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Statistical Methods with SPSS

Module name (EN):
Name of module in study programme. It should be precise and clear.
Statistical Methods with SPSS
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Mechatronics and Sensor Technology, Bachelor, ASPO 01.10.2020
Module code: MST2.SPS
Hours per semester week / Teaching method:
The count of hours per week is a combination of lecture (V for German Vorlesung), exercise (U for Übung), practice (P) oder project (PA). For example a course of the form 2V+2U has 2 hours of lecture and 2 hours of exercise per week.
-
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
5
Semester: 5
Mandatory course: no
Language of instruction:
German
Assessment:
 


[updated 29.04.2024]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

BMT2522.SPSS Biomedical Engineering, Bachelor, ASPO 01.10.2018 , semester 5, optional course
BMT2522.SPSS Biomedical Engineering, Bachelor, SO 01.10.2025 , semester 5, optional course
MST2.SPS Mechatronics and Sensor Technology, Bachelor, ASPO 01.10.2020 , semester 5, optional course
Workload:
Workload of student for successfully completing the course. Each ECTS credit represents 30 working hours. These are the combined effort of face-to-face time, post-processing the subject of the lecture, exercises and preparation for the exam.

The total workload is distributed on the semester (01.04.-30.09. during the summer term, 01.10.-31.03. during the winter term).
The total student study time for this course is 150 hours.
Recommended prerequisites (modules):
None.
Recommended as prerequisite for:
Module coordinator:
Prof. Dr. Gerald Kroisandt
Lecturer: Prof. Dr. Gerald Kroisandt

[updated 24.10.2023]
Learning outcomes:
This course will introduce statistical methods for the design of experiments and the evaluation of technical, biological and medical data.
The course uses practical examples that enable the students to understand the background and correctly apply statistical methods in complex contexts and interpret their results correctly.
Students will be given an overview of the various possibilities, application contexts and risks. After successfully completing this course, students will be able to use the statistics software SPSS.

[updated 29.04.2024]
Module content:
1. Biometrics and epidemiology - what are they?
2. Study design, most important types of studies
   randomized studies, field studies, cross-sectional studies, cohort studies, etc. and dependent and dependent samples)
3. Introduction to SPSS
4. Importance of frequencies, risk analysis and forecasting
   (How often does a disease occur? Normality or deviation? Is the patient sick or healthy?
    What are the risk factors for a disease? What are the consequences of a disease? Evidence-based medicine)
5. Properties of point estimators, special point estimators
6. Tolerance ranges
7. Statistical hypothesis tests
   (null hypothesis, alternative hypothesis, 1st type error,  2nd type error,  statistical significance,
    one- and two-sided test, two- and multiple-sample tests, parametric and non-parametric,
    tests for dependent and independent samples, t-tests, non-parametric methods, etc.)
8. ANOVA (analysis of variance)


[updated 29.04.2024]
Recommended or required reading:
 


[updated 29.04.2024]
 
[Fri Dec 27 18:00:14 CET 2024, CKEY=bsmms, BKEY=mst4, CID=MST2.SPS, LANGUAGE=en, DATE=27.12.2024]