@inbook{a1a566a47a1745a392df2c17afad3a38,
title = "Bayesian Statistics in the Research Field of Professional Learning and Development",
abstract = "This chapter will discuss issues related to analysing empirical data in the research field of professional learning and development using Bayesian statistics. It will start by briefly explaining why the frequentist (so-called classical) approach to analysing empirical data in professional learning and development research is so popular. Also, some conditions when this approach might not be the best solution is discussed and contrasted to the Bayesian approach. The essentials of Bayesian statistics are described and some practical examples of its application are provided. A major part of this chapter is devoted to an example of applying Bayesian statistics in the context of multilevel path analysis. This chapter concludes with a discussion of using Bayesian methods in professional learning and development research and its potential future views.",
keywords = "Bayesian statistics, Multilevel path analysis, Professional learning and development",
author = "Petri Nokelainen and Aldahdouh, \{Tahani Z.\} and Aldahdouh, \{Alaa A.\}",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.",
year = "2022",
doi = "10.1007/978-3-031-08518-5\_10",
language = "English",
isbn = "978-3-031-08517-8",
series = "Professional and Practice-based Learning",
publisher = "Springer",
pages = "213--241",
editor = "Michael Goller and Eva Kyndt and Susanna Paloniemi and Crina Dam{\c s}a",
booktitle = "Methods for Researching Professional Learning and Development",
}