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I always thought that name was strange but I never thought to look it up. Stats books are so dry, they don’t have the inclination to share these kinds of storie

I always thought that name was strange but I never thought to look it up. Stats books are so dry, they don’t have the inclination to share these kinds of stories.

TillE 2y ago
The history of just about anything is very interesting, but it's generally not relevant in a textbook which has a specific purpose.
- mp05 2y ago
  I agree with the sentiment, but I always have wondered what t-test a real engineer uses and why they only teach the "Student" version. Given the context, a bit of a clarifier would have been appreciated.
alpple 2y ago
I wonder if dry reading means written without the influence of drink. I couldn't find an answer online. But, if so, it would be ironic to describe a stat book that ignored a brewer as dry.
ayhanfuat 2y ago
You probably missed it. This is something stat book authors love to mention. I don’t remember a stat intro book that doesn’t have a footnote for “Student t”.
- BeetleB 2y ago
  Just went through mine a few months ago. It definitely doesn't have it.
  - whimsicalism 2y ago
    what book? i'm honestly curious because of how frequently this story is repeated in stats textbooks
    - BeetleB 2y ago
      The author is Jay Devore.
nxobject 2y ago
Wait until you hear about the bad blood between Fisher and Pearson.
jldugger 2y ago
> Stats books are so dry, they don’t have the inclination to share these kinds of stories. It doesn't have to be that way. My pandemic lockdown read was a 10 dollar Stats textbook[1], that comes with tons of classic examples: the Salk polio vaccine, a prosecutor misusing the multiplication rule using purely circumstantial evidence ("what are the odds that police pulled over the wrong couple matching 10 different pieces of description by the victim?"), the classic Gallup poll showing FDR would defeat Landon (versus incumbent _Literary Digest_ showing a Landon win), Gosset's history with Guiness, the early history of probability as gambling strategy, a controversy over Mendel's data on pea plant heredity being _too_ clean, and so on. Sadly, while this book left me well prepared to apply statistical reasoning in my day job, it's departure from typical pedagogy left me feeling unprepared for further reading based on perusal of Stats Wikipedia -- what's a kernel? what's a moment? etc. [1]: https://www.amazon.com/Statistics-Fourth-David-Freedman-ebook/dp/B00SLB5Q72 https://www.amazon.com/Statistics-Fourth-David-Freedman-eboo...
- madcaptenor 2y ago
  In a former life I taught some intro stat courses from this book. It’s a good book for an intro course for people who aren’t going on to further stat classes, although I think for a current class I’d want something that acknowledges how statistics and computers have gotten all tied up with each other. (I don’t have any recommendations - it’s not my job to know this any more.)
- deleted 2y ago
  [deleted]
whimsicalism 2y ago
sorry but this is a classic story mentioned in almost every basic stats textbook i’ve read
roenxi 2y ago
Doubly unfortunate because the philosophical aspects of statistics are more important to students than most of maths. There are something like 4 different schools of thought [0] and people will have a natural propensity to one of them. Although they all agree on the formulas and rigorous aspects, it is actually a challenging proposition to comprehend what someone is doing if you strongly see the world from one perspective and don't realise that academics are potentially approaching the interpretation in one of 3 other ways. It adds a lot of dryness to the textbook because the author can really only talk about the objective parts in an introductory classroom setting. But if you're getting taught by a frequentist and have a subjectivity bent it is easy to spend a year or two confused before someone clues you in that there are unresolved questions of interpretation. [0] https://en.wikipedia.org/wiki/Interpretation_of_probability https://en.wikipedia.org/wiki/Interpretation_of_probability
- enasterosophes 2y ago
  > people will have a natural propensity to one of them. I see what you did there
- riffraff 2y ago
  Interesting, my university book of the subject was pretty tiny but it did talk of the different interpretations, but it only mentioned frequentist and bayesian. I did not suspect the story was much more complicated.
deleted 2y ago
[deleted]
orhmeh09 2y ago
I liked this one a lot Abelson, R. P. (1995). Statistics as Principled Argument. Psychology Press. https://www.routledge.com/Statistics-As-Principled-Argument/Abelson/p/book/9780805805284 https://www.routledge.com/Statistics-As-Principled-Argument/... > In this illuminating volume, Robert P. Abelson delves into the too-often dismissed problems of interpreting quantitative data and then presenting them in the context of a coherent story about one's research. Unlike too many books on statistics, this is a remarkably engaging read, filled with fascinating real-life (and real-research) examples rather than with recipes for analysis. It will be of true interest and lasting value to beginning graduate students and seasoned researchers alike. The focus of the book is that the purpose of statistics is to organize a useful argument from quantitative evidence, using a form of principled rhetoric. Five criteria, described by the acronym MAGIC (magnitude, articulation, generality, interestingness, and credibility) are proposed as crucial features of a persuasive, principled argument. Particular statistical methods are discussed, with minimum use of formulas and heavy data sets. The ideas throughout the book revolve around elementary probability theory, t tests, and simple issues of research design. It is therefore assumed that the reader has already had some access to elementary statistics. Many examples are included to explain the connection of statistics to substantive claims about real phenomena.

