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Past, Present, and Future of Statistical Science

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Past, Present, and Future of Statistical Science

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This is the title of a won­der­ful new book that has just been released, cour­tesy of the Com­mit­tee of Pres­i­dents of Sta­tis­ti­cal Societies.

It can be freely down­loaded from the COPSS web­site or a hard copy can be pur­chased on Ama­zon (for only a lit­tle over 10c per page which is not bad com­pared to other sta­tis­tics books).

The book con­sists of 52 chap­ters span­ning 622 pages. The full table of con­tents below shows its scope and the list of authors (a ver­i­ta­ble who’s who in statistics).

The His­tory of COPSS
A brief his­tory of the Com­mit­tee of Pres­i­dents of Sta­tis­ti­cal Soci­eties (COPSS) Ingram Olkin

Rem­i­nis­cences and Per­sonal Reflec­tions on Career Paths 
Rem­i­nis­cences of the Colum­bia Uni­ver­sity Depart­ment of Math­e­mat­i­cal Sta­tis­tics in the late 1940s Ingram Olkin
A career in sta­tis­tics Her­man Cher­noff”… how won­der­ful the field of sta­tis­tics is …” David R. Brillinger

An unortho­dox jour­ney to sta­tis­tics: Equity issues, remarks on mul­ti­plic­ity Juliet Pop­per Shaf­fer
Sta­tis­tics before and after my COPSS Prize Peter J. Bickel

The acci­den­tal bio­sta­tis­tics pro­fes­sor Donna Bro­gan

Devel­op­ing a pas­sion for sta­tis­tics Bruce G. Lind­say

Reflec­tions on a sta­tis­ti­cal career and their impli­ca­tions R. Den­nis Cook

Sci­ence mixes it up with sta­tis­tics Kathryn Roeder
Lessons from a twisted career path Jef­frey S. Rosen­thal
Pro­mot­ing equity Mary Gray

Per­spec­tives on the Field and Pro­fes­sion

Sta­tis­tics in ser­vice to the nation Stephen E. Fien­berg

Where are the majors? Iain M. John­stone

We live in excit­ing times Peter HallThe bright future of applied sta­tis­tics Rafael A. Irizarry

The road trav­elled: From a sta­tis­ti­cian to a sta­tis­ti­cal sci­en­tist Nilan­jan Chat­ter­jee

Reflec­tions on a jour­ney into sta­tis­ti­cal genet­ics and genomics Xihong Lin
Reflec­tions on women in sta­tis­tics in Canada Mary E. Thomp­son

“The whole women thing” Nancy Reid
Reflec­tions on diver­sity Louise Ryan

Reflec­tions on the Dis­ci­pline

Why does sta­tis­tics have two the­o­ries? Don­ald A.S. Fraser

Con­di­tion­ing is the issue James O. Berger

Sta­tis­ti­cal infer­ence from a Dempster–Shafer per­spec­tive Arthur P. Demp­ster

Non­para­met­ric Bayes David B. Dun­son

How do we choose our default meth­ods? Andrew Gel­man
Ser­ial cor­re­la­tion and Durbin–Watson bounds T.W. Ander­son

A non-​​asymptotic walk in prob­a­bil­ity and sta­tis­tics Pas­cal Mas­sart

The past’s future is now: What will the present’s future bring? Lynne Bil­lard

Lessons in bio­sta­tis­tics Nor­man E. Bres­low

A vignette of dis­cov­ery Nancy Flournoy
Sta­tis­tics and pub­lic health research Ross L. Pren­tice

Sta­tis­tics in a new era for finance and health care Tze Leung Lai
Meta-​​analyses: Het­ero­gene­ity can be a good thing Nan M. Laird
Good health: Sta­tis­ti­cal chal­lenges in per­son­al­iz­ing dis­ease pre­ven­tion Alice S. Whit­te­more
Buried trea­sures Michael A. New­ton
Sur­vey sam­pling: Past con­tro­ver­sies, cur­rent ortho­doxy, future par­a­digms Rod­er­ick J.A. Lit­tle

Envi­ron­men­tal infor­mat­ics: Uncer­tainty quan­tifi­ca­tion in the envi­ron­men­tal sci­ences Noël A. Cressie
A jour­ney with sta­tis­ti­cal genet­ics Eliz­a­beth Thomp­son
Tar­geted learn­ing: From MLE to TMLE Mark van der LaanSta­tis­ti­cal model build­ing, machine learn­ing, and the ah-​​ha moment Grace Wahba
In praise of spar­sity and con­vex­ity Robert J. Tib­shi­rani
Fea­tures of Big Data and spars­est solu­tion in high con­fi­dence set Jian­qing Fan
Rise of the machines Larry A. Wasser­man
A trio of infer­ence prob­lems that could win you a Nobel Prize in sta­tis­tics (if you help fund it) Xiao-​​Li Meng

Advice for the Next Gen­er­a­tion
Inspi­ra­tion, aspi­ra­tion, ambi­tion C.F. Jeff Wu
Per­sonal reflec­tions on the COPSS Pres­i­dents’ Award Ray­mond J. Car­roll
Pub­lish­ing with­out per­ish­ing and other career advice Marie David­ian
Con­vert­ing rejec­tions into pos­i­tive stim­uli Don­ald B. Rubin
The impor­tance of men­tors Don­ald B. Rubin
Never ask for or give advice, make mis­takes, accept medi­oc­rity, enthuse Terry Speed
Thir­teen rules Bradley Efron


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