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multiple regression example 1-1 (univariate)
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Data Science
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Healthcare Monitoring and Improvement
Industrial Process Management
Marketing
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Books and Data Sets
A Guide to Modern Econometrics (Verbeek)
A Handbook of Statistical Analyses Using R (Everitt)
A Primer for Sampling Solids, Liquids, and Gases: Based on the Seven Sampling Errors of Pierre Gy (Smith)
Acceptance Sampling in Quality Control (Schilling)
Advanced Log-Linear Models Using SAS (Zelterman)
AIAG MSA Manual
AIAG SPC Manual
An Introduction to Design of Experiments (Barrentine)
An Introduction to Statistical Learning with Applications in R (Hastie Tibshirani)
Analysis of Financial Time Series (Tsay)
Analysis of Messy Data Volume 1 Designed Experiments (Milliken)
Applied Econometrics with R (Kleiber)
Applied Linear Regression Models (Kutner)
Applied Nonparametric Regression (Härdle)
Applied Statistics and the SAS Programming Language (Cody)
Applied Survival Analysis - Regression Modeling of Time to Event Data (Hosmer and Lemeshow)
ASQ Volume 01: How To Analyze Data With Simple Plots
ASQ Volume 02: How To Perform Continuous Sampling
ASQ Volume 03: How To Test Normality and Other Distributional Assumptions
ASQ Volume 04: How To Perform Skip Lot And Chain Sampling
ASQ Volume 05: How To Run Mixture Experiments for Product Quality
ASQ Volume 06: How To Analyze Reliability Data
ASQ Volume 07: How And When To Perform Bayesian Acceptance Sampling
ASQ Volume 08: How To Apply Response Surface Methodology
ASQ Volume 09: How To Use Regression In Quality Control
ASQ Volume 10: How To Plan An Accelerated Life Test
ASQ Volume 11: How To Perform Statistical Tolerance Analysis
ASQ Volume 12: How To Choose The Proper Sample Size
ASQ Volume 13: How To Use Sequential Statistical Methods
ASQ Volume 14: How To Construct Fractional Factorial Experiments
ASQ Volume 15: How To Determine Sample Size And Estimate Failure Rate In Life Testing
ASQ Volume 16: How To Detect And Handle Outliers
ASTM F1469 Standard Guide for GRR (nondestructive testing)
ASTM Standards on Precision and Bias for Various Applications
Bootstrap Methods and their Application (Davison)
Categorical Data Analysis Using the SAS System (Stokes)
Common Errors in Statistics and How to Avoid Them (Good)
Concepts for R&R Studies (Barrentine)
Data Analysis and Graphics Using R (Maindonald)
Datasets StatSoft (General)
Design and Analysis of Experiments (Montgomery)
Design and Analysis of GR&R Studies (Montgomery)
Destructive, Dynamic, and Attribute Measurement Systems (Mawby)
Dodge-Romig Sampling Inspection Tables
Forecasting and Time Series - An Applied Approach (Bowerman)
Forecasting: Principles and Practice (Hyndman)
Fundamental Concepts in the Design of Experiments (Hicks)
GRR and DGRR Studies (Mario Perez-Wilson)
HALT, HASS, HASA Explained - Accelerated Reliability Techniques
Handbook of Statistical Analysis and Data Mining Applications (Nisbet)
Handbooks of Central Banking (Bank of England)
Introduction to Categorical Data Analysis (Agresti)
Introduction to Modern Nonparametric Statistics (Higgins)
Introduction to Probability and Statistics Using R
Introduction to Statistical Quality Control (Montgomery)
Introduction to Time Series Analysis and Forecasting (Montgomery)
Juran's Quality Handbook (Juran)
Linear Control System Analysis and Design (Houpis)
