Statistics with R

We were asked for text book recommendations for those of you who wish to go deeper on some topics, so here is a short list with comments

• van der Vaart, A., Bijma, F., & Jonker, M. (2017). An introduction to mathematical statistics. Focusing on mathematical foundations, you will learn how different estimation methods work. A lot of exercises for different distributions are provided along with the solution. It is available as an ebook from the SULB page from the University network.
• Gałecki, Andrzej and Tomasz Burzykowski (2013). Linear Mixed-Effects Models Using R : A Step-by-Step Approach This applied book not only covers lmes, but actually starts with linear models. It is available as an ebook from the SULB page from the University network.
• Faraway, Julian James (2006). Extending the Linear Model with R: generalized linear, mixed effects and nonparametric regression models. A standard reference for mixed effect models in R, no ebook version.
• Agresti, Alan (2004). Categorical Data Analysis. This is an easy to understand book, which covers categorical data analyses techniques at all levels (chi square, logistic regression, generalized linear mixed effect models, cumulative logit etc). A pdf version can be found via google scholar.

For next week's introduction to Bayesian statistics, we assigned you a datacamp course to be completed until January 27. In that week, there will be no class and homework sheets to solve. We would like to use the tutorial session instead to discuss the model solutions of the sample exam questions and to practise a little more. However, if you have specific topics, you would like to see more explanations or examples of, please feel free to contact your tutor about it.

This week, tutorials will be regular with class sheet and homework sheet 10, while class sheet and homework sheet 11 will be published in the week of January 27.

In the tutorial session in the first week of February, we will discuss solutions on the second batch of sample exam questions and will have again time to answer individual questions or see more examples.

 

Thank you for taking the time to provide your feedback in our tutorial evaluation (btw the poll is still open, if you want to answer and haven't done so already)!

We were happy to learn that, in general, students feel that they profit from the tutorials in their current format, although some students noted that it is difficult to accommodate an obligatory tutorial.

 

There were a couple of points mentioned (reformulated below), we would like to comment on:

1. "The strict attendance of tutorials is not feasible in winter, because of flu season"
Please note that your absence will not be counted as a fail, if you provide a doctor's certificate for your tutorial time! You can find more information on this in the FAQ and in the Lecture Modalities (Materials section on cms)

2. "Tutorials should be used to present the solutions of prior sheets."
The last 30 minutes of the tutorials are already reserved for that - if you want to see more details, please feel free to contact your tutor about it. In the past, we have presented solutions in great detail in tutorials, but attendance was low.

3. "Tutorials should be used to explain how to approach a problem and solve it accurately to prepare us for the exam"
While working on the class sheets, you are highly encouraged to talk to your tutor and ask for guidance, whenever needed. If you don't know how to approach a problem, they can give you hints and you are welcome to ask for more details in the last 30 minutes of the tutorial slot. We believe that solving class sheets and homework sheets is indeed the best possible preparation for the exam.

As we have changed the format of the tutorials and admission criteria this year, we would love to get your opinion on that.

For completeness, it would be helpful, if many of you could answer it, even if you are no longer following the course (or never did). This is not the official qualis evaluation, but more targeted at our specific adjustments.

https://forms.gle/G6Q3SynJPiDAQDce9

There will be no lecture this week, no tutorial sessions and no homework sheets.

We do offer two office hours, which you are welcome to visit to discuss any open questions with regard to lecture content or homework/class sheet exercise.

Since we still have a lot of fluctuation, it is ok this week to work with students from other groups, that you have worked with during last week's tutorial. The maximum number of students allowed to work together is 4! Please make sure to put the names of ALL students that collaborated on the top of the homework sheet. Also, make sure that you upload the solution for all official AssignmentTeams that were involved, e.g.

Student 1&2 from AssignmentTeam #75 work with student 3 from AssignmentTeam #85 (the other students from these AssignmentTeams were not in the Tutorial and/or did not react to emails). The top of the homework sheet has the names of students 1,2, and 3 and states that they are from different AssignmentTeams. Student 1 uploads the solution for Team #75 and student 3 uploads the identical solution for Team #85.

We will hopefully finalize Teams in the coming week during tutorials, so make sure to tell your tutor in case you can't make it,  but still wish to remain part of your team.

Best wishes and enjoy the holiday tomorrow,

the StatR team

Due to the public holiday on Friday, there will be no tutorial sessions and no class sheet this week.

There is a homework sheet that has to be submitted on Saturday.

We offer two office hours on Thursday (9:00 and 10:00 in SR 107). Please come there if you have questions regarding the homework sheet or the lecture. Next week, we will resume with tutorials as normal.

Please note, that you can also find this information in the timetabel on cms.

We have grouped all remaining students. If you do NOT wish to submit assignments, please drop me a line and I will remove you from your current group.

Also, please get in touch if you have admission to the exam already. We will check your status and remove you from assignment groups (you are of course welcome to work on assignments individually, but you don't need to hand them in).