# 107.329 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"});});

2019W, VO, 3.0h, 4.5EC

## Properties

• Semester hours: 3.0
• Credits: 4.5
• Type: VO Lecture

## 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 (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: A First Course in Design and Analysis of Experiments by Oehlert; Fundamental Concepts in the Design of Experiments , Fifth Edition by Hicks and Turner.
• 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)

Written

## Course dates

DayTimeDateLocationDescription
Wed11:00 - 12:3002.10.2019Sem.R. DB gelb 04 Lecture (Bura)
Mon11:00 - 12:3007.10.2019 - 27.01.2020Sem.R. DA grün 06A Lecture Bura
Wed11:00 - 12:3009.10.2019 - 29.01.2020Sem.R. DA grün 06A Lecture (Bura)
Methods in Applied Statistics - Single appointments
DayDateTimeLocationDescription
Wed02.10.201911:00 - 12:30Sem.R. DB gelb 04 Lecture (Bura)
Mon07.10.201911:00 - 12:30Sem.R. DA grün 06A Lecture Bura
Wed09.10.201911:00 - 12:30Sem.R. DA grün 06A Lecture (Bura)
Mon14.10.201911:00 - 12:30Sem.R. DA grün 06A Lecture Bura
Wed16.10.201911:00 - 12:30Sem.R. DA grün 06A Lecture (Bura)
Mon21.10.201911:00 - 12:30Sem.R. DA grün 06A Lecture Bura
Wed23.10.201911:00 - 12:30Sem.R. DA grün 06A Lecture (Bura)
Mon28.10.201911:00 - 12:30Sem.R. DA grün 06A Lecture Bura
Wed30.10.201911:00 - 12:30Sem.R. DA grün 06A Lecture (Bura)
Mon04.11.201911:00 - 12:30Sem.R. DA grün 06A Lecture Bura
Wed06.11.201911:00 - 12:30Sem.R. DA grün 06A Lecture (Bura)
Mon11.11.201911:00 - 12:30Sem.R. DA grün 06A Lecture Bura
Wed13.11.201911:00 - 12:30Sem.R. DA grün 06A Lecture (Bura)
Mon18.11.201911:00 - 12:30Sem.R. DA grün 06A Lecture Bura
Wed20.11.201911:00 - 12:30Sem.R. DA grün 06A Lecture (Bura)
Mon25.11.201911:00 - 12:30Sem.R. DA grün 06A Lecture Bura
Wed27.11.201911:00 - 12:30Sem.R. DA grün 06A Lecture (Bura)
Mon02.12.201911:00 - 12:30Sem.R. DA grün 06A Lecture Bura
Wed04.12.201911:00 - 12:30Sem.R. DA grün 06A Lecture (Bura)
Mon09.12.201911:00 - 12:30Sem.R. DA grün 06A Lecture Bura

## Examination modalities

The final exam will include 70% and a data analysis project (30%).

## Exams

DayTimeDateRoomMode of examinationApplication timeApplication modeExam
Fri - 29.01.2021Sem.R. DA grün 06A written17.12.2020 10:00 - 27.01.2021 23:55TISS1. Prüfungstermin - 2019W - 31.01.2020
Fri - 05.03.2021Sem.R. DB gelb 04 written30.01.2021 10:00 - 03.03.2021 23:55TISS2. Prüfungstermin - 2019W - 06.03.2020
Thu - 27.05.2021written30.04.2021 10:00 - 25.05.2021 23:55TISS3. Prüfungstermin - 2019W - 28.05.2020

## Course registration

Begin End Deregistration end
30.08.2019 09:00 12.10.2019 14:00

## Literature

Es wird ein Skriptum zur Lehrveranstaltung angeboten.

## Previous knowledge

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

English