Professor John Ting
Email: John_Ting@uml.edu
Office Hours: T/TH 1:00-3:00
Office: Kitson Hall - 200S
Phone: (978) 934-2230
Contact: Reference Librarian Margaret Manion
Email: Margaret_Manion@uml.edu
Phone: 978 934-3211
Office: Lydon Library, Rm. 203
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Welcome to Probability and Statistics for Engineers
This course is about probability and how it is measured: probability, statistics, reliability and decision with applications in engineering. Probability of events, discrete and continuous random variables, probability density functions and distributions, estimation, regression and correlation techniques, risk and reliability concepts.
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Successful completion of this course will enable you to:
apply spreadsheet programs to manipulate and analyze data
o apply formulae, use absolute relative & addressing, plot scatter and bar graphs
apply basic statistical analysis tools to data:
o calculate mean, median, standard deviation, plot histograms, etc
apply basic probability theory (independence, conditional & joint probabilities)
apply Bayes’ theorem for posterior probabilities as applied to engineering and test design
apply basic probability & reliability theory to different engineering situations
apply basic decision theory to assess the expected value of a project
explain and use the basic forms & properties of probability mass & density functions (PMF,
PDF) and cumulative distribution functions (CDF)
explain and apply specific discrete probability functions such as Bernoulli, Binomial,
Geometric
explain and apply specific continuous probability functions such as Normal, lognormal,
Student t, Chi-squared
analyze data to assess the parameters needed for each probability function
utilize appropriate probability functions to estimate probabilities of occurrence for specific
engineering cases
estimate the confidence intervals of the predictions made using probability functions
determine best-fit linear functions for (x,y) data using least-squares regression techniques