The migration

In the past couple of weeks, I’ve been doing lots of work to migrate my website and the blog to a fully-integrated version based on Hugo and blogdown. THE NEW ADDRESS IS http://www.statistica.it/gianluca/blog.

Plenty of people have written very good and detailed templates on how to migrate from other blogging platforms, so I won’t bother adding mine…

I think overall the transition has been OK — some hiccups mostly due to my limited proficiency with pure html, but I did manage to turn the basic (well, I say basic, but it’s actually pretty good and advanced!) academic template into something that is rather customised to my liking. For example, I’ve expanded the page width and included a more complex website structure, which basically replicates the older version — but better, I think.

I have spent lots of time fixing some small issues (eg in the blog posts — most have been fixed, but I think some links may be broken, or some images may not be placed where I had originally intended). Also, there are some bits and bobs that I still haven’t fixed exactly as I want — for example, the search bar (which is a bit of a more complex thing, because of course the site is static, so it requires some ingenuity to allow dynamic searches. People have done it, but I have to figure it out in all the details…). And I need to take care of syndication of the posts etc. But by and large, the new website is kind of ready to go!

For a few more posts, I'll keep both versions of the blog, while I'm setting up all the details in the transition.

At the Oscars!

Well, these days being part of the glittering world of show-biz is not necessarily a good thing, but when your life is soooo glamorous that someone feels the unstoppable need to make a biopic of it... well, you really need to embrace your new status as a movie star and enjoy all the perks that life will now throw at you...

I know, I know... This is still about the Eurovision. But, this time they made a short video to tell the story $-$ you may think the still above hows Marta and me, but these are actually two actors, playing us! 

I think they've made a very good job at rendering us $-$ particularly me, I think. If you believe the movies: 

• We (particularly I) are younger than we really are;
• We drink a lot (although "Marta"'s drink 25 seconds in looks like a cross between Cranberry juice and the stuff they use to show vampires drinking human blood from hospital blood bags)...
• We laugh a lot $-$ I think this is kind of true, though...
• I like how 1 min 24 seconds in, "Marta" authoritatively demands a kiss on the cheek and "my" response to that is covered by floating webpages $-$ kind of rated R...
• The storyline seems to suggest that we thought about doing this as wondered whether we should do a Bayesian model $-$ of course that was never in question!...

Anyway, I think I need to thank the guys at Taylor & Francis (Clare Dodd, in particular), who've done an amazing job! 

Break

Today I've taken a break from the general election modelling $-$ well, not really... Of course I've checked whether there were new polls available and have updated the model! 

But: nothing much changes, so for today, I'll actually concentrate on something else. I was invited to give a talk at the Imperial/King's College Researchers' Society Workshop $-$ I think this is something they organise routinely.

They asked me to talk about "Blogging and Science Communication" and I decided to have some fun with this. My talk is here. I've given examples of weird stuff associated with this blog $-$ not that I had to look very hard to find many of them...

And I did have fun giving the talk! Of course, the posts about the election did feature, so eventually I got to talk about them to...

The Inbetweeners

When it first was shown, I really liked "The Inbetweeners" $-$ it was at times quite rude and cheap, but it did make me laugh, despite the fact that, as it often happens, all the main characters did look a bit older than the age they were trying to portrait...

Anyway, as is increasingly often the case, this post has very little to do with its title and (surprise!) it's again about the model for the UK general election.

There has been lots of talk (including in Andrew Gelman's blog) in the past few days about Yougov's new model, which is based on Gelman's MRP (Multilevel Regression and Post-stratification). I think the model is quite cool and it obviously is very rigorous $-$ it considers a very big poll (with over 50,000 responses), assumes some form of exchangeability to pool information across different individual respondents' characteristics (including geographical area) and then reproportions the estimated vote shares (in a similar way to what my model does) to produce an overall prediction of the final outcome.

Much of the hype (particularly in the British mainstream media), however, has been related to the fact that Yougov's model produces a result that is very different from most of the other poll analyses, ie a much worse performance for the Tories, who are estimated to gain only 304 seats (with a 95% credible interval of 265-342). That's even less than the last general election. Labour are estimated to get 266 (230-300) seats and so there have been hints of a hung parliament, come Friday.

Electoralcalculus (EC) has a short article in their home page to explain the differences in their assessment, which (more in line with my model) still gives the Tories a majority of 361 (to Labour's 216).

