Fundamentals of Analytical Sciences

Course manual 2020/2021

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

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

• Take-home exam (E1), 30% of the grade: This is a practical assignment in which the student is required to work with data and write a small report. The exam commences over a span of a short week and can be done at home.
• Exam (E2), 70%* of the grade
  • 20% of the exam comprises theoretical questions
  • 80% of the exam comprises practical questions (calculations)
• * Bonus (B): There will be 6x 15-minute written tests at the start of the lectures of: February 4, February 11, February 18, February 25, March 4, and March 11.
  • These formative assessments will assess students on basic knowledge from the previous lectures.
  • The tests can only improve your final exam (E2) grade (as a bonus), never lower it.
  • Participation is never mandatory.
  • The mean of the best 4 out of 6 weekly-test grades forms your bonus grade (B).
  • This means that you are allowed to miss out on two tests whilst still profit from a potential bonus grade.
• Final grade (F) calculation
  • If B>E2: F = 0.3*E1 + 0.7*(0.2*B + 0.8*E2)
  • If E2>=B: F = 0.3*E1 + 0.7*E2

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

Staff

• dr. S. Samanipour
• Denice van Herwerden MSc
• S.R.A. Molenaar MSc
• Leon Niezen
• Lotte Schreuders (Advisor)
• Mimi den Uijl (Advisor)