Difference between revisions of "Statistics"
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--https://statmodeling.stat.columbia.edu/2021/01/27/tukeyian-uphill-battles/}} | --https://statmodeling.stat.columbia.edu/2021/01/27/tukeyian-uphill-battles/}} | ||
| − | + | {{Quotation| Josh Wills | |
| + | @josh_wills | ||
| + | |||
| + | People who don't know any statistics just look at the data. | ||
| + | |||
| + | People who know some statistics run hypothesis tests, compute confidence intervals, etc. | ||
| + | |||
| + | People who know lots of statistics just look at the data.}} | ||
| + | |||
| + | ==Instrumental Variables== | ||
.@keisukehirano<br> | .@keisukehirano<br> | ||
is our finest poet. | is our finest poet. | ||
Revision as of 17:54, 12 February 2021
Sample Size
It's curious that with both few observations (n=30) and many (n= 3 million), statistical significance is too lax a standard. Has anyone thought about those problems in conjunction?
Data Visualization
You only have to have this experience of your plotting requests being ignored a few times to realize that you can’t expect to be able to say once, Hey how about plotting all the data first?, in a normal tone, and expect everyone to put aside the more complicated stuff they want to do and make plots. You have to repeat it, again and again, probably loudly, until you seem like some sort of graphing extremist.
--https://statmodeling.stat.columbia.edu/2021/01/27/tukeyian-uphill-battles/
Josh Wills
@josh_wills
People who don't know any statistics just look at the data.
People who know some statistics run hypothesis tests, compute confidence intervals, etc.
People who know lots of statistics just look at the data.
Instrumental Variables
.@keisukehirano
is our finest poet.
Supply and demand:
without a good instrument,
not identified.
No: poems should rhyme if they aren't in kanji.
.
Supply goes up.
Demand goes down..
Without an instrument.
They can't be found..
.
See http://rasmusen.org/published/blp-rasmusen.pdf
.
