Keys for Successful Analysis – Representative Sampling & Estimation of Standard Error Calculation | Malvern Panalytical

Date recorded: June 13 2019

Duration: 48 minutes 50 seconds

In any analytical technique you get out what you put in – that is, the instrument and technique measure what is given to them.

In this webinar we’ll explore (from a theoretical aspect, the Theory of Sampling (TOS), as first formulated by Pierre Gy) the variation seen when different samples are extracted from the bulk lot. In many instances analytical techniques get superb results on tiny amounts of sample but this has repercussions from a representative sampling perspective (think fruit cake and just sampling the raisins).

The variation caused by the inherent heterogeneity of the material represents the best variation that can be achieved and is easily calculable.

Our examples will be based on particle size distribution analysis but the conclusions are transferable to all other metrologies including x-ray fluorescence where elemental content variation is repeated samplings is the norm. The sampling formulae also have implications for count length in x-ray diffraction.

Table of contents

1. Keys for Successful Analysis -Sampling for particle size analysis Estimation of standard error

02:22

2. The presenters

00:08

3. Overview

01:43

4. Obligatory Opening Quotation (O2Q)

01:08

5. Why? Mining examples

02:29

6. Sampling: The impact on costs and decision making

00:49

7. Sampling in the 1890’s

01:33

8. LinkedIn - Mining – GEOSTATISTICS group

00:28

9. Published Abstract

00:35

10. (ALL) My University Notes on Sampling

00:33

11. University Notes (continued)

00:34

12. This is not the time to decide on Ms……

00:48

13. Adapted from: F J Flanagan “Reference Samples in Geology And Geochemistry” U.S. Geological Survey Bulletin # 1582, (1986)

01:14

14. Hofman (1901) – units?

00:42

15. Math will be based up that of Pierre Gy

01:09

16. Assumptions of the listener

00:52

17. What do I need to think about and define before I even attempt a particle size measurement?

03:20

18. What do we mean by representative sampling?

01:49

19. The 3 R’s

01:07

20. Francis Pitard

00:45

21. Cliché time

00:30

22. Fundamental Sampling Error (FSE)

00:49

23. Sampling

00:37

24. Sampling - segregation

00:32

25. T R Woodridge ‘Ore-Sampling Conditions in the West’

00:49

26. The taking of a representative sample

00:31

27. Esbensen – 2 SlideData

00:25

28. NASA lunar regolith

00:19

29. ‘How much sample do we need to take for any required degree of precision?’

00:20

30. Standard Error (Gy: Fundamental Sampling Error, FSE)

02:03

31. Fundamental Sampling Error (FSE)

00:58

32. Fundamental Sampling Error (FSE)

00:21

33. ‘I wish to detect a small amount of agglomeration in my system’

01:17

34. Minimum Mass

00:19

35. ‘I wish to detect a small amount of agglomeration in my system’

00:49

36. Minimum Mass

01:11

37. Calculation of minimum mass

00:30

38. Break out – back to the course – x95

00:16

39. [(1/aL) – 2]

00:10

40. Vezin (yes he!) 1866 (?)

00:15

41. So compare Rawle and Vezin

00:33

42. ‘Gy's Formula: Conclusion of a New Phase of Research’

00:23

43. Professor Robert Richards, MIT

00:34

44. We can turn the calculation ‘around’…

00:35

45. OK - up to 200 mm

00:48

46. The big stuff

00:34

47. So you’re taking only 20 mg……….

00:20

48. So how do you take a sample/specimen?

00:25

49. The x100 represents the single largest particle in the (sampled) distribution

00:29

50. The largest particle….x100

00:09

51. The largest particle….x 100

00:19

52. x100 – ISO 13320: 2009

00:13

53. Sampling - summary

00:25

54. Cliché time

00:13

55. Charles Babbage

00:21

56. References

00:19

57. Sampling personality webinars

00:19

58. Contact Information and Q&A

04:20

59. Thanks for listening

00:22

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