Logistic Regression Using the SAS System (Allison)
Manufacturing Solutions for Consistent Quality and Reliability (Traver)
Mathematical Statistics with Applications (Wackerly)
Matrices with Applications in Statistics (Graybill)
Measuring Quality Improvement in Healthcare (Carey)
Modern Applied Statistics with S-Plus (Venebles)
Multivariate Analysis in Social Science Research (Tacq)
Multivariate Statistical Methods: Practical Research Applications (SAS)
Multivariate Statistical Process Control with Applications (Mason)
New Introduction to Multiple Time Series Analysis (Lutkepohl)
Nonparametric Statistical Methods for Complete and Censored Data (Desu)
Practical Data Science with R
Practical Guide to Business Forecasting (IBF)
Practical Nonparametric Statistics (Conover)
Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications (Miner)
Process Capability Indices in Theory and Practice (Kotz)
Process Quality Control (Ott)
QCI ASQ Certified Quality Engineer Primer
QCI ASQ Certified Six Sigma Black Belt Primer
Recurrent Events Data Analysis (Nelson)
Reliability Maintainability Availability (Locks)
Reliability Statistics (Dovich)
SAGE Cluster Analysis
SAGE Interaction Effects in Logistic Regression (Jaccard)
SAGE Logistic Regression - A Primer (Pampel)
Sampling: Design and Analysis (Lohr)
SAS for Forecasting Time Series (Brocklebank)
SAS Survival Analysis Techniques for Medical Research (Cantor)
SPC Essentials and Productivity Improvement (Levinson)
Statistical Control by Monitoring and Adjustment (Box)
Statistical Design (Casella)
Statistical Methods for Hospital Monitoring with R (Morton)
Statistical Methods for Reliability Data (Meeker)
Statistical Methods for the Social Sciences (Agresti)
Statistical Quality Control (Grant)
Statistical Rules of Thumb (van Belle)
Statistics and Finance (Ruppert)
Statistics as Principled Argument (Abelson)
Statistics for Experimenters (Box Hunter Hunter)
Survival Analysis Using SAS - A Practical Guide (Allison)
Survival Analysis Using the Proportional Hazards Model (SAS)
Testing 1-2-3 Experimental Design in Marketing and Service (Ledolter)
The Elements of Statistical Learning (Hastie Tibshirani)
The Handbook of Applied Acceptance Sampling (Stephens)
The Quality Toolbox (Tague)
The Secrets of Economic Indicators (Baumohl)
The Six Sigma Practitioner's Guide to Data Analysis (Wheeler)
The Survey Research Handbook (Alreck)
Time Series Analysis and Its Applications with R Examples (Shumway)
Time Series Analysis with Applications in R (Cryer)
Use R Applied Econometrics with R (Kleiber)
Use R Bayesian Computation with R (Albert)
Use R Data Manipulation with R (Spector)
Use R ggplot2 Elegant Graphics for Data Analysis (Wickham)
Use R Introductory Time Series with R (Cowpertwait)
Use R Lattice Multivariate Data Visualization with R (Sarkar)
Use R Six Sigma with R (Cano)
Using and Understanding Medical Statistics (Matthews)
Using R for Introductory Statistics (Verzani)
Variance Components (Searle)
Wikis For Dummies (Woods)
World Class Quality (Bhote)
World Class Reliability (Bhote)
Zero Acceptance Number Sampling Plans (Squeglia)
Fundamentals
Common Errors in Statistics
Eyeballing the Data
Distributions
Distribution Characteristics
Graphical Overview of Distributions
Relationship of Expected Value to Variance to RMS
Ethics and Statistics
Ethics ASQ
Hypothesis Testing
a-priori Hypotheses
Hypothesis - Test or Prove
Matrix Algebra
Model Assumptions
Model Assumptions for Specific Methods
Who Says that Model Assumptions Need to be Checked?