As for my model, the very latest estimate is the following:

                mean        sd 2.5% median   97.5%
Conservative 347.870 3.2338147  341    347 355.000
Labour       222.620 3.1742205  216    223 230.000
UKIP           0.000 0.0000000    0      0   0.000
Lib Dem       11.709 2.3103369    7     12  16.000
SNP           48.699 2.0781525   44     49  51.000
Green          0.000 0.0000000    0      0   0.000
PCY            1.102 0.9892293    0      1   2.025
Other          0.000 0.0000000    0      0   0.000

so somewhere in between Yougov and EC (very partisan comment: man how I wish Yougov got it right!).

One of the points that EC explicitly models (although I'm not sure exactly how $-$ the details of their model are not immediately evident, I think) is the poll bias against the Tories. They counter this by (I think) arbitrarily redistributing 1.1% of the vote shares from Labour to the Tories. This probably explains why their model is a bit more favourable to the Conservatives, while being driven by the data in the polls, which seem to suggest Labour are catching up.

I think Yougov model is very extensive and possibly does get it right $-$ after all, speaking only for my own model, Brexit is one of the factors and possibly can act as proxy for many others (age, education, etc). But surely there'll be more than that to make people's mind? Only few more days before we find out...

The swingers

Kaleb has left a comment on a previous post, asking what constituencies my model predicted to change hands, with respect to the 2015 election. This is not too difficult to do, given the wealth of results and quantities that can be computed, once the posterior distributions are estimated.

Basically, what I have done is to compute, based on the "possible futures" simulated by the model, the probability that the parties win each of the 632 seats in England, Wales and Scotland. Many of them seem to be very safe seats $-$ I think this is consistent with current political knowledge, although in an election like this possibly more can change...

Anyway, using the very latest analysis (as of today, 30th May and based on all polls published so far, but discounting older ones), there are 39 seats that are predicted to change hands. The following graph shows the predicted distribution of the probability of winning each of those seats, together of an indication of who won in 2015.

Of course, Labour are the big losers (there are many of the 39 constituencies that were Labour in 2015, but are predicted to swing to some other party in 9 days time). Conversely, the Tories are the big winners and most often, when they do, they are predicted to win that seat with a very large probability. There aren't very many real 50:50s $-$ a couple, I'd say, where the results are predicted to be rather uncertain. 

Incidentally, as of today, this is the distribution of seats predicted by the model.
                mean        sd 2.5% median 97.5%
Conservative 359.467 5.4492757  351    358   371
Labour       209.276 5.3613961  198    211   218
UKIP           0.000 0.0000000    0      0     0
Lib Dem       14.699 2.1621920   10     15    19
SNP           48.055 2.7271620   42     48    52
Green          0.000 0.0000000    0      0     0
PCY            0.503 0.8286602    0      0     3
Other          0.000 0.0000000    0      0     0

Labour are continuing to close the gap on the Tories, but are still a long way out. I'm curious to see what last night not-a-debate did to the polls...

(Too) slowly but surely?

After the tragic events in Manchester and the suspension in the campaigns, things have started again and a couple new polls have been released. Some of the media have also picked up the trend I was observing from my model and so I have re-updated the results.

The increasing trend for Labour does see another little surge, as does the decreasing trend for the Tories. In comparison to my last update, the Lib Dem are slightly picking up again. But all in all, the numbers still tell kind of the same story, I guess.

                mean        sd 2.5% median   97.5%
Conservative 369.251 5.1765622  357    370 378.000
Labour       197.886 5.2142298  190    197 211.000
UKIP           0.000 0.0000000    0      0   0.000
Lib Dem       15.085 2.3852598   11     15  19.025
SNP           49.263 2.3965756   44     49  53.000
Green          0.000 0.0000000    0      0   0.000
PCY            0.515 0.8499985    0      0   3.000
Other          0.000 0.0000000    0      0   0.000

These are the summary results as of today (again after discounting past polls). Lib Dem move from a median number of expected seats of 14 to the current estimate of 15; Labour go from 191 to 197 and the Tories go from 376 to 370, still comfortably in the lead. 

Elections and the law of large numbers

I know most people have been caught up in the minor and irrelevant issue of the US presidential election $-$ what really mattered in the past couple of weeks was another, much more important election: the ISBA Section on Biostatistics and Pharmaceutical Statistics was renewing many of its officers!

