Stockholm university
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Advanced data analysis in analytical chemistry

The course will cover theoretical, practical, and investigative aspects of data analysis for chemical analysis. For this purpose, we cover data visualization and characterization of collected data, basic statistics for hypothesis testing, quantification and method validation.

Information for admitted students spring 2025

Congratulations! You have been admitted at Stockholm University and we hope that you will enjoy your studies with us.

In order to ensure that your studies begin as smoothly as possible we have compiled a short checklist for the beginning of the semester.

Follow the instructions on whether you have to reply to your offer or not.
universityadmissions.se

 

Checklist for admitted students

  1. Activate your university account

    The first step in being able to register and gain access to all the university's IT services.

  2. Register at your department

    Registration can be done in different ways. Read the instructions from your department below.

  3. Read all the information on this page

    Here you will find what you need to know before your course or programme starts.

IMPORTANT

Your seat may be withdrawn if you do not register according to the instructions provided by your department.

Information from your department

On this page you will shortly find information on registration, learning platform, etc.

Welcome activities

Stockholm University organises a series of welcome activities that stretch over a few weeks at the beginning of each semester. The programme is voluntary (attendance is optional) and includes Arrival Service at the airport and an Orientation Day, see more details about these events below.
Your department may also organise activities for welcoming international students. More information will be provided by your specific department. 

su.se/welcomeactivities 


Find your way on campus

Stockholm University's main campus is in the Frescati area, north of the city centre. While most of our departments and offices are located here, there are also campus areas in other parts of the city.

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Sampling home made lemonade
In order for the experiment to be valid, a group of two to three students need to work together when tasting (sampling) and then plotting the data to find the optimal combination.

The course will cover from the fundamentals of statistical tests to application in analytical method validation and modeling. The gained knowledge is applied throughout the course in miniprojects. Additionally, the course content serves as bases for data analysis in the following courses in the Master Program in Analytical Chemistry.

How to make the tastiest lemonade?!

Lemon juice and white syrup

What combination of sweet and sour makes the best tasting lemonade? Our masters students in analytical chemistry are about to find out!

During one of the labs on the course in chemometrics, students are asked to find the optimal concentration of lemon and sugar to make the tastiest lemonade. And the students will use themselves as samplers!

Given a number of samples with different concentrations, each student is asked to give their opinon on each sample, plot them into R and then model the data in order to find the "sweet spot" where most people would enjoy it the most.

Who said analytical chemistry had to be done in lab in a white coat?

  • Course structure

    The course features lectures, workshops, computer lab work, oral and written presentation of scientific work within the following subjects:

    Data presentation, characterization, distributions:  

    different statistics for average and spread, plotting data (scatter plot, histogram, box-plot, etc.), distributions (uniform distribution, normal distribution, t-distribution, etc.), central limit theorem.

    Hypothesis testing:

    type I and II error, p-value, t-test, and F-test, analysis of variance.
    Regression analysis for quantification and modeling: residuals, significance testing, slope and interpretation, calculating the concentration, lack-of-fit, goodness-of-fit, multilinear regression, robust regression.

    Method validation:

    precision, trueness, accuracy, uncertainty, different validation guidelines,  quality control, and accreditation. 

    Teaching format

    Lectures, seminars, exercises and labs.

    Course taught in English.

    Expected learning outcomes

    • Define the hypothesis for testing statistical significance depending on the scientific question. Apply the statistical significance test and interpret the results. Evaluate the suitability of different statistical tests for given data and suggest a hypothesis testing method depending on the research question.
    • Explain the assumptions, limitations, and advantages of the calibration graph method, standard addition method, and internal standard method. Calculate the analysis result for different quantification methods. Evaluate the linear range of a calibration graph and evaluate the statistical significance of a regression line (residual analysis, Lack-of-Fit, significance of the intercept, etc.). Design a suitable calibration method depending on the instrumental method, available materials, and requirements for the analysis. Assess the suitability of the calibration approach for a given quantification approach. 
    • Name method performance characteristics. Calculate the method characteristics and evaluate if they fulfill the method requirements. Evaluate the need for estimating different method performance characteristics depending on the research question. Design a plan for method validation depending on the method under development. 
       

    Assessment

    Written lab reports and written exam.

    Examiner

    Anneli Kruve

  • Schedule

    The schedule will be available no later than one month before the start of the course. We do not recommend print-outs as changes can occur. At the start of the course, your department will advise where you can find your schedule during the course.
  • Contact

    Chemistry Section & Student Affairs Office