More data isn't always better, says Nate Silver

Top statistician warns that an abundance of data lets statisticians 'cherry pick' data points to get the results they want

Big data may seem to promise big insights to users, but more isn't always better, cautions statistician Nate Silver, who became one of America's most well-known faces of data analysis after his FiveThirtyEight blog accurately predicted 2012 presidential election results in all 50 states.

The more data there is, "the more people can cherry pick" data points that confirm what they want it to show, he said.

Abundant data is a notable problem in politics, where many have an interest in the outcome. But it's also an issue in fields ranging from medicine -- where many researchers and journals would rather see studies showing an interesting result than a confirmation of no news -- to earthquake prediction.

It turns out that along with real insight, Big Data can bring "a lot of spurious correlations" -- what appear to be relationships between things that are just random noise, Silver said at the RMS Exceedance conference in Boston today, where RMS announced a new cloud-based RMS(one) risk-management platform..

In addition to writing the FiveThirtyEight blog, now seen at the New York Times, Silver is the author of the book, The Signal and the Noise: why so many predictions fail -- but some don't.

In his presentation, Silver offered four tips for more effectively gaining -- and sharing -- insight from data:

  1. "Think probabilistically," he urged. "Think in terms of probabilities and not in terms of absolutes."

    Don't be afraid of communicating the level of uncertainty that comes with your predictions -- just as most public opinion polls include margins of error -- even if not all of your audience will understand. Some criticised the FiveThirtyEight conclusions of stating the confidence level Silver had in his election predictions, but conveying uncertainty is "important and good science".

    Not doing so can have serious consequences, he noted, such as in 1997 when the National Weather Service predicted a 49-foot flood level for the Red River in Grand Forks, ND. Many in the town were reassured by that, since the city's levees were designed to withstand a 51-foot flood.

    Unfortunately, what was not communicated to Grand Forks residents was the likely margin of error based on past forecasts: plus or minus 9 feet. In fact, the river crested at 54-feet and much of the community was flooded.

    Today, the National Weather Service is much better about noting the uncertainty level of its forecasts, Silver said, citing the "cone of uncertainty" that comes along with projected hurricane paths. Showing uncertainty "in a visual way is important" in helping people evaluate forecasts.

    Probability forecasts are a "way point between ignorance and knowledge," but they are not certainties.

  2. "Know where you're coming from" -- that is, know your weak points, the incentives to reach certain conclusions and the biases against others. "You are defined by your weakest link," he said.

    He noted an experiment on gender bias where people were shown similar technical resumes -- one with a female name and one with a male name. People who claimed to have no gender bias were in fact more likely to discriminate against the female's resume. Why? Those who were aware of their tendencies toward bias were more likely to take action to counteract it, Silver said.

  3. Survey the data landscape, and make sure you have some variance in your data before having confidence in a forecast. (In other words, accurately forecasting the weather in San Diego is not as impressive feat as doing so in Buffalo.)

    Likewise, forecasting a stable economy is easier than in times of a lot of booms and busts, which helps explain why many forecasters were unprepared for the most recession. The forecasters were creating models based on data from 1986-2006, when the economy was unusually stable. A detailed and sophisticated model based on silly assumptions won't do you much good, he noted.

  4. Finally, trial and error are helpful.

    Models tend to work well when they are developed slowly with a lot of feedback. As with many things in life: "You should be suspicious of miraculous results."

Join the newsletter!

Or

Sign up to gain exclusive access to email subscriptions, event invitations, competitions, giveaways, and much more.

Membership is free, and your security and privacy remain protected. View our privacy policy before signing up.

Error: Please check your email address.
Show Comments

Latest Videos

Conversations over a cuppa with CMO: Craig Davis

​Leadership resilience, startups scaling up, marketing best practices, customer insights - these are just a few of the topics we manage to explore in the latest episode of Conversations over a Cuppa with CMO featuring Craig Davis.

More Videos

Good day sir / madamWe CLOSED JOINT-STOCK COMPANY AO KAYUM NEFT OIL COMPANY is one of theleading Oil & Gas trading companies in Russi...

BARYBKIN ALEXANDER ALEXANDROVI

3-pronged marketing approach for property disruptor Brickx

Read more

Good day sir / madamWe CLOSED JOINT-STOCK COMPANY AO KAYUM NEFT OIL COMPANY is one of theleading Oil & Gas trading companies in Russi...

BARYBKIN ALEXANDER ALEXANDROVI

Oath to fully acquire Yahoo7 from Seven West Media

Read more

Thank you for sharing your knowledge. Definitely bookmarked for future reading! Check this website https://a2designlab.com/ with lots of ...

Ryota Miyagi

Brene Brown: What it takes to be a brave leader right now

Read more

Well said! It is high time to look into the cultural values and beliefs of the audience before serving with the ads. If it is against the...

Praveen Kumar

The X factor in multicultural media planning and buying - Digital advertising - CMO Australia

Read more

I completely agree with you. High-quality customer service only strengthens loyalty to the company and helps to increase sales and increa...

Natali

Mercer CMO: How B2B brands can achieve customer love

Read more

Blog Posts

Life beyond the cookie: 5 steps to mapping the future of marketing measurement

​There’s no denying there’s been a whirlwind of response to the imminent demise of the third-party cookie from all parts of the industry. But as we’ve collectively come to better understand the implications, it’s clear this change is giving the digital advertising industry the opportunity to re-think digital marketing to support core industry use cases, while balancing consumer privacy.

Natalie Stanbury

Director of research, IAB Australia

Ensuring post-crisis success

The COVID-19 pandemic has exposed brands’ CX shortcomings and a lack of customer understanding. Given ongoing disruption, customer needs, wants and expectations are continually changing, also causing customers to behave in different ways. Just look at hoarding toilet paper, staple and canned food, medicinal and cleaning products.

Riccardo Pasto

senior analyst, Forrester

A few behavioural economics lesson to get your brand on top of the travel list

Understanding the core principles of Behavioural Economics will give players in the travel industry a major competitive advantage when restrictions lift and travellers begin to book again. And there are a few insights in here for the rest of the marketing community, too.

Dan Monheit

Co-founder, Hardhat

Sign in