Getting good with numbers (3/4): Lost in a sea of data? Trust your eyes!

GLOBIS Faculty Kenichi Suzuki shares some tips on how to utilize numbers for more effective communication in business.

When I studied at the Booth School of Business (University of Chicago), one of my favorite teachers was my statistics lecturer. He always told us to put our data into a graph and do an eyeball test.

As we saw in the last column, analysis is about comparison. But if you’ve ever tried to look at a list of numbers, you’ll know it’s not as easy as it sounds. Sometimes, we can get lost in a sea of data. We tend to trust our brains over our own eyes. We overthink things, when what we really need is to take a step back, a deep breath and a fresh look. So today, I’m going to let you in on a little secret on how to do just that.

Graphs help guide our eyes to the key points in data. Together, graphs and our eyes are the strongest tool we can use for comparison. Graphs let differences and relationships stand out visually within the data. We don’t need to use difficult analysis tools. In this column, I will focus on a specific graph known as a scatter plot.

Showing the relationship between economic wealth and life expectancy

Last time, I left you with a conundrum. Does being rich make you live longer?

So, what kind of relationship do you think there is between the two? Will we live longer because of improved hygiene and nutrition brought by wealth? Or will we live a shorter, lazier life in the lap of luxury? Before we collect the data, we should predict the kind of graph we expect.

This prediction is surprisingly important. Without it, we are likely to just look at the data and think, “That sounds about right!” After making our prediction (or hypothesis), if the graph turns out differently, we should ask Why? This may lead to a new discovery we had not thought about.

So, let's compare the relationship. For wealth, I used GDP per capita*, and for lifespan, average life expectancy at birth. Then I put them into a graph. The size of each bubble represents the size of each country’s population.

We can clearly see from the graph that for most countries, there is a linear relationship: average lifespan increases with wealth. This linear relationship is known as correlation or covariance in the world of statistics. The wealthier the country, the longer its people live.

In fact, I used data from a site called Gapminder World and turned it into a graph using Excel. Try their animation tool which charts more than 200 years of wealth vs lifespan data. Simply go here and hit Play.

We can see a strong impact since the Industrial Revolution of economic development on the average lifespan for citizens in each country.

Scatter plots are the king of graphs

We are all familiar with line graphs, pie charts and bar graphs. They show changes in one variable.

The scatter plot is different. It shows the relationship between two variables, a truly revolutionary invention in the history of graphs. If we just stare at numbers and ask Why?, we’ll never see a causal relationship: whether one causes another. But the scatter plot allows us to see it because we can compare two variables so graphically. According to one theory, an astounding 70 to 80% of the graphs used in science are scatter plots.

We have all likely heard of economies of scale (the larger the scale, the lower the cost) or the experience curve (the more we make something, the lower the cost). Well, these important management concepts too can be represented by a simple scatter plot. If you have two variables whose relationship you are curious about, try remembering to compare them with a graph. It’s easy to do with Excel. A good graph and our eyes are the strongest analysis tool there is.

*GDP per capita is one of the most important economic indicators. But rather than thinking about it too deeply here, let’s take this to mean the average income per citizen in each country.

Translated by Karl O'Callaghan (GLOBIS Faculty; Founder and CEO,; GLOBIS Graduate).

Copyright: Ronnachai Palas