Introduction to Statistical Analysis of Laboratory Data

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Course Director

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Course Fee

$2150.00 Regular Registration

$1950.00 Early Bird Pricing (Register 30 Days in Advance)

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Future Live Stream Sessions (click to register)

Course Description

Statistical analysis is essential for making reliable, defensible decisions from laboratory data, yet many laboratory professionals lack formal training in these critical methods. By completing this course, attendees will gain the confidence to design robust experiments, interpret results accurately and communicate findings to technical and nontechnical audiences. 


Our practical, hands-on approach ensures you can support regulatory submissions, defend data during audits and drive continuous improvement in laboratory operations through sound statistical decision-making.

Who Should Attend Laboratory Data Statistical Analysis Training?

This 15-hour 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. It focuses on the philosophy and understanding of the statistical principles required for conducting sound scientific investigations of laboratory processes and validation, including design and sample size considerations.


It will not simply present statistical formulae. The lectures are oriented toward professionals who have minimal formal training in statistics or mathematics beyond basic algebra. However, for those with more formal training in statistics who wish to apply the techniques, appropriate time and references will be provided for the procedures involved.


Professional Roles


The course curriculum will benefit:


  • Research and development (R&D) managers
  • Analytical laboratory supervisors and staff
  • Manufacturing and production professionals
  • Scientists
  • Technicians
  • Quality assurance professionals
  • Regulatory affairs specialists
  • Method validation specialists


Applicable Industries


This training is essential for professionals working in:

  • Pharmaceutical manufacturing and development companies
  • Biotechnology and biopharmaceutical organizations
  • Contract research organizations (CROs) and testing laboratories
  • Medical device companies
  • Chemical and specialty materials manufacturers
  • Food and beverage companies
  • Environmental testing and consulting firms
  • Academic research institutions and government laboratories


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Additional Course Information

  • Learning Objectives

    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.

  • Agenda

    Statistical measures and descriptive statistics: Central tendency (average or mean, median and mode), dispersion measures such as range, variance, standard deviation, coefficient of variation, unbiased estimates, measurement summary and precision.


    Graphical techniques: Histograms, bar charts and scatter plots. Graphical representation of lab results.


    Distributions and formal statistical laboratory tests: Normal, t-distribution (one sample, two sample and paired), one-way ANOVA to assess effect and necessity of replication, skewed distributions with applications to experimental results and alternative statistical comparison methodologies.


    Estimation statistics: Point and interval estimates, accuracy, precision. Further concepts of method validation, such as sensitivity, specificity, selectivity and linearity.


    Defining robustness and ruggedness: Design selection criteria, calculations, interpretation, effects of repeated experimentation and multiple lab results.


    Defining linearity further: Applications to method comparison and interpretation. Examination of outliers in exploratory analysis of assay results.


    Alternative strategy to linearity: An alternative advanced method for assessing agreement between two methods of laboratory measurements.


    Limit strategies: Limit of detection and limit of quantitation.


    Calibration problem: Techniques involving crude and precise methodologies and measurement of bias.


    Validation using statistical process control: Use of quality control charts to determine laboratory process stability and capability.

  • Testimonials

    "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

Registrant Information:

Each person attending a course will be asked to set up an Attendee Profile Account during the registration process. Creating an Account helps you view your order history and manage your training programs. If you are registering for others, please set up an Account in the Attendee’s name. If you are registering more than one person, you’ll need to set up a separate account for each Attendee.