# Advanced data analysis in analytical chemistry

**Source**: https://www.su.se/english/education/course-catalogue/kz/kz7106?semester=VT2026&eventcode=57026
**Parent**: https://www.su.se/english/education/course-catalogue?q=&internationalStudents=%5B%22true%22%5D&forcedReasonCode=%5B%220%22%5D

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.

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?](https://www.su.se/english/related-articles/kemiska-sektionen/how-to-make-the-tastiest-lemonade)

## [Course structure](#svid10_142dc5821901009a5b52688b)

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.

### 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\
Mi[anneli.kruve@su.se](mailto:anneli.kruve@su.se)

## [Schedule](#svid10_142dc5821901009a5b5268da)

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.

[Schema KZ7106 VT 2026 Dagtid pdf, 67.1 kB.](https://www.su.se/download/18.39dc5cbc19afcf09c001bec/1765460969845/KZ7106+KZ8105_schedule_2026.pdf)

## [Course literature](#svid10_142dc5821901009a5b5268f0)

Note that the course literature can be changed up to two months before the start of the course.

## [Course reports](#svid10_142dc5821901009a5b5268f2)

Course reports are displayed for the three most recent course instances.

## [Contact](#svid10_142dc5821901009a5b52690b)

**Course Coordinator**\
Anneli Kruve, email: [anneli.kruve@su.se](mailto:anneli.kruve@su.se)\
\
**Chemistry Section & Student Affairs Office:** [chemistry@su.se](mailto:chemistry@su.se) \

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## Spring 2026 | Period 1 | Day-time, 75% | On campus | For international students

10 credits

Spring 2026

Period 1Day-time, 75%On campusFor international students

Beginning/EndPlease view course schedule for exact dates

week commencing

18/01/2026 - 21/03/2026

Closed for application

Information about late application[Applies only to certain courses](https://www.su.se/english/education/how-to-apply/important-dates/late-application-1.506150)

Course code: KZ7106

Application code: SU-57026

Level

Master's level

Language

English

Eligibility

Admission to the course requires knowledge corresponding to 90 credits in chemistry excluding orientation courses. English 6 or equivalent.

Selection

Higher Education Credits (up to 270).

[Syllabus - legal document](#)

Tuition fee

Applies to citizens from outside EU, EEA or Switzerland. First instalment: 23333 SEK. The complete course: 23333 SEK.

[More information on tuition fees](https://www.su.se/english/education/how-to-apply/costs-fees-and-scholarships)

Subject

[Chemistry](https://www.su.se/english/education/course-catalogue/education-subjects/science-and-mathematics/chemistry)

Area of interest

[Science and Mathematics](https://www.su.se/english/education/course-catalogue/education-subjects/science-and-mathematics)

Department responsible for education

[Department of Chemistry](http://www.department-of-chemistry)

Find more courses and programmes

Know what you want to study?

[Find your study programme](https://www.su.se/english/education/course-catalogue)

What can I study?

[Explore our subjects](https://www.su.se/english/education/course-catalogue/education-subjects)