All MARUG courses are for MARUG members only. Not a MARUG member yet? Become a member!
Since the academic year 2014-2015, the MARUG offers each block a course to all members. These courses can help you develop your academic skills. The four courses, with different subjects and lengths, are an addition to your regular courses and broaden your knowledge. Since the academic year 2017-2018, the MARUG offers all courses in English!
This course is a perfect for every student that wants to improve or freshen up his or her basic SPSS skills. The course is given by Elly Jannink. She will be able to give you good personal training, since the group only consists of 22 students. At the end of the course, you will get a SPSS certificate and you will be much more confident in working with SPSS.
During the course you will receive assignments about the different facets of SPSS. The following topics will be discussed:
- Data analyisis
- Defining variable (a.o. types, missing values, measuring levels)
- Manipulating variables and data (a.o. recode, compute variable, date and time wizard, count values within cases, select cases, split file)
- Statistics (t-test, Mann-Whitney U-test, Wilcoxon signed rank test, One-Way ANOVA, Cross tables, Chi2-test, Pearson correlation, Spearman correlation, regressive)
- Marking and adapting graphs
- Implementing results in a report
- Reading into existing data
The costs of the SPSS course amount to 30 euros. The course will consist of 3 three-hour sessions. These sessions will take place at Zernike and will be scheduled in such a way that the clashes with the MSc Marketing are limited. The course will be given in the first three weeks of the semester. The course is for MARUG members only. Not a member yet? You can subscribe here.
The sessions will be on the following dates:
Friday 7 September from 13.00 till 16.00 in room 5415.0031
Monday 10 September from 11.00 till 14.00 in room 5415.0042
Friday 14 September from 15.00 till 18.00 in room 5415.0042
In the second block, an R Course will be organised. During this course, we will introduce you in R and we will guide you through all the steps needed to process raw data into a (predictive) model. The course will consist of 5 modules (the first module should be completed at home). At the end of the course, you will have improved your analysis capabilities and you will be able to build your own model. Furthermore, you will go home with an official certificate.
The first module is an introduction to the language R. You will learn the fundamentals of this statistical modelling language. You will get to know what vectors, data frames and matrices are and how to handle factors. Furthermore, you will extract basic summary statistics and create some graphs.
The second module will start with an introduction to Rstudio, which is an IDE for R. You will be shown how to set up projects and how to install packages. You will be going to load, explore and subset data and create some more graphs.
The third module will be about data types and how to handle numerical values which are actually categorical. It will be discussed how to handle missing values, what the apply-function does in data frames and you are going to create some new variables by using if-then-else statements, computations and transformations.
This module focuses on necessary data preparation steps for modelling. During this module, you will dive deeper into handling outliers. The imputation methods for missing values for different types of variables will be dicussed. Next to that, the focus will be on correlations, correlation plots and correlated predictor variables (multicollinearity).
Now you have learned how to process data, it is time to start modelling. You are going to build a decision tree. Building a decision three is not that hard and it can provide you a lot of insights in patterns in the data. Next to that, you are going to build a logistic regression and it will be shown how you can build practically every model you want. Of course model evaluation can not be left out, so classification tables and AUC will be discussed as well and some plots will be created.
The sessions will be on the following dates:
Monday 12 November (session at home)
Monday 19 November from 18.00 till 21.00/22.00 in room 5415.0032
Monday 26 November from 18.00 till 21.00/22.00 in room 5415.0032
Monday 3 December from 18.00 till 21.00/22.00 in room 5415.0032
Monday 10 December from 18.00 till 21.00/22.00 in room 5415.0032
Subscribe here for the R course!
The course for the second block has not been confirmed yet.
The course for the fourth block has not been confirmed yet.