Syllabus

Credits: 6

Schedule: 07.01.2020 - 18.02.2020

Teacher in charge (valid 01.08.2018-31.07.2020): 

Tuukka Saarimaa

Matti Sarvimäki

Otto Toivanen

Teaching Period (valid 01.08.2018-31.07.2020): 

III Spring (2019-2020)

Learning Outcomes (valid 01.08.2018-31.07.2020): 

After this course, the student will have a basic understanding of the use of statistical methods in the analysis of economic phenomena.

Content (valid 01.08.2018-31.07.2020): 

Measuring economic phenomena. Summarizing economic data using descriptive statistics: mean, median, covariance, histogram. The use of actual economic data: register data, public databases, big data. Understanding statistical dependence and causality.

Assessment Methods and Criteria (valid 01.08.2018-31.07.2020): 

Final examination and exercises.

Exam will be changed to home exam.

Spring 2020 re-take exam replaced by independent project.

Workload (valid 01.08.2018-31.07.2020): 

In total 160h, consisting of lectures and exercise sessions and independent work.

Spring 2020 re-take exam replaced by independent project.

Study Material (valid 01.08.2018-31.07.2020): 

Lecture notes and other suitable material.

Prerequisites (valid 01.08.2018-31.07.2020): 

31A00110 Taloustieteen perusteet or ECON-A2100 Principles of Economics
I and ECON-A2200 Principles of Economics II or equivalent studies

Grading Scale (valid 01.08.2018-31.07.2020): 

0-5

Registration for Courses (valid 01.08.2018-31.07.2020): 

via WebOodi

Further Information (valid 01.08.2018-31.07.2020): 

A maximum of 60 students can be accepted to the course. Priority is given to:
1. Students in BSc programme in Economics (quota 40 students)
2. Students in BSc programme in Science and Technology and Students
in BSc programme in Design (quota 5 students)
3. Other Aalto students (quota 15 students)
In each quota students are selected in the order of enrollment. If a given quota
is not filled, more students from other quotas can be accepted to the course.

Description

Registration and further information