## Understanding the 2-Sample t-Test: A Guide to Hypothesis Testing

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You have retrofitted your major production machine to make it run faster. Did the retrofit really improve machine speed? A 2-Sample t-Test can be used to answer that question.

## What You Need to Know About Dispersion in Data Analysis

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When you collect data from your process, the values will vary. This dispersion or variation of data around the central tendency can be measured. Let’s explore the different ways to measure dispersion.

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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.

## 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.

## The Psychology Behind the Likert Scale

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What if you were asked to rate this article on a scale of 1 to 5, with 1 being you didn’t like it and 5 being you loved it. That’s an example of a Likert Scale.

## Exploring Process Capability Analysis: A Versatile Tool for Quality Assessment

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As the name implies, capability analysis is an analysis of the ability of your process to meet your customer’s expectations and requirements. There are a number of calculated metrics which can be used to help you do your capability analysis.

## 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.

## Confidence Bands: An Essential Tool for Statistical Analysis

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The concept of a confidence band is usually associated with regression analysis. We will also explain why a confidence band is not the same as a confidence interval.

## How the Taguchi Method Simplifies Experimental Design and Analysis

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When you have multiple factors at different levels, it can be challenging to figure out which is the optimal combination. Design of Experiments is one common method you can use. The Taguchi Method is another.

## 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.

## 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.

## How Pull Systems Help in Efficient Inventory Management

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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.

## Analytic Hierarchy Process (AHP)

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When faced with multiple decision criteria, how do you prioritize them? Do you flip a coin or use something more structured? You might want to consider using the Analytic Hierarchy Process as a structured format for prioritizing your decisions.

## 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.

## 1-Sample Sign Test

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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.

## Reproducibility

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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.

## Replication

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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.

## Correlation Coefficient (r)

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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.

## 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.

## Process Capability Index

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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.

## Confidence Level

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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.

## Trend Charts

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You can learn a lot about your process by monitoring its change over time. There are different trend charts which will allow you to do that. Let’s look at a few.

## Mood’s Median Test

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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.