|Course level||Advanced Bachelor/Master, open to PhD staff and professionals|
|Session 2||6 July to 20 July 2019|
|Recommended course combination
||Session 2: Programming in Python|
Session 3: Big Data Management and Analysis in Linux
|Co-ordinating lecturers||Dr Meike Morren|
|Other lecturers||Andrea Bassi|
|Form(s) of tuition||Interactive seminar|
|Form(s) of assessment||Programming assignments, final examination|
This course focuses upon understanding statistical models and analysing the results whilst learning to work with R. As well as introducing the software to newcomers, it presents basic and more advanced statistics using an overarching framework of the generalized linear model. We start with descriptive statistics and simple regression, before moving on to multiple regression.
Many problems in data analysis are related to dimension reduction, from data mining problems such as classification to analyzing survey answers. You will learn how to reduce data dimensions using principal component analysis and how to analyse multi-item scales using confirmatory factor analysis. Additionally, you learn how to treat missing data in various models.
Lastly we will introduce how to create and adjust plots in R. Every day consists of short lectures with examples, and exercises in which you apply what you have learned right away. Each week you are supposed to make an assignment which is graded. The focus in the exercises and assignment is the coding in R and how to apply and to interpret generalized linear regression models. By the end of the two weeks you are acquainted with numerous basic functions available in R can write your own functions and can use attractive plots to present your data.
At the end of this course you can:
Meike Morren has been an Assistant Professor of Marketing at VU University Amsterdam since 2012. She was trained as a sociologist and researcher at University of Amsterdam (UvA) and obtained her master degree by completing the research master in Social Sciences in 2006. In 2011, She defended her PhD in Methods and Statistics at Tilburg University treating a mixed methods study on the quality of survey questions. Since graduation, she focuses on green behavior and data quality in surveys in general. She has been published in Journal of Environmental Psychology, Sociological Methodology, Methodology, Cross Cultural Research and Field Methods. She teachs courses at bachelor and master level in statistics and methodology. The main topics are inferential statistics, survey methods, sampling methods, cluster analysis, factor analysis and regression analysis. While in most courses she uses SPSS syntax, in some courses she uses R.