Tag Archives: statistics

Moneyball and the Top 10 Most Popular Books of 2025

Movie-poster-for-Moneyball-starring-Brad-Pitt
IMDb

Well, it’s that time of year again! The end, that is. With thoughts turning to festivities and family gatherings, we naturally look back on the times we’ve had. If that phrase makes you think of graduating high school, I apologize. At VPL, we’re looking back on all the millions of checkouts and check-ins of 2025. Unsurprisingly, many of the same authors remain popular, even the same titles. The lists in their entirety are at the end of this post, but all this talk of checkouts and predicting popularity has me thinking about statistics and what they can tell us about our world. I’ve always found data to be a powerful tool. We can apply statistical analysis to all kinds of subjects, gaining incredible insights on why things happen and whether they will happen again. Think of the brilliance of a movie like Moneyball about Oakland As coach Billy Beane (Brad Pitt) and the work of sabermetrician Bill James. It was James’ application of statistical analysis to the performance of a baseball team – first explained in his Baseball Abstract – that Beane used to take his As to twenty consecutive wins. (Long story short: it’s all about which players manage to get on base when they’re up to bat.) They were the first in the history of the American League to do so. It’s a truly wonderful movie, and not just for us analytical nerds. Michael Lewis’ non-fiction account of the underdog victory story helped director Bennett Miller adapt the events into film. Incidentally, Bill James is now a true crime author, even collaborating with his daughter to craft a meticulously researched account of a suspected serial killer from the turn of the twentieth century. So, with the power of statistics in my mind, I thought I would see what books we have in our catalogue about creative analysis of data. Not so much the straightforward, educational books about data analytics, but the ones with unique or even seemingly incredulous claims.

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Invisible Women

Book Cover of Invisible Women by Caroline Criado PerezWhat with the snow hitting us right about now, it seems like a good time to talk about how snow removal can be sexist. Yup. Snow removal. Sexist.

Edited: Here are the links to Canadian stats! Thank you Victoria!

Northern Sweden has been collecting data on hospital admissions for injuries since 1985, and found in icy or slippery conditions, pedestrians were injured three times more often than motorists, “and account for half the hospital time of all traffic-related injuries”. Furthermore:

[T]he majority of these pedestrians are women. A study of pedestrian injuries in the Swedish city of Umeå found that 79% occurred during the winter months, and that women made up 69% of those who had been injured in single-person incidents… two-thirds of injured pedestrians had slipped and fallen on icy or snowy surfaces, and 48% had moderate to serious injuries, with fractures and dislocations being the most common. Women’s injuries also tended to be more severe. (Criado Perez, c.1: Can Snow-Clearing Be Sexist?, Invisible Women).

Alright, so women are more likely to be injured in icy or slippery conditions (enough to end up in a hospital for treatment), with more severe injuries than men. But why? As it turns out, men and women tend to use different modes of transport, along with very different travel patterns, which is true worldwide to varying degrees (based on the limited sex-disaggregated data we have on the topic): whereas men are more likely to drive and “dominate access to [a household’s car]” (ibid; by which I assume Criado Perez means in man-woman households), with simple travel patterns that consist of commuting to and from town, women tend to walk and take public transport and have more complicated travel patterns, namely trip-chaining: making several interconnected trips at once. This is part of a larger discussion about unpaid labour, which is discussed throughout Invisible Women, but women’s travel patterns tend to include a cornucopia of tasks, including: dropping children off before heading to work; taking aging parents to the doctor; grocery shopping on the way home.

Seeing the data and this information about gender differences in travel patterns, Sweden changed the order of snow plowing to target sidewalks before main roads (because really, it’s a lot easier for the car to drive over snow than for a person to walk (or push a stroller) through the same amount of snow on the sidewalk). Let’s break it down. Considering that pedestrian injuries due to icy and slippery conditions account for, as stated above, “half the hospital time of all traffic-related injuries”, that’s no paltry amount of staff time and effort being devoted to women’s injuries – and this doesn’t even take into account the time this army of injured women need to take off work (paid or unpaid labour) to heal (or even just to go to the hospital in the first place). The conservative estimated cost of these pedestrian injuries throughout one winter was 36 million Kronor (approximately £3.2 million), which “was about twice the cost of winter road maintenance. In Solna, near Stockholm, it was three times the cost, and some studies reveal it’s even higher” (ibid.). All this to say, even if you don’t care at all about gender equality or women getting injured disproportionately, or you think that well in that case more women should just drive to solve this issue**… taking women and their needs into account when policy-making makes sense. I know the conclusion of that sentence was pretty self-evident, and it should be a no-brainer, but clearly, if the decision was made in the first place to plow the roads before taking care of the sidewalks, it wasn’t. It isn’t. Taking women into account doesn’t come naturally, clearly. This is why Invisible Women is such a necessary read, especially now: so that taking women and their needs into consideration will become natural.

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Stats

Charles WheelanYeah, I know. Statistics. Really. I must have run out of things to write about, right? Yes*, but also, no. Stats can be fun! Especially when you’re not being tested on it, and you’re reading just for yourself. And perhaps more importantly, a basic understanding of stats is important, in the sense that it’s important to know at least the basics so you’ll realize when you’re being presented with something that is based upon either no data, or the data has been misrepresented (and if so, then you can dig around a bit to find out why), or even sometimes the data might not add up. So I’m here with an introductory text you might be interested in to get you started: Naked Statistics by Charles Wheelan.

If you’ve taken an introductory statistics course – even if the last time you took one was in high school – you’ll likely find a lot of the information presented in here a refresher. If you’re starting from scratch, Wheelan does a pretty good job breaking down concepts such as standardization, inference, correlation, and regression analysis, describing where you’ll encounter them as well as telling you how data can be misrepresented. You’ll learn about different types of experiments, and the ones from which you can conclude there to be a cause-and-effect relationship, versus the ones from which correlation does not imply causation. It’s accessible, it can be funny, and you’ll come away at the end of the book armed with a basic understanding of probability as well as examples to draw on next time you’re asked to explain the central limit theorem. You’ll be the life of the party – I guarantee it.

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