**The ANOM Procedure**PDF | HTML

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.**The CAPABILITY Procedure**PDF | HTML

A process capability analysis compares the distribution of output from an in-control process to its specification limits to determine the consistency with which the specifications can be met..**The CUSUM Procedure**PDF | HTML

Creates cumulative sum control charts, also known as cusum charts, which display cumulative sums of the deviations of measurements or subgroup means from a target value. Cusum charts are used to decide whether a process is in statistical control by detecting a shift in the process mean.**The FACTEX Procedure**PDF | HTML

Constructs orthogonal factorial experimental designs. These designs can be either full or fractional factorial designs, and they can be with or without blocks. You can also construct designs for experiments with multiple stages, such as split-plot and split-lot designs. After you have constructed a design by using the FACTEX procedure and run the experiment, you can analyze the results with a variety of SAS procedures including the GLM and REG procedures.**The ISHIKAWA Procedure**PDF | HTML

The Ishikawa diagram, also known as a cause-and-effect diagram or fishbone diagram, is one of the seven basic tools for quality improvement in Japanese industry. It is used to display the factors that affect a particular quality characteristic or problem.**The MACONTROL Procedure**PDF | HTML

Creates moving average control charts, which are tools for deciding whether a process is in a state of statistical control and for detecting shifts in a process average..**The MVPDIAGNOSE Procedure**PDF | HTML

Used in conjunction with the MVPMODEL and MVPMONITOR procedures to monitor multivariate process variation over time, to determine whether the process is stable, and to detect and diagnose changes in a stable process.**The MVPMODEL Procedure**PDF | HTML

Used in conjunction with the MVPMONITOR and MVPDIAGNOSE procedures to monitor multivariate process variation over time in order to determine whether the process is stable or to detect changes in a stable process.**The MVPMONITOR Procedure**PDF | HTML

Used in conjunction with the MVPMODEL and MVPDIAGNOSE procedures to monitor multivariate process variation over time in order to determine whether the process is stable or to detect and diagnose changes in a stable process.**The OPTEX Procedure**PDF | HTML

Searches for optimal experimental designs. You specify a set of candidate design points and a linear model, and the procedure chooses points so that the terms in the model can be estimated as efficiently as possible.**The PARETO Procedure**PDF | HTML

Creates Pareto charts, which display the relative frequency of quality-related problems in a process or operation. The frequencies are represented by bars that are ordered in decreasing magnitude. Thus, a Pareto chart can be used to decide which subset of problems should be solved first or which problem areas deserve the most attention.**The RAREEVENTS Procedure**PDF | HTML

Produces control charts for rare events.**The RELIABILITY Procedure**PDF | HTML

Provides tools for reliability and survival data analysis and for recurrent events data analysis.**The SHEWHART Procedure**PDF | HTML

A graphical and analytical tool for deciding whether a process is in a state of statistical control. You can use the SHEWHART procedure to display many different types of control charts, including all commonly used charts for variables and attributes.

**The ANOM Procedure**

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.

PDF | HTML**The CAPABILITY Procedure**

A process capability analysis compares the distribution of output from an in-control process to its specification limits to determine the consistency with which the specifications can be met.

PDF | HTML**The CUSUM Procedure**

Creates cumulative sum control charts, also known as cusum charts, which display cumulative sums of the deviations of measurements or subgroup means from a target value. Cusum charts are used to decide whether a process is in statistical control by detecting a shift in the process mean.

PDF | HTML**The FACTEX Procedure**

Constructs orthogonal factorial experimental designs. These designs can be either full or fractional factorial designs, and they can be with or without blocks. You can also construct designs for experiments with multiple stages, such as split-plot and split-lot designs. After you have constructed a design by using the FACTEX procedure and run the experiment, you can analyze the results with a variety of SAS procedures including the GLM and REG procedures.

PDF | HTML**The ISHIKAWA Procedure**

The Ishikawa diagram, also known as a cause-and-effect diagram or fishbone diagram, is one of the seven basic tools for quality improvement in Japanese industry. It is used to display the factors that affect a particular quality characteristic or problem.

