar and R_bar charts, Process stability and control.
Office hours:
Mondays 10:30 to 11:30 in MSE 4378
Wednesdays 9:30 to 10:30 in MSE 4378
Textbook (required)
Engineering Statistics, Forth EditionEvaluation
By Montgomery, Runger, Hubele. John Wiley & Sons, Inc., 2008
6 Assignments 6%
3 Laboratories 9%
4 Pop quizzes 20%
1 Midterm exam 15%
Final exam 50%
The midterm and final are closed book examinations of the course material. Students are permitted to use a crib sheet consisting of one 8 1/2× 11 paper (double-sided).
I put all the relevant course material on WebCT.