In recent times, I have always been on the losing side of an election (both in Italy and in the UK $-$ although, despite paying my taxes here, I am not allowed to vote in the general elections $-$ and it seemed anywhere there was an election, really...). 

Finally, this time around, the spell was broken and I was elected Programme Chair of the section. I have been working in the section for the past two years as secretary, so it'll be nice to continue this process and link even more all the Bayesian activities I'm involved in!

Always take the weather with you...

Last week, we were in lovely Andalusia $-$ it was Kobi's first half term holiday at school and so we decided to make the most of it. It was actually an awesome week $-$ wonderful weather, nice places and now it's really hard to go back to focus to work... 

Anyway, as part of the trip, we went to visit Gibraltar, which is technically a bit of Britain enclosed within Spanish territory. Guess which bit is which...

Careful whisper

PREFACE: This post is only partially a grumpy man's emotional outburst: just hear me out on this one... 

ABSTRACT: A grumpy man vents about spam emails from random scientific (and sometimes pseudo-scientific) journals.

RELEVANCE OF GEORGE MICHAEL'S PICTURE: Virtually none.

MAIN TEXT: First off, I should say that, luckily, my spam filter works pretty well, so I normally don't really get to see these messages (except for when I take 5 minutes to check what's ended up in the spam $-$ typically these are my 5 minutes of fun...). 

But, I find it super-hilarious to read the weird invitations to contribute papers to the most bizarre journals (that is bizarre with respect to my own field of expertise, of course $-$ they are often good journals, although I think that sometimes the weirdness goes hand in hand with their ridiculousness...). 

Anyway, I particularly really, really like when they start the email with something like this: 

Dear Dr Gianluca@my email address, [of course, to these people my email address is my full name]

We follow very carefully your research and we are impressed by your scientific production. We would be delighted if you could contribute a paper (possibly within the next 20 minutes) to the Journal of Something that has absolutely nothing to do with Statistics, or Health Economics, or anything you've ever done in your life since you were 4 and accidentally sat on your mum's little cactus and all the spiny stems pricked your bottom. [and that, sadly, is a true story...]

Now, that's what I call carefully following somebody's research!

CONCLUSIONS: Incidentally, one of my biggest regrets in life is to have never managed to wear my hair like George Michael. And that's something I've carefully tried to do when I was 14.

Sad night

I've just heard the very sad news that Richard Nixon has passed away this morning. I can't say I knew Richard very well, but I thought he really was a lovely guy and I am very saddened.

I knew of him (among other things) through his work on covariate adjustment in health economic evaluations, which I think was part of his PhD at the MRC Cambridge. I then got in contact with him more closely when I was thinking of organising the short course based on BMHE, since he and Chris were already doing something like that. I suggested we did the course together and he was very enthusiastic about it. In fact, when he was asked to teach a short course at the University of Alberta, he said the three of us should have a go, which we did. Then we taught the course at Bayes 2014, UCL and at a one-day workshop organised by the RSS. He fell ill just before the last edition of the course.

Tonight I have a very vivid memory of the time we were in Edmonton having dinner after the first night of the course when I told that for some reason Italians usually get really crossed about chicken in pizza and that he used to tease me with that every time we've met since, saying that he would love a pizza with chicken. And how we used to introduce ourselves to the audience $-$ and how sometimes people were to young to get the references. I'll miss you, Richard.

Bad medical journal

This is an interesting story, I think and I have to say I'm sort of being inspired in the title of the post from a talk that Stephen Senn gave a while back at UCL. He in turn had been referring to Ben Goldacre's book Bad Pharma $-$ the book argues that the pharmaceutical industry is often guilty of cherry picking the evidence they use to substantiate claims of clinical benefits for their product, while Stephen counters that this is rather a two-way street and often respectable medical journals are just as bad.

So: a while back we have done some work on a paper analysing an intervention to facilitate early diagnose of dementia and then submitted it to one of the leading medical journals. Unfortunately, the intervention didn't turn out to produce a massive difference, but we thought it would be interesting anyway. The paper went out for review $-$ in fact it was assessed by 3 reviewers. As per the journal policy, the reviewers have to state their name explicitly, so that the whole process becomes more transparent. 

