Biostatistics
This course deals with simple quantitative and graphical approaches as well as with more complex methods of biostatistics. Practical applications of the methods and exercises will be taught in R and RStudio (installation instructions are provided in the first exercise).
Content:
Descriptive statistics, probability theory and design of experiments, hypotheses testing, confidence intervals, correlation, simple and multiple linear regression, classification and prediction, diagnostic tests, measurements of agreement.
Organisation:
Slides and exercises with solutions along with literatur links are provided as learning material on this website. However, the course lives from interactions and discussions during the lectures and exercises. There is no obligation to visit the lectures and/or exercises to attend the exam, but the exam requires sound understanding of the concepts that are taught.
For questions and communication, please use Discord (https://discord.com/). Please use this channel and not emails for communication or ask your questions directly after the lecture.
Target group:
The course is tailored for master students of medical physics. However, interested master students from other programs and PhD students can attend and take the exam as well.
Please note that for the current WS 2020 the course is already fully booked, and it is not possible to book the course for students outside the target group anymore. Only registered students are allowed to participate in the exercises and to take the exam.
Dates:
Start/End date: 15.09.2020 - 15.12.2020
Lectures: Tuesdays, 10:00 - 11:45 (VIA ZOOM)
Exercises: Tuesdays, 17:00 - 17:45 (Discord)
Question hour and Test exam: Tuesdays, 1.12.2020, 10:00 - 11:45 (VIA ZOOM)
Exam: Tuesday, 8.12.2020, 10:00
Exam:
The exam will be a 60 minute MC quiz. There will be the same exam for all students. PhD student will have no extra/oral exam. PhD students aiming to earn ECTS with this course need to clarify with the head or direct advisor of their PhD program if they obtain the credits by passing the standard written MC exam.
The exam will happen via Moodle and will be open book. This means that you are allowed to use all the material from the lectures, exercises and additional books and notes. Browsing in the internet during the exam is not allowed and will result in a failing grade. In addition, it is not allowed to contact any other person during the exam, the mobile phone must be turned off. More information on the organization of the test exam and the exam is available in the following document: info_exams
Learning Material:
| Week | Date | Topics | Lectures notes | Exercises | Literature |
|---|---|---|---|---|---|
| 01 | Tue, 15.09.2020 | Introduction & Basics | slides_01_presented | video | ex_01 | ex_01_sol | HSAUR3_Ch01 |
| 02 | Tue, 22.09.2020 | Descriptive statistics for continuous data | slides_02_presented | video | ex_in_class_02 | ex_in_class_02_sol | ex_02 | survey.csv | ex_02_sol | HSAUR3_Ch02 |
| 03 | Tue, 29.09.2020 | Distributions & CIs | slides_03_presented | video_part1 | video_part2 | ex_in_class_03 | ex_in_class_03_sol | ex_03 | ex_03_sol | IPSUR-distributions |
| 04 | Tue, 06.10.2020 | CIs, paired and unpaired tests, p-value | slides_04_presented | video | ex_in_class_04 | ex_in_class_04_sol | ex_04 | training.txt | ex_04_sol | HSAUR3_Ch04 |
| 05 | Tue, 13.10.2020 | Binomial test, sample size calcualtion, multiple testing | slides_05_presented | video | ex_in_class_05 | ex_in_class_05_sol | ex_05 | ex_05_sol | s. last week |
| 06 | Tue, 20.10.2020 | Relative Risk, Odds Ratio, study types, independence test for a categorical variables: Chi-square, Fischer exact test | slides_06_plan | video | ex_in_class_06 | ex_in_class_06_sol | ex_06 | coffee.csv ex_06_sol | s. last week |
| 07 | Tue, 27.10.2020 | Diagnostic tests, Performance measures: Sensitivity, Specificity, Positive Predictive value | slides_07 | video | ex_in_class_07 | ex_in_class_07_sol | ex_07 | ex_07_sol | |
| 08 | Tue, 03.11.2020 | Correlation measures and introduction to linear regression models | slides_08_presented | video | ex_in_class_08 | ex_in_class_08_sol | ex_08 | ex_08_sol | HSAUR3_Ch06 |
| 09 | Tue, 10.11.2020 | Tests and CI in lin regression, multiple linear regression | slides_09 | video | ex_in_class_09 | ex_in_class_09_sol | ex_09 | catheter.rda | ex_09_sol | s. last week |
| 10 | Tue, 17.11.2020 | Logistic regression | slides_10 | video | in-class_ex10 | ex_in_class_10_sol | ex_10 | coffee.csv | ex_10_sol | |
| 11 | Tue, 24.11.2020 | Tree Models, Random Forest | slides_11 | video | ex_in_class_11 | ex_in_class_11_sol | ex_11 | test.fgl.RData | train.fgl.RData | ex_11_sol | |
| 12 | Tue, 01.12.2020 | Q&A, Test Moodle Exam | |||
| 13 | Tue, 08.12.2020 | Exam via Moodle | |||
| 14 | Tue, 15.12.2020 | Causality | slides_14 | | No exercises |