For the Love of Statistics: A Conversation with Hadley Wickham

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Dr. Hadley Wickham is the Chief Scientist at RStudio and an Adjunct Professor of Statistics at University of Auckland, Stanford and Rice University. Hadley developed famous statistical analysis software packages for R (programming language) and co-wrote the book “R for Data Science.” He joined us at our headquarters in Mountain View to talk about the challenges of data science and we were able to ask him a few questions before:

How did you choose to enter the field of statistics and data science? 


It was through the process of elimination. I started out in medical school, which in New Zealand you go straight into right after high school. I originally wanted to become a genetic engineer so I did medical school for three years before deciding it wasn’t for me. I went back to what I enjoyed in high school which was statistics and programming. This was before Data Science was prominent, so I double majored in statistics and computer science at The University of Auckland and it was the perfect combination because it’s the home of R.

What inspired you to create tools for data scientists?

During my PhD I was a statistics consultant and fellow PhD students from other departments would come to me with their data and ask me to help them with analysis. A big part of the struggle was getting the data into the right form for analysis – the actual statistical models seemed like the easier part. I loved programming and thought “maybe I could make this easier for people.”

What advice would you give to someone who is starting out?

Try and find some data that you are interested in. Whether you’re really into sports or knitting, try to find some data that’s of interest to you because that will help you get through the initial frustrations. If you get frustrated with it don’t give up, because everyone gets frustrated. You just have to take a break and remind yourself that you’re human.

Check out our Specialization Statistics with R or Mastering Software Development in R if you’re interested in learning more about Data Science.

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