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Probability and Statistics (5cr)

Code: R504D134-3001

General information


Enrollment
06.10.2025 - 19.01.2026
Registration for introductions has not started yet.
Timing
20.01.2026 - 10.05.2026
The implementation has not yet started.
Number of ECTS credits allocated
5 cr
Virtual portion
3 cr
Mode of delivery
Blended learning
Teaching languages
Seats
0 - 30
Degree programmes
Machine Learning and Data Engineering
Teachers
Jouko Teeriaho
Teacher in charge
Jouko Teeriaho
Course
R504D134

Evaluation scale

H-5

Objective

You learn fundamental concepts of probability and statistics, which are crucial in the field of machine learning and data engineering.

You are familiar with combinatorics and basic theorems and rules of probability and you can apply them. You can handle random variables, and use discrete and continuous variables and distributions to present data and solve problems related to your professional field.

With descriptive statistics, you can characterize data in the form of diagrams and calculate statistical parameters and quantiles. With inferential statistics you come to conclusions and can make predictions based on your data.

You become familiar with applications used to handle large amounts of data.

Content

Combinatorics
Theorems and rules of probability
Discrete and continuous variables and distributions
Descriptive statistics, common diagrams and statistical parameters, quantiles
Inferential statistics and common statistical significance tests such as t-test, ANOVA and chi-square
Correlation and linear regression
Use of applications, such as Excel and Python

Location and time

Spring 2026, Lapland University of Applied Sciences, Rantavitikka campus (Rovaniemi, Jokiväylä 11)

Materials

Study material is available on the Moodle learning platform.


Teaching methods

Lessons and exercises

Exam schedules

The number and date of exams will be agreed on during the course. Resit is possible by the end of the next term.

Completion alternatives

Studying independently is possible. All exercises must be returned in time to be evaluated.

Student workload

5 credits, approximately 133 hours of work

Assessment criteria, satisfactory (1)

You can compute the number of permutations and variations, solve easy probability tasks, calculate simple statistical parameters and present simple diagrams and find linear regression.

Assessment criteria, good (3)

You can solve a wide range of problems related to applications of probability and statistics. You can utilize many theorems and rules of probability. You can compute combinations and various descriptive parameters as well as quantiles. You can create and utilize binomial and continuous distributions. You are able to interpret correlation and perform linear regression and statistical significance tests.

Assessment criteria, excellent (5)

You can apply the theorems and rules of combinatorics and probability to new problems. You are able to apply different discrete and continuous parameters and distributions and create tests and predictions on your data.

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