Credits: 3
Integrated statistical methodology for the improvement of products and processes in terms of performance, quality and cost. Designed experimentation. Statistical process control. Software application. Laboratory activities.
Description
Prerequisite: MATH241.
Semesters Offered
Fall 2017, Spring 2018, Summer 2018, Fall 2018, Spring 2019, Summer 2019, Fall 2019, Spring 2020Learning Objectives
Textbook
Statistics for Engineers and Scientists by Navidi, 4th edition, McGraw-Hill, 2014.
Other supplemental materials:
- Applied Statistics and Probability for Engineers, Montgomery and Runger, Wiley.
- Probability and Statistics for Engineers and Scientists, Walpole et al., Prentice Hall.
- Introduction to Probability and Statistics for Engineers and Scientists, Ross, Elsevier.
Class/Laboratory Schedule
- Two 75 minute lectures each week
Topics Covered
- Week 1: Course info; use of statistics in engineering; sample mean and variance.
- Week 2: Event, sample space, probability, trees; counting rules, permutations, combinations, Venn diagrams; addition and multiplication rules; conditional probability; Bayes's rule.
- Week 3: Random variables, distributions, expected value and variance; functions of random variables; error-propagation; numerical experimentation.
- Week 4: Functions of many random variables; design-under-uncertainty; normal, binomial, hypergeometric distributions.
- Week 5: Poisson and exponential distributions, sampling, estimators, the Central-Limit theorem.
- Week 6: Review and problem solving.
- Week 7: Confidence intervals; estimation using numerical simulation.
- Week 8: Confidence intervals (standard error, T-dist, difference of means, paired observations, proportion, variance).
- Week 9: Concept of hypothesis testing, P-value (single mean, proportion, type I and II errors), hypothesis testing (variance, two means, pairs).
- Week 10: Hypothesis testing (goodness-of-t, independence, goodness-of-t).
- Week 11: Review and problem solving.
- Week 12: Analysis-of-variance (ANOVA).
- Week 13: Linear Regression, Multiple Linear Regression.
- Week 14: Design-of-experiments (DOE).
- Week 15: Review and problem solving.
Learning Outcomes
- an ability to apply knowledge of mathematics, science, and engineering
- an ability to design and conduct experiments, as well as to analyze and interpret data
- an ability to identify, formulate, and solve engineering problems
- an understanding of professional and ethical responsibility
- an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice
Additional Course Information
Textbook
Statistics for Engineers and Scientists by Navidi, 4th edition, McGraw-Hill, 2014.
Other supplemental materials:
- Applied Statistics and Probability for Engineers, Montgomery and Runger, Wiley.
- Probability and Statistics for Engineers and Scientists, Walpole et al., Prentice Hall.
- Introduction to Probability and Statistics for Engineers and Scientists, Ross, Elsevier.