STA 210
Schedule Syllabus Project Sakai Gradescope Help
Schedule
Week 01: Intro
Week 02: SLR
Week 03: SLR
Week 04: ANOVA + MLR
Week 05: MLR
Week 06: Transformations + model comparison
Week 07: Model selection + diagnostics
Week 08: Logistic regression
Week 09: Logistic regression
Week 10: Logistic regression
Week 11: Multinomial logistic regression
Week 12: Log-linear models
Week 13: Missing data + presenting results
Week 14
Week 15

Week 06: Transformations + model comparison

  • Lectures
  • Readings
  • Assignments
  • Announcements

Lectures 🔗︎

Slides Videos Application Exercises (AE)
Monday Variable transformations Variable transformations AE 11: Back to diamonds
Wednesday Model comparison Model comparison AE 12: Model comparison

Readings 🔗︎

Influence of perceived threat of Covid-19 and HEXACO personality traits on toilet paper stockpiling Optional

Assignments 🔗︎

HW 04 due Wed, Sep 30
Lab 05 due Wed, Sep 30

Announcements 🔗︎

From the StatSci Majors Union (both events count towards stats experiences)

If you are interested in statistics, machine learning, or data science and wondering about your possible pathways after Duke, the StatSci Majors Union and the Department of Statistical Science have got you covered!

Alumni In Industry Panel: It’s recruitment season, yes, but don’t panic! Next Monday Sept. 21st at 9pm ET, the SSMU will be hosting an “Alumni In Industry” virtual panel! Join in to hear from Duke Alumni talk about what it is like to work as statisticians in the world of tech and consulting! Panelists are:

  • Hillary Song (BS ‘19)is a consultant at Bain & Co.
  • Michael Lindon(MSS 15, PhD ‘18) is a statistician at Optimizely
  • James Wang(BS ‘19) is a data scientist at Coinbase.

Submit any questions you may have for the industry panel here in advance: https://forms.gle/vTyLJcMn5s2TEdQz6. You can find more info including the Zoom link on Sakai. No registration is required but make sure to sign in to join the Zoom call.

PhD Programs Applications Workshop: Thinking of applying to a PhD program in statistics, machine learning or data science? Find out how at this Department of Statistical Science workshop next Wednesday, 23 Sep, 8-9pm EDT! You’ll hear from:

  • Peter Hoff: Professor and Director of Graduate Studies in Statistical Science, Duke University. https://pdhoff.github.io
  • Michael Valancius, PhD Student, UNC Department of Biostatistics. Michael graduated with a bachelor’s degree in quantitative economics at University of Miami and spent some time in industry before returning to Duke for his MSS and moving on to UNC for his PhD. https://www.linkedin.com/in/michael-valancius/
  • Becky Tang, PhD Student, Duke Department of Statistical Science. Becky came to Duke after completing her undergraduate at Swarthmore and recently won an NSF grant to support her graduate study. https://beckytang.rbind.io
  • Fan Bu, PhD Student, Duke Department of Statistical Science. Fan came to Duke after receiving her bachelor’s degree from Peking University, where she studied data science and big data technology. https://fanbuduke17.github.io
  • Peter Hase, PhD Student, UNC Department of Computer Science. Peter earned his bachelor’s degree in statistical science at Duke before joining the PhD program in Computer Science at UNC, where he works on ML and NLP. https://peterbhase.github.io

For more information on the PhD Applications Workshop see the flyer on Sakai on Sakai or contact stat-dus@duke.edu. Next up, a workshop on applying for Master’s degree programs!

Join the Statistical Science Majors Union in Duke Groups so we can keep you posted on cool stats events! https://dukegroups.com/SSMU/club_signup

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Week 05: MLR
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Week 07: Model selection + diagnostics
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