Welcome to Stat 349!

Stat 349

  • How to write statistical articles and reports

  • Weeks 1-5: Preliminaries

    • CVs
    • How to read scientific articles
    • Organization
    • Transitions
    • Data documentation

  • Weeks 6-12: Components of reports/articles

  • Weeks 13-15: Reports, Editing, Presentations

About Me

  • Associate Professor in Statistics

  • Research:

    • Data Visualization
    • Statistical Algorithms for Forensics
    • Reproducibility
    • Data Science pipelines

 

Alex (left), Ryan (right), and Zoey (top)

 

Edison (Eddie)

Ivy

About Me

  • I have prosopagnosia

Image source: https://susilolab.org/Prosopagnosia.html

Introductions

  • Your name

  • Your major

  • What is your favorite board/tabletop game?

Class Picture

Let’s all time travel back to elementary school…

(but seriously, help a face-blind prof out)

Syllabus Policies

Class Structure

  • More lecture based than previous classes with me… but lots of activities
  • Lots of reading/writing practice
  • Scaffolding for projects - practice on a section, then add to your final project

Grades

Assignments Weight
Reading Quizzes & Participation 10%
User Guide/Documentation 20%
Business Report & Presentation 20%
Homework 50%

Reading Quizzes

  • Due before class starts
  • Will become inaccessible at 10am on Mondays (in normal weeks)
  • Open-book, open-note
  • A deadline to encourage you to do the reading before class

Participation/Attendance

  • I will take attendance
  • You get one free, no excuses necessary absence
  • If you’re sick, don’t come to class!
    • Do the reading/homework,
    • Make an appointment when you feel better (~ 1 week)
    • Reason: missed class xx/xx due to illness
    • Don’t abuse this

Assignments

  • Almost every week

  • Written with Quarto

  • Completed and Submitted on GitHub Classroom

  • If you’re not familiar with Git/GitHub, please let me know

    • https://happygitwithr.com <- full book of instructions and explanations
    • Office hours appointments to get help

  • Due at 6pm on Fridays (usually)

  • Grace period lasts until I start grading - might be Saturday afternoon, might be Monday

Homework Resubmissions

  • 2 resubmissions allowed

  • Due within 1 week of feedback returned. Additionally,

    • Assigned before Spring Break: resubmit by March 13 at 6pm
    • Assigned after Spring Break: resubmit by April 27 at 6pm

  • Comment on Canvas assignment page

  • Upload the assignment as a resubmission

  • Policy subject to good-faith use and my availability

  • Resubmissions will be graded at my leisure. DO NOT email me asking about the resubmission unless it has been at least 2 weeks.

Keep Up With The Work!

  • Learning good writing skills requires time and practice.

  • If you wait until the last minute to write, you can’t revise and practice.

  • This course is paced to give you enough time to revise your work… intentionally.

Projects

  • Scaffolded with homework assignments

  • Fix things I comment on w/ homework!

  • Late work will NOT be accepted without

    • major life events of >2 week duration AND
    • evidence of engagement with the assignment before the event occurred

  • Project presentations will be scheduled during Week 15 and Finals

    • IF presentations get done during Week 15 then we won’t meet for the final

  • Do NOT make travel plans for the end of the semester

User Guide

  • Translate a statistics topic into a practical guide for how to do something

    • What is required to begin? data, etc.
    • What steps need to be taken?
    • How should the results be presented/interpreted?

  • Practice thinking about audience needs and planning scope

    • Think about trying to learn a package based on a sparse vignette that doesn’t address your use case… and prevent that.

  • Takes more time to understand the topic than you think – start early.

  • Rough Draft due February 27 at 6pm

  • Final version due March 5 at 6pm

Business Report

  • Address a statistical question of interest to a business

    • Most of these are somewhat based on my time in industry

  • Find and document relevant data

  • Explain and document your analysis

  • Draw a conclusion and explain that to a non-statistician

  • Make a presentation

  • Rough Draft due April 17 at 6pm

  • Final written report due May 1 at 6pm

  • Presentations in-class April 27, April 29, May 8 (if necessary)

Evaluation Criteria

In addition to the rubric:

  • Grammar and spelling
  • Ability to communicate effectively
  • Intellectual engagement
  • Demonstrated understanding of the material

Simple, elegant solutions > unnecessary complexity

AI

  • The goal of writing classes is to improve your ability to reason… the writing is a side effect

  • AI cannot think/explain/reason – it only predicts the next likely word probabilistically

  • Do NOT use AI as a replacement for doing work. Querying to explore your understanding is probably fine, using it to write or think for you is not.

  • I would rather read something with typos and grammar issues than something that sounds like it’s from AI and not your thoughts.

Evaluation Criteria

Any use of generative AI must be disclosed in an appendix to your submission

You must document the following:

  • the version of the generative AI used (e.g. Claude Sonnet 4.5, GPT 5.2, Copilot GPT-5 chat)
  • the full sequence of prompts and responses
  • any additional inputs you provided to the AI system (documents, images, etc.)
  • a “diff” between the AI responses and your submission, showing exactly what was generated by the AI system and what you changed.

Oral Exams

  • Be prepared to explain your writing process, your approach, and your code

  • Oral exams on the assignment can be used to replace the assignment grade at my discretion

    • This is not intended as punishment – it helps at least as often as it hurts

  • Policy applies to homework and projects