Posts filed under General (3148)

Team Ratings for Round 14

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 78 matches played, 57 of which were correctly predicted, a success rate of 73.1%.
Here are the predictions for last week’s games.

Predictions for Round 14

Here are the predictions for Round 14. 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.

Team Ratings for Round 16

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 105 matches played, 82 of which were correctly predicted, a success rate of 78.1%.
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 the Herald today:

That last number doesn’t look right.  At the 2013 Census, there were just under 90,000 people ordinarily resident in NZ who were born in the People’s Republic of China. Since then, there have been a net 46000 permanent or long-term migrants, according to a Stats NZ app — and recent research from Stats NZ has found that these figures overstate net migration a bit, because they misclassify some people returning home.  So, there are maybe 135,000 people living in NZ who were born in the PRC. Not all of these will think of NZ as home — some of them will be just here to study, for example — but it’s a reasonable group to consider. It’s not 290,000, and I don’t see how you can get that number.

On Twitter this morning, Tze Ming Mok speculated that the number might be people of Chinese ethnicity, but as she said, even that is hard to get as high as 290,000. And, very importantly, other people of Chinese ethnicity don’t necessarily have favourable views of the PRC — though they (and other people of East and Southeast Asian ethnicity) do get the spillover from both anti-PRC sentiment and traditional racism.

• “Often these studies are not found out to be inaccurate until there’s another real big dataset that someone applies these techniques to and says ‘oh my goodness, the results of these two studies don’t overlap‘,” she said. Genevra Allen (who gave one of the inaugural Ihaka Lectures here in Auckland) on machine learning in science.
• Good piece by Jenny Nicholls from North and South on algorithm risks (based around a new book, Hello World, by Hannah Fry)
• From the open AI blog, about a new neural network algorithm for generating realistic text: “Due to concerns about large language models being used to generate deceptive, biased, or abusive language at scale, we are only releasing a much smaller version of GPT-2 along with sampling code. We are not releasing the dataset, training code, or GPT-2 model weights.” Exercise for the reader: does this feel like a good idea? Would it feel like a good idea if Facebook were saying it?
• “PredPol claims to use an algorithm to predict crime in specific 500-foot by 500-foot sections of a city, so that police can patrol or surveil specific areas more heavily.” And they say that when police go to these areas they really do find crimes occurring there. Which…is less reassuring than PredPol seems to think.
• ” For example, a tench (a very big fish) is typically recognized by fingers on top of a greenish background. Why? Because most images in this category feature a fisherman holding up the tench like a trophy. “ About how neural networks work (a bit technical).
• Julian Sanchez argues that, yes, online click-through agreements are bad for data privacy, but partly because data consent is genuinely a hard problem

Team Ratings for Round 1

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Predictions for Round 1

Here are the predictions for Round 1. 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.

Team Ratings for Round 13

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 72 matches played, 52 of which were correctly predicted, a success rate of 72.2%.
Here are the predictions for last week’s games.

Predictions for Round 13

Here are the predictions for Round 13. 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.

Team Ratings for Round 15

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 98 matches played, 77 of which were correctly predicted, a success rate of 78.6%.
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.

Every summer, the Department of Statistics offers scholarships to high-achieving students so they can work with staff on real-world projects. Larisa Morales Soto, below, is working with Dr Beatrix Jones on a project exploring how the dietary patterns of New Zealand children change during their childhood and the transition to adolescence. 

Unlike most of the Department of Statistics’ summer scholars, Larisa isn’t studying locally. Summer scholarship are open to anyone tertiary student who is appropriately qualified, and Larisa, who is in her third year studying genomic science at the National Autonomous University of Mexico at Morelos in south central Mexico, leapt at the chance to gain new experiences overseas.

“What first motivated my search is that this time of the year would be winter in the northern hemisphere, and research internship programs are not very common in this season,” says Larisa, whose study combines biology, computer science and statistics to answer questions in life sciences.

“What finally brought me to New Zealand was the high academic quality and international presence of The University of Auckland. Also, the summer programme would give me the chance to visit the country and get completely immersed in the culture, something I wouldn’t have been able to do without the scholarship.”

The work she is doing looks at how the overall dietary patterns of New Zealand kids change during their childhood and the transition to adolescence. “During early life stages, children’s parents determine their food intake,” she explains, “but as they grow up, they start making decisions on which foods they want to eat, and their previous diet and other external factors can influence this decision-making process.”

The research hopes to shed light on the complex relationship between diet, health and disease during an individual’s lifespan, understanding how different factors help to establish dietary patterns.

Being in New Zealand has brought Larisa personal and academic benefits: “This experience is having a huge impact on my professional training. But also, I feel that it’s making me grow on the personal level as well, because being alone and very far from my home country is a big step. Being here has changed the perspective I had of New Zealand – I’ve been able to see the greatness of the country in terms of natural resources, social culture, economy and politics.”

