I don’t know how he can claim we are the hottest country since he’s closing the NCAR.

You misread the 36.0% approval rating, it’s really 360!

I loved the analysis of the impact of free buses -- what they really need to do is make bus lanes!

I'm encouraged that he seemed to understand he has to get along with Albany. A bit disappointed in some of the tone of the speech, but heck, he was excited. Give him that.

I dig the excitement he is generating and that he's saying different things. But NYC is incredibly difficult to govern and I hope he ends up figuring out how to navigate that and doesn't end up being constantly frustrated.

We shall see. I don't interpret a lot from a result in NYC.

You look only to the parents but not to the differences in their ages which seems to me quite important in this case.

Also: Columbia vs Chicago.

Not sure what to do with San Francisco but who is?

This to me is the central challenge. With 40 years of statistical programming under my belt — all the way back to APL and Fortran — I can fashion highly focused queries and evaluate the results.

Not sure what I’d do if I were teaching stats.

This has not been my experience, not by a long shot.

I find the LLMs produce workable code for most of my low level needs, dramatically reduce my search time for more complex tasks, and have helped complete tasks that otherwise would be beyond my capabilities.

Why would you want to give free college tuition to a rich family? That’s a silly proposal.

4/ I may be missing something, but confirmed my sense with @electionstudies.bsky.social .

Nothing statistically incorrect in the book -- that's important to note. I was just surprised to see that fairly elaborate weight adjustment suggested right up front. for use of the ANES.

3/ .. in the book and post

"If we want to make inferences about the entire U.S. population, we need to adjust the weights."

I don't think that's correct. You can make inferences about the population percentage who voted, for instance, just not the population NUMBER.