Characteristics of Data - Central Tendency and Dispersion
Converting Data to Information: The goal of a six sigma project is not to produce an overwhelming amount of data that ends up intimidating the concerned people. The goal is to find out as much data as possible and convert it into meaningful information that can be used by the concerned personnel to make meaningful decisions about the process. However for that one needs to learn how to statistically deal with huge amounts of data.
Data primarily needs to be understood for its two characteristics viz central tendency and dispersion. Data tends to be centred around a point known as average. The degree to which it is spread out from that point is also important because it has an important bearing on the probability. It is for this reason that we use the following characteristics to make sense of the data involved:
Measures of Central Tendency: Different types of data need different measures of central tendency. Some of the important measures, commonly used are as follows:
Measures of Dispersion: The degree of spread determines the probability and the level of confidence that one can have on the results obtained from the measures of central tendency. Common measures of dispersion are as follows:
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