Statistics Article

Derek Benson’s picture

By: Derek Benson

How early is too early to introduce quality into your everyday life? Have we missed out on improvement opportunities in our personal lives along our paths to achieving our career goals as quality professionals? These questions have me pondering how life could have been different for me growing up with a little more emphasis on data analysis for improvement.

Multiple Authors
By: Stefan H. Steiner, R. Jock MacKay

Fred Faltin’s picture

By: Fred Faltin

All of us draw conclusions based on what we see happening around us. Often what we’re observing is a sample from some larger population of events, and we draw inferences based on the sample without even realizing it. If the sample we observe is not a representative one, our resulting judgments can be seriously flawed, potentially at considerable personal cost.

Bruno Scibilia’s picture

By: Bruno Scibilia

Genichi Taguchi is famous for his pioneering methods of robust quality engineering. One of the major contributions that he made to quality improvement methods is Taguchi designs.

Designed experiments were first used by agronomists during the last century. This method seemed highly theoretical at first, and was initially restricted to agronomy. Taguchi made the designed experiment approach more accessible to practitioners in the manufacturing industry.

Catherine Beare’s picture

By: Catherine Beare

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Although efforts have been made to create policies that support a bias-free workplace, there is still a considerable way to go toward achieving the gender equality that organizations are striving for. Due in part to a lack of clear measurement and transparency, many companies and industries as a whole are still lagging behind in the effort to have women and men equally represented, valued, and rewarded in the workplace.

Donald J. Wheeler’s picture

By: Donald J. Wheeler

Good measurements are like apple pie and motherhood. Who could ever be against having good measurements? Since we all want good measurements, it sounds reasonable when people are told to check out the quality of their measurement system before putting their data on a process behavior chart. Fortunately, this is simply one more bit of advice that is completely unnecessary.

Stanford News Service’s picture

By: Stanford News Service

Most leadership advice is based on anecdotal observation and basic common sense. Stanford Graduate School of Business professor Kathryn Shaw tried a different tack: data-driven analysis.

Joby George’s picture

By: Joby George

Having difficulty managing quality and quality-related data? You’re not alone. Many manufacturers struggle with this these issues due to paper-based or other disparate systems being used to track, manage, and report on quality events. Walk about a production room floor, and there’s a good chance you’ll see a few three-ring binders or folders stuffed with handwritten, quality-related worksheets and forms.

Eston Martz’s picture

By: Eston Martz

If you were among the 300 people who attended the first-ever Minitab Insights conference last month, you already know how powerful it was. Attendees learned how practitioners from a wide range of industries use data analysis to address a variety of problems, find solutions, and improve business practices. For those who weren’t there, here are five helpful, challenging, and thought-provoking ideas and suggestions that we heard during the event.

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