GLP: Basic Statistics for QC Laboratories (GLP03)

Online training with immediate access upon enrollment.

This online course covers a number of practical and essential statistical techniques that are needed for the analyst working in a laboratory setting. Students will learn how and when to apply techniques to data presentation, interpretation, and analysis. Following an introduction, the course covers the following areas: presentation of data, significance, types of data, basic laboratory tests, outliers test, and a summary of the entire course at the end. Once all course requirements have been satisfied, students will have access to a certificate of completion in PDF format.

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The GLP: Basic Statistics for QC Laboratories course is found in the following professional certification program(s):

Good Laboratory Practice (GLP) Professional Certification Program: The Good Laboratory Practice (GLP) Professional Certification Program comprises a set of seven courses designed to provide a comprehensive overview of good lab practice concepts and requirements in compliance w ... Learn more

COURSE OUTLINE:

IMPORTANT TERMS
1. Introduction
2. Important concepts

PRESENTATION OF DATA
3. Introduction
4. Describe and present data
5. Graphical presentation
6. Measures of location
7. Mean, median and mode
8. Bias (accuracy)
9. Range
10. Measures of variance
11. Coefficient of variation
12. Precision, accuracy, bias
13. Review

SIGNIFICANCE
14. Introduction
15. Significant figures
16. Specifications and reporting

TYPES OF DATA
17. Introduction
18. Attribute and variable data
19. Converting data
20. Normal distribution
21. Using normal distribution
22. Population and sample
23. Central Limit Theorem
24. Interpreting distributions
25. Parametric tests
26. Transforming data
27. Use of binomial distribution
28. Review

BASIC LABORATORY TESTS
29. Introduction
30. Selecting statistical tests
31. Hypothesis testing
32. Type I and Type II errors
33. Statistical significance
34. Assessing assay variances
35. F test
36. Single-sample t test I
37. Unpaired two-sample t test I
38. Paired two-sample t test
39. Examples
40. Confidence intervals
41. Selecting a sample size
42. Review

OUTLIERS TEST
43. Introduction
44. The outliers test
45. Using outliers test
46. Review

SUMMARY
47. Summary

COURSE OBJECTIVES:

Present data and results in an effective and efficient manner.
Apply significance and rounding rules to summary data.
Describe, and provide examples of, different types of laboratory data.
Use the 't' test and the 'F' test to evaluate hypotheses.
Use an outliers test to evaluate data sets.
Apply basic process capability to sequential data.