Hi,
How should one treat obvious gold grade outliers from samples collected from a belt?
The sampling is carried out by an automatic belt sampler prior to the ore being milled. The samples are collected and stored in a bin until there is approximately 1 ton of sample. The bin is then sent off to a lab which crushes and splits the 1 ton bin sample to produce 8 separate samples which are then assayed. Assuming there are no issues with the lab procedures, how should one treat a very high value?
For example purposes, say the 8 samples returned grades (g/t) of 2.8, 4.6, 5.2, 4.5, 35.6, 3.6, 4.2, 4.7. The arithmetic mean for the eight is 8.15g/t but if the one high grade is removed the arithmetic mean is 4.23g/t. Should I simply exclude the high value or should I cut the value of the sample to some arbitrary value (say the upper 95% confidence limit)? Although individual chip samples collected from the orebody, for the purposes of evaluation, are highly skewed, the samples from the bin approximate a normal distribution (excluding the high value).
I look forward to any comments or perhaps direction to papers or web sites on this topic.
Many Thanks
Kevin Lowe
This e-mail message has been scanned for Viruses and Content and cleared by NetIQ MailMarshal
* By using the ai-geostats mailing list you agree to follow its rules ( see http://www.ai-geostats.org/help_ai-geostats.htm )
* To unsubscribe to ai-geostats, send the following in the subject or in the body (plain text format) of an email message to [EMAIL PROTECTED] Signoff ai-geostats
