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Name: The Art of Statistics
Rating: 4.5 (233 reviews)
Author: David Spiegelhalter

David Spiegelhalter

Learning from Data

4.5 (233 Bewertungen)

25 Min.

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Media Mathematics

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The Art of Statistics
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What’s in it for me? Improve your data literacy and learn to see the agenda behind the numbers.

You might think that with the growing availability of data and user-friendly statistical software that does the mathematical heavy-lifting for you, there’s less need to be trained in statistical methods.

But the ease with which data can now be accessed and analyzed has led to a rise in the use of statistical figures and graphics as a means of furnishing supposedly objective evidence for claims. Today, it’s not just scientists who make use of statistics as evidence, but also political campaigns, advertisements, and the media. As statistics are separated from their scientific basis, their role is changing to persuade rather than to inform.

And the people generating such statistical claims are not necessarily trained in statistical methods. An increasingly diverse number of sources produce and distribute statistics with very little oversight to ensure their reliability. Even when data is produced by scientists undertaking research, errors and distortions of statistical claims can occur at any point in the cycle – from flaws in the research to misrepresentations by the media and the public.

So, in today’s world, data literacy has become invaluable in order to accurately evaluate the credibility of the myriad news stories, social media posts, and arguments that use statistics as evidence. These blinks will give you all the tools you need to better assess the statistics you encounter on a daily basis.

In these blinks, you’ll learn

how statistics can be used to catch serial killers;
whether drinking alcohol is good for your health or not; and
which remarkable creature can respond to human emotions even after it has died.

Statistics can help us answer questions about the world.

Have you ever wondered what statisticians actually do?

To many, statistics is an esoteric branch of mathematics, only slightly more interesting than the others because it makes use of pictures.

But today, the mathematical side of statistics is considered only one component of the discipline. Statistics deals with the entire lifecycle of data, which has five stages which can be summarized by the acronym PPDAC: Problem, Plan, Data, Analysis, and Conclusion. The job of a statistician is to identify a problem, design a plan to solve it, gather the relevant data, analyze it, and interpret an appropriate conclusion.

Let’s illustrate how this process works by considering a real-life case that the author was once involved in: the case of the serial killer Harold Shipman.

With 215 definite victims and 45 probable ones, Harold Shipman was the United Kingdom’s most prolific serial killer. Before his arrest in 1998, he used his position of authority as a doctor to murder many of his elderly patients. His modus operandi was to inject his patients with a lethal dose of morphine and then alter their medical records to make their deaths look natural.

The author was on the task force set up by a public inquiry to determine whether Shipman’s murders could have been detected earlier. This constitutes the first stage of the investigative cycle – the problem.

The next stage – the plan – was to collect information regarding the deaths of Shipman’s patients and compare this with information regarding other patient deaths in the area to see if there were any suspicious incongruities in the data.

The third stage of the cycle – data – involves the actual process of collecting data. In this case, that meant examining hundreds of physical death certificates from 1977 onwards.

In the fourth stage, the data was analyzed, entered into software, and compared using graphs. The analysis brought to light two things: First, Shipman’s practice recorded a much higher number of deaths than average for his area. Second, whereas patient deaths for other general practices were dispersed throughout the day, Shipman’s victims tended to die between 01:00 p.m. and 05:00 p.m. – precisely when Shipman undertook his home visits.

The final stage is the conclusion. The author’s report concluded that if someone had been monitoring the data, Shipman’s activities could have been discovered as early as 1984 – 15 years earlier – which could have saved up to 175 lives.

So, what do statisticians do? They look at patterns in data to solve real-world problems.

The accuracy of data is often skewed by systematic bias.

Data is not just cold, hard facts – it’s subject to human judgments and biases like any other form of knowledge.

In fact, human judgment is involved in the very first step. Before we can collect data, we sometimes have to make fairly arbitrary decisions about what we’re measuring. If our problem is to count how many trees there are on the planet, then we need to define what exactly a “tree” is. For instance, most studies of this type only include trees that have achieved a diameter of at least 4 inches.

How data is presented affects how it’s interpreted.

The pervasive problem of human interpretation doesn’t only affect the collection of data, but its presentation as well.

Recent years have seen a rise in the study of data visualization as a method for communicating statistical results. Data visualizations are graphical devices used to render data visible to the eye. Statisticians describe visual representations of data as inter-ocular, meaning that patterns in the data become discernible from sight alone – without having to do any mental mathematics.

There is a positive bias in scientific literature caused by selective reporting.

Many researchers spend their entire lives combing data for important discoveries that they rarely find. The pressure to publish significant work sometimes leads researchers to massage the data a little.

Despite their fidelity to the truth, even scientists have been known to engage in some questionable research practices. One such practice is multiple testing, which is when researchers repeat tests until they get the results they want. The more a researcher repeats a test, the greater the chance that they will get false positives – results that seem to confirm a hypothesis but are actually due to chance error.

The media tends to emphasize storytelling at the expense of accuracy.

Once research has been published, it then gets reported by the media. The media, however, tends to exercise creative license.

The good news is that data journalism is flourishing. Journalists are increasingly being trained in how to interpret and communicate data. Statistics can enrich stories by bringing clarity and insight to important issues.

Reported averages can be misleading when the type of average used isn’t specified.

Inappropriate uses of averages have inspired some terrible jokes among statisticians.

Consider this one: “Most of us have more legs than average.” This is true, in a sense, if you calculate the average number of legs using the mean average, which is something like 1.9999 – brought down from 2 by people who’ve lost their legs.

The statistician’s mantra is that correlation does not imply causation.

The charge correlation does not imply causation has become something of a cliché among statisticians. Yet the fallacy of inferring cause from correlation is still commonly made by the media and the public alike, so it’s a message that needs to be reiterated.

This misconception is what leads to comical headlines, such as: “Why going to university increases the risk of getting a brain tumor.”

Probability is frequently misunderstood.

When the author was once asked why people tend to find probability difficult and counterintuitive, he replied that probability just really is difficult and counterintuitive.

Even people running the country have problems understanding it. In 2012, 97 members of parliament in the UK were asked this question: “If you flip a coin two times, what’s the probability of getting two heads?” The answer is one quarter, since getting two heads is one eventuality out of a possible four. The majority of parliament members – 60 out of 97 – could not give the correct answer.

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Worum geht es in The Art of Statistics?

The Art of Statistics (2019) is a non-technical introduction to the basic concepts of statistical science. Sidelining abstract mathematical analyses in favor of a more human-oriented approach, it explains how statistical science is helping us to answer questions and tell more informative stories. Stepping beyond the numbers, it also considers the role that the media and psychological bias play in the distortion of statistical claims. In these blinks you’ll find the tools and knowledge needed to understand and evaluate these claims.

Bestes Zitat aus The Art of Statistics

Data does not speak for itself.

—David Spiegelhalter

Wer The Art of Statistics lesen sollte

Statistics students looking for a non-technical overview of basic issues
Journalists who want to report statistics more accurately
Anyone who wants to better evaluate the statistical claims they encounter day-to-day

Über den Autor

David Spiegelhalter is a British statistician and statistics communicator. One of the most cited and influential researchers in his field, he serves as the Winton Professor for the Public Understanding of Risk in the Statistical Laboratory at the University of Cambridge. He was president of the Royal Statistical Society for 2017 and 2018.

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