A large majority of empirical research in social and health sciences follow parametric approaches to statistical analysis. Notwithstanding their popularity, parametric methods also limits the researcher in significant ways. The need to assume distributional structures can be limiting and may even lead to incorrect estimation. This workshop provides useful tools and analytical methods to conduct non-parametric analyses.
In the first part of this workshop, we will help you learn the key concepts in non-parametric statistics, areas of application and practical considerations for usage in research. Following this, we will cover common hypothesis testing methods within the non-parametric framework. In the latter half, we will have hands-on practice on kernel density estimation and non-parametric regression. All exercises are conducted with R.
Pre-requisites: Please refer to the pre-requisites guide.
Registration Required on Project Mosaic Calendar.
Presenter: Kailas Venkitasubramanian