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Statistical Analysis of Laboratory Data Book Course

Course Duration

5 Days

Course Description

This course presents the theory and application of statistics to and will help you master the fundamentals of laboratory data treatment. Topics include outlier testing, calibration, t-tests, F-tests, one-way ANOVA, specification testing, sampling, interlaboratory testing, statistical process control, calibration, and exploratory data analysis

Course Objective

  • How to understand the strengths and weaknesses of data
  • How to recognize and reduce different types of errors
  • Ways to carry out significance tests
  • How to correctly use outlier tests and when not to use them
  • Ways to define the limits of detection, determination, and quantification
  • How to know what statistical test to use when
  • How to understand the influence of sample size on statistical significance and power
  • Why pooling variances gives stability to analytical results
  • How to set in-house specifications

How to apply statistical process control charts to measurement processes

Course Certificate

UMETTS will issue attendance certificates to all attendees after attending the full course duration.

Who Should attend?

Technicians, scientists, engineers, laboratory managers, R&D managers, manufacturing and production managers, research supervisors, project managers, vice presidents, and others who need to learn and understand statistical methods of data analysis. The course is aimed at both beginning and experienced workers. The course assumes no previous knowledge of statistics.
Through a combination of lectures and problem-solving sessions, you will learn new statistical techniques that you can put to immediate use in the workplace.

Course Outline

Program Agenda

  • Measurement
  • Accuracy And Precision
  • Mean
  • Standard Deviation
  • Pooling
  • z Decisions
  • Confidence Intervals
  • Statistical Samples
  • Means
  • Standard Deviations
  • Student’s t
  • Statistical Testing
  • p Values And Power
  • Algebra And Logic
  • Hypothesis Testing
  • Formal Statistical Tests
  • One-Sample t Test
  • Two-Sample t Test
  • Paired t Test
  • Fisher’s F Test
  • One-Way ANOVA
  • How to carry out a one-way ANOVA
  • Duncan’s multiple range test
  • Outliers
  • Central Limit Theorem

Two of three optional topic groups will be covered in class

Group I:

  • Detection Limits
  • Sensitivity
  • Selectivity
  • Limit Of Detection
  • Minimum Detectable Amount
  • Limit Of Quantitation
  • Mandel Sensitivity

Group II: Statistical Process Control

  • Process Capability
  • Method Development
  • Control Charts
  • Lack Of Control
  • Extremes Of Control
  • Interlaboratory Testing

Group III: Bioassays

  • Ratio Of Means
  • Bioassays
  • Slope Ratio Analysis
  • Parallel Line Analysis