Tips and Techniques for Statistics and Quality Improvement

Blog posts and articles about using Minitab software in quality improvement projects, research, and more.

Minitab Blog Editor

Minitab Blog Editor

When you hear about projects that save Fortune 500 companies millions, you might think operational excellence and continuous improvement programs guarantee success. Experienced practitioners tell a different story. We surveyed nearly 200 of them at all skill levels from major companies across the United States. What was the one factor they believed tied most directly to success?

Continue Reading...

Getting your data from Excel into Minitab Statistical Software for analysis is easy, especially if you keep the following tips in mind.

Continue Reading...

Choosing the correct linear regression model can be difficult. Trying to model it with only a sample doesn’t make it any easier. In this post, we'll review some common statistical methods for selecting models, complications you may face, and provide some practical advice for choosing the best regression model.

Continue Reading...

Although a polar vortex hit most of the northern United States last week, thousands of visitors did converge on Punxsutawney, Pennsylvania this past Saturday to see if their famous groundhog Punxsutawney Phil would see his shadow.

Continue Reading...

Value stream mapping is a cornerstone of the Lean process improvement methodology, and also is a recognized tool used in Six Sigma. A value stream map illustrates the flow of materials and information as a product or service moves through a process. Creating a “current state” value stream map can help you identify waste and also makes it easier to envision an improved state for process in the future.

Continue Reading...

Process validation is vital to the success of companies that manufacture pharmaceutical drugs, vaccines, test kits and a variety of other biological products for people and animals. According to FDA guidelines, process validation is “the collection and evaluation of data, from the process design state through commercial production, which establishes scientific evidence that a process is capable of consistently...

Continue Reading...

You might be thinking, six weeks and you’re still not telling us what happened? When you are solving a manufacturing or development problem you might hear the same thing from your leadership – when will we get the results?

Continue Reading...

 

Previously in our designed experiment on driving the golf ball as far as possible from the tee, we tested our four experimental factors and determined how many runs we needed to produce a complete data set.

Now let’s analyze the data and interpret the covariates and blocking variables.

Continue Reading...

Rafael Villa is a chemical engineer working as a Research and Development leader in the home care division of a company in Peru. His company that manufactures a vast range of consumer package goods and B2B products ranging from food items, such as cereal and candies, to cleaning supplies and home good items. Focusing on the design, formulation and optimization of consumer products, his R&D career has spanned multiple...

Continue Reading...

In our continuing effort to use experimental design to understand how to drive the golf ball the farthest off the tee, we have decided each golfer will perform half the possible combinations of high and low settings for each factor. But how many times should each golfer replicate their runs to produce a complete data set?

 

Continue Reading...