Introduction to Statistical Analysis of Laboratory Data™

This course is designed as an introduction to the statistical principles of laboratory data analysis and quality control that form the basis for the design and analysis of laboratory investigations. The course curriculum will benefit R&D managers, analytical laboratory supervisors and staff, manufacturing and production professionals, scientists, technicians and others who wish to comprehend and interpret methods of data analysis relevant to laboratory experimentation.  Where applicable, topics are presented with relevant regulatory requirements.

This training will concentrate on the philosophy and understanding of the statistical principles required in conducting sound scientific investigations of laboratory processes and validation, including design and sample size issues.  It will not simply present statistical formulae and the lectures are oriented toward professionals having minimal formal training in statistics or mathematics beyond basic algebra.  However, for those with more formal training in statistics wishing to actually apply the techniques, appropriate time and references will be given for the procedures involved.

Those completing the course will have an understanding of the concepts of statistical design, analysis and graphing methods required in laboratory data analysis and reporting.  Attendees will be able to interpret and report results related to design and analysis issues as presented in the scientific literature concerning laboratory data analysis, as well as, quality control methods.

• Basic statistical terminology including simple statistics as well as geometric ( e.g. means, standard deviations) transformations needed to effectively communicate and understand your data results
• The statistical testing (one sided, two sided, non parametric, sample size, and power considerations)  essentials required to initiate a research investigation (i.e., research questions in statistical terms)
• Concepts of accuracy and precision in measurement analysis to ensure appropriate conclusions in experimental results including between and within laboratory variationresults
• Discussion of statistical techniques to compare experimental approaches with respect to specificity, sensitivity and linearity

Advanced Topics (Day Two). This section of the course will go beyond the basics and cover more complex issues in laboratory investigations with examples.  Topics will include:

• Association studies including correlation and regression analysis with laboratory applications
• Analysis of robustness and ruggedness
• Method comparison using more accurate alternatives to correlate analysis and other pair-wise comparisons
• Outliers, limit of detection and limit of quantitation
• Statistical quality control for process stability and capability

Past Participants' Comments:

"Excellent presentation in statistical measurements techniques that can be applied to many disciplines and projects."
Keith B., Associate Director, Reliant Pharma

"I've taken undergrad & graduate level statistics courses (long ago) and the Course Director presented the material so I could understand it much better.  He is great at explaining the concepts."
Lori B., Senior Chemist, Barr