Stats Chat

The Herald has a story about NZ average wage figures published by the job-search website Seek.

Seek’s latest salary report, released today, showed the average salary for jobs advertised on their website, grew to $72,731 per annum – a 1.3 per cent increase on wages since January.

The problem is that this is an average for a set of ads. It’s  not an average for NZ workers as a whole, but it’s not even an average for people who apply for Seek jobs, or even people who get Seek jobs.

The Herald sensibly reports the average hourly wage that StatsNZ computes.

Figures from Statistics NZ show as of March this year, the average hourly wage was $27.48 or $57,158.40 per year.  

Another useful figure is the median weekly income from wage or salary for those receiving some wage or salary, allowing for part-time and overtime work, which the NZ Income Survey estimates (for June 2012) as $806, giving a yearly figure of $42000.

The New York Times has reported on a study in which observers sat discreetly in bathrooms and observed whether people “properly” washed their hands (I reckon it would be quite hard to sit discreetly in a bathroom unless you’re in a cubicle). Anyway, the description of the study gave careful attention to the stats: 10.3% of women and over 15 percent of men didn’t wash at all. Of those who did wash, 22.8% did not use soap. And only 5.8% washed for more than 15 seconds.

The lead author said, “Forty-eight million people a year get sick from contaminated food, and the (American) Centre for Communicable Diseases says 50% would not have gotten sick if people had washed their hands properly. Do as your mum said: Wash your hands.”

Surely there’s some basic confusion over percentages here: 50% of those who got sick wouldn’t have if everyone had washed their hands properly, but we have no idea what percentage of those who don’t wash actually get sick.

As a matter of fact, there is no indication that these particular non-handwashers have anything to do at all with the fact that people eat contaminated food. Does it matter what bathroom activity was being carried out? Whether you use toilet paper or your foot to flush? Whether you work in food services? Whether you subsequently wash your hands before eating dinner?

Though mum may have had good advice, this sort of scare-mongering about food-borne illnesses resulting from not washing one’s hands may actually distract us from the real concerns over germs.

• Read the full analysis by Rebecca Goldin, here. She is Director of Research for STATS, an American non-profit, non-partisan service that  helps journalists think quantitatively through providing education, workshops and direct assistance with data analysis.

The Super 15 Predictions for this week were published earlier because of a reader request: Super 15 Predictions for Round 18

Team Ratings for Round 16

Here are the team ratings prior to Round 16, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

Performance So Far

So far there have been 111 matches played, 66 of which were correctly predicted, a success rate of 59.46%.

Here are the predictions for last week’s games.

Predictions for Round 16

Here are the predictions for Round 16. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

From Stuff

“I’ll never forget the woman whose knee was injected with stem cells to repair it, and came back two months later saying her skin on her face was smoother and more elastic. We hadn’t touched her face,” he says.

What makes the quote interesting is that it’s being advanced as evidence for, not against, the benefits of stem cells.

Injected stem-cells at least have the potential to work, though the story doesn’t mention any actual controlled trials or anything.  What’s less plausible is the idea that rubbing messenger proteins (cytokines) from stem cells on your skin will have any effect. Despite the best efforts of small children, rubbing stuff on your skin doesn’t usually have the same effects as eating it or injecting it. Skin is there for a reason, and it’s quite good at keeping stuff out of your body, especially huge, fragile molecules like cytokines.

If new skin-care technologies really provided a benefit over ordinary moisturisers, it wouldn’t be hard to collect convincing evidence, as has been done for retinoid creams to treat acne, and chemical skin peels for various skin problems. Unfortunately, the new NZ law on unsupported health claims is just for foods and doesn’t apply to things you rub on your skin.

Almost five months ago, I gave birth to my third child. After each birth, I have tracked my weight loss. I have a few self-chosen rules* for this:

1. I don’t weigh myself at all during pregnancy. I don’t want to become obsessive about weight gain and didn’t gain what I consider to be unhealthy/ridiculous amounts. I did seem to put on a lot more weight with my third pregnancy, right at the end.
2. I weigh myself first thing each morning, and only record the weight if it’s gone down. It’s more motivating this way for me.
3. I eat when I’m hungry, and don’t worry too much about how much I eat in the first three months after giving birth. I always try to eat healthily.
4. I don’t follow a diet. I do watch what I eat in the evenings as I find this is when I’m most tempted to eat unhealthily. Living reasonably far from food shops helps curb the temptation to go grab snacks.

*I’m not in any way a weight loss expert. Disclaimers etc!

While there’s plenty of cool technology and apps to track your own weight and fitness data such as Fitbit (there’s even Wifi scales!), I’ve been using a more humble approach by just manually typing my weight into Excel.

I’ve found this to be such a great motivator for me to see my progress, and to compare it against previous births. There’s something quite nice about manually collecting data and seeing the graph update.

So, I’m going to do a great reveal and show my graphs so far. I don’t lose weight after giving birth incredibly fast, so I hope this is also a nice example for others to see.

For reference, I’m 174cm tall, and normally about 66-68kg. When I was younger, I was about 62kg. I have exclusively breastfed each of my babies.

For each birth, there’s been an initial dramatic weight loss in the couple of weeks after giving birth (water retention, body changes etc), then there’s been a flat period. Note that I didn’t start tracking my weight until a little later with my first child. Then there’s been periods of quick weight loss (often connected to increased breastfeeding!) and periods of much slower weight loss.

In case you’re wondering, I’m currently feeding my baby a lot more as she’s started waking in the night again as she has a bit of a cold and may be teething or just being a baby and waking more!

After the first two births, I went down to my target normal weight and then stopped weighing myself.

While watching Discovery Channel’s coverage of Nik Wallenda’s nerve-wracking high-wire walk across the Little Colorado Gorge Grand Canyon*, it was somewhat bothersome to hear the commentators repeatedly say that there was “no room for margin of error”.

I wonder if there’s any other statistical phrase that is used in other contexts so often?

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 June 28 2013.
• Statistics can be bad, exemplary or fascinating.
• The statistic must be in the NZ media during the period of June 22 – 28 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.

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If you have read media stories recently that say ‘yes’, you’d better read this article from the Genetic Literacy Project …

Team Ratings for Round 15

Here are the team ratings prior to Round 15, along with the ratings at the start of the season. I have created a brief description of the method I use for predicting rugby games. Go to my Department home page to see this.

Performance So Far

So far there have been 107 matches played, 65 of which were correctly predicted, a success rate of 60.75%.

Here are the predictions for last week’s games.

Predictions for Round 15

Here are the predictions for Round 15. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.