Fundamentals of Analytical Sciences

Course manual 2019/2020

Course content

In this course general aspects of statistics applied for analytical methods will be treated. Parameters to describe the quality of analytical methods (e.g. accuracy and precision, sensitivity, selectivity, robustness) will be defined. Basic statistical methods applied to modern analytical instrumentation will be discussed. These include data exploration and visualization, statistical inference, hypothesis testing, and calibration, applied to univariate and multivariate data.Attention will also be given to sampling strategies, design-of-experiments, validation procedures and to quality control in analytical laboratories. One of the main objectives of the course is to acquire the skills for adequate software handling for data analysis (e.g. Excel and Matlab).

Study materials

Literature

• Statistics and Chemometrics for Analytical Chemistry, Miller&Miller, Pearson, 6th ed.

Software

• MATLAB

• GPower

Other

• Hand-outs and exercises.

Objectives

• The student is able to classify statistical analysis methods
• The student can propose suitable methods to data processing
• The student is able to set-up an experimental design and interpret the experimental results
• The student can write scripts in MATLAB
• The student can evaluate whether the applied statistical method led to a useful answer to the analytical question
• The student is able to examine the quality of analytical methods (e.g. accuracy and precision, sensitivity, selectivity, robustness)
• The student can find the main characteristics of signals obtained by instrumental analytical techniques
• The student can defend the implication of the choice of statistical method.

Teaching methods

• Lecture
• Seminar
• Computer lab session/practical training
• Laptop seminar
• Self-study

Learning activities

Attendance

This programme does not have requirements concerning attendance (TER part B).

Assessment

There will be 6x 15-minute written tests at the start of the lectures as indicated by the schedule shown in the first lecture (slides available on Canvas) on February 6, February 13, February 20, February 24, March 9 and March 16. In these tests, the students will be assessed on basic knowledge from the previous lectures. If the mean of the best 4 grades** is larger than the exam grade, then the final grade is calculated as follows: Exam (80%), Mean of 4 best tests (20%). If the mean of the best 4 grades is lower than the exam grade, then the final grade is 100% obtained from the exam grade. This means that the tests can only improve your exam grade (as a bonus), never lower it. Participation is not mandatory.

** This means that you are allowed to miss out on two tests.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Timetable

The schedule for this course is published on DataNose.

Contact information

Coordinator

• dr. B.W.J. Pirok