Congratulations Class of 2020!

Yesterday, along with R-Ladies Founder Gabriela de Queiroz I was honored to be asked to give a short talk at an online graduation ceremony for the BSc and MSc Statistics Graduates of the class of 2020 (all R users) at the California State University, East Bay. My talk contains some statistics jargon, but I thought it might be helpful to Class of 2020 graduates in other disciplines who have made some serious effort to acquire critical thinking skills. I know that not everyone thinks a graduation ceremony is important, but it seems to me that the Class of 2020 is getting seriously short changed, and could benefit from some attention. If any readers of this post would like to address the Class of 2020, I would be happy to publish their remarks in R Views.

Address to California State East Bay BSc and MSc Statistics Graduates: May 15, 2020

Dear Fellow Alumni: Congratulations!! It is difficult enough to make that final push to graduate under normal circumstances, but you have done it in the middle of a nightmarish doomsday scenario - Well done! You have demonstrated that you have what it takes to think clearly under pressure.

Your families need you, your friends need you, your communities need you, and it is not an exaggeration to say that the world needs you. You have demonstrated some skill at reasoning about uncertainty, at a time when fearful men and women are anxious about walking out their front doors. They want bright line rules for how to avoid the virus, and they want absolute certainty that they will be safe.

“If I wear a mask will I be protected? If a stay six feet apart does that mean everything will be OK? How about three feet? Well then, can I get my toenails done?”

The role of the statistician is to help people cope with the irreducible uncertainty in the world. Irreducible uncertainty - say that phase to yourself. Let it roll around in your head, but don’t let it scare you. You know that even when you have data that you believe in, data that you have cleaned and curated yourself; when you know something about the application you are working on and you have good reasons to use an informative prior - even then there is uncertainty. There is no way to escape the bias variance trade off - no way to be absolutely certain.

You have acquired a probabilistic mindset that should help you to help others: to help them navigate the narrow path flanked by despair on one side and magical thinking on the other. When you look at the news, you can see how the nuanced explanations of the health care experts get watered down into oversimplified statements that are mostly misleading. It is now an everyday thing to see some authoritative sounding news person or public official show a forecast with enormous error bands and just ignore them. You are now in the group with some responsibility to stand up and say: “Whoa! Hold on here!

Alright, so there’s one minor problem - the world, your community, your prospective employers may not yet know that they need you. The only way to help them to see the light in you is for you to be the person you want to be. If you want to be a statistician or data scientist, start to be one right away. Pick a problem, get the data, visualize it, analyze it, write about it. Put everything on your GitHub page. Talk about it to everyone who will listen.

You don’t have to want to be a data scientist, but you do have to want to grow in some direction. Listen to yourself, trust yourself. Decide what it will take for you to flourish and go for it. Choose your friends carefully, and get involved in some cause bigger than yourself.

Go for it. And wherever you go, walk with humility, but lead the way. Use your hard earned skills to navigate the random and the unpredictable. Take some reasonable risks, but consider the consequences for others.

You can do it! Good luck to you all. Stay safe and prosper.

And, because a graduation event is a good time to remember one’s own teachers, I would like to express my gratitude to Cal State East Bay Professors, Eric Suess and Bruce Trumbo, and also to Donald Lewis, Professor of Philosophy at Cal State Dominguez Hills.