Welcome to SOCIOL 333

Lecture 1

2024-05-15

Introductions

Meet the instructor

Suzanne Schenewerk

She/they

Ph.D. candidate in sociology

Reuben-Cooke 135

Meet the instructor’s cats

Gideon and Harrowhark

(They’re different cats)

Introduce yourselves!

  • Name and pronouns, if you wish

  • Major(s) and year

  • What’s next for you (if you’ve thought about it!)

  • What are you looking forward to in Durham this summer?

Meet this course

  • Quantitative Analysis of Sociological Data
-   basically, statistics/data science for sociologists

  • Our objectives, summed up

    • To give you a set of tools to use to analyze data and communicate what’s happening in the social world

    • To teach you how to critique data analyses that show up in papers, media, etc

Your expectations

  • What are you hoping to get out of this course?

  • What have you heard about this course/similar courses?

My goals

  • That this course is useful

    • We will build skills you can use later

    • Everything we do has a purpose!

  • That this class is supportive

    • We will cover everything you need to know

    • Lots of opportunities to ask questions; lots of in-class practice

What I need from you

  • Come to class!

  • Bring your laptop every day

    • …but please don’t let it distract you (I can tell, seriously)
  • Be engaged and participate

What we’ll do

Let’s meet some data!

Data Description

How many coaches were there at Duke in 2021?

  • 47 for men’s teams (11 head, 36 assistant)
  • 43 for women’s teams (12 head, 31 assistant)

How has that changed since 2003?

How are male and female head coaches distributed between men’s and women’s teams?

How are male and female assistant coaches distributed between men’s and women’s teams?

Everyone all together!

Inference

Do women and men have the same probability of being hired for coaching jobs?

Results interpretation

Why might this be?

What else can we ask with this data set?

How we’ll do it: technology

Why not these?

Why not these?

  • Limited functionality

  • Work is not reproducible

  • Expensive!

Instead! R and RStudio

An RStudio window

Instead! R and RStudio

  • Completely reproducible and open-source

  • Lots of flexibility, and capabilities are always expanding

  • A great resume line–it’s what the pros use

  • Free!

Course logistics

Time check!

  • Please keep me on schedule!

Reminders about summer term

  • Drop/add ends on Friday (yes, that is very soon)
  • No class on Memorial Day (May 27) or Juneteenth (June 19)
  • Something up with your enrollment? Talk to me after class.

Homepage

https://schenewerk.github.io/soc333-sum24/

  • All course materials
  • Links to Sakai, GitHub, etc.
  • Let’s take a tour!

Activities

  • Readings: All available free online, to be completed before class.
  • Class: Attend every day! Your assignments will be much easier if you take advantage of in-class opportunities to complete them.
  • In-class exercises: Complete (at least mostly) during class each day. Turn them in before the next class period. Graded for completion. You’ll have to do these on your own if you miss class.
  • Homework: One or two additional out-of-class assignments.
  • Project: Final project, developed in pieces through the course of the semester. Paper and presentation due at the end.

Exams???

  • nope :)

This week’s tasks

  • Before 11:59pm tonight: Complete the Getting to Know You survey (link in email). This asks you to create a GitHub account if you don’t already have one.

  • Before tomorrow’s class: read IMS ch 1

Checking in: how are you feeling so far about the course?

Let’s get started!

  • Today’s in-class exercise (15 min):
  • Get a GitHub account if you don’t have one (username advice in the survey)
  • Complete the Getting to Know You survey (link in your email)

🔗 https://soc333-sum24.github.io/