Software Tools for Data Analysis
STA 9750
Michael Weylandt
Week 1

STA 9750 Week 1

Today:

  • Tuesday Section: 2025-08-26
  • Thursday Section: 2025-08-28

Weekly Course Updates:

  • Brief updates and reminders about course logistics
  • Syllabus and Brightspace are binding
    • If something is left out of here, it still happens!

Today: Introduction to STA 9750

STA 9750: Software Tools for Data Analysis

Course Overview

STA 9750 is:

  • Getting s#!t done
  • Establishing a professional data analyst portfolio
  • Increasing your effectiveness in other courses
  • Building your networks with faculty and classmates

Learning Objectives

Formal learning objectives can be found here

Key aims:

  • Deal with real data, no matter how messy and unhelpful
  • Engage with important technologies and learn to quickly adopt new tools
  • Communicate to both technical and non-technical audiences
  • Perform substantial and thoughtful analyses

Course Website

All course information can be found on the course website

No authentication required - mobile friendly

Source code on my GitHub

Course Website

Look online for:

Instructor

Me: Michael Weylandt

Assistant (i.e., new) Professor in the Department of Info. Systems and Statistics

Previously:

  • Researcher at Sandia National Labs (US Government Lab)
  • Postdoc with US Intelligence Community
  • Ph.D. in Statistics at Rice University (Houston, TX)
  • “Quant” at Morgan Stanley and a (defunct) hedge fund

See my website for more on me and my research

Course Schedule

  • Lecture / Lab sessions
    • Tuesdays / Thursdays on Zoom (here!) at 6:05pm
    • 14 weeks (with two holidays)
  • Office Hours
    • Before class (on days we have class) at 5:00pm
    • Different Zoom Link
  • Asynchronous
    • Piazza course discussion platform

Course Schedule

Major Topics:

  • Web Communication and Literate Programming Technologies
  • Introduction to R
  • Tidy Data Manipulation (SQL-type operations)
  • Plotting and Data Visualization
  • Data Import, Web Scraping, and Text Cleaning
  • Statistical Analysis

Grading

  • 24% Pre-Assignments
  • 36% Mini-Projects
  • 40% Course Project

Extra credit for contribution to course materials or ‘above and beyond’ on Piazza

Final grades curved to match ZSB grading guidelines

Course Policies

See syllabus for fine print:

  • Regrading: Must request within 48 hours; total regrade
  • Late work: Not without prior permission or DoS letter ex post
  • Grace period: two days on mini-project initial submission
  • External Resources / AI: Free to use for coding only
  • Absences: No excuse required, but must attend on presentation days
  • Accomodations: ADA (SDS) or Religious (direct with instructor)

Pre-Assignments

Pre-Assignments:

  • Weekly reading before class followed by a short quiz
  • Introduce new material + helps me know where folks are confused
  • Completion grading
  • Starts next week
  • Every week except three presentation weeks

Mini-Projects

Traditional homework assignments - “mini-projects”

  • Guided real-data analysis using course technologies
  • Increasingly ambitious over the semester
  • Practice real data analysis
  • Communication and coding
  • Professional portfolio
  • One ungraded ‘set-up’ + four graded

More later in the course

Course Project

In lieu of exams, semester-long group project

  • Three presentations + two reports
    • Project Proposal
    • Mid-Semester Check-In
    • Final Presentation
    • Individual Final Report
    • Group Final Report

More later in the course

Workload Expectations

Per federal and state requirements, 9 hours weekly = 6 hours outside of class

  • 10 hours of Pre-Assignments
  • 10 hours of Post-Class Review
  • 35 hours of Mini-Projects (homework)
  • 35 hours of Course Project

Note that course project = sum of all mini-projects - be ambitious!

Care Resources

See Care Resources for Students for helpful resources

  • Mental health support
  • Physical health / medical care
  • Food Security
  • Financial Security
  • Immigration Support

Any questions?

Getting Started with R and RStudio

Lab 01

Open Lab #01 and follow the instructions to get started with R and RStudio


Random assignment to Zoom breakout rooms

I will visit rooms to provide support


Call everyone back at 8:30pm

Mini-Project #00

You can now start thinking about Mini-Project #00

  • Create an account on GitHub + GitHub student developer pack
  • Setting up your own website using quarto (like my course site)
    • Future Mini-Projects submitted here
  • ‘Road test’ to make sure everything is working correctly
  • Register on course discussion board (Piazza)
  • Verification of Enrollment

Due 2025-09-12

Wrap-Up

Course Introduction

  • All materials on course website
  • Review of course structure and key policies
  • More details about mini-projects and course-project to follow

Getting Started with R

  • Install R, RStudio, git, and quarto
  • Run a basic bit of R code to confirm things work well

Next Week

Writing documents using Markdown and Quarto

  • First Pre-Assignment
    • Read online
    • Submit quiz on Brightspace

Life Tip of the Week

Weekly feature: “Life Tip of the Week”

  • Advice about Baruch, finances, law, etc.

Getting the most out of your time here

Life Tip of the Week

Office Hours

  • What: Time set aside by Faculty for “drop-in” student interactions

  • Why: Homework help, review, diving deeper, chit-chat, connections to other courses, career advice - anything you want!

  • Where/When: Before class on Zoom

Build relationships with professors before you ask for things!

Happy to just ‘hang out’ but I will prioritize course related questions

Musical Treat