How to Understand the Basics when it comes to Six Sigma Statistics
There are a number of ways to explain and help in understanding projects that might be used for Six Sigma statistics. These are simple and should be easy to grasp for a green belt, a black belt, or a master black belt.
There are generally two different types of statistics which are normally looked at within the Six Sigma Methodology. These are commonly known as separate branches called descriptive and inferential stats. These two methods differ in use and in relevance, depending on what is being studied and the data being extracted.
The descriptive kind of statistics is relatively easy to understand. It involves any type of data that is held and analyzed in the form of numbers, graphs, and/or charts. All data is examined in order to understand a whole group. The data that is inevitably gathered by the end of the experiment relates to and represents the entire group being measured.
To apply this kind of statistics, it is highly essential that mathematical terms such as mean, median and mode are understood and applied correctly. These are terms that describe the range and average of the specific data being gathered in mathematical terms. It is also crucial that standard deviation and variance is understood. The numbers gathered by this form of data collection are the actual and complete numbers linked to what is being measured.
The inferential kind of statistics uses sample statistics. This is most useful when attempting to conclude relationships of certain population parameters when the populations being studied are just too large to handle. This method is mainly carried out during the Analyze and Improve stages of the Six Sigma DMAIC Process, regression analysis and correlation analysis. This method was devised, due to the fact that it is impossible to come to a conclusion regarding an entire group or population in some cases.
For example, it is impossible to extract the average weight of a certain type of fish found in the Atlantic Ocean using data extracted from each and every fish, such as you would do with the gathering of descriptive statistics. It is for this reason that a sampling method of gathering is applied, as it is impossible to catch and measure every fish in the Atlantic Ocean. Statistical Sampling generally involves choosing and analyzing a particular sample of the group as a whole (population) and coming to a conclusion regarding the population in its entirety.
A sample is simply selected from the whole population. Certain results are then determined based on the chosen sample. After all the relevant data has been gathered and details have been determined, sample statistics should be measured and calculated to come up with an estimation of entire population’s parameters. By using a range of means, variances, and proportions, a relevant comparison is then drawn up. This is achieved by using a hypothesis, detailing the population. For Six Sigma statistics to be determined as either false or not false, they are first thoroughly analyzed and examined until a probable occurrence is identified.
The end result does not always have to be decided as true. Actually, this is a timely effort and usually takes a long time. However, Six Sigma statistics allow for possibilities to be derived from a certain population, eventually and successfully leading to an accurate conclusion.