SAS/QC(R) 9.2 User's Guide
Acknowledgments- Using This Book
- Overview
- Organization
- Typographical Conventions
- Conventions for Examples
- Accessing the SAS/QC Sample Library
- Online Documentation
- Part 1 General Information
- What's New in SAS/QC
- Components of SAS/QC Software
- Overview
- ADX Interface for Design of Experiments
- SQC Menu System for Statistical Quality Control
- Procedures for Design of Experiments
- Procedures for Control Chart Analysis
- Procedure for Process Capability Analysis
- Procedures for Basic Quality Problem Solving
- Procedure for Reliability Analysis
- Procedure for Analysis of Means
- SAS/QC Graphics
- Part 2 The ANOM Procedure
- PROC ANOM and General Statements
- BOXCHART Statement
- Overview
- Getting Started
- Creating ANOM Boxcharts from Response Values
- Creating ANOM Boxcharts from Group Summary Data
- Saving Summary Statistics for Groups
- Saving Decision Limits
- Syntax
- Details
- Constructing ANOM Boxcharts
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Axis Labels
- Missing Values
- Examples
- PCHART Statement
- Overview
- Getting Started
- Creating ANOM Charts for Proportions from Group Counts
- Creating ANOM Charts for Proportions from Group Summary Data
- Saving Group Proportions
- Saving Decision Limits
- Syntax
- Details
- Constructing ANOM Charts for Proportions
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Axis Labels
- Missing Values
- Examples
- UCHART Statement
- Overview
- Getting Started
- Syntax
- Details
- Constructing ANOM Charts for Rates
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Axis Labels
- Missing Values
- Examples
- XCHART Statement
- Overview
- Getting Started
- Creating ANOM Charts for Means from Response Values
- Creating ANOM Charts for Means from Group Summary Data
- Saving Summary Statistics for Groups
- Saving Decision Limits
- Syntax
- Details
- Constructing ANOM Charts for Means
- Constructing ANOM Charts for Two-Way Layouts
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Axis Labels
- Missing Values
- Examples
- INSET Statement
- Overview
- Getting Started
- Displaying Summary Statistics on an ANOM Chart
- Formatting Values and Customizing Labels
- Adding a Header and Positioning the Inset
- Syntax
- Details
- References
- Part 3 The CAPABILITY Procedure
- Introduction
- PROC CAPABILITY and General Statements
- Overview
- Getting Started
- Syntax Overview for the CAPABILITY Procedure
- Syntax for the PROC CAPABILITY Statement
- Syntax for the CLASS Statement
- Syntax for the SPEC Statement
- Details
- Input Data Sets
- Output Data Set
- Descriptive Statistics
- Signed Rank Statistic
- Tests for Normality
- Percentile Computations
- Robust Estimators
- Computing the Mode
- Assumptions and Terminology for Capability Indices
- Standard Capability Indices
- Specialized Capability Indices
- Missing Values
- ODS Tables
- Examples
- CDFPLOT Statement
- COMPHISTOGRAM Statement
- HISTOGRAM Statement
- Overview
- Getting Started
- Creating a Histogram with Specification Limits
- Adding a Normal Curve to the Histogram
- Customizing a Histogram
- Syntax
- Details
- Formulas for Fitted Curves
- Kernel Density Estimates
- Printed Output
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- SYMBOL and PATTERN Statement Options
- Examples
- Example 13.1: Fitting a Beta Curve
- Example 13.2: Fitting Lognormal, Weibull, and Gamma Curves
- Example 13.3: Comparing Goodness-of-Fit Tests
- Example 13.4: Computing Capability Indices for Nonnormal Distributions
- Example 13.5: Computing Kernel Density Estimates
- Example 13.6: Fitting a Three-Parameter Lognormal Curve
- Example 13.7: Annotating a Folded Normal Curve
- INSET Statement
- Overview
- Getting Started
- Displaying Summary Statistics on a Histogram
- Formatting Values and Customizing Labels
- Adding a Header and Positioning the Inset
- Syntax
- Details
- Positioning the Inset Using Compass Points