In her down time, Larisa has been using the university sports and recreation centre and the library, as well as visiting parks, museums and other attractions in the city and Hauraki Gulf. She also fitted in a quick trip to the South Island with a friend she made here.

This won’t be the last we see of her, says Larisa: “I am definitely coming back in the future.”

• For general information on University of Auckland summer scholarships, click here.

Every summer, the Department of Statistics offers scholarships to high-achieving students so they can work with staff on real-world projects. Yongshi Deng, below, is working with communications company Vodafone New Zealand on a project analysing and predicting customer behaviour. 

Yongshi, who has a BSc in Mathematics and Statistics and an Honours in Statistics from the University of Auckland, is spending seven weeks working within Vodafone’s Big Data and Analytics team.

Her research focuses on analysing and modelling opt-out behaviour among Vodafone’s fixed line customers – those who have purchased broadband, landline telephone and television services. She is using a combination of data on what customers do when they use these services, network data and information from Vodafone’s call centre.

It’s a big job, Yongshi says, but she is relishing it: “I enjoy this project a lot, as I can put my knowledge I learn from my degrees into practice.” There are plenty of problems to solve: “The major challenge is data cleaning, since big, real-world datasets can be very messy. There are millions of missing values that need to be handled.”

Another challenge is variable selection. “The dataset I am currently working on has more than 120 variables, so this makes dimension reduction indispensable,” Yongshi explains. It’s critical that she chooses a good combination of variables to build models that can generalise well for unseen data. This step, she says, is based not only on statistical tests but also on domain knowledge, which she gets from her colleagues at Vodafone.

Yongshi’s supervisor at Vodafone, Neel Sengupta, says that having students in-house brings benefits to both parties. “They get to see what business data looks like and the sheer scale of it. The benefit for us is that we get to see the advancements coming out of universities that we might not necessarily see in a commercial set-up.”

Yongshi’s supervisor in the Department of Statistics, Ciprian Giurcaneanu, agrees that the biggest benefit to students of such work experience is that ”they get in contact with the real world. This allows them to see how useful in practice are the techniques that they have learned in our department.” They also have to fend for themselves: “The lecturer “who knows everything” is not there, and the students have to find their own answers to their questions.”

Yongshi is originally from Dongguan, China. This year, she plans to pursue a PhD at the University of Auckland, and already has a good idea of the field she wants to research: “I am particularly interested in applying machine learning techniques to solve real-world problems.”

Yongshi says that statistics is a “fantastic subject” that not only helps her explore the world, but keeps her motivated and engaged. She particularly appreciates the R programming skills that she has learned in the Department of Statistics. “The department provides a wide range of statistical courses and R is integrated in most courses, which has equipped me with the skill and knowledge I’ll need for further study.”

• For general information on University of Auckland summer scholarships, click here.

Every summer, the Department of Statistics offers scholarships to high-achieving students so they can work with staff on real-world projects. Simon Goodwin, below, is working with Dr Jesse Goodman on random graph dynamics and hitting times.

Simon’s summer scholarship is related to the study of random graphs, looking at how to investigate networks that look as if they are random or pseudo-random, like social networks, family trees or the global flight network.  His task in particular is looking at the nodes in these structures that are hard to reach by moving randomly, and what this means for the structure of the graph as a whole.

You can conceptualise it like this: Produce a random graph by connecting pairs of vertices uniformly at random. Then run a random walk on this random graph: at each step, move to a uniformly chosen neighbour of the current position. The hitting time is the number of steps needed to reach a particular target vertex, and it varies in a particular way depending on the size of the random graph.

Simon’s work looks at the effect of changing the random graph. Between each random walk step, he might “rewire” some edges: pick a fraction of edges, disconnect the vertices on either side, then randomly reconnect those vertices to see if these graph dynamics make it faster (or slower) to reach the target vertex.

“Looking at the structure of these random theoretical objects we can learn about vast real-world networks that have no clearly apparent structure,” Simon explains. “The results I am trying to find would also have theoretical applications in the study of random graphs.”

Simon is about to start his third year studying maths and statistics: “My main interest is in pure maths, but I am also very interested in theoretical statistics, mainly in probability. I am intrigued by all things random.”

In fact, he dropped physics for statistics last year, “and I haven’t regretted it for one moment – sorry physics! I am mainly interested in probability but I have also enjoyed learning about data analysis and I have an interest in statistical computing.”

He adds, “Probability is such an interesting field, as it has a strong theoretical backing while also having many obvious applications such as games with dice and cards, as well as many less obvious applications, from financial-market analysis to quantum physics.”

Simon is hoping to become an academic: “I hope to continue into postgraduate study and then spend the rest of my life studying and teaching what I love.” When he’s not studying, Simon loves playing video games and roleplaying games like Dungeons and Dragons, as well as walking around the scenic spots of Auckland.

• For general information  on University of Auckland summer scholarships, click here.