Planning the Study
Probability
Properties of Point Estimators
Purpose of Statistics
Role of Statistics in a Quality Management System
Sampling and Randomization
Example - Nonrandomized Testing Order
Example - Sampling and Randomization for DGRR
Random Number Generators
Sampling from Multicavity Molds
Sampling Topics - misc
RNG Types
Statistical Inference Basic Elements
Choosing a Statistical Test
Statistical Inference - Misc
Test Matrix
Statistical Rules of Thumb
Statistics and Consultation
Summation Math
Types of Data
Censored Data
Measurement Scales
Types of Errors
Inflating Type 1 Error
Producer and Consumer Risk
Type 1 and Type 2 Error
Types of Sampling and Inferences
Methods
Acceptance Sampling
100 Percent Screening Inspection
Acceptance Sampling Supporting Concepts
Bayesian Acceptance Sampling
Nonstandard Sampling Approaches
Variables Sampling Plans
Acceptance Sampling Common Fallacies
Lot-by-Lot Sampling by Variables
Operating Characteristic (O-C) Curve
Purpose of Acceptance Sampling
Sample Size based on Fixed Percentage
Sample Size based on Square Root of (N) plus One
ANOVA
ANCOVA
ANOVA Supporting Concepts
Factorial ANOVA
Main Effects ANOVA
Multivariate ANOVA
One-Way ANOVA
Random Effects ANOVA
Repeated Measures ANOVA
Variance Components
Contrasts
Decomposition of Total Sums of Squares
Example of Variance Partitioning
Fixed, Random, and Mixed Effects
One-Way ANOVA Example 1 (R)
One-Way ANOVA Example 1 (Statistica)
Post-hoc Tests
Tests for Equality of Variances
Types of Sums of Squares
EMS Tables
EMS Table Rules
Bayesian Methods
Data Management
Data Collection Strategies
Data Table Unstacked (Wide) vs Stacked (Long) Format
Expand Grouped Data to Individual Cases
Using VBA in MS Excel
Unstacking Data
Data Mining
Text Mining
Web Analytics
Descriptive Statistics
Bias of Sample Variance
Breakdown Analysis
Tests for Normality
Variance Interval Estimate
Anderson-Darling
Kolmogorov-Smirnov
Lillifors
Shapiro-Wilk
Design of Experiments
Box-Behnken Design
Central Composite Designs
DOE Supporting Concepts
Factorial Designs
Fractional Factorial Designs
GHTF SG3 Annex B DOE
Latin Square Designs
Mixture DOE
Nested Designs
Plackett Burman Designs
Randomized Complete Block Design
Response Optimization
Response Surface Methods
Shainin DOE
Split-Plot Designs
Block Confounding
Center Points
Circumscribed CCD
Circumscribed CCD with Block
Design Matrix and Notation
Design Principles
Face Centered CCD
Linear Contrasts
Mixed Levels Factorial Designs
Mixture DOE Example 1 ASQ (Statistica)
OFAT (One Factor at A Time)
Orthogonality
Presentation Materials for Concepts in Experimental Design Course
Process Qualification - Optimized vs. Nominal
Tables of Fractional Factorial Designs
Three-Level Factorial Designs
Two Factor Factorial Design
Two-Level Factorial Designs
Two-Level Fractional Factorial Designs
Experiment Design
Three Level Factorial Design Matrix
Treatment Design
Two Factor Factorial - Montgomery Example 5-1 (Statistica)
Two-Level Factorial Design Matrix
Two-Level Two-Factor Factorial Example 1 (Statistica)
Financial Data
Financial Data Supporting Concepts
Volatility
Graphical Methods
Graphical Method Miscellaneous
Histogram
Normal Probability Plot
Pareto Chart
Pie Chart
Scatter Plot
Adding Horizontal Line to Plot Example (Statistica)
Adding Vertical Line to Plot Example (Statistica)
IOTT
Linear Models
GLM
GLZ
Logistic Regression
Probit Regression
Probit Regression Model Example 1 (R)
Measurement System Analysis
GR&R - Attribute Data
GR&R - Censored Data
GR&R - Destructive Testing
GR&R - Modeling Approach
GR&R - Multivariate Data
GR&R - Ordinal Data
GR&R - Variables Data
Interrater Agreement
MSA FAQ from AIAG
MSA for Reliability-based Test Methods
MSA miscellaneous notes
MSA Supporting Concepts
DGR&R Example 1 Perez-Wilson (Statistica)