- Positioning the Inset in the Margins
- Positioning the Inset Using Coordinates
- Examples
- INTERVALS Statement
- OUTPUT Statement
- PPPLOT Statement
- PROBPLOT Statement
- QQPLOT Statement
- Overview
- Getting Started
- Syntax
- Details
- Construction of Quantile-Quantile and Probability Plots
- Interpretation of Quantile-Quantile and Probability Plots
- Summary of Theoretical Distributions
- Graphical Estimation
- SYMBOL Statement Options
- ODS Graphics - Experimental
- Examples
- Dictionary of Common Options
- References
- Part 4 The CUSUM Procedure
- Introduction
- PROC CUSUM Statement
- XCHART Statement
- Overview
- Getting Started
- Creating a V-Mask Cusum Chart from Raw Data
- Creating a V-Mask Cusum Chart from Subgroup Summary Data
- Saving Summary Statistics
- Creating a One-Sided Cusum Chart with a Decision Interval
- Saving Cusum Scheme Parameters
- Reading Cusum Scheme Parameters
- Syntax
- Details
- Basic Notation for Cusum Charts
- Formulas for Cumulative Sums
- Defining the Decision Interval for a One-Sided Cusum Scheme
- Defining the V-Mask for a Two-Sided Cusum Scheme
- Designing a Cusum Scheme
- Cusum Charts Compared with Shewhart Charts
- Methods for Estimating the Standard Deviation
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Missing Values
- Examples
- INSET Statement
- References
- Part 5 The FACTEX Procedure
- Introduction to the FACTEX Procedure
- Details of the FACTEX Procedure
- Syntax
- Statement Descriptions
- PROC FACTEX Statement
- BLOCKS Statement
- UNITEFFECTS Statement
- EXAMINE Statement
- FACTORS Statement
- MODEL Statement
- OUTPUT Statement
- SIZE Statement
- Advanced Examples
- Example 25.1: Completely Randomized Design
- Example 25.2: Resolution IV Augmented Design
- Example 25.3: Factorial Design with Center Points
- Example 25.4: Fold-Over Design
- Example 25.5: Randomized Complete Block Design
- Example 25.6: Two-Level Design with Design Replication and Point Replication
- Example 25.7: Mixed-Level Design Using Design Replication and Point Replication
- Example 25.8: Mixed-Level Design Using Pseudo-factors
- Example 25.9: Mixed-Level Design by Collapsing Factors
- Example 25.10: Hyper-Graeco-Latin Square Design
- Example 25.11: Resolution IV Design with Minimum Aberration
- Example 25.12: Replicated Blocked Design with Partial Confounding
- Example 25.13: Incomplete Block Design
- Example 25.14: Design with Inner Array and Outer Array
- Example 25.15: Fractional Factorial Split-Plot Designs
- Example 25.16: Design and Analysis of a Complete Factorial Experiment
- Computational Details
- Types of Factors
- Specifying Effects in the MODEL Statement
- Factor Variable Characteristics in the Output Data Set
- Statistical Details
- Resolution
- Randomization
- Replication
- Confounding Rules
- Alias Structure
- Minimum Aberration
- Split-Plot Designs
- Output
- ODS Tables
- Theory of Orthogonal Designs
- Overview
- Structure of General Factorial Designs
- Suitable Confounding Rules
- Searching for Confounding Rules
- Speeding Up the Search
- General Recommendations
- References
- Part 6 The ISHIKAWA Procedure
- Introduction to the ISHIKAWA Environment
- Details of the ISHIKAWA Environment
- Summary of Operations
- Operations
- Adding Arrows
- Labeling Arrows
- Moving Arrows
- Deleting Arrows
- Resizing Arrows
- Swapping Arrows
- Balancing Arrows
- Notepads
- Managing Complexity
- Zooming Arrows
- Isolating Arrows
- Merging Diagrams
- Creating Graphics Output Using SAS/GRAPH Software
- Creating Bitmap Graphics Output
- Modifying Fonts
- Modifying Box Colors
- Modifying Arrow Colors and Line Styles
- Modifying Text Colors
- Modifying Arrow Heads
- Modifying Environmental Attributes
- Saving an Ishikawa Diagram for Future Editing
- Reading an Existing Ishikawa Diagram
- Displaying Multiple Ishikawa Diagrams
- Input and Output Data Sets
- Syntax
- Examples
- References
