| Your question | Representation |
| How are my measurements distributed? | Histogram |
| Are these two groups different? | Moustache Boxes + Statistical Evidence |
| Is my process stable? | Control Chart |
| Which defects should be addressed first? | Pareto |
| Are these two measures related? | XY Cloud |
| Which characteristics are related to one another? | Correlation matrix |
| Which factor has the greatest impact on my results? | Multivari |
| What sets my good pieces apart from my bad ones? | Bob vs. Wow |
| Does this measure allow us to distinguish between good and bad? | ROC Curve |
| What proportion is less than that value? | Ogive Diagram |
| Is this part atypical in all dimensions? | T² |
Data Analysis User Guide
01. General
Getting Started with the Data Analysis Module
Access the Data Analysis menu in Ellistat
Structure of the Data Analysis Module: Menus and Tables
Create and Organize a Project in Data Analysis
Share an analysis project
Data grids for a Data Analysis project
Import Your Data (Excel, CSV) into Data Analysis
Export the data
Data Types: Qualitative and Quantitative Variables
Right-click: quick access to functions
My graphics
Working from an analysis page
User creation
Messages and Special Cases
Desktop vs. Online Data Analysis: What Are the Differences?
Appendix: Vocabulary
02. Gage R&R
R&R and MSA: Validating Your Measurements
Menu
In what order should I proceed?
Accuracy of a Measurement Method: Conducting a Bias Analysis
Custom R&R calculations: ANOVA, CPC, NDC
R&R Measurement by Attributes: Evaluating a Visual Inspection
Linearity of a Measuring Device: Conducting the Study
List
R&R Gage: Which calculation standard should be used?
Comparing Two Measurement Methods: Method and Reading
Messages and Special Cases
Appendices: Definitions
03. Charts
Statistical Charts: The Data Analysis Guide
Select Your Data
Just Charts, or Statistical Evidence?
The Catalog by Family
Representing Proportions: Pareto, Pie Charts, Bar Charts
Histogram, box-and-whisker plot: representing a population
Correlation and Linear Regression: A Guide
Multi X: Multiple Factors at Once
Multi Y: Multiple Answers at Once
Which chart should you choose for which question?
Messages and Special Cases
Appendix: Key Figures
04. Descriptive Statistics
Descriptive Statistics in Data Analysis
Menu
Prepare the data
Detail
Overview
Attribute Control Charts (p, np, c, u)
Discrete Distribution Laws: Binomial, Poisson… Fitting Your Data
Continuous distributions: adjusting a distribution law
Fourier decomposition: detecting cycles
Calculator
Messages and Special Cases
Appendix: Definitions
05. Inferential Statistics
Statistical Tests in Data Analysis: The Guide
Menu
Hypothesis Testing: What a p-value Tells Us (and What It Doesn't)
Choosing a Statistical Test: Difference or Equivalence (TOST)
Performing a test based on the mean and standard deviation
Test Power and Sample Size
BoB vs. WoW: The Shewhart Method for Identifying a Cause
Component Inversion (Shainin): Finding the Culprit
Dichotomous search
Sources of Variation: Generalized ANOVA
Messages and Special Cases
Appendix
06. Multivariate Statistics
Multivariate Analysis in Data Analysis: The Guide
ACP, ACM, FAMD: Which multivariate analysis should you choose?
Prepare the baking sheet
PCA: A Step-by-Step Guide to Principal Component Analysis
Factor Analysis of Mixed Data (AFDM/FAMD)
ACM: A Step-by-Step Guide to Multiple Correspondence Analysis
Hotelling's T²: Detecting Multivariate Drift
Unsupervised Classification: Grouping Your Data
Dendrogram: Interpreting a Hierarchical Classification
Messages and Special Cases
Calculation Conventions
07. DOE: Design of Experiments
Design of Experiments in Data Analysis: The Guide
Menu
Experimental designs: factor, level, interaction, alias
Which experimental design should you choose based on your objective?
The work cycle common to all plans
2-Level Factorial Design and Taguchi Tables
Mixed-level experimental designs (XN)
Sweeping plan
Response Surface Model: Building and Analyzing
Smart DOE
Space-Filling Scheme
Plan D-Optimal: When and How to Use It?
Grid and Analysis
Messages and Special Cases
Appendix: Definition
08. ML (Machine Learning)
Machine Learning on Production Data: The Guide
Menu
Build a Machine Learning Model Using Your Data
Optimization
Bayesian Optimization
Mixture Optimization: Formulation Using a Mixture Design
Messages and Special Cases
Appendix: Definitions
09. Tolerance
Statistical Tolerance in Data Analysis – Introduction
The three menu items
Specigraph: View a specification
Monte Carlo Simulation Applied to Tolerancing
Chain of Measures: Arithmetic and Statistical Calculations
Glossary: Tolerances
10. Reliability
Reliability Analysis in Data Analysis: The Guide
Reliability Menu
Reliability: Essential Concepts (Failure Rate, MTBF)
Reliability Calculation: Method and Example
Stress-Resistance Method: Estimating Risk
Estimating Reliability Based on Lifespan Data
Tracking Warranty Returns: Analyzing Failures
Return Tracking Card
Accelerated Testing: Estimating Reliability as Quickly as Possible
Messages and Special Cases
Appendix: Definitions
Which chart should you choose for which question?
Reading time