August 12, 2013
Stat of the Week Competition: August 10 – 16 2013
Each week, we would like to invite readers of Stats Chat to submit nominations for our Stat of the Week competition and be in with the chance to win an iTunes voucher.
Here’s how it works:
- Anyone may add a comment on this post to nominate their Stat of the Week candidate before midday Friday August 16 2013.
- Statistics can be bad, exemplary or fascinating.
- The statistic must be in the NZ media during the period of August 10 – 16 2013 inclusive.
- Quote the statistic, when and where it was published and tell us why it should be our Stat of the Week.
Next Monday at midday we’ll announce the winner of this week’s Stat of the Week competition, and start a new one.
The fine print:
- Judging will be conducted by the blog moderator in liaison with staff at the Department of Statistics, The University of Auckland.
- The judges’ decision will be final.
- The judges can decide not to award a prize if they do not believe a suitable statistic has been posted in the preceeding week.
- Only the first nomination of any individual example of a statistic used in the NZ media will qualify for the competition.
- Individual posts on Stats Chat are just the opinions of their authors, who can criticise anyone who they feel deserves it, but the Stat of the Week award involves the Department of Statistics more officially. For that reason, we will not award Stat of the Week for a statistic coming from anyone at the University of Auckland outside the Statistics department. You can still nominate and discuss them, but the nomination won’t be eligible for the prize.
- Employees (other than student employees) of the Statistics department at the University of Auckland are not eligible to win.
- The person posting the winning entry will receive a $20 iTunes voucher.
- The blog moderator will contact the winner via their notified email address and advise the details of the $20 iTunes voucher to that same email address.
- The competition will commence Monday 8 August 2011 and continue until cancellation is notified on the blog.
Rachel Cunliffe is the co-director of CensusAtSchool and currently consults for the Department of Statistics. Her interests include statistical literacy, social media and blogging. See all posts by Rachel Cunliffe »
Statistic: These lovely and uninformative visualisations. I especially like that the Age of CEO is incorrectly sorted.
Source: Auckland University Business School
Date: Recently
It’s proof that visualisations are not informative by default
11 years ago
Statistic: Can I please nominate the New Zealand Herald, for displaying a complete ignorance of how averages work?
“Aucklanders’ rates bills have arrived in letterboxes and the figures have come as a shock to some homeowers who have seen rises of 10 per cent – despite the council promising an average increase of 2.9 per cent.”
Source: http://www.nzherald.co.nz/nz/news/article.cfm?c_id=1&objectid=10911222
Date: Today (Monday 12 August)
Because averages and maximums are not the same thing.
11 years ago
Statistic: There’s a massive hole in your logic dear Steve
Source: Stuff.co.nz
Date: 14 August 2013
I’ve seen many mistakes in the calculations of life expectancy at retirement but this one is bizarre.
Steve Waite uses the life expectancy of a 30 year old to calculate the life expectancy of a 65 year old!
He says that in the past “the average 30 year old male could expect to live till they were 71” and therefore they would receive super for 6 years.
Using the 1980 life tables (from stats.govt.nz) the correct figure should be 13 years.
Today’s figures, Steve says, are that “we can expect the average 30 year old male today to live till they are 81” and that they are on super for 16 years.
The correct figure for a 65 year old is 19 years.
Steve then divides 16 by 6 to get 2.66 and says that the cost of super is 255% of what it used to be. The correct figure is 19 divided by 13 which is only 1.46. A BIG difference from 2.66.
The “massive hole in our bucket” isn’t anywhere as big as Steve makes out.
11 years ago
Statistic: “[H]arm prevention orders are imposed on the ‘balance of probabilities’ and are predicted to [a]ffect about 80 people a year, which implies that about 41 actual child abusers will be prevented from any contact with children for a ten year period, and about 39 people who aren’t child abusers will suffer the same fate.”
Source: The Dim Post
Date: 14-8-2013
This is an interesting use of statistics to explore the consequences of the proposed “Child Harm Prevention Orders.”
11 years ago
Statistic: 39 people who aren’t child abusers will suffer
Source: The Dim Post
Date: 14 August 2013
(Hat tip to Simon Connell for this one.)
“[H]arm prevention orders are imposed on the ‘balance of probabilities’ and are predicted to [a]ffect about 80 people a year, which implies that about 41 actual child abusers will be prevented from any contact with children for a ten year period, and about 39 people who aren’t child abusers will suffer the same fate.”
The calculation is incorrect. It assumes that if a person is guilty on the balance of probabilities then P(guilty) = 0.51
But this is wrong. All we can say is that P(guilty) > 0.5
The range of probabilities will vary from 0.5 to 1. This means that the number of innocent people will be 40 or less, most likely MUCH less.
We don’t know the distribution of probabilities but if it is uniform then the expected number of innocent people will be only 20.
If there is a bias towards the more serious offenders then the number will be less than 20.
11 years ago