- Part 7 The MACONTROL Procedure
- Introduction
- PROC MACONTROL Statement
- EWMACHART Statement
- Overview
- Getting Started
- Creating EWMA Charts from Raw Data
- Creating EWMA Charts from Subgroup Summary Data
- Saving Summary Statistics
- Saving Control Limit Parameters
- Reading Preestablished Control Limit Parameters
- Syntax
- Details
- Constructing EWMA Charts
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Methods for Estimating the Standard Deviation
- Axis Labels
- Missing Values
- Examples
- Example 30.1: Specifying Standard Values for the Process Mean and Process Standard Deviation
- Example 30.2: Displaying Limits Based on Asymptotic Values
- Example 30.3: Working with Unequal Subgroup Sample Sizes
- Example 30.4: Displaying Individual Measurements on an EWMA Chart
- Example 30.5: Computing Average Run Lengths
- MACHART Statement
- Overview
- Getting Started
- Creating Moving Average Charts from Raw Data
- Creating Moving Average Charts from Subgroup Summary Data
- Saving Summary Statistics
- Saving Control Limit Parameters
- Reading Preestablished Control Limit Parameters
- Syntax
- Details
- Constructing Uniformly Weighted Moving Average Charts
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Methods for Estimating the Standard Deviation
- Axis Labels
- Missing Values
- Examples
- INSET Statement
- References
- Part 8 The OPTEX Procedure
- Introduction to the OPTEX Procedure
- Details of the OPTEX Procedure
- Syntax
- Statement Descriptions
- PROC OPTEX Statement
- BLOCKS Statement
- CLASS Statement
- EXAMINE Statement
- GENERATE Statement
- ID Statement
- MODEL Statement
- OUTPUT Statement
- Advanced Examples
- Example 34.1: Nonstandard Linear Model
- Example 34.2: Comparing Fedorov Algorithm to Sequential Algorithm
- Example 34.3: Using an Initial Design to Search an Optimal Design
- Example 34.4: Optimal Design Using an Augmented Best Design
- Example 34.5: Optimal Design Using a Small Candidate Set
- Example 34.6: Bayesian Optimal Design
- Example 34.7: Balanced Incomplete Block Design
- Example 34.8: Optimal Design with Fixed Covariates
- Example 34.9: Optimal Design in the Presence of Covariance
- Example 34.10: Adding Space-Filling Points to a Design
- Data Details
- Computational Details
- References
- Part 9 The PARETO Procedure
- Introduction
- PROC PARETO Statement
- VBAR Statement
- Overview
- Getting Started
- Creating a Pareto Chart from Raw Data
- Creating a Pareto Chart Using Frequency Data
- Restricting the Number of Pareto Categories
- Syntax
- HBAR Statement
- Overview
- Getting Started
- Creating a Pareto Chart from Raw Data
- Creating a Pareto Chart Using Frequency Data
- Restricting the Number of Pareto Categories
- Syntax
- INSET Statement
- Overview
- Getting Started
- Displaying Summary Statistics on a Pareto Chart
- Customizing Labels and Formatting Values
- Adding a Header and Positioning the Inset
- Syntax
- Details
- Details and Examples
- Details
- Terminology
- Labels for Chart Features
- Scaling the Cumulative Percent Curve
- Output Data Sets
- ODS Graphics - Experimental
- Constructing Effective Pareto Charts
- Missing Values
- Role of Variable Formats
- Large Data Sets
- Examples
- Example 39.1: Creating Before-and-After Pareto Charts
- Example 39.2: Creating Two-Way Comparative Pareto Charts
- Example 39.3: Highlighting the ``Vital Few''
- Example 39.4: Highlighting Combinations of Categories
- Example 39.5: Highlighting Combinations of Cells
- Example 39.6: Ordering Rows and Columns in a Comparative Pareto Chart
- Example 39.7: Merging Columns in a Comparative Pareto Chart
- Example 39.8: Creating Weighted Pareto Charts
- References
- Part 10 The RELIABILITY Procedure
- The RELIABILITY Procedure
- Overview
- Getting Started
- Analysis of Right-Censored Data from a Single Population
- Weibull Analysis Comparing Groups of Data
- Analysis of Accelerated Life Test Data