PDF | HTML**The MACONTROL Procedure**

Creates moving average control charts, which are tools for deciding whether a process is in a state of statistical control and for detecting shifts in a process average.

PDF | HTML**The MVPDIAGNOSE Procedure**

Used in conjunction with the MVPMODEL and MVPMONITOR procedures to monitor multivariate process variation over time, to determine whether the process is stable, and to detect and diagnose changes in a stable process.

PDF | HTML**The MVPMODEL Procedure**

Used in conjunction with the MVPMONITOR and MVPDIAGNOSE procedures to monitor multivariate process variation over time in order to determine whether the process is stable or to detect changes in a stable process.

PDF | HTML**The MVPMONITOR Procedure**

Used in conjunction with the MVPMODEL and MVPDIAGNOSE procedures to monitor multivariate process variation over time in order to determine whether the process is stable or to detect and diagnose changes in a stable process.

PDF | HTML**The OPTEX Procedure**

Searches for optimal experimental designs. You specify a set of candidate design points and a linear model, and the procedure chooses points so that the terms in the model can be estimated as efficiently as possible.

PDF | HTML**The PARETO Procedure**

Creates Pareto charts, which display the relative frequency of quality-related problems in a process or operation. The frequencies are represented by bars that are ordered in decreasing magnitude. Thus, a Pareto chart can be used to decide which subset of problems should be solved first or which problem areas deserve the most attention.

PDF | HTML**The RAREEVENTS Procedure**

Produces control charts for rare events.

PDF | HTML**The RELIABILITY Procedure**

Provides tools for reliability and survival data analysis and for recurrent events data analysis.

PDF | HTML**The SHEWHART Procedure**

A graphical and analytical tool for deciding whether a process is in a state of statistical control. You can use the SHEWHART procedure to display many different types of control charts, including all commonly used charts for variables and attributes.

PDF | HTML

**The ANOM Procedure**

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.

PDF | HTML**The CAPABILITY Procedure**

A process capability analysis compares the distribution of output from an in-control process to its specification limits to determine the consistency with which the specifications can be met.

PDF | HTML**The CUSUM Procedure**

Creates cumulative sum control charts, also known as cusum charts, which display cumulative sums of the deviations of measurements or subgroup means from a target value. Cusum charts are used to decide whether a process is in statistical control by detecting a shift in the process mean.

PDF | HTML**The FACTEX Procedure**

Constructs orthogonal factorial experimental designs. These designs can be either full or fractional factorial designs, and they can be with or without blocks. You can also construct designs for experiments with multiple stages, such as split-plot and split-lot designs. After you have constructed a design by using the FACTEX procedure and run the experiment, you can analyze the results with a variety of SAS procedures including the GLM and REG procedures.

PDF | HTML**The ISHIKAWA Procedure**

The Ishikawa diagram, also known as a cause-and-effect diagram or fishbone diagram, is one of the seven basic tools for quality improvement in Japanese industry. It is used to display the factors that affect a particular quality characteristic or problem.

PDF | HTML**The MACONTROL Procedure**

Creates moving average control charts, which are tools for deciding whether a process is in a state of statistical control and for detecting shifts in a process average.

PDF | HTML**The MVPDIAGNOSE Procedure**

Used in conjunction with the MVPMODEL and MVPMONITOR procedures to monitor multivariate process variation over time, to determine whether the process is stable, and to detect and diagnose changes in a stable process.

PDF | HTML**The MVPMODEL Procedure**

Used in conjunction with the MVPMONITOR and MVPDIAGNOSE procedures to monitor multivariate process variation over time in order to determine whether the process is stable or to detect changes in a stable process.

PDF | HTML**The MVPMONITOR Procedure**

Used in conjunction with the MVPMODEL and MVPDIAGNOSE procedures to monitor multivariate process variation over time in order to determine whether the process is stable or to detect and diagnose changes in a stable process.

PDF | HTML**The OPTEX Procedure**

Searches for optimal experimental designs. You specify a set of candidate design points and a linear model, and the procedure chooses points so that the terms in the model can be estimated as efficiently as possible.