Example DGRR Sampling and Randomization Plan
Factors for Use in GR&R Studies
GR&R Example 1 AIAG (R)
GR&R Example 1 AIAG (Statistica)
GR&R Example 2 Barrentine (Statistica)
GR&R Example 3 ASTM F1469 (R)
GR&R Example 3 ASTM F1469 (Statistica)
GR&R Example 4 Mario Perez-Wilson (Statistica)
GR&R Modeling Approach Example 1 Mawby (Statistica)
GRR Models and EMS Tables
Interrater Agreement Example 1 (Statistica)
Interrater Agreement Example 2 (Statistica)
ROC Curves
Sensitivity and Specificity
Various Models for GR&R Studies
Visual Simulations for GR&R
Metrology
Measurement Uncertainty - EMC
Measurement Uncertainty Budget
Types of Metrology
Misc Methods
Bias-Variance Trade-off
Central Limit Theorem
Confidence Intervals
Independence of Sample Mean and StdDev
Maximum Likelihood Estimation
Order Statistics
Multivariate Methods
Canonical Correlation
Discriminant Analysis
Factor Analysis
MANOVA
Multivariate Supporting Concepts
Principal Component Analysis
Multivariate Normality
Nonparametric Methods
Chi-Squared Test
Kolmogorov-Smirnov Test for Two Populations
McNemar's Test
Nonparametric Tolerance Intervals
Odds Ratio
Rank Transform
Wilcoxon Signed Rank Test
Chi Squared Test Example 1 (R)
Chi Squared Test Example 1 (Statistica)
Chi Squared Test Example 2 (Statistica)
McNemar's Test Example 1 (R)
McNemar's Test Example 1 (SAS)
McNemar's Test Example 1 (Statistica)
Relative Risk
Simpson's Paradox
Process Analysis
Capability and Performance Indices
EPC
Guidelines for Process Capability Ratios and Risk
Precontrol
Process Analysis Supporting Concepts
SPC - Attributes Data
SPC - General Information
SPC - Multivariate Methods
SPC - Specialized Applications
SPC - Variables Data
Tolerance Intervals
ARL and ATS
c chart
Confidence Intervals for Process Capability Ratios
CUSUM chart
EWMA chart
Example - SPC on Regression Residuals
Example Create Histogram with Ppk in Title
Factors for Constructing Variables Control Charts
Hotelling's T-squared Control Chart
MOSUM
Multiple Stream Control Charts
Multivariate Cusum Contol Chart
Multivariate EWMA Control Chart
np chart
p chart
Phase 1 SPC
Phase 2 SPC
Range Estimation of Standard Deviation
Red Bead Experiment
Relationship Between SPC and DOE
Short Run SPC Methods
SPC Executive Overview
SPC Runs Rules
SPC Subgroups
Tier Chart
Tolerance Diagram
u chart
Variation and Process Adjustments
X and MR chart
X-bar and R chart
X-bar and S Chart
CUSUM Example 1 (Statistica)
p chart - OC Curve and ARL Example
p-chart Example 1 (Statistica)
p-chart Example 2 (Statistica)
X-bar and R Chart Example 1 (R)
X-bar and R Chart Example 1 (Statistica)
X-bar and S Chart Example 1 (Statistica)
Regression
Linear Regression
Logistic Regression
Model Selection Methods
Multiple Linear Regression
Nonlinear Regression
Polynomial Regression
Regression Supporting Concepts
Shelf Life - Stability Studies
Trigonometric Regression
Anscombe's Quartet
Cumulative Logit Model
Definitions of Linear
Extrapolation
Firth Penalized Likelihood
Incomplete Regression
Least Squares
Logistic Regression Example 1 (R)
Logistic Regression Example 1 (Statistica)
Logistic Regression Example 2 (Statistica)
Multicollinearity
Nonlinear Regression Example 1 (DePaul)
Nonlinear Regression Example 2 (R)
Parsimony
Polynomial Regression Example 1 (R)
Polynomial Regression Example 1 (Statistica)
Qualitative (Dummy) Variables
R-square - Coefficient of Determination
R-squared vs Adjusted R-squared
Regression - Algebra vs Calculus and Probability
Regression - Equality of Slopes Model
Regression Confidence Bands
Regression Diagnostics - Residuals
Regression Fallacy
Regression Model Heteroskedasticity
Relationship Between Regression and ANOVA
Transforms on Response Variable
Variance Stabilizing Transform
Why Logistic vs. Linear Regression
Cumulative Logit Example 1 (R)
Reliability
Degradation
