Engineering Statistics Handbook in the Tidyverse
Preface
Structure of the book
Software information and conventsions
Acknowledgements
1
Exploratory Data Analysis
1.1
A EDA Example
1.2
But first… let’s start working in the tidyverse
1.3
Common graphical analysis used in the e-Handbook
1.4
Case studies from chapter 1 of the NIST/SEMATECH e-Handbook
1.4.1
Normal random numbers
1.4.2
Uniform random numbers
1.4.3
Random walk
1.4.4
Beam deflections
1.4.5
Filter transmitance
1.4.6
Standard resistor
1.4.7
Heat flow meter 1
1.4.8
Ceramic strength
2
Measurement Process Characterization
2.1
Packages used in this chapter
2.2
Characterization
2.3
Gauge R & R studies
2.4
Case Studies
2.4.1
Check standard
2.4.2
Gauge study
3
Production Process Characterization
3.1
Pacakges used in this chapter
3.2
Case Studies
3.2.1
Furnace Case Study
3.2.2
Machine Case Study
4
Modeling
4.1
Packages used in this chapter
4.2
Introduction
4.2.1
A simple linear regression model
4.2.2
Beyond the linear regression
4.3
Case Stuidies
4.3.1
Load cell output
4.3.2
Thermal expansion of copper
4.3.3
Quadratic/Quadratic (Q/Q) model
4.3.4
Cubic/Cubic Rational Function
4.4
Applying models to multiple datasets
4.4.1
Revisting the Ascombe dataset
4.4.2
Model-level summaries
4.4.3
Coefficient-level summaries
4.4.4
Observation Data
5
Process Improvment
5.1
Packages used in this chapter
5.2
Case Stuidies
5.2.1
Eddy current probe sensitivity
6
Process Monitoring
6.1
Packages used in this chapter
6.2
Case Stuidies
6.2.1
Lithography Process Example
7
Product and Process Comparisons
7.1
Packages used in this chapter
7.2
Exercises
7.2.1
7.2.2. Are the data consistent with the assumed process mean?
7.3
Student’s t-test
7.3.1
“illustrative example of the t-test” in section 7.2.2 - particle (contamination) counts
7.3.2
Do two processes have the same mean? in section 7.3.1 - Example of unequal number of data points
7.4
One more classic example! (from Student himself)
7.4.1
plot of Student’s (W.S. Gossett) data
7.5
Anova
7.5.1
Tidy the data and compute the sum of squares
7.6
Let’s let R do the work:
7.7
Which populations have different means?
7.7.1
Tukey (or Tukey-Kramer) test
7.8
ANOVA Block analysis
7.8.1
Tidy up the data
7.8.2
One-way ANOVA
7.8.3
Plot of the data
7.8.4
ANOVA with blocking factor
7.8.5
But what is different?
7.9
Two-way ANOVA with interaction
8
Assessing Product Reliability
References
Published with bookdown
An Incomplete Solutions Guide to the NIST/SEMATECH e-Handbook of Statistical Methods
8
Assessing Product Reliability
This chapter was not covered in the course and may be added at a later date.