Infographic: Here are 15 Common Data Fallacies to Avoid
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Here are 15 Common Data Fallacies to Avoid

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In today’s tech-driven economy, data is essential for gaining new insights, making decisions, and building products.

In fact, there is so much data out there, that the quantity of it is doubling every two years⁠—and by 2025, there will be 175,000 exabytes of data in existence.

This is an unprecedented figure, and it’s hard to put into perspective. To give you some sense, a single exabyte is equal to 1,000,000,000 GB of data, and five exabytes has been said to be roughly equal to “all of the words ever spoken by mankind”.

Common Fallacies With Data

As you can imagine, digging through all of this data can be quite the challenge.

Data comes in many different forms and not all of them are easy to analyze. As a result, it is tempting to take shortcuts with data, or to try and fit the incoming data we receive into our pre-conceived notions of how things ought to be.

Today’s infographic comes to us from Geckoboard and it shows the common mistakes that people make in analyzing data. We’ve reformatted their PDF to fit here.

15 Common Data Fallacies

Here are 15 Common Data Fallacies to Avoid

How do we avoid painting a bullseye around the arrow, so that we can interpret the meaning of data in a logical, consistent, and methodological way?

The key is to understand common mistakes that people make with data, and why these errors skew our interpretations.

Examples of Fallacies

Here are four examples of fallacies, and why each is considered a faux-pas by data scientists.

1. Survivorship Bias

When people analyze the qualities it takes to be a successful entrepreneur, we typically look at the existing population of established entrepreneurs for clues. However, by limiting our sample just to this “surviving” group of entrepreneurs, we run the risk of survivorship bias.

There are lessons we can learn from all of the entrepreneurs who have failed—they are just much harder to find. Integrating that data into the story can help complete a much fuller picture.

2. False Causality

Did you know that there is a 95% correlation between the marriage rate in Kentucky and the amount of people who drown each year from falling out of fishing boats? (See it, and other bizarre correlations here)

Kentucky marriages vs. people who drown

Does this mean that there is some sort of relationship between the two variables?

Finding a high level of correlation can happen simply by chance—but awarding false causality is one of the most amateur statistical mistakes in the book.

3. The Gambler’s Fallacy

If the roulette wheel turns up black for 26 times in a row, does that mean that it will revert back to red on the next spin?

It’s easy to say that the odds don’t change, but imagine being in the moment. The Gambler’s Fallacy happens with data analysis as well: just because something happens unusually frequently over a period of time doesn’t mean that nature will “even it out”.

4. The Cobra Effect

Data can be used to measure progress in achieving business goals, but what if there is incentive to game these goals?

Wells Fargo, in an effort to upsell existing clients, introduced an incentive called “eight is great”. In short, their employees were encouraged to sell eight accounts per customer, which could take the form of credit cards, savings accounts, and other financial services.

In an example of good intentions gone awry, Wells Fargo employees began breaking the rules to meet their targets. Millions of unauthorized credit card and deposit accounts were opened based on this perverse incentive, and the bank was eventually ordered to pay a $142 million settlement.

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Demographics

Visualizing Population Density Patterns in Six Countries

These maps show the population density of several countries, using 3D spikes to denote where more people live.

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beautifully rendered population density maps of six major countries

As of 2022, Earth has 8 billion humans. By 2050, the population is projected to grow to 10 billion.

In the last 100 years, the global population more than quadrupled. But none of this growth has been evenly spread out, including within countries.

This series of 3D maps from Terence Teo, an associate professor at Seton Hall University, renders the population density of six countries using open-source data from Kontur Population. He used popular programming language R and a path-tracing package, Rayshader, to create the maps.

France and Germany: Population Density Spikes and Troughs

Let’s take a look at how the population spreads out in different countries around the world. Click the images to explore higher-resolution versions.

This image shows a map of France and its population spread.

France is the world’s 7th largest economy and second-most-populous country in the EU with 65 million people. But a staggering one-fifth of the French population lives in Paris and its surrounding metro—the most populous urban area in Europe.

Many residents in the Paris metropolitan area are employed in the service sector, which makes up one-third of France’s $2.78 trillion gross domestic product.

This image shows a map of Germany and its population spread.

Unlike France, Germany has many dense cities and regions, with Berlin, Munich, Stuttgart, and Cologne all having over a million residents. Berlin is the most populated at 3.5 million residents in the city proper, and 6 million in the wider urban area.

That said, the relatively recent reunification of West and East Germany in 1991 meant that post-WWII growth was mostly concentrated in West Germany (and West Berlin).

Italy and Chile: Coast to Coast

In Italy, another phenomenon affects population density and urban development—a sprawling coastline.

This image shows a map of Italy and its population spread.

Despite having a large population of 59 million and large metropolitan areas throughout, Italy’s population spikes are closer to the water.

The port cities of Genoa, Napoli, and Palermo all have large spikes relative to the rest of the country, as does the capital, Rome. Despite its city center located 15 miles inland from the sea, it extends to the shore through the district of Ostia, where the ancient port of Rome existed.

This image shows a map of Chile and its population spread.

Meanwhile in Chile, stuck between the Andes to the east and the Pacific Ocean to the west, population spikes corroborate with its many port towns and cities.

However, the country is more concentrated than Italy, with 40% of its residents congregating around the capital of Santiago.

Turkey and Canada: Marred by Mountains and Climes

Though Chile has difficulties with terrain, it is relatively consistent. Other countries have to attempt to settle many different climes—regions defined by their climates.

This image shows a map of Türkiye and its population spread.

Mountains to the south and east, a large, semi-arid plateau, and even a small desert leave few centers of urban growth in Türkiye.

Predictably, further west, as the elevation comes down to the Aegean and Mediterranean Seas, population spikes begin to heighten. The largest of course is the economic and cultural hub of Istanbul, though the capital Ankara is also prominent with more than 5 million residents.

This image shows a map of Canada and its population spread.

In Canada, the Rocky Mountains to the west and freezing cold temperatures in the center and north account for the large country’s relative emptiness.

Though population spikes in Western Canada are growing rapidly, highly populous urban centers are noticeably concentrated along the St. Lawrence River, with the Greater Toronto Area accounting for more than one-sixth of the country’s 39 million people.

Increasing Urbanization

According to the World Bank, more than half of the world’s population currently lives in cities, and that trend is only growing.

By 2050, 7 out of 10 people are projected to live in cities. This congregation makes cities a beehive of productivity and innovation—with more than 80% of the world’s GDP being generated at these population centers.

It’s in this context that mapping and studying urban development becomes all the more important, particularly as policymakers try their hand at sustainable urban planning.

As Teo puts it:

“By showing where people are (and are not), they show us where political and economic power is concentrated, and perhaps where and who our governments represent.”

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