Final answer:
The question related to 'kd' and 'extraced value' lacks clarity, but it seems to be a confusion with standard deviation and an extracted data point. Standard deviation measures variability in a data set while an extracted value is a single data point. Their usefulness depends on the purpose of the data analysis.
Step-by-step explanation:
It seems there may be a miscommunication in your question concerning 'kd' and 'extraced' as these terms are not commonly used in mathematics or statistics context in this form. Assuming you might be referring to 'standard deviation (SD)' instead of 'kd', and 'extracted value' typically refers to a specific data point within a dataset, the answer to whether one is better than the other depends on what exactly you're trying to achieve with your data analysis.
Standard deviation is a measure of the amount of variation or dispersion of a set of values. A low standard deviation indicates that the values tend to be close to the mean (average) of the set, while a high standard deviation indicates that the values are spread out over a wider range.
An 'extracted value' would simply be a single point of data that's been selected from a data set. Without additional context, it's not comparable to a standard deviation because they serve entirely different purposes. Standard deviation is used for understanding the variability in a data set, whereas an 'extracted value' might be used as a specific case or example within that data set.