MSG Team's other articles

10200 How Loose Monetary Policies by Central Banks Create Asset Bubbles and Lead to Inflation

Loose or Tight Monetary Policies ? The debate over whether central banks around the world must pursue loose monetary policies or tight monetary policies has become sharp in the aftermath of the global financial crisis. Loose monetary policy refers to the practice of central banks keeping interest rates low, stimulating the economy as banks would […]

11414 Strategic Processes – Meaning and its Features

These are the top level processes that an organization is exposed to. These include tasks that need a high level of intellectual capability and will have wide spread effects in the structure and functioning of the organization. The nature of these processes can be compared to those that the human brain performs. Here are some […]

11852 What is Custo Brazil

Brazil is the most expensive country to live in Latin America. The real problem is that Brazil has become more expensive than most countries in Europe and maybe it is expensive when compared to America as well. The real problem is that people in these developed countries make three times the income of an average […]

8949 Digital Payments: What they are, How they Work, and their Benefits and Problems

In recent months, all of us have heard extensively about the “war on cash”, the move to make India and other countries “cashless economies” and the general trend among policymakers worldwide to move the economies of the world to a digital and information enabled paradigm. In this context, it is worth noting that the emphasis […]

11999 Why Most Projects Run into Problems and How to Avoid them and What to do about it

Some Problems that Projects Face Research has shown that nearly 80 percent of all projects run into problems related to cost overruns and time slippages in addition to many of them not being completed. Without taking into account the projects that do not progress beyond the initiation and planning/conceptualization phase, it is indeed troubling for […]

Search with tags

  • No tags available.

Data can be described as the backbone of any six sigma project. This is because the whole idea of six sigma and operations is to use statistics to manage operations in the factory workshop. Hence, for a six sigma team to understand the types of data and when and how to use them is of vital importance. Here are the types of data that are used for statistical analysis:

Continuous Data: Continuous data is of the type that must be measured as against the type that we can count. Consider for example length of an object as a data type. Length of an object can be between 1 feet and 2 feet, it can be 1.5 feet, it can even be 1.54 or 1.546 feet depending upon the number of decimals and the degree of precision that have been decided in the data collection plan.

Discrete Data: Discrete data is the data that needs to be counted as opposed to being measured.

Here the values fall in one of the categories.

  • Binary: The data in such cases needs to be entered in one of the two categories like true or false, applicable to six sigma analyses or not applicable to six sigma analysis. Many times the outcomes of success and failure determine the operations of the shop floor. It is in such cases that the binary discrete category comes in handy.

  • Ordered Categories: The data in these cases needs to be entered in one of the multiple categories that are ranked. Here there may be more than two categories. In fact there usually are more than two categories involved. The categories may be based on the relative importance or on some type of number scale.

  • Unordered Categories: The data in these cases is entered in one of the multiple categories that need not be ranked. There are usually more than 2 categories. Data lying in one category is usually no different from data lying in any other category.

  • Count: This is simple counting of data without any categorization involved. This represents the discrete variables in its truest form but is rarely used in the six sigma process because it does not provide much analytical insight into the variables being studied.

Why is the Type of Data Important ?

The type of data is important because it has material impact on the analysis. Where continuous data is involved, the probability of an exact event becomes zero, ranges need to be used. For instance the probability of the length of an object being exactly 2 feet is zero in a continuous distribution. However, if the measurement is discrete the results can be found out.

Article Written by

MSG Team

An insightful writer passionate about sharing expertise, trends, and tips, dedicated to inspiring and informing readers through engaging and thoughtful content.

Leave a reply

Your email address will not be published. Required fields are marked *

Related Articles

Characteristics of Data – Central Tendency and Dispersion

MSG Team

Causes of Measurement Variation

MSG Team

Steps Involved in Conducting a Measurement System Analysis

MSG Team