PDF | HTML**The PARETO Procedure**

Creates Pareto charts, which display the relative frequency of quality-related problems in a process or operation. The frequencies are represented by bars that are ordered in decreasing magnitude. Thus, a Pareto chart can be used to decide which subset of problems should be solved first or which problem areas deserve the most attention.

PDF | HTML**The RAREEVENTS Procedure (Experimental)**

Produces control charts for rare events.

PDF | HTML**The RELIABILITY Procedure**

Provides tools for reliability and survival data analysis and for recurrent events data analysis.

PDF | HTML**The SHEWHART Procedure**

A graphical and analytical tool for deciding whether a process is in a state of statistical control. You can use the SHEWHART procedure to display many different types of control charts, including all commonly used charts for variables and attributes.

PDF | HTML

**The ANOM Procedure**

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.

PDF (4.69MB) | HTML**The CAPABILITY Procedure**

A process capability analysis compares the distribution of output from an in-control process to its specification limits to determine the consistency with which the specifications can be met.

PDF (9.79MB) | HTML**The CUSUM Procedure**

Creates cumulative sum control charts, also known as cusum charts, which display cumulative sums of the deviations of measurements or subgroup means from a target value. Cusum charts are used to decide whether a process is in statistical control by detecting a shift in the process mean.

PDF (2.99MB) | HTML**The FACTEX Procedure**

Constructs orthogonal factorial experimental designs. These designs can be either full or fractional factorial designs, and they can be with or without blocks. You can also construct designs for experiments with multiple stages, such as split-plot and split-lot designs. After you have constructed a design by using the FACTEX procedure and run the experiment, you can analyze the results with a variety of SAS procedures including the GLM and REG procedures.

PDF (5.6MB) | HTML**The ISHIKAWA Procedure**

The Ishikawa diagram, also known as a cause-and-effect diagram or fishbone diagram, is one of the seven basic tools for quality improvement in Japanese industry. It is used to display the factors that affect a particular quality characteristic or problem.

PDF (3.11MB) | HTML**The MACONTROL Procedure**

Creates moving average control charts, which are tools for deciding whether a process is in a state of statistical control and for detecting shifts in a process average.

PDF (4.02MB) | HTML**The MVPDIAGNOSE Procedure**

Used in conjunction with the MVPMODEL and MVPMONITOR procedures to monitor multivariate process variation over time, to determine whether the process is stable, and to detect and diagnose changes in a stable process.

PDF (2.54MB) | HTML**The MVPMODEL Procedure**

Used in conjunction with the MVPMONITOR and MVPDIAGNOSE procedures to monitor multivariate process variation over time in order to determine whether the process is stable or to detect changes in a stable process.

PDF (3.29MB) | HTML**The MVPMONITOR Procedure**

Used in conjunction with the MVPMODEL and MVPDIAGNOSE procedures to monitor multivariate process variation over time in order to determine whether the process is stable or to detect and diagnose changes in a stable process.

PDF (3.82MB) | HTML**The OPTEX Procedure**

Searches for optimal experimental designs. You specify a set of candidate design points and a linear model, and the procedure chooses points so that the terms in the model can be estimated as efficiently as possible.

PDF (4.51MB) | HTML**The PARETO Procedure**

Creates Pareto charts, which display the relative frequency of quality-related problems in a process or operation. The frequencies are represented by bars that are ordered in decreasing magnitude. Thus, a Pareto chart can be used to decide which subset of problems should be solved first or which problem areas deserve the most attention.

PDF (3.33MB) | HTML**The RELIABILITY Procedure**

Provides tools for reliability and survival data analysis and for recurrent events data analysis.

PDF (10.7MB) | HTML**The SHEWHART Procedure**

A graphical and analytical tool for deciding whether a process is in a state of statistical control. You can use the SHEWHART procedure to display many different types of control charts, including all commonly used charts for variables and attributes.