Now, interestingly, the 3 reviewers' comments were (I am copying their comment verbatim, but add my own text in italics below):

1. The authors report a well-designed and well-conducted cluster RCT which addresses a subject of high clinical importance.  The findings are conclusively negative in terms of their simple informational intervention effecting earlier diagnosis. This is however an important and clinically useful negative finding, in that it demonstrates that a very simple intervention is not effective in enhancing timely diagnosis. This means that a more multifaceted approach may be needed to address the clinical and policy priority for earlier ab d better diagnosis of dementia. The change in ascertainment of primary outcome to include an imputed MMSE score from ACE data was necessary in the light of unpredicted change in clinical practice due to the prospect of incurring a charge from the copyright holders.  The method used is scientifically reasonable and will not have obscured the results of the intervention. This is a good strong paper with an important negative finding that warrants publication.
2. THE MANUSCRIPT: [title of the paper] is very important and of high standard.I cecommend [sic] the publication in [name of the journal] without restriction. 
3. This is a cluster randomized controlled trial of a simple intervention meant to empower patients and their families to seek early assessment for memory difficulties from their primary care physicians. The intervention which included an information leaflet and personalized physician letter was laudably developed with input from patients and caregivers. The experimental design was quite rigorous and utilized an appropriate sample size calculation. One might argue about the choice of the primary outcome measure and whether the intervention as designed could reasonably have been hypothesized to have families bring their relative to EARLIER attention or not (as opposed to bringing them at all), but all outcomes were clearly described and reported. Unfortunately, the study was largely negative. Besides the potential reasons suggested by the authors, not enough attention is paid to primary care physician attitudes to the value, or lack thereof, of an early diagnosis of a memory disorder, when there is a widely perceived lack of effective therapies. Until effective therapies are available, or until physicians can be convinced of the reasons why an earlier diagnosis is advantageous, earlier GP referral to a memory service is unlikely to occur even in the context of a highly empowered patient population.

I think one could argue that reviewer number 3 (remember, in the spirit of the open and transparent policy of the journal, the reviewer is named) is perhaps less enthusiastic than the other two. But I think I would be very happy to receive these sort of review for any paper I ever submit to a journal. And that you'd expect a request for changes to the manuscript (to be fair, reviewer 1 had some minor comments requesting clarification in a couple of parts in the text) but full consideration for publication, at this stage.

Well, that's not quite what happened, because the research editors overruled the reviewers and rejected the paper straightaway. Now, obviously, it is perfectly possible that the editors find flaws in the reviews (although I think you'd question the choice of reviewers, if all 3 turned out to be not up for the job, in the view of the editors who have appointed them...). But I think that their comments were rather out of place $-$ for example, they mention a "8 year difference between Intervention and Control groups", while actually the difference in age was less than a year (and they got confused with an 8 point difference in % of males).

I don't want to sound petty and, as I said, the journal have all the rights to reject the paper $-$ after all, we did acknowledge some of the limitations (e.g. we had important issue with missing data and we dealt with it using statistical methods $-$ interestingly, that wasn't a problem for the editors per se, although they said they thought we had "changed our primary outcome", while we simply imputed missing values for the primary outcome using, among other variables, a similar outcome variable, as mentioned by reviewer number 1). So I think it would have been OK to be told that, because of the issue with missing data, the results did not look strong enough. In fact, we did acknowledge the uncertainty in our estimation, but even after modelling missingness the results were negative, so I think that should have been less of an issue. 

Anyway, we did appeal (more to make a point than in hope of any real change) and yet again I was on the losing side $-$ I'm starting to think I should probably start supporting all the causes that I really do not believe in, so that I'll either win some of the future referenda to create as many city-states are there are in the world, or at least will see them fail and take some credit for my personal jinx...

How to be Bayesian and spare yourself a dreadful afternoon with your stupid football team losing the derby

Yesterday was the second-last game of the Italian Serie A; I've been a Sampdoria supported since I was 12 $-$ at that time, they were starting to become one of the best clubs in Serie A (and that was back in the 80's when Serie A was arguably the best league in the world), although they hadn't won anything and didn't have prospects for that season either. But they were a young, good side, playing nicely and so I kind of fell in love with them (and their shirt). Then they did become a very good side, winning the league and a few more trophies $-$ so good timing on my part! But also, then they reverted to some relative mediocrity $-$ of course, once you've decided you support a team, you're stuck with them no matter what.

