Open University

Tampere

Statistical Modeling 1, Lectures

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Advanced studies

Faculty of Information Technology and Communication Sciences

Technology and Natural Sciences

Apply for Open University studies by using the following links:<ul><li><a href="https://tau-avoin.ilmoittaudu.fi/lobby/?realization=J-otm-52631a63-188a-459e-b402-e4f4ba58a53c_2023-tampere-DATASTAT740" target="_blank">DATA.STAT.740 Statistical Modeling 1, lectures, Tampere</a></li></ul>You can find a link to the Open University Admissions service and application instructions on the <a href="https://www.tuni.fi/en/study-with-us/open-higher-education-studies/open-university/applying-open-university">Applying to Open University studies</a> page.Some of the studies require prior studies. For example, studying intermediate studies may require some completed basic studies. These are described on the Information about studies tab of the study unit under prior requirements.When you have been admitted to the studies, you must enrol separately via the Sisu information system for the implementation of the unit of study and, for example if set, for a practise group of your choice. You will receive instructions on how to do this by e-mail after you have confirmed your acceptance of the study place by paying the required fee.

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City Centre Campus

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Look information at <a href="https://www.tuni.fi/en/study-with-us/open-higher-education-studies/open-university/applying-open-university">Applying to Open University studies</a>.

Linear models, Nonlinear normal models, Nonnegative response models, Count data models, Categorical data models, Survival data analysis.

<h2>Common</h2><h3>Exercise: </h3>12.01.2024 12:00 - 14:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) 19.01.2024 12:00 - 14:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) 26.01.2024 12:00 - 14:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) 02.02.2024 12:00 - 14:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) 09.02.2024 12:00 - 14:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) 16.02.2024 12:00 - 14:00, TAU Pinni B0016 opetustila (41) 23.02.2024 12:00 - 14:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) <h3>Lecture: </h3>10.01.2024 10:00 - 12:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) 12.01.2024 10:00 - 12:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) 17.01.2024 10:00 - 12:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) 19.01.2024 10:00 - 12:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) 24.01.2024 10:00 - 12:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) 26.01.2024 10:00 - 12:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) 31.01.2024 10:00 - 12:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) 02.02.2024 10:00 - 12:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) 07.02.2024 10:00 - 12:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) 09.02.2024 10:00 - 12:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) 14.02.2024 10:00 - 12:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) 16.02.2024 10:00 - 12:00, TAU Pinni B0016 opetustila (41) 21.02.2024 10:00 - 12:00, TAU P&#228;&#228;talo A207 A3 auditorio (69) 23.02.2024 10:00 - 12:00, TAU P&#228;&#228;talo A207 A3 auditorio (69)

After the course, the student can apply modern statistical modeling tools especially for regression and classification problems. The student understands the theory of linear models and can form nonlinear models under normal distribution. The student is familiar with the theory of generalized linear models in the case of gamma and other positive distributions. The student knows how to model count data by Poisson regression models and zero-inflated models and understands the theory of logistic regression analysis. The student is also familiar with basics of survival data analysis.

<h2>Prerequisites</h2>Recommended preceding studies: Understanding of basics of statistics &nbsp;and probability. For example minimum of TUNI courses consists of DATA.STAT.110 Introduction to Statistics and MATH.APP.210 Introduction to Probability and &nbsp;Statistical Inference (or equivalent).

Alan Agresti (2015). Foundations of Linear and Generalized Linear Models. John Wiley &amp;amp; Sons Incorporated.

Statistical Modeling 1, Lectures

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Statistical Modeling 1, Lectures