# 107.A15 Methods in Applied Statistics This course is in all assigned curricula part of the STEOP.\$(function(){PrimeFaces.cw("Tooltip","widget_j_id_21",{id:"j_id_21",showEffect:"fade",hideEffect:"fade",target:"isAllSteop"});});This course is in at least 1 assigned curriculum part of the STEOP.\$(function(){PrimeFaces.cw("Tooltip","widget_j_id_23",{id:"j_id_23",showEffect:"fade",hideEffect:"fade",target:"isAnySteop"});}); 2023W 2022W 2021W 2020W 2019W 2018W 2017W 2016W 2015W 2014W 2013W 2012W 2012S

2023W, UE, 1.0h, 1.5EC

## Properties

• Semester hours: 1.0
• Credits: 1.5
• Type: UE Exercise
• Format: Hybrid

## Learning outcomes

After successful completion of the course, students are able to  (1) design experiments and analyze the resulting data; (2) carry out supervised and unsupervised statistical analysis of categorical data (survival function estimation, Cox proportional hazard regression) using the R programming language.

## Subject of course

COURSE OUTLINE

I. Design of Experiments

• Components of an experiment, terms and concepts
• Completely randomized designs: Models, parameter estimation, contrasts, checking assumptions
• Multiple comparisons
• Power and sample size
• Fixed, random and mixed models, nesting
• Variance reduction designs: complete block design, latin square
1. Categorical Data Analysis
• Categorical data: nominal vs ordinal
• Two-way contingency tables
• Three-way contingency tables
• Logistic regression
2. Survival Analysis
• Time to event data and censoring
• The survival and the hazard functions
• Survival function estimation
• Cox proportional-hazards regression model

## Teaching methods

### Three reference books are used:

• DOE: Design and Analysis of Experiments, 10th Edition by Montgomery (available at TU Library)
• Categorical Data: An Introduction to Categorical Data Analysis, Second Edition by Agresti (available online at the TU Library)

• Survival Analysis: Applied Survival Analysis, Second Edition by Hosmer, Lemeshow and May (available online at the TU Library)

Immanent

## Course dates

DayTimeDateLocationDescription
Tue13:00 - 14:0010.10.2023 - 23.01.2024HS 14A Günther Feuerstein Methods in Applied Statistics
Methods in Applied Statistics - Single appointments
DayDateTimeLocationDescription
Tue10.10.202313:00 - 14:00HS 14A Günther Feuerstein Methods in Applied Statistics
Tue17.10.202313:00 - 14:00HS 14A Günther Feuerstein Methods in Applied Statistics
Tue24.10.202313:00 - 14:00HS 14A Günther Feuerstein Methods in Applied Statistics
Tue31.10.202313:00 - 14:00HS 14A Günther Feuerstein Methods in Applied Statistics
Tue07.11.202313:00 - 14:00HS 14A Günther Feuerstein Methods in Applied Statistics
Tue14.11.202313:00 - 14:00HS 14A Günther Feuerstein Methods in Applied Statistics
Tue21.11.202313:00 - 14:00HS 14A Günther Feuerstein Methods in Applied Statistics
Tue28.11.202313:00 - 14:00HS 14A Günther Feuerstein Methods in Applied Statistics
Tue05.12.202313:00 - 14:00HS 14A Günther Feuerstein Methods in Applied Statistics
Tue12.12.202313:00 - 14:00HS 14A Günther Feuerstein Methods in Applied Statistics
Tue19.12.202313:00 - 14:00HS 14A Günther Feuerstein Methods in Applied Statistics
Tue09.01.202413:00 - 14:00HS 14A Günther Feuerstein Methods in Applied Statistics
Tue16.01.202413:00 - 14:00HS 14A Günther Feuerstein Methods in Applied Statistics
Tue23.01.202413:00 - 14:00HS 14A Günther Feuerstein Methods in Applied Statistics

## Examination modalities

Continuous assessment via oral examination and regular homework tasks throughout the semester.

## Course registration

Begin End Deregistration end
12.09.2023 08:00 13.10.2023 14:00 27.10.2023 08:00

## Curricula

Study CodeObligationSemesterPrecon.Info
033 203 Statistics and Mathematics in Economics Mandatory5. Semester
033 521 Informatics Mandatory elective
066 395 Statistics and Mathematics in Economics Mandatory elective

## Literature

No lecture notes are available.

## Previous knowledge

Probability and statistics at the level of Applied Mathematical Statistics; Calculus and Linear Algebra.

## Miscellaneous

• Attendance Required!

English