A few stories from graduate school at the University of Minnesota School of Statistics where Seymour Geisser was head. I didn't have as many interactions with Seymour as some folks did, but his philosophy certainly influenced me. Perhaps I'll detail his influence on my research in another post. 

The most common Seymour story involves seminar. Each year he told the graduate students that attending seminar was obligatory, but not mandatory. Or was it mandatory but not obligatory? We interpreted this to mean we really ought to go, but if we could live with ourselves, we could skip. We were obliged to go, but not mandated to go. Me, I attended every seminar except one where I missed not one, but two buses and arrived so late that I would have greatly disturbed seminar, so I left rather than open the closed seminar room door at the front of the room. The next time I missed seminar, I was out of town on job interviews. 

Seymour sat in the front row at seminars, and would crane his head around to inspect the audience. We assumed he was checking on grad student attendance, though we didn't really know. I now do the same thing at seminars, looking around at the audience to see how/whether the graduate students are attending seminar in the numbers they are supposed to be. And yes, it's something I picked up from Seymour. 

Seymour was very enamored with algebra. In his multivariate class we were oft treated to his love of algebraic manipulation. Some proofs/calculations could get complex enough that Seymour would start recycling notation, defining a symbol $a$ to be one thing early in the calculation, then later redefining the symbol to be something different. Unfortunately this offended my righteous sense of rightness. Towards the end of day one in a two day proof (one day = one class lecture), I had a premonition we were to be treated to more redefining of notation. Somewhat imperiously, I requested that Seymour not reuse notation. Actually, it's possible I instructed him not to or insisted that he not redefine notation. He looked startled (that's the closest I can get to describing his facial expression), and I can't recall his verbal response. But sure enough, at the beginning of the second day, $a$ got a new definition. 

Seymour could be quite generous. I opted to work with Dennis Cook for my thesis. Originally we had agreed I would work on optimal design, specifically on optimal design in the presence of non-constant variance. I told plenty of people that that was my research area, but over a 9 month period I spent almost no time on the subject. It was clear I wasn't going to extract a dissertation out of optimal design and I began to look for another topic. Eventually Dennis and I discussed perhaps working on diagnostics, and I think I was particularly interested in Bayesian diagnostics. Well, Bayesian diagnostics was Seymour's purview and he had a grant on the subject. So I went over to meet with him. He showed me his grant, and even allowed me to make a copy to read over to see if there was something in there that was of interest to me. Grants often hold proprietary information on a professor's research program; sharing a grant isn't a given among researchers. 

I eventually settled into a dissertation on Bayesian diagnostics, though not something that derived from Seymour's grant. And eventually I had a final defense and Seymour was on my committee. After presenting a nerve-wracking seminar in front of a large crowd, my dissertation committee and I retired to the library to grill me. There was an interaction with my thesis topic and having Seymour on my committee. My thesis involved a set of measures of case influence along with a graphical influence tool. I knew how to assess influence on the posterior. But as is well known, Seymour was a predictivist; supposedly he did not even believe in parameters except as intermediaries to get to a prediction. And I did not know how to use my measures to assess predictive influence, influence on predictions. The committee members asked me questions in turn. When Seymour's turn came, he started asking me about my time in the consulting clinic. I was a bit startled, because I wasn't expecting this direction. It hadn't previously occurred to me that Seymour might know (and why would he care?) that I had been in the consulting clinic. 

He asked: What are consulting clinic clients most concerned with? I responded with some cant about F-tests and p-values. He pushed: what else are they interested in? And I mentioned they sometimes want estimates and standard errors but not as often. And what else, he asked again. Design sometimes. Sample size. And again he queried. I stonewalled. We danced for half an hour. I answered truthfully, because no one coming in to the consulting clinic had ever once asked about predictions. I knew and everyone in the room knew what Seymour wanted. But because I didn't know how to extend my dissertation to predictions, I wasn't going to volunteer the idea of predictions and wasn't going to make it easy for him to ask the obvious and perfectly sensible question. And Seymour was equally stubborn and wanted me to mention predictions first. Eventually Dennis intervened with a gentle 'Seymour, we talked about this' comment. And the defense continued. 

These days I have a better understanding of what a dissertation defense is about and what the possible outcomes involve. But at the time I thought I was under real threat of flunking the final defense. 

The class of influence measures that I used in my dissertation involved a set of divergence measures between densities. Turns out someone else had investigated them previously, though not for purposes of influence diagnostics. Seymour knew of the paper (Csiszar, 1967). Once I had the reference from Seymour, it still took me a while to find the paper. Pre-internet, this counted as a pretty obscure reference, but Seymour knew it. Eventually I got my thesis published (Weiss and Cook 1992, Biometrika). And a few years after that, I figured out how to do predictive inference as well (Weiss 1996, JRSS-B). Seymour didn't get a citation in the 1992 paper, but I did send a couple citations his way in the 1996 paper. 

