NBIB53 · 6 credits · Basic level (G1F) · Tillämpad matematik

Data Analysis, Visualization and Statistical Inference

Active · next start VT 2027

89%

passed the latest ordinary exam

TEN1 · 2 Jun 2026 · 38 students

73%

passed the ordinary exams, all sittings over the last 5 years

TEN1 · 114 students

Unusually easy in 2025/26

89% passed the ordinary exam in 2025/26 (38 students), against 63% on average in earlier years (76 students).

Part of 3 programmes

Exam

73% passed · 114 students

58% passed · 50 students

Pass the re-exam: 58% (50 students), compared with 73% (114 students) on the ordinary exam
Get 4 or 5: 29% (164 students)

Partial exams, hand-ins and labs. They are not part of the figures at the top.

Hand-in or lab

100% passed · 105 students

No sittings with at least 5 students.

Show small sittings (7)

Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.

The goal of the course is to provide a ground compentence for the use of statistical tools to visualize and analyze biological data.

Upon course completion, the student should be able to:

Process and prepare data for analysis using R (syntax-based software package).
Visualize biological data in accordance with good practice.
Identify and explain basic statistical concepts and theories.
Carry out basic statistical inference using parametric and non-parametric methods.
Report conclusions from completed statistical analysis and evaluate these conclusions in their context.

Basic programming in R.
Import and processing of data with tidyverse.
Visualization of the distribution of variables with ggplot2.
Probabilities and distributions, for example the normal, t-, and binomial distributions.
Descriptive statistics with location and dispersion measures.
Statistical inference in one and two populations using parametric and non-parametric methods, for example t-test and Mann-Whitney test.