The getting started guide states:
Instructions for installing Panel and the example notebooks can be found in the Installation Guide
However the installation guide does not mention anything about installing example notebooks.
And in all honesty, I would prefer to just run python programs without jupyter notebooks. But if notebooks are required, then the docs should have those instructions.
Yes it seems like the installation guide has been simplified but the getting started guide hasn’t been updated accordingly 
Panel (and most of the other holoviz tools I believe) have a command line subcommand that allows to download the examples data (including some assets and the notebooks): panel examples. I’ve not used that in a long time so I don’t know how well it works now but if it does we should certainly document it in the getting started guide.
As for using notebooks or not, I personally really like playing with Panel objects in a notebook until I get a good feeling about how they work. It allows to super quickly iterate and prototype things. I find that really powerful and would miss it if it wasn’t there! (Serving a python file with panel serve file.py --autoreload is also a good way to iterate on an application but I think you already need a good understanding about how Panel works).
As a software developer, I am more comfortable with panel serve file.py --autoreload . I think a data scientist might be more comfortable with notebooks, but I have no experience with them and do not wish to learn.
Just to join the discussion. I personally prefer using .py files and panel serve with --autoreload. But I really appreciate that it also works in Jupyter as a lot of my colleagues in analysis, data science and trading prefer that environment. It means we can use the same framework and work together.
It means I can build python packages for their domain that also works in the notebook. We use that all the time to make working with data or visualizations easier for users.
I use to do the Panel testing in Jupyter notebooks
and then convert final notebook into .py file with following command in my script
jupyter nbconvert --to script main.ipynb
main.ipynb converted to main.py
