Different types of Data and its Importance
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.
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.
- How to Create a Detailed Process Map ?
- Identify the Vital Few Inputs
- Characteristics of Data
- Data Shapes & Characteristics of Shapes
- Data Collection Plan
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