Explaining Data Science to High School Students
My attempt to make data science cool (because it is)
Since my kids were born, I wanted to be the cool dad on career day, where my sage advice would change a life. But I work in high tech, and even for most adults, technology is scary, not cool. But when my son Jack took computer science, I volunteered to talk about data science and make it sound cool. Panic struck when, a week before my talk, my talk track wasn’t exciting or motivational. Fortunately, I had an insider: my son, Jack.
What do Do High Schoolers Want to Know?
I asked Jack what he thought the class would want to know. He said, “the first thing all my friends have on their mind is: much money you can make?”
It wasn’t the inspirational introduction I was looking for, but it was a start, and Jack had a lot of other basic questions.
A few weeks later, among test tubes and periodic tables, I started with Jack’s question. “The average salary for a data scientist is $113,000 a year.”
Blank faces.
Jack had the same look when I tried to rent his attention. $113,000 a year was meaningless to him. His friends talk in terms of $10, $13 and $16 an hour. “Any idea how much money that is per hour?” I asked. One student guessed $30 a hour, because that was twice of what she was making.
I did the reveal: “$113,000 is $67 / hour.”
A few backs straightened. I had their attention.
Why Data Scientists Matter
“But what’s really important is why data science matters, how you can change the world with data science, and why it’s fun,” I continued.
The blessing and curse of this world is that we have tons of data, but not enough insight, and not enough people who care about extracting that insight. And that’s what data scientists do: they extract meaning from data. They help us understand the world and discover new things.
Data scientists extract meaning from data. They help us understand the world and discover new things.
I gave some quick examples of Al Gore used data science evangelize for global warming policy change; the New York Times uses data science to explain how border walls work; ESPN uses data science to show how the Patriots pulled off another improbable Superbowl win.
To make it concrete, I showed the class this table of numbers and asked what they saw.
Their unresponsiveness was exactly what I wanted. This data doesn’t tell a story. We need a data scientist to find meaning among these nonsensical numbers.
I showed the class how Joseph Minard found meaning in these numbers in 1869. He created what many consider the best statistical graphic of all time. In one image, he shows six dimensions of data and tells a devastating story.
The numbers describe Napoleon’s march on Russia, including time, troop size, troop location and temperature.
The tan jagged line represents the size and direction of Napolean’s army. Beginning at left, Napolean entered Russia in 1812 with 422,000 troops. The tan ink dwindles as they travel east, from left to right. Six months later the troops reach Moscow.
322,000 men had died. Then they turned around.
At far right, Napoleon begins his retreat. Troop size on the return is black. Minard adds a line graph on the bottom to display the temperature, beginning at 0 degrees and dipping as low as 30 degrees below zero.
The thin black sliver shows that only 10,000 of 422,000 men survived.
Minard’s graphic is the Mona Lisa of statistical graphics — the longer you linger, the more you see. For example, on September 28, 1813, the data labels on the black line read 50,000, then 28,000. 22,000 men died crossing the Berezina river, near Minsk.
Why did Minard create this graphic? It’s a warning of the devastation that war can bring.
Examples of Modern Data Science
I finished with modern examples of data science in drug discovery, intelligence security in airports, wind energy analytics, algorithmic trading, IoT applications in the home, social analytics to better understand demographics and health issue.
My last pandering ploy was to show how the Mercedes Formula Race team uses analytics to optimize car configuration, passing strategy, and real-time race conditions.
The class was asked how data science can applies to geology, law, and art. Good questions.
I considered my missionary mission accomplished.
My Talk Worked on Me, Too
My spy Jack overheard a few kids talk about how much data scientists make. At least they were talking!
The bonus was that explaining why data science matters made me reconnect with why data science is cool. Through teaching, I had reennergized myself.
Mark Palmer is the SVP of Analytics at TIBCO software. As the CEO of StreamBase, he was named one of the Tech Pioneers that Will Change Your Life by Time Magazine. To connect, visit my About.Me page.
