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What Is the Runs Test and How Can It Help You Improve Your Process?

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Randomness and independence are two required characteristics for understanding and analyzing process variation. The Runs Test allows you to check for the randomness of a set of sequentially collected data. 

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Understanding the Tollgate Review Process

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The word gating is often used in the context of Six Sigma and DMAIC and is usually referred to as tollgate reviews. The purpose is to evaluate your progress, and make sure you’re still heading in the right direction. 

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ANOVA: A Simple Guide to Comparing Multiple Group Means

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ANOVA is a powerful statistical method for comparing several samples (3 or more) to each other to see if the populations that the means came from are statistically different.

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Understanding Customer Needs: A Guide to Segmentation Strategies

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In the context of marketing, segmentation is the process of dividing a target market into groups with similar needs and behaviors. This allows you to develop unique strategies to meet specific wants and needs. 

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Optimizing Quality Control: The Role of Short-Run SPC

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If your manufacturing process produces multiple products or SKUs in short runs, how many control charts will you need to monitor those different products? With short-run SPC, you might only need one. 

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Navigating the Mechanics and Calculations of Pull Systems

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Does your organization use a pull or push system to allow your manufacturing function to meet your customers’ demand for your products? Let’s learn why a pull system might be a better approach for optimizing your organization.

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Employee Empowerment: Exploring the Voice of the Employee (VOE)

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When managing any organization, there are four voices you should be listening to; Voice of the Customer, Voice of the Process, Voice of the Business and Voice of the Employee. Let’s focus on learning more about the Voice of the Employee or VOE. 

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Making Informed Conclusions: Using the 1-Sample Sign Test for Median Analysis

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We know that many hypothesis tests have an underlying assumption of normality. But, what if your data is not normal? Let’s see how the 1-sample sign test can help. 

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Understanding Reproducibility: Ensuring Reliable Measurement Systems

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If you have your three laboratory technicians measure the same samples using the same equipment and measurement process will they give you the same answers? Let’s learn more about the concept of reproducibility.

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Improving Experimental Precision with Replication: A Comprehensive Guide

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When you talk about Design of Experiments, you can discuss the 3 Big R’s; Randomization, Repetition and Replication. Let’s learn more about Replication and contrast that with the other R’s. 

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Analyzing Correlation Coefficients: Discovering Patterns in Data

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The correlation coefficient (r) answers the question of how strong and in what direction is the relationship between two continuous variables. Let’s explore this statistical descriptor and what it tells you about your data.

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Achieving Excellence: How to Attain the Coveted Rank of Master Black Belt

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Will having a Master Black Belt help your organization beat up your competitors? Yes. By having a skilled and experienced Master Black Belt, your organization will have the capabilities to improve all that they do and gain competitive advantage. Let’s see how.

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Process Capability Index: The Key to Customer Satisfaction and Business Success

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Can your process meet the expectations and specifications of your customer? The Process Capability Index is a simple way of answering that question. Let’s see how.

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Confidence Level for Business Applications: Determining the Right Threshold

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When dealing with data and statistics, there is no certainty. As the researcher, you get to choose the level of confidence you need to make your decisions.

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Understanding the Mood’s Median Test: An Overview

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Your data has failed the assumption of normality needed for a parametric test of hypotheses. If you have two or more groups you want to analyze, what do you do? Maybe the Mood’s Median Test will help. 

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Nominal Data

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Sometimes you are interested in analyzing data that is not measurable. Nominal data consists of unordered categories which can be counted but not measured.  

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Mallows Statistic (C-p)

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When you hear the phrase Mallows’ Statistic (Cp) think of multiple regression analysis. The question you want to answer is which combination of predictor variables will give you the best prediction model. Let’s learn a little more. 

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Independent Variable

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What is an independent variable and why is it important to understand? And how is it different from a dependent variable? Let’s answer those questions for you.

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data analysis

Data Transformations Helped One Company Better Analyze Their Process Data

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Normality of the data is an underlying assumption for the use of many statistical tools. When normality doesn’t exist, transforming the data may be necessary. Let’s see how one company did that.

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Pharma Co. Saved Nearly $1M Using Attribute Agreement Analysis

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Can you always believe data which is based on people’s opinions and self-reporting? The obvious answer is no. Let’s see how one company used Attribute Agreement Analysis to determine the reasons for speaker program cancellations.

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pharmaceutical company DOE success

How Design of Experiments (DOE) Helped a Pharma Company Extend Product Shelf Life

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Through the use of Design of Experiments (DOE), a pharmaceutical company was able to extend the shelf life for one of its life saving liquid oncology medicines. Let’s see how this saved the company money, lowered the price of the drug and helped save lives. 

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Error Mode Effects Analysis (EMEA)

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The famous poet, Alexander Pope said, “To err is human … ” Using Error Mode Effects Analysis (EMEA) will help mitigate, eliminate and prevent those human errors.

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Trivial Many

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Where should you focus your improvement efforts; the vital few or the trivial many? Let’s define these two terms so you can answer the question.

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Six Sigma Strategy

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Six Sigma is a philosophy of business and a set of tools for improving all your organizational processes. There are three strategies or desired outcomes of deploying Six Sigma. Let’s explore them further.

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