- Knowledge in statistics is key for understanding and conducting scientific research. It is important to have basic statistical literacy in order to design experiments, analyze data and eventually present results and draw reasonable conclusions.
Statistical analysis can be performed by using a script-based software, which guarantees the traceability and reproducibility of statistical analyses. The software R is optimal for this, since R provides access to a very broad range of (up-to-date) statistical methods, and is also open source. Furthermore, R is the dominating programming language for statistical analyses in Academia and is also widely used in industry.
Ascertainment of reproducibility is important for evidence-based science and therefore of central concern to scientists.
- For doctoral researchers and PostDocs who were recruited based on a job offer released on 01/01/2019 or later the participation in the following courses is mandatory:
- It is recommended to first participate in the course “Introduction to R” and afterward in “Introduction to Statistics” since the exercises of the statistics course require knowledge of R. The course “Reproducible and Open Research” formally does not depend on participation in the other two courses, but it is advantageous to have knowledge in programming and statistics. Moreover, it is recommended to participate in all three courses during the first year as a doctoral researchers or PostDoc at Helmholtz Munich.
- HELENA students may also check the description of the program here.
- For questions concerning the approval of already existing programming skills and/or knowledge in statistics please email us.
- To apply for the approval of already existing and verifiable programming (R or Python) and/or statistics knowledge, please read the following documents carefully.
Checklist for the approval of courses in 3 steps
1. Decision for approval:
It might happen that you know the content of the courses offered by the Core Facility Statistical Consulting from other lectures or courses. Nevertheless, we recommend you to refresh your knowledge in our courses. So please think about how good your statistical knowledge really is before you apply for approval. In general, we would only recommend this if you hold a degree from a related discipline like statistics or epidemiology. Doctoral researchers should also consider that after a successful approval credit points of the same amount must be earned in in other courses of the HELENA program. In doubt please don’t hesitate to ask us.
2. Required documents:
You need the following documents:
- The form for the approval of foreign-earned credit
- Course description including an overview of the course content
- A copy of the certificate of attendance, transcript of records, or similar
All documents must be submitted either in German or English. If necessary, provide a translation.
The description of the course should be extracted from the module manual or workshop description. The part referring to the relevant course should be extracted and/or marked.
3. Submit the Application:
The application can either be submitted in the original version, or as a scan. The digital version is preferred.
The application should be addressed to:
Kainat Khowaja via email
Core Facility Statistical Consulting
Helmholtz Zentrum München
Ingolstädter Landstr. 1
FAQ for approval of courses
General Remark: In general, the examination regulations of your program of studies are valid. Changes in these regulations will be applied. Thus, previous approvals may become invalid. Similarly, this information sheet may become outdated. Therefore, please read the examination regulations carefully to finish your studies with success.
Question 1: What does approval of modules mean?
If you already know the contents that are presented in the Statistics and/or Programming courses of the Core Facility Statistical Consulting previously (from Bachelor studies, Master studies, Workshops, or similar) and you don’t want to refresh your knowledge, you may apply for approval of these courses. If this application is accepted, you don’t need to attend the courses. However, doctoral researchers will have to attend other courses from the HELENA program. The current course program of HELENA can be found here.
Question 2: What do you mean with “course description”?
The description of the original course as it was announced. This could be an excerpt of the module handbook, an announcement of the workshop, or similar. An official document that contains a description of what was done in the course and how much time was spent on the course.
Question 3: Are there precedents?
There is no published list of precedents. We check each case separately. However, we try to be as fair as possible.
Question 4: Do you have to provide an approval of a course?
No! Most courses will be accepted. However, you have to specify in your application as detailed as possible how your previous courses cover the topics of our courses.
Question 5: How do you convert my grades?
Not at all. There are no exams in our courses and therefore no grades.
Question 6: Will you only approve previous knowledge in R or also in other statistical software?
We approve verifiable knowledge in other script based statistical software such as SAS, Stata, Matlab or Python. Knowledge in statistical software which is not script based such as SPSS, GraphPad Prism or SigmaPlot will usually not approved. In case of approval, please be aware that all our statistics courses (also the advanced ones) are based on R. The reproducibility course does not require previous knowledge of R.
Question 7:Are introductory statistics courses from the Bachelor usually recognized?
In general, introductory statistics courses from the bachelor's program are not recognized. The aim of the obligation rule is to ensure that all doctoral researchers have an active knowledge of statistics. This is necessary to correctly classify and interpret the results of their research projects. Active Statistical knowledge is necessary to ensure reproducible research. Therefore, generally, only current courses, i.e. from the Master's program, are recognized. However, if statistical methods were applied in the further course of the study, e.g. in the context of the master thesis, a publication or another (published) project, an approval of this knowledge is also possible.
Question 8:In my Bachelor studies I heard a lecture very similar to the course "Introduction to Statistics", but in my Master studies I heard only advanced statistics courses which do not fit to the content of the course "Introduction to Statistics". Which course should I include in the application for credit?
The easiest way to check for equivalency is to indicate both courses. The introductory Statistics course for content match and the advanced course for evidence that the statistics knowledge was actively held.
Question 9:Can only classical courses / lectures with exam be approved?
No. Other certificates such as master's theses or scientific publications can also be approved. In each case, however, it must be clearly evident that the applicant has performed the main work in terms of the achievements to be approved. For example, a scientific publication must contain an “Authors contributions” list.
Question 10: I have more questions, that are not answered here. What can I do?
Write an email to Kainat Khowaja
Please use the form attached at the top of the page to request the approval of foreign-earned credit.