Thursday, June 20, 2013

How to give a decent presentation

Hi everybody,

I frequently attend conferences, and about as frequently give presentations there. Sadly, over the years, I've seen many smart and gifted people struggle to share their work with their audiences. Luckily, over time, watching & doing presentations has taught me a little bit about what makes a good presentation.

In general materials on presentations, there is a lot of emphasis on using the right fonts, maintaining eye contact with the audience and otherwise being "convincing". Such advice is of little use for the attendants & presenters at technical conferences though.

We want good content, not suave presentations! And that is a good thing since many of us in the tech community tend to be a lot better with computers than with being 'flashy'.

This year we'll again be seeing the four-yearly cycle of great hacker conferences in The Netherlands continue with OHM2013: Observe Hack Make. These events are volunteer organized, and as part of doing my bit, I thought I'd compile what I've learned about doing presentations. This will make me feel less guilty also when I see people digging trenches etc.

On you can find a Google document that contains a presentation on doing just that: giving a decent presentation. And, since slides can't and shouldn't tell the whole story, I've narrated this presentation here and here on YouTube.

This presentation outlines a process of getting to great content (and also touches on how to present that content well). This process starts with answering questions: WHY, WHO, WHAT and HOW. The WHY and WHO determine WHAT to tell, and at which level of knowledge your presentation should start.

The HOW tells you how to replicate your knowledge in the minds of the audience.

At OHM, I too will be presenting, and as an example, I'll go through these four questions here for my presentation on "What you need to know about what you eat: health & weight".

  • WHY: We all get more and more obese, even people perfectly following government advice on how to eat and exercise. Over the past decade, a new consensus has arisen on why we get fat, and we now know that the conventional wisdom has it all upside down, and is making us sick. I'm presenting because I want to share what I've learned in order to let everybody share this new knowledge, so we can save their health!
  • WHO: Hackers with shoddy exercise and eating habits. Many of us where at GHP and HEU over 20 years ago, and I can tell you, the hacker community.. is getting bigger (or at least larger). Especially us 'older' folks are starting to care about what we eat and do. The audience will care, but will not necessarily know the finer distinctions between cis- and trans-fats etc.
  • WHAT: We have one hour, so we can't explain the full modern nutritional theory. So, we'll be explaining basics, plus specific things people can do to improve their health. Also, pointers so people know where to go to learn more.
  • HOW: I have to build it up. If I just get on stage and start ranting about glucolipotoxicity, nobody will know what to make of the story. Introduction is my own story, and that of my family. This makes it personal and interesting. Then we demolish the conventional wisdom with powerful and horrifying graphs. Next we explain some basics that make it obvious current advice is all upside down. Then, once that is clear, clarify what does work. Finally, we round off with a highlight of the most interesting people, books & groups.

With these questions answered, I know what content I need to write, what pictures and graphs I need to gather, and how to keep people paying attention!

It is my sincere hope that if you'll present at OHM, or at any other geeky conference, that you'll be able to benefit from the presentation, and that you'll be better able to get your ideas across!

Finally: to anyone aiming to present at OHM, please contact me if you think I could help with your presentation, for example, by brainstorming on WHO you'll be explaining to and WHAT!

Thursday, June 13, 2013

Some notes on medical statistics

Over the past year, I've been reading more and more about the causes of obesity and the (related) epidemic of diabetes, since both run in my family.  In my readings, I've encountered a lot of dodgy statistics to bolster research claims.

Statistics allow us to make statements like 'the chance that these dice are unfair is less than 1%', based on throwing them n times and observing the results. We call such results 'significant', where the threshold for significance is often set at '5% chance of results being random and not because of some effect'.

(and for the statistics professionals, I know my terminology is sloppy. Have this comic to make up for it:)

The world of medical research also tries hard to do statistics, and by and large fails at this. Partially this is due to a misunderstanding of how statistics work, and partially this is a problem of language.

For example, a pill which causes a 1% absolute reduction in the number of heart attacks in a population can easily result in a 'statistically significant effect'.  This is because we might be *very* sure that the "Odds Ratio" of having a heart attack is 0.99 and not 1.  "p < 0.05".  This number is not clinically significant though, or more concretely, it is an irrelevant number.

Public relations departments, funding considerations and industry relations however just scream to turn this mathematical, statistical significance into a bold press release reporting an actual significant medical advance.

However, since heart attacks are rare, hundreds of people would spend decades taking this particular pill before a single actual heart attack would be prevented.  And who knows how many side effects there would have been!  So, statistical significance does not equal practical significance.

A far better metric is called The Number (of people) Needed To Treat (NNT) to get benefit.  For example, the NNT of common painkillers for treating a normal headache is very close to 1, since they almost always work.

The NNT is far more powerful than "relative statistical significance". For example, although 25% of the over 45 population in the US is now prescribed statin pills, its NNT for preventing a heart attack for people without prior heart disease is 300 person years, or, described differently, if 60 of those people take statins for 5 years, 59 of them receive no benefit.  All 60 are at risk for potential side effects however.

The NNT for preventing a *fatal* heart attack in this population is in fact immeasurably high ('infinite'). For people who have had a heart attack already, the NNT for preventing death is around 80 for 5 years.

There is also "the NNT for harm", which for statins is about 10 after 5 years. In other words, of those 60 people treated for 5 years, 6 of them would have a serious side effect.

The NNT & NNT for harm are medical statistics done right; and it is therefore no surprise these numbers are exceedingly unpopular in press releases and articles.

So next time you read about a medical breakthrough.. look beyond the reported statistical "significance" and see if you can find the NNT.

Some good links for further reading: