Saturday, 16 October 2021

Quibans 102: Fly me to the match

This story comes from the BBC Sport website.  It was then picked up by other news outlets.  Sky Sports included much of the same material, but the final bullet-point comes from their version of the story.

Man Utd defend decision to fly 100 miles to Leicester for Premier League game

United say they would not normally fly to the game but plans changed due to "circumstances". There were reports of traffic congestion on the M6.

Flying is a significant contributor to global warming and world leaders are meeting later this month in an attempt to avoid a climate catastrophe.

Aviation actually only contributes about 3.5% of the world's global carbon emissions, according to Carbon Brief, but only a very small percentage of the world flies frequently, meaning those who do are disproportionately responsible for these emissions.

Domestic flights are the least energy-efficient way to travel, as shown by the graphic below. France has moved to ban all short-haul domestic flights.

In response to BBC questions around the travel plans, United said they:

§  Have a policy to purchase certified green electricity for all club buildings and facilities.

§  Achieved the Carbon Trust Standard certification for a sixth consecutive year in 2020.

§  Achieved 12 consecutive years of energy and carbon reductions through the Manchester United Energy & Carbon Reduction Programme.

  • Since the programme's launch in 2008, they have reduced annual carbon emissions by over 2,700 tonnes, a reduction equivalent to emissions produced by 540 homes for a year.

 

 

Questions:

1) In the table, what hasn’t been explained?

2) What is the link between the two figures in the table for cars?

3) Why might the figure for a bus be less than for a car, but more than for a coach?

4) Look at the final bullet point.  How many km driven by car are equivalent to the emissions produced by a home in a day?

Here are the figures used in the table (taken from a government document):

 

 

 

Diesel

Activity

Type

Unit

kg CO2

Cars (by size)

Small car

km

  0.14024

miles

  0.2257 

Medium car

km

  0.16877

miles

  0.27161

Large car

km

  0.20763

miles

  0.33415

Average car

km

  0.17152

miles

  0.27603

 

Questions:

5) From the graphic in the story, a diesel car uses 171g per km.  Where is that figure?

6) What is the conversion factor between km and miles (it’s not exactly 1.6) ?

7) Find the average of the km figures for the small, medium and large cars.  Is this the same as the average car?  Comment!


Here is more data from the government document:

 

kg CO2

Diesel

  0.17152

Petrol

  0.18014

Hybrid

  0.11346

Battery Electric Vehicle

0.05973

Questions: 

8) Comment on the choice to use diesel cars in the graphic.

9) Do hybrid cars use their batteries exactly half the time?

10)  In the bus data (not yet shown), there is data about Local bus (not-London), Local London bus, Average local bus.  Do you expect the London or the not-London figure to be higher?  Will the average figure be halfway between the London and not-London figures, or closer to one of them (which one)? 

Here is the bus data:

Type

Unit

kg CO2

Local bus (not London)

passenger.km

  0.11974

Local London bus

passenger.km

  0.08163

Average local bus

passenger.km

  0.10391

Coach

passenger.km

  0.02728

Questions: 

11)  Were you right?

12) How many days of extra CO2 did each player use?

 

Answers:

1) These are presumably average figures.  Some cars will be more polluting than others because they have a bigger engine or are older, etc.  The same will be true for planes.  They haven’t explained why they used Diesel cars; I assume there are more petrol cars on the road.  They haven’t explained the +121g fully.  Does that give an equivalent total CO2 rating for a domestic flight of 254g per km?

2) A car with 1 passenger emits 171g per km.  Dividing this by 4 for a car with 4 people in it, which gives 42.75g per person – which has been rounded to 43g here.  Does this work?  A car with an additional 3 people in it will be heavier and will therefore presumably emit more…

3) I guess: a bus will emit a lot more than a car, but carries a lot more people, so the amount per person is less.  A coach stops less often than a bus (wasting fuel while idling), and is more likely to have a higher occupancy.

4) 2700 tonnes is the amount of CO2 produced by 540 homes in a year, so that is 5 tonnes = 5000kg per year.  This is 5000kg / 365 per day = 13.7kg = 13700g.  Dividing this by 171g, gives us 80km.  (I don’t know whether ‘produced by 540 homes’ includes the CO2 the occupants emit in their cars, or whether this is just the CO2 emitted by the building itself, for heating, cooking, food, etc.)

