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Six Sigma Methodology at Verso

Six Sigma Article 19 Verso




In Article 18, we explored Data Collection. Now, let's delve into Sampling in the Measure Phase in this article. We'll cover everything about Sampling, focusing particularly on the best Sample Size strategy.


What is Sampling:

·       Sampling involves the selection of units from a population.

·       The aim is to ensure that the sample accurately represents the population.

·       Sampling helps save time, money, and effort by reducing the amount of data needed.


·       The population refers to the complete set of data, the universal set, often denoted by the symbol “N”.

·       The population mean is represented by “μ”

·       Standard deviation is represented by the symbol “s”


·       A sample is a part or subset of a population.

·       The sample mean is represented by the symbol “x̄”.

·       The standard deviation is represented by the symbol “s”.

When do we sample:

·       When the cost associated with data collection is high.

·       When the time required to collect all the data is significant.

·       When measuring a high volume process.

·       If there's doubt that a sample may not truly represent the process – DO NOT SAMPLE.

 To make sure that a sample represents the population:

·       Understand the nature of the process thoroughly.

·       Familiarize yourself with the characteristics of the population.

·       Employ a sampling strategy that aligns with the process.


·       It's preferable to collect a small sample spread over a longer time period than to gather one large sample over a shorter time period.

·       Sample more frequently for unstable processes and less frequently for stable processes.

·       Sample more frequently for processes with short cycle times and less frequently for processes with long cycle times.

Sample Size Calculation

Sample size calculation

Now that we've explored Sampling in the Measure Phase, I encourage you to continue our journey with us. Join us in the next article where we'll focus on Measurement System Variation and delve deeper into the Measure Phase.

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