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Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
Stability01:28

Stability

The time response of a linear time-invariant (LTI) system can be divided into transient and steady-state responses. The transient response represents the system's initial reaction to a change in input and diminishes to zero over time. In contrast, the steady-state response is the behavior that persists after the transient effects have faded.
The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...
Stability of structures01:14

Stability of structures

In mechanical engineering, the stability of systems under various forces is critical for designing durable and efficient structures. One fundamental way to explore these concepts is by analyzing systems like two rods connected at a pivot point, O, with a torsional spring of spring constant k at the pivot point. This system is similar in appearance to a scissor jack used to change tires on a car. In this case, the arms of the linkage (equivalent to the rods in this system) are entirely vertical,...
Statgraphics01:10

Statgraphics

Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
Introduction to Statistical Process Control01:15

Introduction to Statistical Process Control

Statistical Process Control (SPC) is a method used to monitor and control quality within processes, particularly in manufacturing and service delivery, by employing statistical methods. SPC aims to distinguish between natural (common cause) variation and variation due to specific changes or events (special cause), allowing for timely improvements and sustained quality. The control chart, a pivotal tool in SPC, visually displays data over time alongside a central line of upper and lower control...
Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...

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Have more confidence in your stability data: two points to consider.

Journal of pharmaceutical and biomedical analysis·2005
See all related articles
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Related Experiment Video

Updated: Jul 7, 2026

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
05:47

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

Published on: August 29, 2025

A six-sigma approach to stability testing.

Karl De Vore1

  • 1Bio-Rad Laboratories, Irvine, CA 92688, USA. karl_devore@bio-rad.com

Journal of Pharmaceutical and Biomedical Analysis
|February 12, 2008
PubMed
Summary

Stability testing in diagnostics and pharmaceuticals can be improved using statistical thinking and Six Sigma concepts. These methods enhance process capability and increase confidence in stability data for better product development.

Area of Science:

  • Pharmaceutical Sciences
  • Diagnostic Technology
  • Quality Management

Background:

  • Stability testing is crucial for ensuring the quality and efficacy of diagnostic and pharmaceutical products.
  • Current stability testing methodologies may present opportunities for enhancement.
  • Implementing advanced statistical approaches can address these limitations.

Purpose of the Study:

  • To define stability testing within the diagnostic and pharmaceutical sectors.
  • To highlight areas for improvement in current stability testing processes.
  • To introduce statistical thinking and Six Sigma as tools for enhancing stability testing.

Main Methods:

  • Application of statistical thinking principles.
  • Integration of Six Sigma methodologies (e.g., DMAIC).

Related Experiment Videos

Last Updated: Jul 7, 2026

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
05:47

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

Published on: August 29, 2025

  • Development of tools and rationale for test setup, criteria, and volume.
  • Main Results:

    • Enhanced process capability in stability testing.
    • Increased confidence in generated stability data.
    • Improved establishment of appropriate testing criteria and volume.

    Conclusions:

    • Statistical thinking and Six Sigma significantly improve stability testing.
    • These methodologies lead to more robust and reliable data.
    • The study provides practical tools for optimizing stability testing protocols.