Maintenance
Nonparametric Survival Analysis
One Shot Reliability (UPF)
Overview of Reliability
Parametric Reliability Analysis
Recurrent Events
Reliability Supporting Concepts
Checking for Differences between Survival Curves
Failure-Free Testing
Kaplan-Meier Survival Compare Multiple Groups Example 1 (Statistica)
Kaplan-Meier Survival Compare Two Groups Example 1 (Statistica)
Kaplan-Meier Table and Curve Example 1 (Statistica)
Verifying Arrhenius
NIST Arrhenius Example 1 (R)
Warranty Programs
Resampling and Bootstrap
Simulation
Statistical Power and Sample Size Calculation
Confidence Misunderstood
Power - Chi-Square Test
Power - Independent Samples t-test
Power - Logistic Regression
Power - Nonparametric Methods
Power - One Sample t-test
Power - One-Way ANOVA
Power - Survival Analysis
Statistical Power Guidelines
t-test
Dependent (Paired) Samples t-test
Independent Samples t-test
One Sample t-test
t-test Dependent - Example 1 (R)
t-test Dependent - Example 1 (Statistica)
t-test Independent (by Variables) - Example 1 (Statistica)
t-test Independent - Example 1 (R)
t-test One Sample - Example 1 (R)
t-test One Sample - Example 1 (Statistica)
Time Series
ARIMA
Decomposition Methods
Exponential Smoothing
Granger Causality
Intervention Model
R Functions for Time Series Analysis
Simple Moving Average
Time Series Supporting Concepts
Vector Autoregression
Adaptive Smoothing
ARIMA Diagnostic Tests
ARIMA Model Fitting Guidelines
ARIMA Polynomial Roots
Census II Decomposition
Cointegration
Decomposition - Additive and Multiplicative
Double Exponential Smoothing
Examples of Intervention Responses using R
Exponential and Damped Trends
Forecast Model Evaluation
Granger causality - Example 1 (R)
Holt-Winters' Method
Impulse Response Function
Lagged Scatter Plot - Example 1 (R)
Managing Autocorrelation
Moving Median - Example 1 (R)
Simple Exponential Smoothing
Simple Moving Average - Example 1 (R)
Testing for Autocorrelation
Unit Root
Vector Autoregression - Example 1 (R)
Year-Over-Year Approach
Adaptive Smoothing - Example 1 (R)
Census II - Example 1 (R)
Decomposition - Example 1 (R)
Double Exponential Smoothing - Example 1 (R)
Holt Winters Additive Seasonal - Example 1 (R)
Holt Winters Multiplicative Seasonal - Example 1 (R)
Managing Autocorrelation - Adding Predictors - Example 1 (R)
Managing Autocorrelation - Cochrane Orcutt - Example 1 (R)
Managing Autocorrelation - Regression with Lagged Variables - Example 1 (R)
Managing Autocorrelation - Regression with Time Series Errors - Example 1 (R)
R vs SAP APO Double Exponential Smoothing
Simple Exponential Smoothing - Example 1 (R)
Testing Autocorrelation - Example 1 (R)
Transformations
Box-Cox Transform
Reference Materials
Online References
Against All Odds Video Series (Annenberg)
NIST Engineering Statistics Handbook
ReliaSoft Reliability Engineering Resources
StatSoft Electronic Statistics Textbook
Standards
GUM (Guide to the Expression of Uncertainty in Measurement)
VIM (International Vocabulary of Metrology)
Statistical Tables
Templates
Software
.Software Validation
JMP
Microsoft Excel
Excel Tricks
Minitab
miscellaneous
AnalyticBridge - List of Free Software Packages
NIST Software
Python
QI Macros
R
Distributions in R
Instructional Videos for R
Other R
R Code
Websites Related to R
RapidMiner
Reliability Overview
ReliaSoft
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SAS Code
SPSS
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Stat-Ease webinars
StatCrunch
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Noteworthy StatSoft Blog Entries
Statistica Integration with R
StatSoft Data Mining
Version Control Systems
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u chart
General Notes
The u-chart with n = 1 is equivalent to a
c chart
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