- Weibull Analysis of Interval Data with Common Inspection Schedule
- Lognormal Analysis with Arbitrary Censoring
- Regression Modeling
- Regression Model with Nonconstant Scale
- Regression Model with Two Independent Variables
- Weibull Probability Plot for Two Combined Failure Modes
- Analysis of Recurrence Data on Repairs
- Comparison of Two Samples of Repair Data
- Analysis of Interval Age Recurrence Data
- Analysis of Binomial Data
- Syntax
- Primary Statements
- Secondary Statements
- Graphical Enhancement Statements
- PROC RELIABILITY Statement
- ANALYZE Statement
- BY Statement
- CLASS Statement
- DISTRIBUTION Statement
- FMODE Statement
- FREQ Statement
- INSET Statement
- LOGSCALE Statement
- MAKE Statement
- MCFPLOT Statement
- MODEL Statement
- NENTER Statement
- PROBPLOT Statement
- RELATIONPLOT Statement
- UNITID Statement
- Details
- Abbreviations and Notation
- Types of Lifetime Data
- Probability Distributions
- Probability Plotting
- Nonparametric Confidence Intervals for Cumulative Failure Probabilities
- Parameter Estimation and Confidence Intervals
- Regression Model Observation-wise Statistics
- Recurrence Data from Repairable Systems
- ODS Table Names
- ODS Graph Names - Experimental
- References
- Part 11 The SHEWHART Procedure
- Introduction
- Uses of Shewhart Charts
- Characteristics of Shewhart Charts
- Classification of Shewhart Charts
- Learning to Use the SHEWHART Procedure
- PROC SHEWHART and General Statements
- Overview
- Syntax Overview for the SHEWHART Procedure
- Syntax for the PROC SHEWHART Statement
- Input and Output Data Sets
- BOXCHART Statement
- Overview
- Getting Started
- Creating Box Charts from Raw Data
- Creating Box Charts from Subgroup Summary Data
- Saving Summary Statistics
- Saving Control Limits
- Reading Preestablished Control Limits
- Syntax
- Details
- Constructing Box Charts
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Methods for Estimating the Standard Deviation
- Percentile Definitions
- Axis Labels
- Missing Values
- Examples
- Example 42.1: Using Box Charts to Compare Subgroups
- Example 42.2: Creating Various Styles of Box-and-Whisker Plots
- Example 42.3: Creating Notched Box-and-Whisker Plots
- Example 42.4: Creating Box-and-Whisker Plots with Varying Widths
- Example 42.5: Creating Box-and-Whisker Plots with Different Line Styles and Colors
- Example 42.6: Computing the Control Limits for Subgroup Maximums
- Example 42.7: Constructing Multi-Vari Charts
- CCHART Statement
- Overview
- Getting Started
- Creating c Charts from Defect Count Data
- Saving Control Limits
- Reading Preestablished Control Limits
- Creating c Charts from Nonconformities per Unit
- Saving Nonconformities per Unit
- Syntax
- Details
- Constructing Charts for Numbers of Nonconformities (c Charts)
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Axis Labels
- Missing Values
- Examples
- IRCHART Statement
- Overview
- Getting Started
- Creating Individual Measurements and Moving Range Charts
- Saving Individual Measurements and Moving Ranges
- Reading Individual Measurements and Moving Ranges
- Saving Control Limits
- Reading Preestablished Control Limits
- Specifying the Computation of the Moving Range
- Syntax
- Details
- Constructing Charts for Individual Measurements and Moving Ranges
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Methods for Estimating the Standard Deviation
- Interpreting Charts for Individual Measurements and Moving Ranges
- Axis Labels
- Missing Values
- Examples
- MCHART Statement
- Overview
- Getting Started
- Creating Charts for Medians from Raw Data
- Creating Charts for Medians from Subgroup Summary Data
- Saving Summary Statistics
- Saving Control Limits
- Reading Preestablished Control Limits
- Syntax
- Details
- Constructing Median Charts
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Methods for Estimating the Standard Deviation
- Axis Labels
- Missing Values
