Fantastic, Mr President

President Macron of France took a teenager to task for failing to show him – or more correctly, the Office of his Presidency – due respect.

It is a fantastic clip, in which the French leader displays gravitas whilst taking the opportunity to educate.

The day you want to start a revolution you study first in order to obtain a degree and feed yourself, OK?

Wise words.

It would have been so easy for him to have ignored the low level “cheek” from the garcon – and how often have we, as teachers let things slide, or seen colleagues do so?

As @Marcus Haddon said on Twitter:

I’ve seen some headteachers in the UK have less interaction with their students than this.

Watch the clip for a 30 second masterclass in how to set a positive role model.

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Most Competitive League in Europe

One in eight thousand

Saturday saw Aston Villa face Fulham FC in what is widely regarded as the most valuable game in world football – the winners of the Championship play off can look forward to the next season in the Premier League, a season worth circa £170 million, a sum far eclipsing the prize money of any other competition.

The above is easy to quantify, less so is the assertion that the English Championship is the hardest to gain promotion from, the most competitive league in Europe, although many will make this claim.

So which is the most competitive league in Europe?

Before we can answer that question, we have to determine how we can answer that question.

My solution (of course!) is to employ some maths – let the numbers do the talking.

Standard Deviation is a measure spread, a measure of how close to the mean (average) the data is spread.  A low standard deviation tells us that the data is closely clustered around the mean, whilst a high standard deviation tells us that the data is spread out around a wide range of values.

I calculated the standard deviation for fifteen different European leagues, and compared the standard deviations of the points each team gained in the season. The leagues with a lower standard deviation, I concluded, were more competitive than those with a higher standard deviation.  A lower standard deviation means that the points for each team were closer to the mean, suggesting that the clubs in that league were more matched, and therefore the league more competitive than those leagues with a high standard deviation.

68 95 99

68, 95, 99 – no, not the years that Spurs won the cup, but a handy rule of thumb, sometimes known as the 68-95-99.7 rule (or three sigma rule if you want to sound clever).  What it tells us is that for a normal distribution (or bell curve, and we can expect points scored in a league to be of this form) 68% of data points (points gained in our example) lie within one standard deviation (in either direction, above or below) the mean, 95% lie within two standard deviations and 99.7% (or nearly all) results lie within three standard deviations of the mean.

And the winner is …

So after all this maths, which league is the most competitive? Is it the English Championship as so many pundits would have you believe?

No, the most competitive league in Europe is the Russian Premier League, with a standard deviation of 13.3, closely followed by the Bundesliga with a standard deviation of 14.0.

The English Championship is not as competitive as the two divisions below it, although it is more competitive that the English Premier League it feeds into.

And it seems that the Bundesliga is bucking the trend – the other “big” European leagues have the higher standard deviations, suggesting that they are less competitive, with Italy’s Serie A coming bottom with a standard deviation of 20.6.

League of leagues

So here is my league of leagues, based on standard deviation, the most competitive at the top, least at the bottom:

League Standard Deviation
Russian Premier League 13.3
Bundesliga (Germany) 14.0
League 2 (England) 15.1
League 1 (England) 15.3
Greek Super League 15.8
Scottish Divison 1 16.8
Championship (England) 17.1
Dutch Eridivise 17.4
Ligue 1 (France) 17.6
Scottish Premier 17.6
Scottish Divison 2 17.7
La Liga (Spain) 18.2
Premier League (England) 19.2
Portugues Liga 19.3
Serie A (Italy) 20.6

 

Posted in Handling Data, Uncategorized | Tagged , | 3 Responses

Financial Times – could do better

The above tweet [link] popped up in my twitter feed this morning, and it got me thinking.

Not about whether or not Dominic Raab’s claims* were valid.

No, I spent quite some time trying to figure out what that “graph” (info-graphic is probably a better term) was trying to say.

I just couldn’t figure it out.

Now, I’ll be the first to admit, I’m no economist and I’ve never formally studied the subject. But I would describe myself as reasonably numerate and (as I have written before) as a mathematician I am far more interested in the applied side of the subject to the pure; I am used to taking equations, data, charts and graphs and interpreting them. But on seeing the above, I just couldn’t understand it.

First schoolboy error was no axis labels (and no numbers on the y axis at all.)