How Children Succeed: Grit, Curiosity, and the Hidden Power of Character
by Paul Tough

Unless your definition of children includes college students, the second word of the title is a misnomer. This book is about how young people, from infants to college students succeed. Perhaps a bit more subtly and more accurately, Tough's book describes how adults in various organizations, from NGOs to schools organize teaching and mentorship to assist young people to develop the traits that may allow them to succeed in today's society. The book describes approaches to developing character in young people so that they can succeed against the odds stacked against them. It describes mentoring of young mothers to help them raise children who can succeed against a backdrop of poverty. It describes a middle school chess team from Brooklyn that succeeds in national competition against teams from much higher socio-economic schools. Tough describes several schools that have been built from the ground up to instill 'character' in the students with the idea that the schools don't necessarily select a priori for kids who will be successful. Rather most of the schools are set in impoverished areas. One school was rather rich; there the problem was kids from families so rich, the kids were overprotected and never learned how to pick up the pieces after a failure. This part of the book harkens somewhat to Malcolm Gladwell's David and Goliath.

This book is something you want to read if you have a baby in the house. Spoiler alert: the answer is to hug and hold your baby. None of letting your kid cry himself out in the crib so he learns how to comfort himself. Pick him up and hold him. My explanation: then the kid doesn't learn how to cry. They learn to comfort themselves by always being comfortable. Don't let the kid practice being out of control. Let your kid practice always being in control; that's how you raise a kid who can handle herself when she grows up. 

But this book has also affected how I advise grad students. The problem for rich kids is overprotection. So rather than tell my grad students everything, it's important to let them figure things out for themselves. 

The book isn't perfect. But I'm glad its not perfect. If it were perfect, it would be too late; everyone would know this stuff, and we wouldn't need to learn this stuff. 

I highly recommend How Children Succeed to everyone. If this doesn't affect how you deal with other people, then you're not in a situation where you deal with other people ever. If you're that lone hermit, fine, don't read this. But everyone else should read this book today. 

This is the text, minus the nice formatting, of an email from Dennis Cook (my thesis advisor and current director of the U of MN School of Statistics) and Wes Johnson (a U of MN alum, a good friend, a great colleague and a student of Seymour Geisser's) about the University of Minnesota School of Statistics (my alma mater) activities in honoring Seymour Geisser. And there is a request for donations at the end, I hope you don't mind. I'll post something about Seymour's influence on my research in another post. 

Dear Colleagues,

This year marks the tenth anniversary of Seymour Geisser's death. Starting in the early 1970's, Seymour guided the then-nascent School of Statistics to one of the top statistics departments in the world, maintaining that standing throughout his tenure as director. He was a scholar in the best traditions of our discipline, a mentor to many of us, and our leader. We can still see Seymour jousting with seminar speakers to convince them that prediction should be the ultimate goal of their work. We will be taking steps over the next year to honor Seymour and his legacy.

The School's website will have a special page devoted to Seymour. We encourage you to visit that webpage and recall Seymour's impact on your professional life.

Several people have furnished accounts of Seymour's influence, which we have included on his webpage. Here are a few excerpts from those accounts:

As my thesis advisor, Seymour saw that I would make good progress without active supervision and that I was cantankerous enough to resist it, so he mostly left me alone and let his lessons seep in rather than try to pound them in. Only much later did I appreciate how much restraint and wisdom -- as well as shrewdness -- his advising style required. 
--James Hodges (PhD 1985)

Simply put, Seymour Geisser was a great scholar, educator, and human being. He was a very caring individual who made a deep impact on my personal life and my career in so many ways.
--Joseph Ibrahim (PhD 1988)

As department leader and in his classes, Prof. Geisser set an environment where we would be challenged to think broadly. Vigorous debate, being challenged to create and defend, and his care for all to grow and learn are his legacy that benefited me and so many others. 
--Dennis Jennings (PhD 1982)

Seymour combined a deep understanding of the foundations of statistics with a keen (perhaps ruthless) eye for what has meaning in practice.
--Robert McCulloch (PhD 1985)

If you have a special memory or tale of Seymour that you are willing to share, we would love to hear from you and to include it on his webpage. Please forward it to Doug Hawkins.

The Geisser lecturer for this year will be Joe Ibrahim, currently scheduled for October 30, 2014. Please stop by if you are in the neighborhood at that time.

We are making a special effort to bring the Seymour Geisser Fellowship to a sustaining level. The fellowship will be used to support a PhD student whose work best reflects Seymour's scholarship and heritage. We encourage you to consider honoring Seymour's memory by contributing to his fellowship. Contributions can be made online.

Wishing you all the best over the coming year,

R. Dennis Cook Director, School of Statistics University of Minnesota

Wesley O. Johnson Professor, Department of Statistics University of California, Irvine

The War of Art: Winning the Inner Creative Battle
by Steven Pressfield

Pressfield is the author of several bestsellers. The War of Art is a 12 step self-help support group for procrastinators, a biological and psychological disection of procrastination and your own personal writer's side-kick in the war against procrastination all in one short text. Pressfield calls the cause of procrastination resistance. Resistance is the voice inside your head, the one that tells you you'll never make it, you're going to fail. Resistance tells you that you NEED to watch the next episode in your TV show, NOW; that going shopping IMMEDIATELY is more important than sitting down to write your dissertation. Pressfield takes resistance apart, explains it in clear language and explains how to overcome it. The book is a quick read. Reading War of Art won't satisfy resistance and as soon as you read the book, resistance is going to kick into high gear with long discussions of why it's important to, well, do whatever it is except get up and do what needs doing, powdermilk. 

