ABSTRACT
This chapter leads readers through basic methods of machine learning that can be used in management research: correlation analysis, PCA (principal component analysis), clustering: k-means and GMM (Gaussian mixture model). These methods allow researchers to discover some relations in the samples/data. They are general enough to be applied in many other management research topics. After completing this chapter, readers will know how to use these methods in their own research and will have a set of code snippets that can be used in her/his analysis. Therefore, this chapter is invaluable for students and researchers willing to use modern machine learning techniques in their research. The full code with descriptions/comments will be published under open-source license and will be publicly available on GitHub.
