Analysis of Lab Data with Excel
Next Date
Tue/Wed, 1-2/12/2026
Participants
3 - 12
Duration
2 Days
Course Form
online, classroom in Basel or in-house ℹ
Course Description
Are you interested in interpreting, evaluating and guaranteeing the quality of your laboratory results, for instance in an analytical context? This course will provide you with an overview of key concepts and methods required for such data analyses, e.g. for method validation. It is aimed at scientists who have basic statistical knowledge at the level of “Visualization of Lab Data with Excel” or equivalent know-how, as well as elementary Excel skills.
What are you going to learn?
This 2-day course bridges theory and practice by focusing on practical applications. Participants will work with data visualization, modelling, and validation techniques which are all applied directly in Excel and enhanced by the validated EasyStat macros. Exercises based on real-life examples constitute an important part of the class, ensuring that you gain experience in analysing and validating laboratory data.
Who should attend?
Lab technicians and supervisors, chemists, engineers
Elementary statistical knowledge is assumed (as provided in "Visualization of Lab Data with Excel")
Basic knowledge of Excel is essential
Course Fees
- CHF 795.- per day + 8.1% VAT (incl. course documents and individual participant coaching during the practical exercises) for online courses
- CHF 865.- per day + 8.1% VAT (incl. course documents, individual participant coaching during the practical exercises, break refreshments and lunch) for classroom courses.
Which topics are covered?
Basic Concepts
Simple graphical representation of results (histogram & boxplot)
Confidence interval for the mean
Applications in validation (accuracy, trueness and precision)
Outliers and outlier tests
Comparison of Samples (Series of Measurements)
Graphical comparisons (parallel boxplots)
Statistical tests for the difference between two samples
Analysis of variance for the comparison of several samples
Inter-Laboratory Experiments
Repeatability and reproducibility of measurement methods
Variance component analysis in the evaluation of inter-laboratory trials
Linear Regression
Fitting a straight line
Confidence intervals for slope and intercept
Goodness of fit and residual analysis
Transformations to achieve linearity
Prediction and calibration
Regression through the origin
Questions about Data Analysis or EasyStat?
We are always at your disposal if you have any questions. Simply call us on +41 61 686 98 77 or use the Contact Form.