Index

A

aliasing experiments analysis of variance ANOVA applications of latent variable models references and readings assignable cause assumptions for least squares

autocorrelation autoscaled autoscaling average average run length axial points experiments

B

bar plot visualization Bernoulli distribution binary distribution biplot block (data set) blocking experiments

bootstrapping box plot visualization breakdown point brushing latent variable modelling business intelligence

C

candidate set optimal designs capability of a process, [1] categorical factor experiments centered process centering centering, about median central composite designs Central limit theorem collinearity colour visualization common cause complementary half-fraction experiments confidence interval, [1] for proportions for variance interpreting least squares ratio of variances unknown variance

confounded confounding confounding pattern contribution plots control charts controlling for another variable convex optimization least squares Cook's D-statistic correlation covariance covariates Cp Cpk cross-validation, [1] cube plot cumulative distribution curvature response surface CUSUM process monitoring

D

data historian data table visualization defining relationship experiments, [1] definitive screening design experiments degrees of freedom loss of density

derivation least squares Design of experiments see experiments design resolution experiments deviation variables discrepancy least squares dummy variable see also indicator variable

E

enterprise resource planning error statistical EWMA process monitoring exercises experiments latent variable modelling least squares process monitoring univariate data visualizing data experiments aliasing axial points blocking categorical factor complementary half-fraction defining relationship, [1] definitive screening design design resolution exercises factor fractional factorial generating relationship objective outcome Plackett-Burman designs references and readings replicates response response surface methods run saturated design screening designs usage examples variable words

exponentially weighted moving average see EWMA

F

factor experiments feedback control, [1]

fractional factorial experiments frequency distribution frequency, relative

G

generating relationship experiments

H

happenstance data

histograms

I

independence, [1] lack of independence in least squares indicator variable industrial practice process monitoring influence least squares

inspection costs integer variables least squares integer variables in least squares interaction effects interaction plot interpret score plot latent variable modelling inverse cumulative distribution

K

key performance indicator

KPI see key performance indicator

L

latent variable modelling brushing exercises interpret score plot linking loadings plot, interpretation of principal component analysis references and readings what is a latent variable least squares assumptions for confidence interval convex optimization derivation discrepancy exercises influence integer variables leverage multiple linear regression (MLR) objective function outliers, [1] references and readings summary of steps usage examples

leverage least squares linking latent variable modelling loadings plot, interpretation of latent variable modelling location, [1] (process monitoring) logistic regression long-term reference set lower control limit, [1] lower specification limit

M

MAD main effect mean median median absolute deviation see MAD

monitoring chart assessment monitoring charts moving average multiblock multiple linear regression (MLR) least squares

N

non-constant error variance nonparametric modelling normal distribution check if formal definition table for

O

objective experiments objective function least squares off-specification product optimal designs candidate set

orthogonality outcome experiments outlier, [1], [2] outliers least squares, [1]

P

paired test parameter population partial least squares see projection to latent structures PCA see principal component analysis phase 1 (monitoring charts), [1], [2] phase 2 (monitoring charts) Plackett-Burman designs experiments PLS see projection to latent structures Poisson distribution pooled variances population parameter prediction error interval prediction interval, [1] principal component analysis latent variable modelling references and readings

probability process capability process monitoring process capability ratio process monitoring CUSUM EWMA exercises industrial practice process capability references and readings Shewhart chart usage examples process width product development usage examples product quality projection to latent structures references and readings

Q

quantile-quantile plot (q-q plot)

R

R2 (correlation coefficient) rare events raw material variability references and readings applications of latent variable models experiments latent variable modelling least squares principal component analysis process monitoring projection to latent structures univariate data visualization relative frequency replicates experiments

residual plots response experiments response surface curvature response surface methods experiments RMSEE RMSEP robust least squares robust statistics robustness example run experiments

S

sample saturated design experiments scaling scatter plot visualization scree plot screening designs experiments Shewhart chart process monitoring significant difference see tests for differences sparklines

special cause spread, [1] standard deviation standard error, [1] standard form standardize a variable statistic statistical process control statistical tables studentized residuals subgroups (monitoring charts) summary of steps least squares system failures systematic error

T

t-distribution table for table see data table tail, in a histogram

testing least squares models tests for differences time-series plots visualization transformations two treatments

U

uncentered process capability process monitoring unconstrained optimization uniform distribution univariate data exercises references and readings usage examples

upper control limit, [1] upper specification limit usage examples experiments least squares process monitoring product development univariate data

V

variability cost of in raw materials variable experiments variance visualization bar plot box plot colour data table references and readings scatter plot time-series plots

visualizing data exercises

W

Western Electric rules what is a latent variable latent variable modelling

words experiments

Y

Yates order