Introductions

Spatial Statistics - BIOSTAT 696/896

Michele Peruzzi

University of Michigan

Welcome

  • Class times: Monday and Wednesday, 11.30pm–1pm in 3755 SPH1
  • Office hours: Tuesdays 2pm–3pm (Zoom link on Canvas) by appointment
  • Schedule office hours with me via email: peruzzi@umich.edu
  • Textbook: Banerjee, Carlin, Gelfand, 2015, Hierarchical Modeling and Analysis for Spatial Data

Course contents

  • Introduction: types of spatial data. Failures of linear regression.
  • Preliminaries: a bunch of things you should be familiar with when working with spatial data and associated models. All “theory” questions will not directly ask you about preliminaries, but may require them when answering. Goal: make the course more self-contained
  • Point-referenced data
  • Multivariate spatial data
  • Additional/advanced topics (depending on time and your preferences, TBD)

Lecture goals, class etiquette

  • I want lectures to be opportunity for discussion and learning
  • Interrupt me at any time
  • Am I going too fast? You missed a detail? Something is unclear? Stop me immediately
  • Do not be afraid to ask
  • Asking and interrupting in a meaningful way = participation
  • Please write your name on a piece of paper with a sharpie so I can attempt to learn
  • No question is “stupid” or obvious or useless. ASK IT

AI policy

  • I encourage you to use AI tools to aid your own learning and understanding of the material
  • Example uses: clarifying or summarizing, generating code snippets, finding references, creating practice questions, create flashcards, more in-depth explanations of concepts
  • AI should boost your own thinking, not replace it
  • All individual assessments will be written, in-person, no AI allowed. Be ready for them.
  • Be aware of AI limitations: it can generate incorrect or misleading information. Learn to verify outputs.

Evaluation

  • 30% quizzes (3 in-class, 1 take-home)
  • 30% written in-class individual mid-term exam
  • 40% written in-class individual final exam

Quizzes:

  • 3 in-class written multiple choice quizzes
  • 1 take-home data analysis quiz (you will have more than 1 week to complete it)
  • Lowest quiz score dropped

Written exam policy:

  • Open book, open notes. Bring as much material as you want.
  • No computer/tablet/phone use.

Accommodations

  • Let me know ASAP if you need accommodations
  • Refer to syllabus

Questions?

  • Last day to drop: Tuesday, January 27
  • Question time