What can I read that will give me a meta-view of the diverse field of statistics and data science? With few exceptions much of what I get my hands of goes straight into formulae and methodologies. Preferably something sufficiently high level as to bring in diverse areas such as econometrics, psychometrics, machine learning, etc.
To be more concrete, preferably something that:
- Summarises and discusses the various branches of statistics/data science; what problems are encountered in each branch.
- Talks about differences between the branches and their histories.
- Contrasts methodological approach.