EMSE 6115

Syllabus

Introduction

Lecture Notes

R - Files

Python - Files

Example Exam Questions

Solutions -
Dekking

Solutions -
Devore

Solutions -
WMMY

LA

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Uncertainty Analysis for Engineers :

Course Description:
This course covers the basics of probability theory and statistics and ventures into some topics that go beyond an introductory course such as: simulation, the Poisson process, the law of large numbers, and the central limit theorem. Examples and datasets in this course are mostly from real-life situations. A first course in calculus is needed as a prerequisite for this course as well as introductory proficiency with Micro Soft Excel. In addition to high-school algebra, some infinite series are used. Integration and differentiation are the most important skills, mainly concerning one variable (the exceptions, two dimensional integrals, are encountered in Chapters 9–11). The statistical software package MINITAB shall be used where appropriate. Student are encouraged to learn R and run the R-scripts made available on the left.

Required Software: MINITAB, MicroSoft Excel.

Required Textbooks:

1. "A Modern Introduction to Probability and Statistics, Understanding Why and How" by F.M. Dekking, C. Kraaikamp, H.P. Lopuhaä and L.E. Meester, Springer-Verlag, 2005.
2. Probability and Statistics for Engineers and Scientists, 9th Edition, with MyLabs subscription, Walpole, Myers, Myers and Ye, Pearson Publishing, 2017.

Registration Instructions to Pearson:
Student_Registration_Handout

Optional Textbook:

1. "Modern Mathematical Statistics with Applications" by Devore, Jay L., Berk, Kenneth N., 2nd ed. 2012.

Dekking-Devore Crosswalk.pdf - Courtesy of Phillip Scrader