Course Contents

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

Modes of Study and Registration

Independent work, only for CBDA-students.

Please see the Moodle page for details and instructions.

Contact teaching (lectures and excercises) is only in Finnish. For details, see the teaching schedule of the finnish version (MTTTA14 Tilastotieteen matriisilaskenta ja laskennalliset menetelmät). The lectures are based on study material which is available in English.

Content

This course covers some basic principles for designing experiments, topics related to linear models for an analysis of variance and analysis of covariance, and conducting an appropriate analysis of data from several types of experiments: completely randomized, randomized complete block, split plot and cross-over.

Modes of study

Participation in classroom work, exam.

Recommended preceding studies

MTTTP1 Introduction to Statistics or other basic course in Statistics.

Students can get support for their studies in Statistics from the workshop.

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.

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

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

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

Content

• Lecture I (75 minutes): Estimation based on (i) Complete Sample, (ii) Failure-Truncated Sample; Quiz I (30 minutes): Based on Lecture I.
• Lecture II (60 minutes): Estimation based on Time-truncated Sample; Quiz II (30 minutes): Based on Lecture II.
• Lecture III (60 minutes): Prediction of Future Observation(s) Based on Exponential Samples; Quiz III (30minutes): Based on Lecture III.

Modes of study

Participation in course work and a practical work.

Please also note visiting lecture:

Professor (retired), Bikas Sinha, Indian Statistical Institute

Topic: “F AM NOT LICKED” – The Twelve Penny Problem with Applications

• 2.11.2017 at 14.15–15.00, Pinni B3109.

Students can get support for their studies in Statistics from the workshop.

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.

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

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

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

Students can get support for their studies in Statistics from the workshop.

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.

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

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

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

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 special methods for the analysis of longitudinal data are presented including likelihood-based methods and multiple imputation.

Modes of Study

Course work, exam.

Ilmoittautuminen NettiOpsussa.

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.

TUT-students, to enrol please send e-mail to: mtt-studies@uta.fi

TTY:n opiskelijat hakeutuvat kurssille JOO-opiskelijoina. Ilmoittaudu ensin sähköpostitse osoitteeseen: mtt-studies@uta.fi

Students should bring their own laptops in practicals.

Students can get support for their studies in Statistics from the workshop.

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.

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

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

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