This part of the Orientation Course is compulsory also to new Finnish students selected in spring 2018.

Teachers:

• Zheying Zhang (SDE)
• Jaakko Peltonen (CBDA)
• Martti Juhola (CBDA)

Maisteriohjelman, opetuksen ja ohjauskäytäntöjen esittely kandivaiheessa oleville opiskelijoille.

Tilaisuuteen osallistuminen ei edellytä ilmoittautumista.

This module is made up of class sessions including group work (20 hours), as well as independent out of class tasks (61 hours). The module will be three periods long and will take place in the autumn semester of the first year of the master’s degree programme.

If you wish to complete the course during the academic year 2018-2019, contact the teacher no later than March 15, 2019.

This module (54 hours) is online apart from individual teacher-student tutorials for discussion of the submitted thesis extract. The work consists of readings, group analysis tasks and thesis writing work. Students should take the module after their research proposal has been accepted by their programme and they are about to embark upon the writing of their thesis.

In cases where more students register for a course than space allows, priority is assigned as follows:

1. First priority is given to the degree students of the University of Tampere.
2. Second priority is given to the exchange students of the University of Tampere.
3. Third priority is given to the Tampere3 students and to the high school students of the UTA Teacher Training School.

In addition, there is a quota of 5 for the Open University students in every group.

In cases where more students register for a course than space allows, priority is assigned as follows:

1. First priority is given to the degree students of the University of Tampere.
2. Second priority is given to the exchange students of the University of Tampere.
3. Third priority is given to the Tampere3 students and to the high school students of the UTA Teacher Training School.

In addition, there is a quota of 5 for the Open University students in every group.

The course focuses on the basic and general features of scientific research, methodology, and argumentation, as applicable to any field of study. Some central themes in the philosophy of science will also be discussed, in an introductory manner.

The course is intended to all new international UTA Master’s degree students, but it will serve also international Doctoral students. Other degree and exchange students may join if there are free places.

Contact person: Coordinator of international education, Anna Wansén-Kaseva

Osallistuminen opetukseen, viikkoharjoitukset ja harjoitustyö sekä tentti.

Enroll on the course TIETA6 Data Structures in NettiOpsu

Self studying, weekly excercises, practical work, and exam.

Read about the recommended prior knowledge from the course website.

Course Contents

Matrix basic operations, random number generation, cross-validation, Jackknife, Bootstrap, use of the R program

Modes of Study and Registration

Independent work and exercises, mainly for CBDA-students.

Please see the Moodle page for details and instructions.

Lectures of the course MTTTA14 Tilastotieteen matriisilaskenta ja laskennalliset menetelmät are held only in Finnish. The lectures are based on study material which is available in English for independent study.

In the workshop students can get support for their studies in Statistics.

The idea is that students work independently or in groups with the problems that have arisen. The workshop has a teacher and you can ask for the advice from him. However, the idea is that the teacher will not solve the problems for you. The workshop does not provide any compensation of the solved exercises.

Support in using statistical software (e.g. SPSS and R) is also available in workshop.

Period I: especially for students taking MTTTA14 Matrices for Statistics and Computational Methods.

Period II: especially for students taking MTTTA2 Matemaattisen tilastotieteen perusteet.

Period III: especially for students taking MTTTA4 Statistical Inference 1.

This course explores methods for the analysis of longitudinal data and latent variable methods for linear models, generalized linear models, and nonlinear models.  Focusing on applications, this course explores: the analysis of repeated measures ANOVA, multivariate approaches, random-effects regression, covariance-pattern models, generalized-estimating equations and generalizations, latent variable methods including finite mixture modelling, and likelihood methods.  Students will develop expertise using the SAS and R computer packages, although no previous programming experience will be assumed.  Grading is based on homework and computer assignments and a project, as well as several exams.

Course begins with a lecture on Monday 17th of September.

There are three exams during the course.

Recommended preceding studies:

Basic courses of statistics and Regression analysis

If you are considering to begin the thesis work, it is a good time to enrol. It is recommended that you'd begin the seminar before you have agreed on the topic and/or supervisor of the thesis.

Students can enrol ANY TIME, not just at the beginning of the period. If enrolment is not open, contact the teacher by email.

Modes of study

- Lectures
- Exercises (independent work)
- Exam

Maisteriohjelman, opetuksen ja ohjauskäytäntöjen esittely kandivaiheessa oleville opiskelijoille.

Tilaisuuteen osallistuminen ei edellytä ilmoittautumista.

This module is made up of class sessions including group work (20 hours), as well as independent out of class tasks (61 hours). The module will be three periods long and will take place in the autumn semester of the first year of the master’s degree programme.

General description

Knowledge about statistical methods and data analysis is of great importance in almost any field of research. In this course, general concepts of statistics will be provided so that students can be able to independently carry out a small scale empirical research with the statistical software SPSS or R. After the course, students should be familiar with the basic concepts of statistics, ranging from descriptive statistics, basic inference (estimation, confidence intervals and hypothesis testing), linear models (analysis of variance, simple and multiple linear regression), non-parametric tests and logistic regression.

