Basics of statistics (5 ECTS) TILM3582

This intensive course is an elementary course for students that have no knowledge or just a little knowledge of statistics and statistical methods.  It starts with terminology and descriptive methods like graphics and descriptive summing of data.  Using simple examples of some probability distributions participants will be leaded to get understanding of sample distributions for different type of variables.  And finally some basic statistical models will be introduced  and used in practicals.  

 

TOPICS OF THE COURSE

·         Terminology of statistics

·         Different types of quantitative studies

·         Types of variables

·         Data matrix

·         How to describe data with graphics, frequency tables and numbers?

·         Basics of probability distributions, sample measures and statistical inference

·         How to investigate associations and dependencies between variables?

·         How to compare groups?

·         How to interpret results?

·         Good way of reporting results

 

 

TEACHING METHODS AND EVALUATION

·         Lectures and group assignments (12 h)

·         Computer practicals (6 h)

·         Active participation in practicals (pass/fail)

 

TIMETABLE (week 51)

Lectures:

 

·         Mon 17.12.2018 10:00-11:30 QA, Auditorio Quantum

·         Mon 17.12.2018 12:00-13:30 XXI, Agora luentosali XXI

·         Tue 18.12.2018 10:00-11:30 QA, Auditorio Quantum

·         Tue 18.12.2018 12:30-14:00 QA, Auditorio Quantum

·         Wed 19.12.2018 10:00-11:30 QA, Auditorio Quantum

·         Wed 19.12.2018 12:30-14:00 QA, Auditorio Quantum

 

Computer practicals (6 h):

 

Group 1 (Quantum 111-112): 18 Dec 2018 08.15 - 09.45, 19 Dec 2018 08.15 - 09.45, 20 Dec 2018 08.15 - 09.45

Group 2 (Quantum 111-112): 18 Dec 2018 14.15 - 15.45, 19 Dec 2018 14.15 - 15.45, 20 Dec 2018 10.15 - 11.45

TEACHER

·         Lecturer Jouko Katajisto

 

LEARNING OUTCOMES

By the end of the course the student should be able to

·         understand the basic principles of statistics;

·         use suitable descriptive methods for different types of variables;

·         Form simple statistical models and interpret the results