Anyway, this season has been rather crappy and yesterday it was a crucial game: we were playing the derby against local rival Genoa entering the game with 40 points and two games left in the campaign. Two teams couldn't reach us any more (as they were trailing by over 6 points). But at least one between Carpi and Palermo could still overtake us if we lost our two remaining games and they won all of theirs. Also, Udinese was just one point behind us so they too could overtake us, technically. With three teams being relegated, we weren't statistically safe yet.

So, that's kind of nervous and earlier last week I thought about this a bit. I had a bad feeling about our game, because we've not been great lately (the previous game we were beaten by Palermo) and, clearly, Genoa would try really hard to mess it up for us... But, irrespective of the outcome of the derby, if at least one between Carpi, Palermo and Udinese failed to win their match we would be safe (as there wouldn't be enough points left for them to catch us). Carpi played at home against Lazio, whose season hasn't been great either, but they were already safe and with not much else to fight for, except a strong finish; Palermo were away at Fiorentina, who theoretically were still fighting for a Europa league qualification and so should have something to play for; Udinese were away at Atalanta, who much as Lazio were mathematically safe and with not much to play for.

Although one can make a much more complex model, I reasoned that instead of the actual result, what was only important was the chance that either of the three teams behind us would win and so I set up a model with $ y_{\rm{Car}} \sim \mbox{Bernoulli}(\theta_{\rm{Car}})$, $y_{\rm{Pal}} \sim \mbox{Bernoulli}(\theta_{\rm{Pal}})$ and $y_{\rm{Udi}} \sim \mbox{Bernoulli}(\theta_{\rm{Udi}})$ where the "success" would in fact be the worst possible outcome, ie a win for them.

Then I set up some priors: I reasoned that because they were playing at home, Carpi may have a slightly higher chance of winning the game $-$ I figured something about 35%. Also, I thought (hoped) that Lazio wouldn't be a walkover and so I assumed that 90% of the mass for the chance of Carpi winning their game was around 45%. These can be turned into an informative Beta(15.80107,28.4877) prior $-$ it's fairly easy to work out the parameters of a Beta distribution given the mode (0.35, in this case) and some percentile (0.45 as the 90th percentile, in this case); Christensen et al (page 100) show some theory, while this is some relevant R code.

This is effectively the prior I was assuming:

and I thought it was just about reasonable (the dotted vertical lines indicate a rough estimate of the 95% prior credible interval). Then I did something similar to derive the priors for a Palermo and Udinese win $-$ because they were playing away, I figured they would have an average chance of winning of around 20% with 90% of the mass before 40%, which can be turned into a Beta(3.279775,10.1191) prior, looking like this:

Again, I was relatively happy with this and so used these priors in my model, which one could code in R as something like

p.car ~ rbeta(10000,15.80107,28.4877) # P(win) on average .35 and with 95% mass <= .45

p.pal ~ rbeta(10000,3.279775,10.1191) # P(win) on average .2 and with 95% mass <=.4

p.udi ~ rbeta(10000,3.279775,10.1191) # P(win) on average .2 and with 95% mass <=.4

p.safe <- 1-(p.car*p.pal*p.udi)

The most important variable in the model is the probability of Sampdoria being mathematically certain of avoiding relegation, p.safe, which is 1 minus the probability of the worst happening $-$ this assumes independence in the three games for Palermo, Carpi and Udinese; in general that's probably not the best assumption, but in this case they kind of had to win to have a good shot at safety themselves and so I think it's OK to assume independence. The results were kind of reassuring:

$-$ I got an estimated posterior average of 97.8% with a 95% credible interval of 93.8 to 99.7%. 

I am not really one to stay at home on a Sunday just to watch the football game (so perhaps I'm not really a footaball fan?) and we'd planned to see some friends, but this reassured me that we shouldn't be in too much trouble, even if we lost the derby. In the event, Kobi wasn't great (possibly as a result of venturing an outing at the seaside on Saturday) and so we stayed at home $-$ but I decided not to bother with watching the game (again: a) a bold move for a real football fan, confident about his team; b) a cowardly move from a real football fan scared of what the outcome may be; c) not a real football fan).

We did lose the derby very badly, but Carpi, Palermo and Udinese all failed to win their games, which means we are safe. I'm glad I didn't watch the game...