PDF (17.2MB) | HTML

**The ANOM Procedure**

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. [HTML]**The CAPABILITY Procedure**

A process capability analysis compares the distribution of output from an in-control process to its specification limits to determine the consistency with which the specifications can be met. [HTML]**The CUSUM Procedure**

Creates cumulative sum control charts, also known as cusum charts, which display cumulative sums of the deviations of measurements or subgroup means from a target value. Cusum charts are used to decide whether a process is in statistical control by detecting a shift in the process mean. [HTML]**The FACTEX Procedure**

Constructs orthogonal factorial experimental designs. These designs can be either full or fractional factorial designs, and they can be with or without blocks. You can also construct designs for experiments with multiple stages, such as split-plot and split-lot designs. After you have constructed a design by using the FACTEX procedure and run the experiment, you can analyze the results with a variety of SAS procedures including the GLM and REG procedures. [HTML]**The ISHIKAWA Procedure**

The Ishikawa diagram, also known as a cause-and-effect diagram or fishbone diagram, is one of the seven basic tools for quality improvement in Japanese industry. It is used to display the factors that affect a particular quality characteristic or problem. [HTML]**The MACONTROL Procedure**

Creates moving average control charts, which are tools for deciding whether a process is in a state of statistical control and for detecting shifts in a process average. [HTML]**The MVPDIAGNOSE Procedure**

Used in conjunction with the MVPMODEL and MVPMONITOR procedures to monitor multivariate process variation over time, to determine whether the process is stable, and to detect and diagnose changes in a stable process. [HTML]**The MVPMODEL Procedure**

Used in conjunction with the MVPMONITOR and MVPDIAGNOSE procedures to monitor multivariate process variation over time in order to determine whether the process is stable or to detect changes in a stable process. [HTML]**The MVPMONITOR Procedure**

Used in conjunction with the MVPMODEL and MVPDIAGNOSE procedures to monitor multivariate process variation over time in order to determine whether the process is stable or to detect and diagnose changes in a stable process. [HTML]**The OPTEX Procedure**

Searches for optimal experimental designs. You specify a set of candidate design points and a linear model, and the procedure chooses points so that the terms in the model can be estimated as efficiently as possible. [HTML]**The PARETO Procedure**

Creates Pareto charts, which display the relative frequency of quality-related problems in a process or operation. The frequencies are represented by bars that are ordered in decreasing magnitude. Thus, a Pareto chart can be used to decide which subset of problems should be solved first or which problem areas deserve the most attention. [HTML]**The RELIABILITY Procedure**

Provides tools for reliability and survival data analysis and for recurrent events data analysis. [HTML]**The SHEWHART Procedure**

A graphical and analytical tool for deciding whether a process is in a state of statistical control. You can use the SHEWHART procedure to display many different types of control charts, including all commonly used charts for variables and attributes. [HTML]

For the complete

**The ANOM Procedure**

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. [HTML]**The CAPABILITY Procedure**

A process capability analysis compares the distribution of output from an in-control process to its specification limits to determine the consistency with which the specifications can be met. [HTML]**The CUSUM Procedure**

Creates cumulative sum control charts, also known as cusum charts, which display cumulative sums of the deviations of measurements or subgroup means from a target value. Cusum charts are used to decide whether a process is in statistical control by detecting a shift in the process mean. [HTML]**The FACTEX Procedure**

Constructs orthogonal factorial experimental designs. These designs can be either full or fractional factorial designs, and they can be with or without blocks. You can also construct designs for experiments with multiple stages, such as split-plot and split-lot designs. After you have constructed a design by using the FACTEX procedure and run the experiment, you can analyze the results with a variety of SAS procedures including the GLM and REG procedures. [HTML]**The ISHIKAWA Procedure**

The Ishikawa diagram,1 also known as a cause-and-effect diagram or fishbone diagram, is one of the seven basic tools for quality improvement in Japanese industry. It is used to display the factors that affect a particular quality characteristic or problem. [HTML]**The MACONTROL Procedure**

Creates moving average control charts, which are tools for deciding whether a process is in a state of statistical control and for detecting shifts in a process average. [HTML]**The MVPDIAGNOSE Procedure**

