Course information
Learning outcomes
After passing the course the students can conduct simple statistical analyses. They know how to calculate summary statistics and how to properly visualize data. Students are able to select suitable summary statistics and parameter estimators for different types of data sets and construct, e.g., bootstrap confidence intervals for parameters. Students are able to select suitable statistical tests for different testing settings. They know how to apply different t-tests, chi-square tests and nonparametric tests and understand the general statistical assumptions that are required for applying these tests. Students are able to detect different types of dependencies between variables and they are familiar with univariate and multivariate linear regression analysis. They can conduct linear regression analysis in practice and they understand the underlying model assumptions.
Content
The course is an introduction to statistical analysis and inference. Course topics include, but are not limited to, estimation, parametric and nonparametric tests, statistical dependence and correlation, and linear regression analysis. Software R is used in this course.
Teacher
Pauliina Ilmonen, Jukka Kohonen, Pekka Pere
Study material
Lectures slides and textbook Sheldon M. Ross, Introduction to Probability and Statistics for Engineers and Scientists (6th ed), Academic Press 2021.
Workload
Lectures 24 h (2), Exercises 24 h (2), Homework assignments 40 h, reading and studying the lecture materials 40 h
Prerequisites
Recommended prerequisites:
MS-A05XX First course in probability and statistics, MS-A00XX Matrix algebra
Evaluation
lectures, exercises and exam
Teaching time and location
The teaching time and the location of the course can be found in the Sisu information system.
- The link leads to Completion methods tab of the course page
- From the top of the page (Version drop-down menu), check that the academic year 2026-2027 is selected
- From the blue bar, choose the right teaching and open the Groups and study events tab to see the teaching time and location of the course. To see exam times, click Exam.
Exam instructions at the Open University
The teacher has four (4) weeks to grade the exam submissions starting from the exam date.
Other information
Equivalences to other courses:
Mat-2.2104 Introduction to Statistical Inference, MS-C2104 Introduction to statistical inference
Online learning environment for the course
The MyCourses online learning environment is a tool for both students and teachers for communication and managing everyday course work. You need an Aalto User ID to log in to the course's MyCourses workspace and participate in teaching.
Digital workspace of the course:
MyCourses
More details on completing the course will be available at MyCourses closer to the start of the course.
Registration and course fee
Registration for Open University courses is done via the link below:
Course registration
Registration for this course starts on 14.12.2026 at 9.00
Registration for this course ends on 18.1.2027 at 23.59
It is not possible to register before the registration period has started or after it has ended.
The number of participants is limited to 5.
This course is organized by the Aalto University School of Science.
The course fee is paid upon registration for each course at a time and it is binding. Familiarize yourself with registration and payment rules as well as other guidelines for students:
Registration, payments and rules