Resistance is that thing that makes us read tons of Andy Gelman blog posts instead of working on our next paper. Blogging could arguably also be a form of resistance. I prefer to think blog-keeping is my way of staying sane and cataloging a few of my semi-great thoughts for my future students to hear. Are you listening, future students? Hear hear! And more importantly, blogging is my way of practicing writing on a frequent enough basis to grease the mental writing wheels. 

The War of Art title harkens back to The Art of War by Sun Tzu, available for free on most fine digital reading platforms in multiple versions. I've yet to make it even partway through Sun Tzu's book, but I made it through Pressfield's book in a few bus trips in to work. 

Resistance is feudal. [I've always wanted to write that.] It holds you in fief, and demands you do anything but what is important. 

I'll keep this review short. Be done with your blog reading. NOW. STOP READING THIS BLOG! Go do something you aspire to. If something is holding you back, that something is resistance. Read The War of Art and get yourself on track. 

This is the first of perhaps three short book reviews. 

Certain basics of writing I go over with almost every student. Organization, content, paragraphs and sentences. Roy Peter Clark's Writing Tools: 50 Essential Strategies for Every Writer covers most of the them. Clark is an entertaining writer and this is a highly enjoyable read. It's worth reading as literature, even if you aren't in the market for improving your writing. This is highly recommended for beginning professional writers. That includes beginning statisticians like my students and continuing statisticians like myself. 

There are four major parts: Nuts and Bolts, Special Effects, Blueprints, and Useful Habits. Each part contains from 10 to 16 short chapters each presenting a different 'Tool'. As I read, my head kept nodding up-down, yes-yes, uh-huh, yep, told so-and-so that at our last meeting, made those comments yesterday to such and such. Roy Peter Clark presents the tools more succinctly, colorfully and intelligently than I can. He's got more tools than I have and they are ordered, cataloged and polished; I learned a lot!

One strength is that he presents his advice as tools, not as rules. Rules suggest hard and fast brook no prisoners strict laws. A tool is adaptable to many different situations. A tool helps, rules restrict. 

Nuts and Bolts gives expert guidance on writing strong sentences. Less is he explaining common mistakes and more on how to avoid the mistakes in the first place. This is material I spend a lot of time on with my students. Begin sentences with subjects and verbs (Tool 1); place strong words at the beginning and at the end (Tool 2); strong verbs create action, save words (Tool 3). Those are the title, subtitle, and part of the subtitle for the first three tools. Clark crystallizes rules I didn't realize I knew, and adds to the tools I have for writing and for advising students. Clark explains when to use passive voice -- virtually every student starts writing too much passive voice. Some students were taught to use passive in scientific writing (didn't that advice die decades ago?). Students write in passive voice when they are unsure of what they write; they try to distance themselves from what they have written. 

Fear not the long sentence (Tool 7) is advice I usually can't use, but set the pace with sentence length (Tool 18) prefer the simple over the technical (Tool 11), in short works don't waste a syllable (Tool 37) are very appropriate for scientific writing. Prefer the simple over the technical has the subhead: Use shorter words, sentences and paragraphs at points of complexity. This is great general advice as well as great specific advice for any given sentence as technical writing is almost always quite complex. Get the name of the dog (Tool 14) is about supplying informative details -- something that virtually all students do not understand until taught. That model you just presented: tell us what it does, how it works (data in, inferences out, but how?), and why it is needed (What's so great about it?)! 

Other tools would never have occurred to me, but are quite valuable. Save string (Tool 44) talks about saving up little ideas, thoughts and data until you have enough for a paper. I've been doing that, sometimes for decades, but didn't have a name for the behavior or a way to even think about the behavior. Some tools I should engage in but haven't: Recruit your own support group (Tool 47) I should do more of, while (Tool 41) turn procrastination into rehearsal, is my excuse for every delay. Some tools are better for fiction and newspaper writing, but they're fun to read and think about and may be utile even in scientific writing. Tool 26, use dialogue as a form of action talks about how the eye is drawn to short sentences with lots of white space -- advice I promptly used in advising someone preparing presentation slides. 

Tune your voice (Tool 23) I took to heart as advice to me about advising my students: let my students find their own voice. Similarly, limit self-criticism in early drafts (Tool 48) is vital for getting the meat of a project on paper before tightening up language and organizing the content. Too much criticism to early and the creative brain shuts down and that segues into my next review. 

I strongly recommend Peter Roy Clark's Writing Tools, 50 Essential Strategies for Every Writer to every graduate student and to any professor who wishes to improve their writing.