Hello everyone – I’m so excited (and nervous!) to get to tweet with you all this week. I’ll start by telling you some general things about myself.
I’m an Associate Professor of Statistics at Northwestern University and a Faculty Fellow at the Institute for Policy Research. I also Co-Direct the Statistics for Evidence-Based Policy and Practice Center. For more info see here: bethtipton.com
I call my field “Social Statistics” and I much of what I study has to do with the role of statistics in the creation and use of evidence for decision making, particularly in the field of education research.
A few things about me:

1) I defended my dissertation 10 years ago last week.
2) I quit my first PhD program in Sociology after two years to move with my boyfriend to NM for him to do Teach for America. We lived on the Navajo Nation for three years and got married while there.
3) I eventually earned my PhD in Statistics from Northwestern and was a pre-doctoral @IESResearch fellow while there.
@IESResearch 4) After graduate school, I was an Assistant Professor @TeachersCollege, where I worked with students from education policy, psychology and health. I was faculty there for 7 years before returning to Northwestern.
@IESResearch @TeachersCollege 5) I have twin boys that will be 9 soon. I had them at the end of my first year on the tenure track.
@IESResearch @TeachersCollege 6) My husband is Black and my kids are biracial. This year they were old enough to understand that the world is not fair or kind to Black people. This year has broken me in so many ways but has also motivated me.
@IESResearch @TeachersCollege 7) My kids have been at home with my husband and me since March 2020. I can’t even remember what it was like to have my work and home separate. What a year.
@IESResearch @TeachersCollege 8) I went to college at a small liberal arts school in KY @Transy. I studied math, English, and sociology. I studied abroad in Ireland.
@IESResearch @TeachersCollege @Transy 9) I was born and raised (mostly) in Berea, KY. My family on both sides has been in KY for several generations. I’m not the first to go to college, though I am the first to earn a PhD or any sort of doctorate.
@IESResearch @TeachersCollege @Transy 10) My parents were both in the Army when I was growing up. This was a huge part of my life and instilled in me the importance of service.

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Women in Statistics and Data Science

Women in Statistics and Data Science Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @WomenInStat

27 Apr
I work primarily with nested data. One example is in experiments, with students nested in schools. Another is meta-analysis, with effect sizes nested in studies. In this thread, I’ll focus on students nested in schools, but this applies more generally.
Question 1: Do you need to take nesting into account in your analysis? Our world is naturally nested – students in classrooms in teachers in schools in districts and so on. Does this mean we need to take all of these levels into account? No.
Nesting only needs to be accounted for if it is part of how our sample of data is generated – either how the data is selected (sampled) or the who gets an intervention being studied (assignment).
Read 19 tweets
23 Apr
The #DataFeminism book also made me look inward and examine my own biases, which I am exceedingly grateful for.

Namely, it forced me to reckon with some of my fundamental operating assumptions as a statistician & data scientist.

Examples threaded below...
In chapter 3, the authors discuss the role of emotion in data visualization, specifically calling out giants in the field like Edward Tufte and Alberto Cairo (no snitch tagging, please) for what is presented as an anti-emotion stance.
On Tufte: "Any ink devoted to something other than the data themselves ... is a suspect and intruder to the graphic. Visual minimalism, according to this logic, appeals to reason first. ... Decorative elements ... are associated with messy feelings ... and emotional persuasion."
Read 12 tweets
23 Apr
There are 7 core principles of #DataFeminism:

1. Examine Power
2. Challenge Power
3. Elevate emotion and embodiment
4. Rethink binaries and hierarchies
5. Embrace Pluralism
6. Consider Context
7. Make labor visible
Principle 1: Examine Power

"#DataFeminism begins by analyzing how power operates in the world."

data-feminism.mitpress.mit.edu/pub/vi8obxh7/r…
Principle 2: Challenge Power

"#DataFeminism commits to challenging unequal power structures and working toward justice."

data-feminism.mitpress.mit.edu/pub/ei7cogfn/r…
Read 8 tweets
22 Apr
Good morning! Happy Thursday!

For #ThrowbackThursday I thought I'd highlight some of the amazing women who have been mentors (and friends) to me. Without support from an amazing community of women in mathematics & statistics I would not be where I am today! #WomenInSTEM
(These will be in chronological order)
.@lpudwell : Lara Pudwell

Lara was my advisor during my summer REU experience at @ValpoU in 2011.

Without her mentorship, I don't think I would have ever considered graduate school!
Read 7 tweets
24 Mar
Let's talk data visualizations today! Best practices, ideas, tools, resources or even some really neat visualizations - what are your recommendations?
I found this visualization of at-risk workers in COVID times very good at expressing key points, though I did not like the scroll feature too much!

nytimes.com/interactive/20…
Quite unlike the wealth disparity visualization where the scrolling was on point made all the difference:

mkorostoff.github.io/1-pixel-wealth/
Read 4 tweets
23 Mar
As we practice and teach Data Science, we continuously learn, unlearn and revise old and new concepts.
What are some freely available reading lists that give that help this or give a great intro to Data Science?

(1/n)
This one is from University of Washington and goes over some basic concepts: students.washington.edu/bxie/info370/

(2/n)
Another great one which details specific vital segments like clustering and dimensionality is this book/course from University of Utah: cs.utah.edu/~jeffp/teachin…

(3/n)
Read 8 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Too expensive? Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal Become our Patreon

Thank you for your support!

Follow Us on Twitter!