What's my job again?

For quite some time now, Kobi (who's just turned 4) has been kind of obsessed with Monster University. In fact, all he really cares about is one particular scene in which, as part of the "scare games", the monsters have to run through a corridor while other monsters throw spiky balls at them (this is called a "toxicity challenge"). 

Anyway, he wants to play this game all the time (including yesterday, Sunday, at 7.30am): he starts running around the house while we have to throw a few balls (one of which is actually spiky $-$ though not toxic! $-$ at him).

More interestingly, when Marta and I were trying to explain what kind of job we do, we told him that we both work in university. To which he replied: "Oh, so you throw spiky balls?". I wonder what the Bayesian version of that could be...

Italians do it better!

I've just spent a little over one hour to sort out my registration, travel and accommodation for the upcoming ISBA conference, later this year in Sardinia $-$ well, I say "sort out"... I think most of the details have been sorted out, so fingers crossed...

Last time I went to ISBA was the last time it was in 2006, the second-last edition organised directly as a "Valencia Meeting" and it was a-we-so-me! It was already a rather big conference, but I think it was a lot more manageable (both financially and academically) than it has become, since 2010.

Anyway, I'll be speaking on a session about our work on the regression discontinuity design, so I'll go to this edition (if all the planning goes well, that is...).

So far, it seems that one perk is that booking through Italian websites is way cheaper than doing so through English websites. I guess Italians do do it better...

Theta Rounds

Later this week, I'll escape the cold British winter and flee to the even colder Canadian winter (-13 Celsius, I think!), to be in Toronto for a few days $-$ I suppose I'm going to need a lot more than a scarf...

Anyway, I've been invited by Petros, so by taking advantage of the UCL reading week (no lectures for my Bayesian methods in health economics course), I'll first teach on the last day of the course on Decision Modelling Using R organised by the Toronto Health Economics and Technology Assessment (THETA, in short) Collaborative. 

Then on Friday, I'll give a talk on our work on the expected value of partial information. I think the talk will be also a webinar, so it will be possible to register and attend virtually.

By looking at the range of activities, THETA seems like a very active and interesting group, so I'm looking forward to this!

The aviator

To continue with the weirdest week in terms of emails, I have received one today that says: 

Dear Dr. Baio,

I represent XXX (an imprint of YYY).  We are looking to publish books in aviation that are scientific, academic or professional in nature.

As you work in this field, please let me know if you’d like to work on a new book related to aviation. It could be a book that you develop on your own, or an edited volume comprising invited chapters. I can provide more details after I hear from you. Would you also provide some details of your professional background?


I find particularly amusing the final request about details of my professional background $-$ may be would be a good idea to first check on that?...

Who do you think I am?

Today I've received an email inviting me to submit a paper to a scientific journal (it doesn't really matter what journal it is, or whether or not my own work is actually relevant for them). I looove the way they've addressed to me, though. I think that from now on, I'll actually demand to be called "Gianluca Luca Baio G."!

Two peas in a pod

Earlier today I've seen this post about Frank Wilcoxon's work on non-parametric statistics, on the Significance website. I've only very recently become involved in using some non-parametric methods (notably for our work on the EVPPI and on variable selection using random partition models).

Also, Marta and I have very recently become super-involved with the work of Dr Nefario and I couldn't help but noticing the extraordinary similarity between the two...

My compliments

I've been told of a nice review of BMHE in the Australian and New Zealand Journal of Statistics, by Patrick Graham. I was very pleased by the review. Particularly about a couple of bits. One, for example, says

A general strength of the book is its anchoring in practical examples. This feature should appeal to its intended audience: students in an advanced course in health economics. Another attractive feature of the book is that the author has followed what might be called the “Gelman approach” of using very informative table headings and figure captions.

$-$ a "Gelman approach" is kind of what I was going for, so that's very nice!

Another bit of which I was very pleased says

While the book would probably not suffice as a stand-alone text for a general course on Bayesian inference some of the examples could help enliven such a course by illustrating the application of Bayesian methods to complex models designed to inform important and difficult decisions.

which again was something I was aiming for, while writing the book.

On a related note, we're preparing some interesting (I think) changes/additions to BCEA $-$ I'll blog about these soon!

In my humble opinion...

The American Statistical Association have shared this picture on their Facebook page $-$ I think the quote is brilliant!