The Lady Tasting Tea Note 2

Ladies in the statistics.

Though there is a “lady” in the title of this book, when you read it, you will notice that there are not too many women mentioned in the book. Few words about Florence Nightingale, a whole chapter about Florence Nightingale David, and some subsections about other women in statistics. As the book said, the early years of statistical development were dominated by men. However, the situation changed a lot nowadays. I have met a lot of great women in statistics and I also learned a lot from them. For my bachelor and masters program, I have twice female classmates than males, which makes me never think about the influence of gender in statistics in the early years. So in this blog, I want to write something about some of the women in statistics who at some level influence my ideas in statistics and also in my research life.

Florence Nightingale David

First, I want to briefly review the chapter about Florence Nightingale David. I was surprised to know that her parents were friends of Florence Nightingale and that’s where her name was from. Since she worked with Karl Pearson for a long time, she “saw all the protagonists from a worm’s-eye point of view.” However, no one noticed that she didn’t have her doctorate until Neyman found it a few months before Karl Pearson died. Her work was absolutely underestimated, especially during she working in the department with Karl Pearson, Jerzy Neyman, Ronald Fisher and Egon Pearson (William Gosset sometimes walked by). Later I found that she founded the statistics department at the University of California, Riverside, which makes me miss my department at UCI.

Prof. Jessica Utts

F·N·David makes me remember Prof. Jessica Utts when I was in UC Irvine. I first time met her in Shanghai at an ICSA (International Chinese Statistical Association) conference in 2016, when Prof. Utts served as the 111th president of the ASA (American Statistical Association). At the time, I was an undergraduate student in my senior year and just finished my applications for graduate study in US. If I remember it correctly, I was there because my girlfriend wanted to talk with some professors and looked for some opportunities to join their program. We attended that conference unofficially, and pretended as PhD students who forgot their name tags. That is my first time “attending” an international academic conference and I was overwhelmed by the famous statisticians just in front of me, who I only saw their names on some of my textbooks. I joined one talk by Prof. Utts about data science and statistical education, which was also the first time I heard and thought about these topics. Then I also joined a session with representatives from many famous statistical organizations, after which I talked to Prof. Utts and told her I applied for UCI and hope to see you soon. As you see, the wish came true. There are some interesting things she told us during the department party, like how does the first few years look like for our department, and how she joined this department with Prof. Wesley Johnson. She also told us that if you google “women statistician”, you will find her name there (at that time she was the third or the fourth in the list). One interesting fact about her is that she once stuided remote viewing and it received wide-spread media coverage. You can find related articles on her website.

I recognized Prof. Utts as someone opened the door of statistics for me (just for me!) since I had no idea about what statistics looks like outside China at that time and she was the first “influential” statistician I have talked with. I still remember one of the sentences in her talk, “Statistics in China is 50 years behind America.” I should admit this is the truth and the statistical education in China needs to have a big revolution by our generation. This becomes one of the reasons why I want to be a professor.

Prof. Zhaoxia Yu

Prof. Yu taught me some courses like probability and statistics, multivariate statistical methods at UCI. But I would like to also appreciate that she gave me the first research opportunity. In the first year at UCI, she gave me some tasks to review literatures about principal geodesic analysis, where I first time read English papers and gave a presentation. Though I’m not working on image analysis now, I still learned a lot from that experience. And in the last term at UCI, she also provided me an opportunity to assist a visiting scholar for his research, where we used factor analysis on data related to autism. When she talked with me in Chinese, it gave me a feeling like my mom talking with me. It may be because they are both professors working in a university and in a similar age. Most of my research experiences on my CV when I applied PhD programs are related to Prof. Yu, so I’m very thankful for her teaching and help.

Prof. Audrey Béliveau

Last but not least, I would like to thank my supervisor Audrey who gave me a chance to pursue a PhD in this great school. It was after April 15th when she gave me the email about interview, and I have already accepted an offer from a US school (not as famous as Waterloo but the funding is attractive). And at that time, I was travelling in Guangzhou with Mei. I was so happy to hear that I got the offer from University of Waterloo, and the first thing I did is to search if UWaterloo is in the April 15 Resolution. After I found that it’s okay to accept the offer, I made the desicion in one minute and decline my previous offer. Well, it is not a good move but Mei lives in Toronto so Waterloo is obviously a better choice.

At first, I was worried that Audrey is an assistant professor, which means that I might have more tasks as her PhD. But she is so kind and helpful, and even support me to attend a conference without presenting anything. Our group even has a social event (commonly borad game night) every year. I feel very lucky to have her as my supervisor and am looking forward to working with her in the rest of my PhD time here.

Yiran Wang
Yiran Wang
Postdoctoral Associate

My current research areas are Bayesian methods and causal mediation analysis.

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