Statistical inference

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 statistical inference. Course topics include estimation, simple parametric and nonparametric tests, statistical dependence and correlation, linear regression analysis and analysis of variance. Software R is used in this course.

Teacher

Jukka Kohonen, Pauliina Ilmonen, Pekka Pere

Study material

Lectures slides and the textbook Sheldon M. Ross, Introduction to Probability and Statistics for Engineers and Scientists (5. p), Academic Press 2014.

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 at Sisu information system

1. The link leads to Completion methods tab of the course page
2. From the top of the page (Version drop-down menu), check that academic year 2025-2026 is selected  

3. From the blue bar, click Lecture and open the Groups and teaching times tab to see the teaching time and the location of the course. Exam times can be seen by clicking Exam.
    

   Exam instructions at the Open University

The teacher has four (4) weeks to grade the exam submissions starting from the exam date.

Further information

Equivalences to other courses: Mat-2.2104 Introduction to Statistical Inference, MS-C2104 Introduction to statistical inference

Online learning environment for the course  

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 8.12.2025 at 9.00  
Registration for this course ends on 12.1.2026 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

Activating Aalto ID and Multifactor Authentication

You can activate your Aalto User ID the day after the registration and you should activate it no later than the day before the start of the course.
Instructions for activating your Aalto user ID

Once you have activated your Aalto user ID, also enable multifactor authentication. Some of Aalto University's services require multifactor authentication.

Instructions for using Multifactor Authentication