Study Guide

Objectives

The aim of the course is to familiarise students with commonly used validation parameters and to identify concepts in probability calculus.
On completion of the course, the student will
• identify commonly used validation parameters and the types of measurements needed to calculate their parameters
• be able to calculate the parameters related to validation parameters
• identify probabilistic concepts and understand how they relate to validation parameters

Content

• validation parameters: accuracy, linearity, limit of detection and limit of quantification - key figures for validation parameters: relative bias, RSD/CV, linear range, LOD, LOQ
• sample: histogram, sample mean and sample standard deviation
• density and accumulation function of a continuous random variable
• normal distribution, t-distribution
• single explanatory variable regression analysis, residuals

Assessment criteria, satisfactory (1-2)

The student can calculate validation parameters for validation parameters and calculations related to probabilistic calculus, such as examples

Assessment criteria, good (3-4)

In addition to the above, can explain concepts related to validation parameters, probability calculus and regression analysis

Assessment criteria, excellent (5)

In addition to the above, can apply his/her knowledge to a wider range of issues related to validation parameters, probability and regression analysis