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"Survey

Do You Understand Your Survey Results?

Many companies spend considerable amounts of money on customer and employee surveys every year. The survey results are used to amend strategies, design new products and services, focus improvement activities, target staff development activities and … to celebrate success.

The question is: Can we always rely on what we see?

"Wilcox

Making Sense of the Wilcoxon Test

At MyInsurance, survey results have been collected in 2017, 2018 and 2019. The rating was done on a 10-point Likert ranging from 1 … very poor to 10 … outstanding. As always, the upper 3 points, i.e. 8, 9 and 10, are seen as customer is satisfied. All other ratings are undesirable. How did MyInsurance do over the years?

""/

Making Sense of Test For Equal Variances

Three teams compete in our CHL business simulation. After completing Day One, it looks like the teams show a very different performance. Although the means look very similar, the variation is strikingly different. To test this assumption of different variation among the teams, the Test for Equal Variances is deployed.

"Kano

Make Use of Your Survey Data – Kano It

Nearly all medium-size and large companies spend hundreds of thousands or even millions on customer surveys every year. Customer survey results serve to amend strategies, design new products and services and focus improvement activities. Gathering customer survey data is only the first step.

"Two

Making Sense of the Two-Proportions Test

Consider a production process that produced 10,000 widgets in January and experienced a total of 112 rejected widgets after a quality control inspection (i.e., failure rate = 1.12%). A Six Sigma project was deployed to fix this problem and by March the improvement plan was in place. In April, the process produced 8,000 widgets and experienced a total of 63 rejects (failure rate = 0.79%). Did the process indeed improve?

"innovation

Making Sense of Binary Logistic Regression

In some situations, Six Sigma practitioners find a Y that is discrete and Xs that are continuous. How can a regression equation be developed in these cases? Black Belt training indicated that the correct technique is something called logistic regression or binary regression. But this tool is often not well understood.

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