I always thought that name was strange but I never thought to look it up. Stats books are so dry, they don’t have the inclination to share these kinds of stories.

TillE 2y ago

The history of just about anything is very interesting, but it's generally not relevant in a textbook which has a specific purpose.

mp05 2y ago
I agree with the sentiment, but I always have wondered what t-test a real engineer uses and why they only teach the "Student" version. Given the context, a bit of a clarifier would have been appreciated.

alpple 2y ago

I wonder if dry reading means written without the influence of drink. I couldn't find an answer online. But, if so, it would be ironic to describe a stat book that ignored a brewer as dry.

ayhanfuat 2y ago

You probably missed it. This is something stat book authors love to mention. I don’t remember a stat intro book that doesn’t have a footnote for “Student t”.

BeetleB 2y ago
Just went through mine a few months ago. It definitely doesn't have it.
- whimsicalism 2y ago
  what book? i'm honestly curious because of how frequently this story is repeated in stats textbooks
  - BeetleB 2y ago
    The author is Jay Devore.

nxobject 2y ago

Wait until you hear about the bad blood between Fisher and Pearson.

jldugger 2y ago

> Stats books are so dry, they don’t have the inclination to share these kinds of stories. It doesn't have to be that way. My pandemic lockdown read was a 10 dollar Stats textbook[1], that comes with tons of classic examples: the Salk polio vaccine, a prosecutor misusing the multiplication rule using purely circumstantial evidence ("what are the odds that police pulled over the wrong couple matching 10 different pieces of description by the victim?"), the classic Gallup poll showing FDR would defeat Landon (versus incumbent _Literary Digest_ showing a Landon win), Gosset's history with Guiness, the early history of probability as gambling strategy, a controversy over Mendel's data on pea plant heredity being _too_ clean, and so on. Sadly, while this book left me well prepared to apply statistical reasoning in my day job, it's departure from typical pedagogy left me feeling unprepared for further reading based on perusal of Stats Wikipedia -- what's a kernel? what's a moment? etc. [1]: https://www.amazon.com/Statistics-Fourth-David-Freedman-ebook/dp/B00SLB5Q72 https://www.amazon.com/Statistics-Fourth-David-Freedman-eboo...

madcaptenor 2y ago
In a former life I taught some intro stat courses from this book. It’s a good book for an intro course for people who aren’t going on to further stat classes, although I think for a current class I’d want something that acknowledges how statistics and computers have gotten all tied up with each other. (I don’t have any recommendations - it’s not my job to know this any more.)
deleted 2y ago
[deleted]

whimsicalism 2y ago

sorry but this is a classic story mentioned in almost every basic stats textbook i’ve read

roenxi 2y ago

Doubly unfortunate because the philosophical aspects of statistics are more important to students than most of maths. There are something like 4 different schools of thought [0] and people will have a natural propensity to one of them. Although they all agree on the formulas and rigorous aspects, it is actually a challenging proposition to comprehend what someone is doing if you strongly see the world from one perspective and don't realise that academics are potentially approaching the interpretation in one of 3 other ways. It adds a lot of dryness to the textbook because the author can really only talk about the objective parts in an introductory classroom setting. But if you're getting taught by a frequentist and have a subjectivity bent it is easy to spend a year or two confused before someone clues you in that there are unresolved questions of interpretation. [0] https://en.wikipedia.org/wiki/Interpretation_of_probability https://en.wikipedia.org/wiki/Interpretation_of_probability

enasterosophes 2y ago
> people will have a natural propensity to one of them. I see what you did there
riffraff 2y ago
Interesting, my university book of the subject was pretty tiny but it did talk of the different interpretations, but it only mentioned frequentist and bayesian. I did not suspect the story was much more complicated.

deleted 2y ago

[deleted]

orhmeh09 2y ago

I liked this one a lot Abelson, R. P. (1995). Statistics as Principled Argument. Psychology Press. https://www.routledge.com/Statistics-As-Principled-Argument/Abelson/p/book/9780805805284 https://www.routledge.com/Statistics-As-Principled-Argument/... > In this illuminating volume, Robert P. Abelson delves into the too-often dismissed problems of interpreting quantitative data and then presenting them in the context of a coherent story about one's research. Unlike too many books on statistics, this is a remarkably engaging read, filled with fascinating real-life (and real-research) examples rather than with recipes for analysis. It will be of true interest and lasting value to beginning graduate students and seasoned researchers alike. The focus of the book is that the purpose of statistics is to organize a useful argument from quantitative evidence, using a form of principled rhetoric. Five criteria, described by the acronym MAGIC (magnitude, articulation, generality, interestingness, and credibility) are proposed as crucial features of a persuasive, principled argument. Particular statistical methods are discussed, with minimum use of formulas and heavy data sets. The ideas throughout the book revolve around elementary probability theory, t tests, and simple issues of research design. It is therefore assumed that the reader has already had some access to elementary statistics. Many examples are included to explain the connection of statistics to substantive claims about real phenomena.