Category Archives: Fun

Let the children take us to space

44 years ago a feather and a hammer were dropped at the same time on the moon by Commander David Scott of Apollo 15. An experiment that continues to cause wonder and inspire children today. Indeed, it may well have been an experiment children would have dreamed up for the astronauts to do. This post is simply to get the children of New Zealand thinking of experiments and possibilities once more.

We are going to have a rocket launch facility in our own backyard.  Wow!  If that doesn’t excite, then little will.  Rocket Lab inspires not just because big controlled explosions are cool (well duh!), but because those involved are innovative, and commercially savvy. Exactly the qualities I’d like to see fostered in the next generation.

Peter Beck, founder and CEO of Rocket Lab has promised that anyone can reach space.  Well said Peter. Here’s my vision to add to his.

  • Let that anyone be the children of New Zealand.
  • Let New Zealanders launch our first satellite (#NZS1 for want of a better handle)
  • Let that satellite be locally dreamed up and grown
  • Let there be a competition to gather ideas for what NZS1 should do
  • Let our children vote on which idea they’d like to see launched first
  • Let the money be crowd-sourced from within New Zealand (less than $2 each!).
Rocket Lab's vision for their launch facility (used with permission)

Rocket Lab’s vision for their launch facility (used with permission: http://www.rocketlabusa.com)

R_014 R_011

 

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Ten Commandments of PowerPoint™ presentations

In my “most cringing” file, ranking somewhere alongside brussel sprouts and Abba, are PowerPoint(TM) presentations that are unreadable and distracting. I have made it my mission to rid the world of annoying animation, fantastic fonts, garrulous graphs, and tortuous tables. The following are my commandments – ignore them and dreadful things will be visited on your presentations to the tenth generation, follow them and you will be showered with the blessing of satisfied audiences the world over.

  1. Thou shalt have no other PowerPoint but the compatible version

Make sure the version of PowerPoint you are producing your presentation on is compatible with that being used at the conference. Mysterious disappearing images and font changes can occur otherwise.

  1. Thou shalt not make thyself animated images

Little creatures running across the screen are no longer cute – just annoying. Everyone has seen them before. Furthermore, they have the disturbing habit of crashing programs. If you are new to PowerPoint they may excite you – do not fall into temptation.

  1. Thou shalt not sully a slide with masses of graven clipart

Any image displayed should be illustrative of a point being made. Rarely should one use more than one image per slide. Too many images are a distraction to the audience.

  1. Remember to contrast text and background and keep it sharp

Light coloured fonts must be on very dark backgrounds and vice-versa.   Yellows on pale blues, for example, are usually not visible when projected. Remember, the projector screen is going to have lights shining on it – so it will be much duller than your computer screen. A test is to try and read your computer screen from 5 or more meters away.

  1. Honour thy audience

This commandment requires you to consider your audience and their needs.   They can only take in “so much” information, so keep the number of PowerPoint slides to a minimum – no more than one per minute of presentation (preferably one per 3 minutes). Present your name and who you represent on the first slide (so they know they are in the correct room). Don’t display your full letterhead on every page. Be careful not to display images of half dressed women or cartoons that may offend someone in the audience.

  1. Thou shalt not write screeds of text

As a rule of thumb – No MORE than 6 or 7 lines of text per page. Unless there is a need to quote something AND for the audience to read that quote, then do not write paragraphs. Keep the text simple and short (bullet points). Remember – the text is to illustrate what you are saying and provide a skeleton to hang your points on. The text is NOT the presentation.

  1. Thou shalt not display small fonts

All fonts should be 24pt or above. It may look large on your computer screen, but to someone sitting 10 or 20 metres away from a projection screen it will be the equivalent of a 10 point font in a book.

  1. Thou shalt not display serif fonts

Serif fonts are those like Times New Roman or Garamond that tend to get thinner in the middle of the letter. These are good for reading on paper, but NOT for projecting as they are much more difficult than the non-serif fonts like Arial or Verdana to read. Also, only use the most common fonts that all computers are likely to have as you may find your favoured font is not displayed as you expect. Furthermore, avoid italics and any hand-writing fonts – they can’t be read.

  1. Thou shalt not use images as backgrounds

Images behind texts nearly always make the text difficult to read. Don’t do it.