5) It looks like they have used the ‘average car’ figure (which seems fair enough).  This is   0.17152.  It should be rounded to 172g.

6) Dividing the miles figure by the km one gives 1.609 every time.  The next digit is either a 3 or a 4, so this is accurate to 4sf.

7) Working out the average of the small/medium/large, we get 0.172213.  The ‘average car’ value given is 0.17152, which is slightly different.  Presumably they didn’t work out this average but took into account that there are more medium cars on the road than small cars, etc.  The figures given for each size of car are already averages and it is sometimes problematic to take an average of averages.

8) Presumably there are more petrol cars on the road than any other type.  Did they choose diesel cars because it made cars look better (and therefore made flying look even worse)?  Or did they note that hybrids and electric cars and even better, so it would be fair to use diesel as a kind of average figure?

9) Using half petrol and half electric gives 0.11994, whereas the hybrid figure is 0.11346, so it doesn’t use battery for half the km.  (Using diesel and electric doesn’t work either.)

10)   I expect not-London to be higher, because rural buses will have fewer passengers on them than city buses and London is a big city.  There are many more not-London buses though, so I think the ‘average local bus’ figure will be closer to not-London and won’t be halfway between.

11)   Halfway between the not-London and London figures is 0.100685  The average is more than this, so it is closer to not-London.

12) We don't know whether they needed a coach at the other end to take them to their hotel, etc, but if we compare a 100-mile flight with a 100-mile coach journey, we get the following (and the distance by road is likely to be longer than 100-miles because on a plane you can go as the crow flies! And if the traffic was bad then the coach will have presumably used more fuel):  254g per km for the flight, subtract 27g per km for the coach gives an additional 227g per km.  Multiply this by 160km (equivalent to 100 miles) to get 36.32kg of CO2.  At 13.7kg per home per day, that's an extra 3 days worth of home-carbon to make that flight.  (And it's not just the players and subs but the rest of the support staff too).  

I wonder whether they will drive or fly home ... 


Sources:

https://www.bbc.co.uk/sport/football/58938198

https://www.skysports.com/football/news/12040/12435210/manchester-united-defend-decision-to-fly-to-leicester-for-premier-league-match

https://www.gov.uk/government/publications/greenhouse-gas-reporting-conversion-factors-2019

 

Sunday, 16 May 2021

Quibans 101: Criminals' names

 With thanks to Cat van Saarloos for the data file, here’s a Quibans from the Daily Mirror.

Police release names most commonly linked with crime - and it's bad news for Davids

Bottom of Form

Choosing a baby's name can be a huge decision and many parents spend time agonising over the choices in front of them.

What you are called can have a lasting impact on your life, but can it effect the chances of you ending up behind bars?

Recent research conducted by casino experts Goodluckmate has shown that some names are more common amongst troublemakers in the UK, with David and Sarah topping the list.

Top 10 lawbreaking male names

1.    David - 1,010 criminal charges

2.    Daniel - 1,001 criminal charges

3.    Michael - 895 criminal charges

4.    Paul - 874 criminal charges

5.    James - 796 criminal charges

6.    John - 742 criminal charges

7.    Mark - 742 criminal charges

8.    Lee - 701 criminal charges

9.    Christopher - 691 criminal charges

10. Andrew - 660 criminal charges

Top 10 lawbreaking female names

1.    Sarah - 117 criminal charges

2.    Amy - 111 criminal charges

3.    Claire - 104 criminal charges

4.    Lisa - 103 criminal charges

5.    Lauren - 101 criminal charges

6.    Kelly - 99 criminal charges

7.    Rachel - 98 criminal charges

8.    Nicole - 85 criminal charges

9.    Michelle - 80 criminal charges

10. Louise - 75 criminal charges

A spokesperson for Goodluckmate said: "Our names play a huge part in our identity, but can they influence who we turn out to be? Are there some names that are more likely to end up on a judge’s docket?