Used in conjunction with the MVPMODEL and MVPMONITOR procedures to monitor multivariate process variation over time, to determine whether the process is stable, and to detect and diagnose changes in a stable process. [HTML]**The MVPMODEL Procedure**

Used in conjunction with the MVPMONITOR and MVPDIAGNOSE procedures to monitor multivariate process variation over time in order to determine whether the process is stable or to detect changes in a stable process. [HTML]**The MVPMONITOR Procedure**

Used in conjunction with the MVPMODEL and MVPDIAGNOSE procedures to monitor multivariate process variation over time in order to determine whether the process is stable or to detect and diagnose changes in a stable process. [HTML]**The OPTEX Procedure**

Searches for optimal experimental designs. You specify a set of candidate design points and a linear model, and the procedure chooses points so that the terms in the model can be estimated as efficiently as possible. [HTML]**The PARETO Procedure**

Creates Pareto charts, which display the relative frequency of quality-related problems in a process or operation. The frequencies are represented by bars that are ordered in decreasing magnitude. Thus, a Pareto chart can be used to decide which subset of problems should be solved first or which problem areas deserve the most attention. [HTML]**The RELIABILITY Procedure**

Provides tools for reliability and survival data analysis and for recurrent events data analysis. [HTML]**The SHEWHART Procedure**

A graphical and analytical tool for deciding whether a process is in a state of statistical control. You can use the SHEWHART procedure to display many different types of control charts, including all commonly used charts for variables and attributes. [HTML]

For the complete *SAS/QC 9.3 User's Guide*, go to the SAS/QC product documentation page.

**The ANOM Procedure**

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. [HTML]**The CAPABILITY Procedure**

A process capability analysis compares the distribution of output from an in-control process to its specification limits to determine the consistency with which the specifications can be met. [HTML]**The CUSUM Procedure**

Creates cumulative sum control charts, also known as cusum charts, which display cumulative sums of the deviations of measurements or subgroup means from a target value. Cusum charts are used to decide whether a process is in statistical control by detecting a shift in the process mean. [HTML]**The FACTEX Procedure**

Constructs orthogonal factorial experimental designs. These designs can be either full or fractional factorial designs, and they can be with or without blocks. You can also construct designs for experiments with multiple stages, such as split-plot and split-lot designs. After you have constructed a design by using the FACTEX procedure and run the experiment, you can analyze the results with a variety of SAS procedures including the GLM and REG procedures. [HTML]**The ISHIKAWA Procedure**

The Ishikawa diagram,1 also known as a cause-and-effect diagram or fishbone diagram, is one of the seven basic tools for quality improvement in Japanese industry. It is used to display the factors that affect a particular quality characteristic or problem. [HTML]**The MACONTROL Procedure**

Creates moving average control charts, which are tools for deciding whether a process is in a state of statistical control and for detecting shifts in a process average. [HTML]**The MVPMODEL Procedure (Experimental)**

Used in conjunction with the MVPMONITOR procedure to monitor multivariate process variation over time in order to determine whether the process is stable or to detect changes in a stable process. [HTML]**The MVPMONITOR Procedure (Experimental)**

Used in conjunction with the MVPMODEL procedure to monitor multivariate process variation over time in order to determine whether the process is stable or to detect and diagnose changes in a stable process. [HTML]**The OPTEX Procedure**

Searches for optimal experimental designs. You specify a set of candidate design points and a linear model, and the procedure chooses points so that the terms in the model can be estimated as efficiently as possible. [HTML]**The PARETO Procedure**

Creates Pareto charts, which display the relative frequency of quality-related problems in a process or operation. The frequencies are represented by bars that are ordered in decreasing magnitude. Thus, a Pareto chart can be used to decide which subset of problems should be solved first or which problem areas deserve the most attention. [HTML]**The RELIABILITY Procedure**

Provides tools for reliability and survival data analysis and for recurrent events data analysis. [HTML]**The SHEWHART Procedure**

A graphical and analytical tool for deciding whether a process is in a state of statistical control. You can use the SHEWHART procedure to display many different types of control charts, including all commonly used charts for variables and attributes. [HTML]