Taxonomy of Data

STAT 20: Introduction to Probability and Statistics

Agenda

• Concept Questions: Taxonomy of Data
• Reading Questions
• Worksheet on Paper
• Break
• RStudio & Markdown Introduction

Concept Questions

Types of Variables

There are three things a variable could be referring to

1. a phenomenon
2. how the phenomenon is being recorded or measured into data
   • what values can it take? (this is often an intent- or value-laden exercise!)
   • for numerical units, what unit should we express it in?
3. How the recorded data is being analyzed
   • binning/discretizing income data
   • if a barchart has too many bars, using a histogram.

Go through the bullet points. Then walk through with height:

height as a phenomenon is a continuous variable

height as it’s recorded is discrete

height as it’s analyzed can be binned into “short” / “tall” which is an example of… (shout out)

What type of variable is age?

Answer at pollev.com/<name>

01:00

So we spent a fair amount of time looking at this picture last week and thinking about what’s going on. We transferred information we gleaned from the picture into claims such as “The shoebill is going to eat the duck” or the truth which is “The shoebill is moving the duck out of its path.” Both of these claims, regardless of their veracity, are generated from a process of making claims with data. That data, this image, on the surface, seems to be very different than much of the data we will work with in this class: namely tabular data stored in data frames. However, that isn’t really the case. Images are data and we can make it tabular!

Images as data

• Images are composed of pixels (this image is 1520 by 1012)

• The color in each pixel is in RGB

• Each band takes a value from 0-255

• This image is data with 1520 x 1012 x 3 values.

In case you’re not used to working with pixels, imagine making a grid that’s 1520 x 1012 and overlaying it on the image. Each box within that grid is a pixel. It’s this tiny, minute area. Pixels are properties of physical things like your laptop which has a pixel resolution and they’re properties of digital things like this image.

Grayscale

• Grayscale images have only one band
• 0 is black, 255 is white
• This image is data with 1520 x 1012 x 1 values.

Grayscale

• To simplify, assume our photos are 8 x 8 grayscale images.

Images in a Data Frame

Consider the following images which are our data:

• Let’s simplify them to 8 x 8 grayscale images

Images in a Data Frame

If you were to put the data from these (8 x 8 grayscale) images into a data frame, what would the dimensions of that data frame be in rows x columns?

01:00

Worksheet on Paper

20:00

Break

03:00

Writing in RStudio

Goal: write a brief memo about your home county.

Step-by-step

1. Create and save a new .qmd file.
2. Add a title and author.
3. Add a header with the name of the county and state (if you are from abroad, provide the name of a county and state that you would like to visit)
4. Add 1-3 paragraphs about this county in text, as described by Wikipedia.
5. An example of bold and italics text.
6. A bulleted list of your top three favorite things about this county.
7. A sentence at the bottom with an acknowledgement that text came from Wikipedia along with a link to that source.

Step-by-step

1. Create and save a new .qmd file.
2. Add a title and author.
3. Add a header with the name of the county and state (if you are from abroad, provide the name of a county and state that you would like to visit)
4. Add 1-3 paragraphs about this county in text, as described by Wikipedia.
5. An example of bold and italics text.
6. A bulleted list of your top three favorite things about this county.
7. A sentence at the bottom with an acknowledgement that text came from Wikipedia along with a link to that source.

20:00