The headline in bold mentioned house price increase from 1991 to 2016, suggesting a time series graph, where we are accustomed to seeing time flow from left to right.  The title did imply that we were looking at a change over time, yet this makes no sense in the context of the graphic (I’ve given up callling it a graph because, although presented to try and look like a graph for (I presume) gravitas, it ain’t a graph).

I was now becoming increasingly confused.

Having twigged it was not a time series graph, my mind then picked up on a couple of key features of the graphic.  The title said “average house price” and the top number on the x-axis was 275.  I knew that the average UK house price is around £275K (I’ve since checked – its a little lower, but in that ball park) so perhaps the graphic was meant to represent the average house price in the UK? But that made the chart even more nonsensical.

By this stage I was genuinely perplexed. I genuinely had no idea what this tweet and graphic was trying to say.

I could have (and perhaps should have) left it there and got on with my day. But I couldn’t. It was bugging me, so I did a bit of digging to see if I could fathom what the Economics Editor of the FT was trying to convey. It seems I wasn’t alone in my confusion, finding this thread on Reddit

[–]AlcoholicAxolotl1 point

I have no idea what this is trying to show.

[–]easy_pie1 point

I’m struggling to follow what his point is

[–]daveime#Puglife 1 point

Is it big or small?

Who the f$$k knows? Graph with no labels, one axis without values and the other without values or units. What is the Y axis exactly, Hedgehogs per Furlong?

FT Economics Editor, seriously? He must have been absent when they did graphs.

Fortunately, on the same thread, another user, DavidChild, was able to simply and succinctly explain what the Tweeter was trying to say:

Dominic Raab claimed immigration caused a 20% increase in house prices. The bar along the bottom shows percentages, the red and green showing the proportion of the change attributed, and not-attributed, to immigration.

The role of teachers and journalists alike is to educate and illuminate.

This graphic failed to do either – I would have expected more. *Dominic Raab was guilty himself of mangling statistics to suit his own ends and it is right that his (mis)use of data is called into question, but if one of my A level, or even GCSE, students had presented this to me, they wouldn’t have been getting many marks.

In conclusion, Chris Giles, Economics Editor at the FT: could do better.

Posted in Handling Data, Maths Fail | Leave a comment

Hell’s Angles

I stumbled across the above the other day (source) and it made me chuckle, reminding me a little of of this post about cute angels and other mathematical bloopers.

The cartoon above was drawn by Dan Piraro and can be found on his Bizaro website – well worth a visit. By virtue of the fact that you are reading my blog, I’m guessing you are of a mathematical bent (but whether that bend forms an acute or obtuse angle, who knows!) and therefore may particularly enjoy this cartoon of his.

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Nick Gibb – a poor man’s George Osborne?

Back in 2014, I wrote “What a turnip” as the then Chancellor of the Exchequer, George Osborne, refused to answer the simple times table: “what is seven times eight?”

Today it was the turn of the School’s Minister, Nick Gibb, who was on TV announcing his scheme for all eight and nine year old children to sit a compulsory times tables test.

Of course, the inevitable happened: he, himself, was asked a times tables question (what is 8 x 9?) and he, like Osborne before him, refused to answer.

I get why he (and other politicians) choose not to answer – what is in it for them? Nothing.  Get it right and “meh, you should know that”, get it wrong and it’ll haunt you forever, could even spell the end of a glittering* political career.   (* tongue firmly in cheek)

But the presenter, Kate Garraway, skewered him perfectly – in the context of the world of an eight year old, sitting a formal test is as high pressure as doing a TV interview is for a government minister.

To be fair, I don’t disagree with all that the Minister has said and done.  The results for individuals, or individual schools, will not be published, the data will be used as a tool to measure performance in this skill across LEA and the country. And he spoke of the need for instant recall of times tables allowing the freeing up of working memory for other tasks, and I agree with this.  As a maths teacher, I support anything that will promote numeracy and mental arithmetic – a solid foundation in these skills is not essential to future success in mathematics, but they certainly do help. A lot.

Anyway, you can watch the cringe-worthy ministerial squirming on the video below – it should start at the point the question was asked, but if you can spare six or seven minutes, its worth watching the whole interview from the beginning.

Posted in Maths Fail, Numeracy | 1 Response