Space is limited in this course due to computer room capacity. Priority will be granted for the first enrolments, based on the proportions: 60% PhD students and 40% for BSc and MSc students.

Please note that this course cannot be included inside the minimum 120 ECTS of Master's Degree Programme in CBDA (basic level course).

MTTTP1 Tilastotieteen johdantokurssi lectured in period I, II or III-IV is recommended for Finnish students.

If needed, priority is given to the students in CBDA

In cases where more students register for a course than space allows, priority is assigned as follows:

1. First priority is given to the degree students of the University of Tampere.
2. Second priority is given to the exchange students of the University of Tampere.
3. Third priority is given to the Tampere3 students and to the high school students of the UTA Teacher Training School.

In addition, there is a quota of 5 for the Open University students in every group.

Schedule:

16.1. Seija-Leena Nevala: Finland – 101 years of Independency

23.1. Katja Keisala: How to Communicate in Finland

30.1. Johanna Peltoniemi: Finnish Political System

6.2. Juho Kaitajärvi-Tiekso: Finnish Popular Music from "Humppa" to Lordi

13.2. Hannu Sinisalo: Boundaries of Finnishness and Ethnic Minorities in Finland

20.2. Marko Seppänen: Finnish Innovations - Past, Present and Future

27.2. no lecture

6.3. Tuija Koivunen: Women, Men and Work

13.3. Ari Vanamo: Finnish Forests and Forestry

20.3. Lina van Aerschot: Finnish Welfare and Social Services

27.3. Raisa Harju-Autti: Finnish Education System

3.4. Katja Fält: Finnish Art History in a Nutshell

10.4. Arja Luiro: Finnish Gastronomy

17.4. Jyrki Jyrkiäinen: Special Features of Finnish Mass Media

24.4. exam

+ the date of retake exam will be announced later

Please enrol before the first lecture (16.1).

The course focuses on the basic and general features of scientific research, methodology, and argumentation, as applicable to any field of study. Some central themes in the philosophy of science will also be discussed, in an introductory manner.

The course is intended to all new international UTA Master’s degree students, but it will serve also international Doctoral students. Other degree and exchange students may join if there are free places.

Contact person: Coordinator of international education, Anna Wansén-Kaseva

Modes of study

- Lectures
- Exercises (independent work)
- Exam

Contents

- Introduction to functional and shape data analysis with R and Matlab

- Functional principal component and canonical correlation analysis

- Linear and mixed models for functional and shape data sets

- Linear differential operators in functional data analysis

- Procrustes analysis in statistical shape analysis

- Shape distributions

TTY:n opiskelijat ilmoittautuvat kurssille ristiinopiskelupalvelun ohjeiden mukaisesti.

Recommended preceding studies:
Understanding of basics of statistics and probability. For example minimum of UTA courses consists of MTTTP1 Introduction to Statistics and MTTTP5 Basics of Statistical Inference (or equivalent).

Note one exercise group in Central campus (Pinni B ML40) on Fri 10-12.

In TUT POP portal.

This course is organized by TUT and UTA students must

1. Apply for study right through Service for Cross-Institutional Studies.
2. Make sure to apply for the right to study well in advance so that you have enough time to also activate the user account of TUT and
3. to sign up for the studies according to the schedules of TUT.

Read carefully the UTA instructions

This course cannot be taken if student has done TIETS39 Machine Learning Algorithms.

Note. The prerequisite SGN -courses are not required from UTA students.

Recommended preceding studies: Data Structures, basics of statistics, basics of mathematics and linear algebra.

NOTE, contact teaching (lectures and excercises) is in Finnish. The lectures are based on study material which is available in English. Weekly exercises will be available in English and are to be sent to the teacher.

For summer course see Weto

See instructions on coursepage.

Read about the recommended prior knowledge from the course website.

Content

It is quite common that we do not get all the information we want for  our statistical analysis. For example, in medical research a person can  refuse to provide certain information they feel sensitive, such as  weight, substance abuse, sexual orientation etc. Particularly, missing  data in longitudinal studies is more the rule than an exception. Missing  data in statistical analysis causes all sorts of problems. For example,  the desired statistical method cannot be directly applied; loss of  information or the results obtained can be biased if the analysis is not  done properly accomplished. The course introduces various missing data  mechanisms and their effects on statistical analysis. In addition, it  presents and evaluates some of the commonly used methods for statistical  analysis with missing data. Also advanced methods are presented, as well as special methods for the analysis of  longitudinal data including likelihood-based methods and multiple imputation.

Modes of Study

Course work, exam.

This course is an advanced study version of MTTA2 Statistical Analysis with Missing Data, and the student can only complete one of the two versions.