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Engineering Statistics & Industrial Applications

Foreword
A statistician is a mathematician broken down by age and sex.
Practice is the best of all instructors. We all learnt by doing, by experimenting
(and often failing) and by asking questions.

Final Exam with solutions
We provide the comprehensive final exams, and the detailed solutions with step by step explaination, plus the final grading rules!
Final Exam 1     Final Exam 1 with solutions     Final Exam 2     Final Exam 2 with solutions

Practice Final Exam 1       Practice Final Exam 1 with solutions
Practice Final Exam 2       Practice Final Exam 2 with solutions
Practice Final Exam 3       Practice Final Exam 3 with solutions

Lecture Notes
Here are the example-demonstrated lecture notes, step by step explaination. The copyright strictly belongs to NIST/SEMATECH.

Chapter01: Exploratory Data Analysis
This chapter presents the assumptions, principles, and techniques necessary to gain insight into data via EDA--exploratory data analysis.

Chapter02: Measurement Process Characterization
The purpose of this section is to illustrate the planning, procedures, and analyses outlined in the various sections of this chapter with data taken from measurement processes at the National Institute of Standards and Technology. A secondary goal is to give the reader an opportunity to run the analyses in real-time using the software package, Dataplot.

Chapter03: Production Process Characterization
The goal of this chapter is to learn how to plan and conduct a Production Process Characterization Study (PPC) on manufacturing processes. We will learn how to model manufacturing processes and use these models to design a data collection scheme and to guide data analysis activities. We will look in detail at how to analyze the data collected in characterization studies and how to interpret and report the results. The accompanying Case Studies provide detailed examples of several process characterization studies.

Chapter04: Process Modeling
The goal for this chapter is to present the background and specific analysis techniques needed to construct a statistical model that describes a particular scientific or engineering process. The types of models discussed in this chapter are limited to those based on an explicit mathematical function. These types of models can be used for prediction of process outputs, for calibration, or for process optimization.

Chapter05: Process Improvement
The purpose of this section is to illustrate the analysis of designed experiments with data collected from experiments run at the National Institute of Standards and Technology and SEMATECH. A secondary goal is to give the reader an opportunity to run the analyses in real-time using the Dataplot software package.

Chapter06: Process or Product Monitoring and Control
This chapter presents techniques for monitoring and controlling processes and signaling when corrective actions are necessary.

Chapter07: Product and Process Comparisons
This chapter presents the background and specific analysis techniques needed to compare the performance of one or more processes against known standards or one another.

Chapter08: Assessing Product Reliability
This chapter describes the terms, models and techniques used to evaluate and predict product reliability.

Discussion Quiz with solutions
Quiz 1 with solutions   Quiz 2 with solutions   Quiz 3 with solutions   Quiz 4 with solutions   Quiz 5 with solutions

Midterm Exam with solutions
Midterm Exam 1       Midterm Exam 1 with solutions
Midterm Exam 2       Midterm Exam 2 with solutions
Midterm Exam 3       Midterm Exam 3 with solutions