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Statistical Methods for Quality Improvement

Statistical methods for quality improvement involves the use of collected data and quality standards to find new ways to improve products and services. These methods characteristically involve attempts to infer the properties of a large collection of data.

OriginPro provides various methods and tools for quality improvement:

Statistical Process Control (SPC)

The Statistical Process Control (SPC) App, for OriginPro brings together five key SPC features: image

Control Charts

The SPC App offers a wide variety of configurable control charts:

For Subgroups

  • Xbar-R
  • Xbar-S
  • I-MR-R/S
  • Xbar
  • R
  • S
  • Zone

For Individuals

  • I-MR
  • Z-MR
  • Individuals
  • Moving Range

Attributes Charts

  • P/U Chart Diagnostic
  • P/U Chart
  • Laney P' / U'
  • NP
  • C

Time-Weighted Charts

  • Moving Average
  • EWMA

Process Overview

The Process Overview tool in the SPC app offers reports with charts and capability statistics. It helps you to identify problem areas and gain insights into your data:

  • Xbar / Individuals charts
  • Probability plot
  • Capability histogram
  • Capability plot
  • Capability statistics

Capability Analysis

Capability analysis is used to detect whether a process meets specifications. The SPC app provides 5 types of capability analysis tools for different data types:

  • Normal
  • Between/Within
  • Non-normal
  • Binomial
  • Poisson

Data Transformation

The SPC app provides 3 transformation functions to make data approximately normal:

  • Box-Cox Transform
  • Johnson Transform
  • Yeo-Johnson Transform


The Process Overview tools generate a combination report with multiple charts and statistics. It enables a user to assess the quality or capability of a process in a glance


The reports of Capability Analysis include control charts and capability reports with Cp, Cpk, Pp and Ppk indices, to help the user to access whether the process meet the specifications

Identify Data Distribution

The SPC App provides 14 distributions and 3 transformation functions to help to identify your data distribution:

  • Normal
  • Logistic
  • Lognormal / 3-Parameter-Lognormal
  • Log-logistic
  • Weibull / 3-Parameter Weibull
  • Gamma
  • Rayleigh
  • Smallest Extreme Value
  • Largest Extreme Value
  • Exponential / 2-Parameter Exponential
  • Gaussian Mixture
  • Folded Normal
  • Box-Cox Transformation
  • Johnson Transformation
  • Yeo-Johnson Transformation

Origin provides 14 distributions and 3 transformation functions to help to identify your data distribution


Start from the decision map, choose a proper tool basing on your data type and generate powerful reports.

Measurement System Analysis (MSA)

Origin provides two tools for Measurement System Analysis:


Gage R&R Study

The Gage Study - Continuous Data App supports the following features:

  • Type 1 Gage Study
  • Gage Linear Bias Analysis
  • Crossed Gage R&R Study
  • Nested Gage R&R Study
  • Expanded Gage R&R Study
  • Create Gage Worksheet

Attribute Agreement Analysis

The Attribute Agreement Analysis App is designed to assess the degree of agreement between appraisers' ratings and known standards. This App supports the following:

  • Kappa Statistics
  • Kendall's Coefficient of Concordance
  • Within Appraisers Analysis
  • All Appraisers vs. Standard Analysis
  • Agreement Graphs
  • Confidence Intervals
  • Misclassification Rates


The results of Gage R&R Study in Origin include a combination report with graphical analysis and a report sheet with ANOVA table, variance components and Gage R&R statistics

Tolerance Intervals

Origin offers Tolerance intervals app, which is important tool in quality improvements. It can help to understanding and managing variability in production processes. The tolerance intervals app in Origin provides following features

  • Support multiple distributions
    • Normal
    • Lognormal
    • Gamma
    • Exponential
    • Smallest Extreme Value
    • Weibull
    • Largest Extreme Value
    • Logistic
    • Loglogistic
    • Nonparametric
  • Parametric and non-parametric tolerance intervals
  • Graphical report including interval plot, histogram and probability plots

Design of Experiments (DOE)

The Design of Experiments (DOE) App for OriginPro enables researchers to walk through each step of the design of experiments process.


Power and sample size

  • Determine the minimum sample size required to achieve a certain level of power for detecting a specified effect size
  • Find the right balance that ensures robust and valid experimental outcomes


  • Factorial designs, including 2-level factorial, Plackett-Burman and general full factorial
  • Response surface design, including central composite and Box-Behnken


  • Design evaluation tools including coefficients, standard error and p-value.
  • Build models with linear+interaction+square, or customize terms in regression model.
  • Statistics table to examine the goodness-of-fit, and analysis summary with ANOVA
  • Fits and residual diagnostics
  • Find Y from X to extract fitted data.


  • Fitted Plot
  • Residual Plot
  • Effects Plot
  • Main Effects Plot
  • 2-way Interaction Plots
  • Contour Plot
  • Surface Plot


  • Search for optimal responses based on the goal:minimize, maximize and target.
  • Constraint factors to a region or hold at a fixed value.
  • Display the optimization plot, in which you can tune factor settings to improve the solution.


Origin provides various graphs to help you to visualize the results.


Move the vertical red lines to change factor values to view how they affect the composite desirability and the responses in the real time


The Design of Experiment tool provides available design list to help user to make decisions

Additional Tools


  • One, Two, Three-Way ANOVA
  • Repeated Measure ANOVA
  • Means Comparison / Post-hoc Tests

Learn More

Hypothesis Icon.png Hypothesis Testing

  • One, Two, Paired Sample T-Test for Mean
  • One, Two Sample Test for Variance
  • One , Two Sample Proportion Test
  • Power and Sample Size

Learn More

MSA Icon.png Multivariate Analysis

  • Principal Component Analysis
  • Cluster Analysis
  • Discriminant Analysis
  • Partial Least Square

Learn More

Regression Icon.png Regression

  • Linear Regression
  • Multiple Linear Regression

Learn More

Regression Icon.png Reliability

  • Kaplan-Meier Estimator
  • Cox Proportional Hazard Model
  • Weibull Fit

Learn More

Charts Icon.png Statistical Charts

  • Pareto Charts
  • Scatter Plots
  • Histograms
  • Box Charts

Learn More

Tolerance Intervals Icon.png Time Series Analysis

  • Trend & Decomposition
  • Correlation
  • Smooth
  • ARIMA Model
  • Stationary Test

Learn More

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