    AICOS News
23.02.2020
AICOS Technologies at PCH Meetings 2020 in Lyon
News PCH Lyon March, 2020
más 05.01.2020
Datos de primavera cursos en línea !
La agenda de cursos para la primera mitad del año...
más 26.01.2011
News
más Búsqueda Cursos

# Analysis of Lab Data with Excel

Tue/Wed, 16-17/6/2020

# Disculpe las molestias, la página solicitada no está disponible en español.

The course covers measurement accuracy, comparison of two samples, Analysis of Variance (ANOVA) including interlaboratory trials, as well as linear regression (including confidence limits for the regression parameters) and calibration.
This course requires statistical knowledge at the level of "Visualization of Lab Data" or equivalent, as well as elementary knowledge of Excel.

What would you learn ?
This 2-day course is aimed at those who need to interpret, evaluate and guarantee the quality of results obtained from their analytic laboratories. After the course, participants will be able to apply the relevant statistical tools using Excel. In particular, emphasis is made on data visualization and modelling. Concepts and methods needed e.g. for validation purposes are addressed, such as the analysis of variance (ANOVA) for the comparison of several samples or analysis of inter-laboratory experiments, and linear regression for prediction and calibration.

The emphasis is on the practical application of these methods. Exercises using real examples constitute an important part of the course. The course uses Excel with supplementary macros ( EasyStat ).

Who should attend ?
• Lab technicians and supervisors, chemists, engineers
• Elementary statistical knowledge is assumed (as given in the course "Visualization of Lab Data" )
• Basic knowledge of Excel is essential

Which topics are covered ?
 Basic Concepts Simple graphical representation of results (Boxplot & Histogram) 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 2 samples Analysis of variance for the comparison of several samples Inter-laboratory Experiments Reproducibility of measurement methods Variance components in the evaluation of inter-laboratory trials Linear Regression Fitting a straight line Confidence intervals on the slope and intercept Goodness of fit and residual analysis Transformations to achieve linearity Prediction Regression through the origin Calibration Calibration as inverse Regression Confidence intervals

Any questions ? 