The quality of analytical data is a vital aspect of the work of an analytical scientist. The application of statistics is central to the assessment of data quality and an understanding of statistics is essential to the interpretation of analytical results. The application of statistics is required for method validation and measurement uncertainty calculations, and is thus essential for meeting ISO/IEC 17025:2005 accreditation requirements. 

This computer-based course provides an introduction to the basic statistical tools that analytical scientists need for their work. The course starts from looking at data and then explains the most common statistical parameters and how to calculate them.

What are the benefits?

This course is designed to help delegates to understand some of the most important statistical concepts used by analytical scientists, calculate the most common statistics, apply significance testing and use linear regression in calibration.

Course content, the course will cover:

* Introduction to statistics

* Significance testing, t- and F tests

* Analysis of variance

* Control charts

* Linear regression