What are Outliers in Geostatistics? List three potential causes of outliers? Mention three ways in dealing with outliers? In resource exploration data management, quality control and quality assurance programs are put in place to control precision and accuracy of assay results. What is Precision and Accuracy in data management? What techniques and procedures are put in place to ensure precision and accuracy are monitored.
What are Outliers in Geostatistics? List three potential causes of outliers? Mention three ways in dealing with outliers? In resource exploration data management, quality control and quality assurance programs are put in place to control precision and accuracy of assay results. What is Precision and Accuracy in data management? What techniques and procedures are put in place to ensure precision and accuracy are monitored.
MATLAB: An Introduction with Applications
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ISBN:9781119256830
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i. What are Outliers in Geostatistics? List three potential causes of outliers? Mention three ways in dealing with outliers? In resource exploration data management, quality control and quality assurance programs are put in place to control precision and accuracy of assay results. What is Precision and Accuracy in data management?
What techniques and procedures are put in place to ensure precision and accuracy are monitored. ii
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An outlier is an observation that lies an abnormal distance from other values in a random sample from a population. In a sense, this definition leaves it up to the analyst (or a consensus process) to decide what will be considered abnormal. Before abnormal observations can be singled out, it is necessary to characterize normal observations.
There are also different degrees of outliers:
- Mild outliers lie beyond an “inner fence” on either side.
- Extreme outliers are beyond an “outer fence.”
Intuitively a geostatistical functional data is an outlier if it is in some way
significantly different from its neighbours. Thus the problem becomes to define
the concept of neighbourhood and of significantly different. According to these
observations, we pay attention to local differences among spatial neighbourhood by
considering the spatial correlation structure among curves. In this sense, outliers are
curves spatially located (geostatistical functional data) which are inconsistent with
their neighbourhoods
Most common causes of outliers on a data set:
- Data entry errors (human errors)
- Measurement errors (instrument errors)
- Experimental errors (data extraction or experiment planning/executing errors)
- Intentional (dummy outliers made to test detection methods)
- Data processing errors (data manipulation or data set unintended mutations)
- Sampling errors (extracting or mixing data from wrong or various sources)
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