  1. Thou shall at all times and everywhere minimise the use of graphs and tables and shall only display the necessary information

Alas, this commandment is one that is broken time and again. Any lines on graph must be AT LEAST 3 pt, preferably 5pt thickness. All axes must be labelled (preferably 24 pt). Put on the graph ONLY the data that you are going to speak about. If you are going to talk about a specific data point then put a large red circle around it. Similarly with tables – display ONLY the data you will talk about. You will find that you can’t fit more than about three columns and 4 rows of a table. If you have to, split the table up over a couple of slides. Alternatively, provide the full graphs and tables as handouts. Presenting graphs and tables that cannot be read easily by everyone in the room will irritate your audience and to fail to communicate.

In all that you do, remember that PowerPoint is but a tool to support your voice and your message. You should always be prepared to deliver your presentation if, for some reason, the PowerPoint projector fails.

Here endeth the lesson

John W. Pickering (C) 2005

It’s all about the math, dummy!

No one understands the electoral maths of the NZ electoral system including the electoral commission apparently. Last night I put the latest figures from the “Poll of Polls” into the electoral commission calculator and I discovered the calculator was broken! I put the figures in with United Future winning one electorate seat, but when it crunched the numbers it gave me a parliament without United Future in it. Hmmm… have I uncovered a conspiracy to keep Peter Dunne out of parliament, or is it just evidence that someone got their math wrong. Let’s hope it’s the latter and that they’ll get it right on the night.

Electoral Commission calculator results captured 17 September 2014

Electoral Commission calculator results captured 17 September 2014

In the meantime, let’s consider two concepts this election hangs on – the so called “Wasted vote” and the “Overhang.” The Wasted Vote is the proportion of votes that go to parties that do not make it into parliament by either crossing the 5% Party vote threshold OR by winning at least one electoral seat. The overhang is when a party or parties win more electoral seats than the proportion of their Party vote entitles them too. This means that the size of parliament would increase. Normally 120 and 1/120th of the party vote (0.83%) is equivalent to one member of a party. However, for example, if a party receives just 1% of the vote, but wins 2 electorate seats then this will increase the size of parliament to 121. The various permutations of polls have the current election resulting in a parliament ranging from 120 to 124 seats.

The number of seats in parliament is crucial because it means the effective number of seats a party of block of parties must win in order to form the majority to govern increases. 61 seats are needed for a 120 or 121 member parliament, 62 for a 122 or 123, and 63 for a 124 member parliament.

About the Wasted vote two ideas are important:

The Wasted vote supports the party already with the most votes the most

The Wasted vote could determine who governs!

Let’s assume that 61 seats are necessary in a 120 seat parliament. Ie a block needs 61/120th of the party vote (50.83%) to govern. Crucially this percentage, though, is NOT the percentage of the vote that block gain on the night (which is what the polls try and predict). What it is, is the “effective percentage” after the Wasted votes are taken into account. A scenario could help. Consider an election with two parties crossing the 5% threshold to get into parliament and all the rest being wasted votes. Let’s call the two parties the Big, Rich and Totally Selfish (BRATS*) party and the Really After Total State (RATS**) party. Consider this, there are 1 million voters. BRATS gets 450,000 votes on the night (45%). But, 10% (100,000) of the vote is Wasted. That means the proportion of votes the BRATS get out of the non-wasted votes is 450,000/900,000 giving an “effective percentage” of 50% which would give them 60 seats in parliament.  The RATS would have the same in this scenario. We can turn this question around the other way and ask how high a proportion of the total vote does the Wasted vote have to be for the BRATS “effective percentage” to cross the 50.83% threshold needed to govern? This will depend on the total proportion of votes the BRATS receive  (in our example 45%). The graph below illustrates this.

The percentage of wasted votes the BRATS need in order to govern based on the actual percentage of votes they receive

The percentage of wasted votes the BRATS need in order to govern based on the actual percentage of votes they receive

So, folks, if on the night your vote is in the waste basket, rest assured it will have an effect on the outcome of this election.  The only truly wasted vote is the one that is not cast!

_______________________________________

*Led by Mr I.M. Wright

** Led by Mr M.Y. Tern

How to improve your citation record

Peter Griffin over on Griffin’s Gadgets published a fun post on New Zealand’s seven most influential scientists based on data collected by Thomson Reuters and available at http://highlycited.com. Apparently they are all in the top 1% of cited scientists.  The ODT was obviously impressed by all this number waving and boasted of one of Dunedin’s own being part of the elite.  I was devestated not to be on that list, so I got thinking how I could move up the rankings.  Using Google scholar instead of Thomson Reuters is better for the ego of course because they allow a broader range of journals to be counted as citing or citable.  Unfortunately, if everyone did this I’d not be ranked any better.  Alternatively, I could send tweets out to everyone whom I cited hoping they’d be good enough to cite me back.  If I was really smart, I’d choose to cite most frequently those who publish most often.  Then I came across an easy answer in this graph – I must publish in Multidisciplinary journals!  I better get on with it, only 1650 potential citing days till PBRF 2018 …