"We wanted to find out if a name can make someone more likely to become a criminal, so we made Freedom of Information requests to police forces around the country, asking for the names of people that were charged with crimes in the last two years, so we could discover the names most likely to commit crimes.

"In total, we received 42,671 names from various police forces around the country, allowing us to work out which names had the most criminal charges attached to them."

 

Here is a first set of questions:

Question 1) What errors can you see in the article?

Question 2) Comment on this sentence: “We wanted to find out if a name can make someone more likely to become a criminal”

Question 3) Is this a good use of public money?

Question 4) What is the problem with saying “people called David are more likely to break the law”?

Question 5) What other information would it be useful to have?

Question 6) How much more likely are men to commit crimes than women?

 

And possible answers:

Answer 1) Aside from the maths/stats errors that appear below (and which could also fit here), in this phrase “but can it effect the chances” the word ‘effect’ should be ‘affect’.

Answer 2) This is a correlation vs causation misunderstanding!

Answer 3) A casino company submitted a freedom of information request (FOI) to police forces, asking for this information.  The police forces legally have to respond to FOI request, which costs time and money.  Is it worth it for a request like this?  (Well – it produced a Quibans, but I’m struggling to see any other use!)

Answer 4) If the name David is more common then there are likely to be more law-breakers called David. 

Answer 5) A list of how common each name is.

Answer 6) On the top ten lists there are 8112 males and 973 females, suggesting that men are 8.3 times as likely to commit a crime than women.

There is further information on the casino website:

The UK’s most popular names

When we look at the UK’s current most popular names, how do they measure up?


Question 7)  Any comments about this?

 

Answer 7) I was wrong!  The names David and Sarah don’t appear on the list of most popular names. 

But there is more.  Here’s the end of the casino article:

Methodology

We made Freedom of Information requests to police forces around the UK asking for data regarding the first names of those who had been charged with a crime in the 19/20 financial year within their area. Of the constabularies we made requests to, 17 were able to send data, amounting to a total of 42,671 names. We then took the total number of people charged with each name, giving us our results.

When looking at the UK’s most popular names, we took the top five names for baby boys and baby girls in the UK in 2019.

Question 8) What’s the problem with their methodology?

Question 9) What would be a more sensible thing to do instead?  What other info do you need?

 

Answer 8) They are comparing the number of crimes committed by people with each name in 2019-2020 with how many babies that name was given to in 2019.  If the frequency of names changes year to year, then this is a daft comparison to make, because there won’t be any babies in the crime figures!

Answer 9) It would be more sensible to use name-frequency data from perhaps 30 years ago.

 

Cat has provided data from the ONS (Office for National Statistics), showing the popularity of each name for each year ending in a ‘4’.  Cat’s spreadsheet is here.  The students could analyse this.

Here is the start of the spreadsheet for male names:



And here it is with the 10 names highlighted:

My analysis follows (but there are lots of other ways of doing it). 

Taking the average position for male names in the years 1964 (babies born then would be 55 in 2019), 1974 (age 45), 1984 (age 35) and 1994 (age 25), gives the following table.  David is second on the list:

Name

Average position

James

7.5

David

7.75

Christopher

8

Michael

8

Andrew

8.5

Mark

15.25

ROBERT

15.25

John

17.75

Paul

18

RICHARD

18

MATTHEW

18.25

Daniel

19.25

STEPHEN

21.5

THOMAS

21.5

JONATHAN

23.5

STEVEN

27

PETER

27.25

NICHOLAS

27.75

SIMON

29.25

ANTHONY

30.25

WILLIAM

30.75

ADAM

31.5

Lee

33

 

Aside from Lee (position 23), the other nine names (which are shown in lower case in the table) are all in the top 12.

If instead we focus only on 1974 and 1984 we get this list:

David

3

Christopher

3.5

James

4.5

Paul

5

Andrew

5.5

Mark

6

RICHARD

6.5

Michael

7

MATTHEW

8

Daniel

10

John

13.5

Lee

13.5

 

David appears at the top, and all of the ten names are within the top 12.

 

Quibans 111: How much energy and water do our AI tools really use?

Here is how I used the article below from the Times.  Before showing the article, I started with this information and these questions: Mic...