The Mad Hatter’s Guide to Data Viz and Stats in R
  1. Data Viz and Stats
  2. Data Kits
  3. Healthcare Data Kits
  • Data Viz and Stats
    • Tools
      • Introduction to R and RStudio
    • Data Kits
      • Healthcare Data Kits
    • Descriptions
      • Data
      • Inspect Data
      • Graphs
      • Summaries
      • Counts
      • Quantities
      • Groups
      • Distributions
      • Groups and Distributions
      • Change
      • Proportions
      • Hierarchy
      • Evolution and Flow
      • Ratings and Rankings
      • Surveys
      • Time
      • Space
        • Introduction to Maps
        • What is Vector Data?
        • The Grammar of Maps
        • Interactive Maps with leaflet
      • Networks
      • Miscellaneous Graphing Tools, and References
    • Inference
      • Basics
      • 🎲 Samples
      • Randomization
      • One Mean
      • Two Independent Means
      • Two Paired Means
      • Multiple Means (ANOVA)
      • Correlation
      • One Proportion
      • Two Proportions
    • Modelling
      • Modelling with Linear Regression
      • Modelling with Logistic Regression
      • 🕔 Modelling and Predicting Time Series
    • Workflow
      • Facing the Abyss
      • I Publish, therefore I Am
      • Data Carpentry
    • Arts
      • Colours
      • Fonts
      • Annotations
      • More Annotations
      • Highlighting
      • Scales
    • AI Tools
      • Using gander and ellmer
      • Using Github Copilot and other AI tools to generate R code
      • Using LLMs to Explain Stat models
    • Case Studies
      • Demo:Product Packaging and Elderly People
      • Ikea Furniture
      • Movie Profits
      • Gender at the Work Place
      • Heptathlon
      • School Scores
      • Children's Games
      • Valentine’s Day Spending
      • Women Live Longer?
      • Hearing Loss in Children
      • California Transit Payments
      • Seaweed Nutrients
      • Coffee Flavours
      • Legionnaire’s Disease in the USA
      • Antarctic Sea ice
      • William Farr's Observations on Cholera in London
    • Projects
      • No Free Hunch

On this page

  • 1 Introduction
  • 2 Data Kits
  • 3 What are these DataKits???!!!
  • 4 Instructions
  1. Data Viz and Stats
  2. Data Kits
  3. Healthcare Data Kits

Healthcare Data Kits

Published

September 12, 2026

Modified

September 12, 2026

Abstract
Data sets for teams in class

1 Introduction

On this page are Six Datakits: Sets of Data + Instructions for each team in class. Read further on how to download and how to use these.

2 Data Kits

Team Data Kit
Team#1: Vidhi / Dheemant / Sadiyah

Team#2: Shaariq / Siva / Taniska

Team#3: Sachi / Veda / Charita

Team#4: Meghana / Shreeya / Shivgun

Team#5: Anmol / Debu / Ishita

Team#6: Kasyap / Jayani / Rachana

3 What are these DataKits???!!!

Each DataKit contains:

  • Three datasets. One Theme, Healthcare.
  • One Dataset / Panel on your Wall: You will describe, chart, and analyze one dataset per Panel on your Wall
  • Your Wall will reside on your own personal web site which I will show you how to make, with Bricks that I will toss you.
  • Each group folder also has studio-wall.qmd — the Quarto main character main page for the Wall.
  • All the datasets are found data sets. (even if found by your Facilitator only.)
  • Campus hunches are a made-data panel. (a fourth one). This data you will make yourself.
  • Invent the hunch/sentence on Day 1; collect data on Day 7. ( I will explain this in class.)
  • On the last day of the course, we will walk around admiring the Walls and their Panels.
  • Each Team should make their Wall in a manner that matters to them, and is also effective in conveying what they want to say, with the data and analysis.

4 Instructions

  • Download and unzip your Datakits and place all the files inside a data subfolder at the root of your Quarto website project directory. ( I will show in class.)
  • Read the studio-wall.qmd file in your group folder. This is the main page for your Wall. ( You may need to rename and move it appropriately.)
  • Read the codebook.qmd file in your group folder. This is the codebook for your datasets. This will tell you what you are expected to do with each of the datasets.
  • Read the README.md file in your group folder. This will give you additional instructions that you must use to build you website. Pay attention to section named Pedagogy. This Section tells you how to build your individual Panels. (Again, I will explain in class.)

Avvaluvuthaan.

Ippadikku
Arvind V.

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