Number of cites per document v H index for New Zealand documents published 2011-12. Source: SCImago. (2007). SJR — SCImago Journal & Country Rank. Retrieved June 25, 2014, from http://www.scimagojr.com

Number of cites per document v H index for New Zealand documents published 2011-12.
Source: SCImago. (2007). SJR — SCImago Journal & Country Rank.
Retrieved June 25, 2014, from http://www.scimagojr.com

 

The legend of Chris Martin: Part II

Chris Martin was Not-out a remarkable 50% of the time.  That is, 52 times out of 104 innings.  Is this a record?  I don’t know an answer, so I sent off an email to the gurus at Cricinfo to see if they do.  Michael Jones replied that “Yes it is” for batsman with over 100 innings (see here)!  Well done Chris! What this does raise is the possibility of working out whether it was better for an incoming batsman to swing and hope to score a few runs before Chris was out, or whether they should just play normally? For this we must first consider what to do with the innings in which both Chris and the other batsmen were Not out.  In such circumstances the choice is to include the innings on both sides or to exclude. I’ve chosen to exclude as I think this has the least room for bias.

Now let us apply my Rule #1 and visualise the data (see previous Chris Martin post).

Christ Martin's Partnerships: Data source: Crininfo

Christ Martin’s Partnerships:
Data source: Crininfo

Plot A is a histogram in which I have grouped for each of the two sets of data (the partnership scores when Chris was Out and the scores when he was Not out) into bins.  Each bin is 5 runs wide except for the first.  That is the first bin is from 0 to 2.5 (really to 2), the second from 2.5 to 7.5 etc.   What can be seen from this is that there appear to be more very low partnerships when Chris was Out than when the other batsman was Out.  However, don’t be fooled by histograms like this.  Remember, there were not the same number of innings in which he was out (52) compared to when the other batsman was Out (49).  This may distort the graph.

Plot B is better, but harder to read.  Each black or red dot is a score.  The coloured boxes show the range called the “Interquartile range”.  That is, 25% of the scores are below the box, and 25% are above.  The line in the middle of the box is the median – that is 50% of score are below and 50% of scores are above. The “Whiskers” (lines above and below the box) show the range of scores.

Plot C is less often used in the medical literature (at least), but is really very useful.  It plots cumulatively the percentage of scores below a particular score for each of the two sets of data.  For example, we can read off the graph that about 27% of the partnership scores for when Chris Martin was out were zero.  If we look a the dashed line at 50% and where it intersects the blue line, then we see that 50% of the scores for when Chris Martin was out were 2 or below.  This is a bit more informative than plot B.

What all the plots show is that the distribution of scores in both data sets is highly skewed.  That is, there are many more scores at one end of plot A than the other, or the lines in plot C are not straight lines.  This is very important because it tells us what tests we can not use and how we should not present data.  Quite often when I referee papers, and in papers I read I see the averages (means) presented for data like this.  This is wrong.  They are presented like:

Chris Out:  8.4±13.9

Chris Not  Out: 10.8±11.8

The first number is the mean (ie add all the scores and divide by the number of innings).  The second number after the “plus-minus” symbol is called the standard deviation.  It is a measure of the spread of the numbers around the mean.  In this case the standard deviation is large compared to the mean.  Indeed anything more than half the size of the mean is a bit of a give away that the distribution is highly skewed and that presenting the numbers this way is totally meaningless.  We should me able to look at the mean and standard deviation and conclude that about 95% of the scores are between two standard deviations below the mean and two above.  However two below (8.4 – 2*13.9) is a negative score!  Not possible.

What should be presented is the medians with interquartile range (ie the range from where 25% are below and 75% are below).

Chris Out:  2.0 (0-12.8)

Chris Not  Out: 8 (1-16.5)

We are now ready to apply a statistical test found in most statistical packages to see if Chris being out or the other batsmen being out was better for the partnership.  The test we apply is called the Mann-Whitney U test (or Kruskall-Wallis test if we were comparing 3 or more data sets).  Some people say this is comparing the medians – it is not, it is comparing the whole of the two data sets.  If you don’t believe me, see  http://udel.edu/~mcdonald/statkruskalwallis.html.