- Examples
- MRCHART Statement
- Overview
- Getting Started
- Creating Charts for Medians and Ranges from Raw Data
- Creating Charts for Medians and Ranges from Summary Data
- Saving Summary Statistics
- Saving Control Limits
- Reading Preestablished Control Limits
- Syntax
- Details
- Constructing Charts for Medians and Ranges
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Methods for Estimating the Standard Deviation
- Axis Labels
- Missing Values
- Examples
- NPCHART Statement
- Overview
- Getting Started
- Creating np Charts from Count Data
- Creating np Charts from Summary Data
- Saving Proportions of Nonconforming Items
- Saving Control Limits
- Reading Preestablished Control Limits
- Syntax
- Details
- Constructing Charts for Number Nonconforming (np Charts)
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Axis Labels
- Missing Values
- Examples
- PCHART Statement
- Overview
- Getting Started
- Creating p Charts from Count Data
- Creating p Charts from Summary Data
- Saving Proportions of Nonconforming Items
- Saving Control Limits
- Reading Preestablished Control Limits
- Syntax
- Details
- Constructing Charts for Proportion Nonconforming (p Charts)
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Axis Labels
- Missing Values
- Examples
- RCHART Statement
- Overview
- Getting Started
- Creating Range Charts from Raw Data
- Creating Range Charts from Summary Data
- Saving Summary Statistics
- Saving Control Limits
- Reading Preestablished Control Limits
- Syntax
- Details
- Constructing Range Charts
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Methods for Estimating the Standard Deviation
- Axis Labels
- Missing Values
- Examples
- SCHART Statement
- Overview
- Getting Started
- Creating Standard Deviation Charts from Raw Data
- Creating Standard Deviation Charts from Subgroup Summary Data
- Saving Summary Statistics
- Saving Control Limits
- Reading Preestablished Control Limits
- Syntax
- Details
- Constructing Charts for Standard Deviations
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Methods for Estimating the Standard Deviation
- Axis Labels
- Missing Values
- Examples
- UCHART Statement
- Overview
- Getting Started
- Creating u Charts from Defect Count Data
- Saving Control Limits
- Reading Preestablished Control Limits
- Creating u Charts from Nonconformities per Unit
- Saving Nonconformities per Unit
- Syntax
- Details
- Constructing Charts for Nonconformities per Unit (u Charts)
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Axis Labels
- Missing Values
- Examples
- XCHART Statement
- Overview
- Getting Started
- Creating Charts for Means from Raw Data
- Creating Charts for Means from Subgroup Summary Data
- Saving Summary Statistics
- Saving Control Limits
- Reading Preestablished Control Limits
- Syntax
- Details
- Constructing Charts for Means
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Methods for Estimating the Standard Deviation
- Axis Labels
- Missing Values
- Examples
- XRCHART Statement
- Overview
- Getting Started
- Creating Charts for Means and Ranges from Raw Data
- Creating Charts for Means and Ranges from Summary Data
- Saving Summary Statistics
- Saving Control Limits
- Reading Preestablished Control Limits
- Syntax
- Details
- Constructing Charts for Means and Ranges
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Subgroup Variables
- Methods for Estimating the Standard Deviation
- Capability Indices
- Axis Labels
- Missing Values
- Examples
- XSCHART Statement
- Overview
- Getting Started
- Creating Charts for Means and Standard Deviations from Raw Data
- Creating Charts for Means and Standard Deviations from Summary Data
- Saving Summary Statistics
- Saving Control Limits
- Reading Preestablished Control Limits
- Syntax
- Details
- Constructing Charts for Means and Standard Deviations
- Output Data Sets
- ODS Tables
- ODS Graphics - Experimental
- Input Data Sets
- Methods for Estimating the Standard Deviation
- Axis Labels
- Missing Values
- Examples
- INSET and INSET2 Statements
- Overview
- Getting Started
- Displaying Summary Statistics on a Control Chart
- Formatting Values and Customizing Labels
- Adding a Header and Positioning the Inset
- Syntax
- Details
- Dictionary of Options
- Graphical Enhancements
- Overview
- Displaying Stratified Process Data
- Displaying Stratification in Levels of a Classification Variable
- Displaying Stratification in Blocks of Observations
- Displaying Stratification in Phases
- Displaying Multiple Sets of Control Limits
- Displaying Auxiliary Data with Stars
- Creating a Basic Star Chart
- Adding Reference Circles to Stars
- Specifying the Style of Stars
- Specifying the Method of Standardization
- Displaying Trends in Process Data
- Step 1: Preliminary Mean and Standard Deviation Charts
- Step 2: Modeling the Trend
- Step 3: Displaying the Trend Chart
- Clipping Extreme Points
- Labeling Axes
- Selecting Subgroups for Computation and Display
- Tests for Special Causes
- Standard Tests for Special Causes
- Requesting Standard Tests
- Interpreting Standard Tests for Special Causes
- Modifying Standard Tests for Special Causes
- Applying Tests with Varying Subgroup Sample Sizes
- Labeling Signaled Points with a Variable
- Applying Tests with Multiple Phases
- Applying Tests with Multiple Sets of Control Limits
- Enhancing the Display of Signaled Tests
- Nonstandard Tests for Special Causes
- Specialized Control Charts
- Overview
- Autocorrelation in Process Data
- Multiple Components of Variation
- Short Run Process Control
- Analyzing the Difference from Nominal
- Testing for Constant Variances
- Standardizing Differences from Nominal
- Nonnormal Process Data
- Multivariate Control Charts
- Interactive Control Charts
- References
- Part 12 Appendices
- The GAGE Application
- Introduction
- Getting Started
- Invoking the GAGE Application
- Entering Data
- Performing a Range Chart Analysis
- Performing an Average Chart Analysis
- Selecting a Statistical Method
- Performing an Average and Range Analysis
- Performing a Variance Components Analysis
- Saving the Data
- Entering Another Set of Data
- Reading Data from a Data Set
- Details
- The RELIABILITY Graphical Interface
- Functions
- Introduction
- Function Descriptions
- AOQ2 Function
- ASN2 Function
- ATI2 Function
- BAYESACT Call
- C4 Function
- CUSUMARL Function
- D2 Function
- D3 Function
- EWMAARL Function
- PROBACC2 Function
- PROBBNML Function
- PROBHYPR Function
- PROBMED Function
- STDMED Function
- Details
- Special Fonts in SAS/QC Software
- References
Index here
| Product | Release |
|---|---|
| SAS/QC | 9.2 |
- Type
- Usage and Reference
- Copyright Date
- March 2008
- Last Updated
- 28Feb2009
| PROC ANOM and General Statements |
Overview
Analysis of means (ANOM) is a graphical and statistical method for
simultaneously comparing 
treatment means with their overall mean
at a specified significance level 
. You can use the ANOM
procedure to create ANOM charts for various types of response data,
including continuous measurements, proportions, and rates.
In addition, you can use the ANOM procedure to do the following:
- create charts from either response values or summarized data
- analyze multiple response variables
- specify decision limits in terms of the significance level ()
- compute decision limits from the data and automatically adjust decision limits for unequal sample sizes
- save chart statistics and decision limits in output data sets
- tabulate chart statistics and decision limits.
See Chapter 3, "SAS/QC Graphics," for a detailed discussion of the alternatives available for producing charts with SAS/QC procedures.
Uses of Analysis of Means
Terminology
History
Using the ANOM Procedure
Copyright © 2008 by SAS Institute Inc., Cary, NC, USA. All rights reserved.