Introduction

Stat 251

2025-01-23

Introductions

Introduce yourself!

  • Name / Year / Major

  • What do you hope to learn in this class?

  • Previous computing experience?

  • Is a poptart a ravioli? Why or why not?

My Introduction

  • Heike Hofmann

  • Professor in Statistics

  • At UNL since August, I was at ISU for 20 years

  • first computer language was Pascal :)

  • R user since 1996, Python user (? I have learned it four times by now)

On PopTarts and Ravioli:

The Cube Rule of Food, from Reddit

Thus, a PopTart is a calzone.

Syllabus

Contact Info

Course Objectives

  1. Use appropriate visualizations to explore and assess data and its applicability to a problem
  1. Write code to reshape and reformat moderately complex and/or messy data in a reproducible manner
  1. Create graphical displays to explore data, assess statistical models, and present model results
  1. Adapt pre-existing code for sophisticated visualizations to new data.

Course Objectives

  1. Implement an algorithm or procedure for data modification given in pseudocode
  1. Write pseudocode to describe and document modifications made to a data set
  1. Access documentation and source code to determine how software works (or why it doesn’t)
  1. Identify problems in a data set that limit the analyses which are appropriate for the data

Textbook

https://srvanderplas.github.io/stat-computing-r-python/

Cover image of the textbook

Course Materials

  • Canvas
    • quizzes
    • weekly readings
    • homework/exam/project submission
  • Course site
    • slides
    • weekly readings
    • homework/exam/project descriptions

Everything should be cross-linked properly but email me if there’s an issue.

Class Schedule

Outline

Subject to change based on the events of the semester…

Date Topic
Jan 21 Getting Started
Jan 23 Version Control
Jan 28 Review: Functions
Jan 30 Review: Functions
Feb 4 Review: Data Structures
Feb 6 Review: Data Structures
Feb 11 Data Input
Feb 13 Data Input
Feb 18 Data Visualization
Feb 20 Data Visualization
Feb 25 Data Cleaning
Feb 27 Data Cleaning
Mar 4 Exam 1 Questions
Mar 6 Strings
Mar 11 Strings
Mar 13 Midterm Due
Mar 25 Reshaping Data
Mar 27 Reshaping Data
Apr 1 Joining Data
Apr 3 Joining Data
Apr 8 Dates and Times
Apr 10 Dates and Times
Apr 15 Project Work
Apr 17 Project Work
Apr 22 Lists
Apr 24 Lists
Apr 29 Project Work
May 1 Screencast Video Due
May 6 Spatial Data
May 8 Peer Review of Screencast Due
May 14 Scheduled Final

Grades

Assignments Weight
Reading Quizzes 10%
Weekly Homework & Participation 50%
Midterm Exam 20%
Project 20%

Approximately Weekly Homework – started in class

Academic Integrity Policy

  • You may (should!) work with each other on homework assignments

  • Work alone on exams

  • You must be able to explain anything you submit
    At my discretion, I can use a one-on-one discussion of your work to replace the grade for that work.

  • ChatGPT, StackOverflow, Google are tools, but they do not help you think

University Policies

https://executivevc.unl.edu/academic-excellence/teaching-resources/course-policies/

Setting Up

Install Course Software

Textbook Chapter 2

Next Time

We’ll work on Version Control with Git

Please read before class:

Octocat Image Source