So, I apply the test and it gives me the number p=0.12.  What does this mean?  It means that if Chris Martin were to bat in another 104 innings, and another, and another etc, then 12% of the time we would see the difference (or greater) between the Outs and Not Out partnerships that we do actually see (see significantly p’d for more explanation of p).  12% for a statistician is quite large and so we would suggest that there is no overall difference in partnerships whether Chris Martin was Out or was Not Out.  Alas, Chris Martin’s playing days are over and we have the entire “population” of his scores to assess his batting prowess.  The kind of statistical test I’ve presented is only really useful when we are looking at a sample from a much greater population.  However, in the hope that Chris may make a return to Test cricket one day, then what is presented here should give pause for thought for the next batsman who goes out to bat with him… perhaps there is not a lot to gain by swinging wildly, and thereby increasing their chances of getting out; they are probably not improving the chances of the team.

Annual Academic Spam Awards

More annoying than those who boast of the number of unread emails in their inbox are the spammers who contribute to that number.  I’m fortunate to have a university IT department that effectively filters mountains of spam.  Nevertheless, some make it through to my inbox.  In the forlorn hope that I will shame these spammers into disappearing in a puff of smoke I hereby announce my Annual Academic Spam Award winners.

The Robert the Bruce award for persistence.

The Omics Group.

Like Coalgate… they really get in…despite 135 automatic deletes they still sneak through inviting me to write for journals or participate in conferences on topics I don’t know how to spell let alone am able to pontificate about.

The Serpent award for the most tempting conference title of the year

BABE-2013… Omics group!

Dear Dr. John W Pickering,

It is my great pleasure to invite you on behalf of organizing committee for the 4th World Congress on Bioavailability and Bioequivalence Pharmaceutical R & D Summit (BABE-2013), to ….

The CIA award for knowing something about me other than my name

Nephro-2012… Omics group!

Dear Dr. John W Pickering,

We are aware of your busy schedule, still would like to contact you again …

Stop spying on me!

The Stating the bleeding obvious award

Team Catalyst, New Delhi

Dear Professional,

Diseases are the major cause of death,…

The Nutter of the year and Supreme winner of the 2013 AASAs

Alex of the Ukraine

Hello.

I found your e-mail address on medical site.
My name is Alex, I am from Ukraine, I am 32 years old man, I do not drink alcohol and do not smoke cigarettes, my blood is O+ and I have a good health. If you need liver transplant I am ready to give part of my liver, but I want to receive a big compensation for that…

If you do not need liver transplant, but you know somebody who need it, please send my message to this person or keep it just in case.

[ email address removed ]

Alex

P.S. This is not a joke and I am not a cheater or scammer.

All that’s left is to add a reference so that you don’t think I am the only one:

Academic Spam: Comic ID 1590 "Piled Higher and Deeper" by Jorge Cham www.phdcomics.com

Academic Spam: Comic ID 1590
“Piled Higher and Deeper” by Jorge Cham
http://www.phdcomics.com

New way to spread the word

Changes to Flipboard mean it’s now a great tool for science outreach, or indeed any outreach.

If you don’t know what Flipboard is, then checkout Flipboard.com or better yet, download the app.  It combines the beauty of a magazine with the usefulness of a reading list.  I use it on an iPad, there’s also an Android version.  Flipboard began life with in-house  magazines – Time, National Geographic, Popular Science, Cult of Mac etc etc etc.  Now, you can create your own magazines and share them if you wish (or keep them to yourself as a great way of maintaining a round-tuit reading list).  I’ve created two magazines called “Kidney Punch” and “Poland” both of which can be found using the search feature within Flipboard (the magnifying glass). There are a number of subscribers to them.  With two “clicks” I can flip any article I want from other Flipboard magazines, from my Twitter feed (beautifully presented in Flipboard as a magazine),  other social media feeds, or using their bookmarklet from any website (including your own blog of course). If you are going to be public, then keeping the articles flowing is important if you want readers to return.

Note, you may read the in-house mags by downloading the app.  To make your own and read other mags you must create and account and then restart Fliboard – it’s all free.

The front page of Kidney Punch magazine on Flipboard

The front page of Kidney Punch magazine on Flipboard

A page inside Kidney Punch .

A page inside Kidney Punch .

@kiwiskiNZ twitter feed inside Flipboard.  By clicking on the + symbol I can flip anything I want to Kidney Punch or any other of my magazines

@kiwiskiNZ twitter feed inside Flipboard. By clicking on the + symbol I can flip anything I want to Kidney Punch or any other of my magazines