ASA Connect

Hello,

I have been teaching a Probability - Mathematical statistics sequence at the MS level (in Statistics) for several years. The book by Casella and Berger, which I used when I started out, was and still is excellent, but more recently I found myself looking for something more lively in terms of practical/applied examples. For the first part of the sequence (Probability) I am now using Blitzstein & Hwang (Introduction to Probabiity, 2nd ed.), which I think strikes a good balance between rigorous theory and lively examples. The theory is a bit watered down compared to Casella & Berger, but still good enough for my students. However, I haven't been able to find a decent replacement to Casella & Berger for the Statistical Inference part of my sequence. All the books the I have seen are either too applied, hiding too much of the theory, or they are too advanced for my students in terms of the theory.

In summary, the Holy Grail I am looking for is a sort of Casella & Berger of the 2020s, possibly covering only the inference part without the probability buildup. If anybody has suggestions, they would be gratefully appreciated!

Thank you in advance!

Giovanni

------------------------------
Giovanni Petris, PhD
Professor
Director of Statistics
Department of Mathematical Sciences
University of Arkansas - Fayetteville, AR 72701
------------------------------

I'd encourage you to look at four books that I find compelling (each for different reasons):

1. Foundations of Statistics for Data Scientists (Agresti and Kateri): https://www.routledge.com/Foundations-of-Statistics-for-Data-Scientists-With-R-and-Python/Agresti-Kateri/p/book/9780367748456
2. Mathematical Statistics and Data Analysis (Rice): https://www.amazon.com/Mathematical-Statistics-Analysis-Available-Enhanced/dp/0534399428
3. Mathematical Statistics with Resampling and R (Chihara and Hesterberg): https://sites.google.com/site/chiharahesterberg/home
4. Foundations and Applications of Statistics: An Introduction using R (Pruim): https://www.ams.org/publications/authors/books/postpub/amstext-13

I suspect that the first and second would be at the right level for what you describe.

There was an interesting and lively session at JSM this year about the future of the theoretical statistics (aka inference or mathematical statistics).

------------------------------
Nicholas Horton
Beitzel Professor of Technology and Society (Statistics and Data Science)
Northampton, MA United States
------------------------------

Original Message:
Sent: 12-07-2022 17:11
From: Giovanni Petris
Subject: Book suggestion for Mathematical Statistics

Hello,

I have been teaching a Probability - Mathematical statistics sequence at the MS level (in Statistics) for several years. The book by Casella and Berger, which I used when I started out, was and still is excellent, but more recently I found myself looking for something more lively in terms of practical/applied examples. For the first part of the sequence (Probability) I am now using Blitzstein & Hwang (Introduction to Probabiity, 2nd ed.), which I think strikes a good balance between rigorous theory and lively examples. The theory is a bit watered down compared to Casella & Berger, but still good enough for my students. However, I haven't been able to find a decent replacement to Casella & Berger for the Statistical Inference part of my sequence. All the books the I have seen are either too applied, hiding too much of the theory, or they are too advanced for my students in terms of the theory.

In summary, the Holy Grail I am looking for is a sort of Casella & Berger of the 2020s, possibly covering only the inference part without the probability buildup. If anybody has suggestions, they would be gratefully appreciated!

Thank you in advance!

Giovanni

------------------------------
Giovanni Petris, PhD
Professor
Director of Statistics
Department of Mathematical Sciences
University of Arkansas - Fayetteville, AR 72701
------------------------------

Have a look at Modern Mathematical Statistics with Applications (Springer, 3rd ed), by Devore, Berk, and Carlton.  It does blend application with theory, though it is pitched more at the junior-senior level than at graduate students.

------------------------------
Jay Devore
Professor Emeritus of Statistics
------------------------------

Original Message:
Sent: 12-07-2022 17:11
From: Giovanni Petris
Subject: Book suggestion for Mathematical Statistics

Hello,

I have been teaching a Probability - Mathematical statistics sequence at the MS level (in Statistics) for several years. The book by Casella and Berger, which I used when I started out, was and still is excellent, but more recently I found myself looking for something more lively in terms of practical/applied examples. For the first part of the sequence (Probability) I am now using Blitzstein & Hwang (Introduction to Probabiity, 2nd ed.), which I think strikes a good balance between rigorous theory and lively examples. The theory is a bit watered down compared to Casella & Berger, but still good enough for my students. However, I haven't been able to find a decent replacement to Casella & Berger for the Statistical Inference part of my sequence. All the books the I have seen are either too applied, hiding too much of the theory, or they are too advanced for my students in terms of the theory.

In summary, the Holy Grail I am looking for is a sort of Casella & Berger of the 2020s, possibly covering only the inference part without the probability buildup. If anybody has suggestions, they would be gratefully appreciated!

Thank you in advance!

Giovanni

------------------------------
Giovanni Petris, PhD
Professor
Director of Statistics
Department of Mathematical Sciences
University of Arkansas - Fayetteville, AR 72701
------------------------------

Hello Giovanni,

I don't know if any book fits the bill exactly (I haven't seen many good applied examples in theoretical mathematical statistics books), but my colleague's book comes close.
"The Simple and Infinite Joy of Mathematical Statistics," by Jem Corcoran: https://www.amazon.com/Simple-Infinite-Joy-Mathematical-Statistics/dp/B0BD1YPQRN/



------------------------------
Eric Vance
Associate Professor and Director
Boulder CO, United States
------------------------------

Original Message:
Sent: 12-07-2022 17:11
From: Giovanni Petris
Subject: Book suggestion for Mathematical Statistics

Hello,

I have been teaching a Probability - Mathematical statistics sequence at the MS level (in Statistics) for several years. The book by Casella and Berger, which I used when I started out, was and still is excellent, but more recently I found myself looking for something more lively in terms of practical/applied examples. For the first part of the sequence (Probability) I am now using Blitzstein & Hwang (Introduction to Probabiity, 2nd ed.), which I think strikes a good balance between rigorous theory and lively examples. The theory is a bit watered down compared to Casella & Berger, but still good enough for my students. However, I haven't been able to find a decent replacement to Casella & Berger for the Statistical Inference part of my sequence. All the books the I have seen are either too applied, hiding too much of the theory, or they are too advanced for my students in terms of the theory.

In summary, the Holy Grail I am looking for is a sort of Casella & Berger of the 2020s, possibly covering only the inference part without the probability buildup. If anybody has suggestions, they would be gratefully appreciated!

Thank you in advance!

Giovanni

------------------------------
Giovanni Petris, PhD
Professor
Director of Statistics
Department of Mathematical Sciences
University of Arkansas - Fayetteville, AR 72701
------------------------------