Download png, svg

AI explanation

^{Show image generation prompt} Model: dalle-3
Prompt: [A scene from Skyrim] A lone figure wanders through the smog-covered streets of El Paso, the heavy pollution casting an eerie glow over the bustling cityscape. Suddenly, a frenzied squirrel leaps from a nearby tree, its eyes glinting with ferocity as it launches a surprise attack on a startled resident. In the distance, a group of people are frantically typing on their smartphones, their expressions reflecting the panic of being "attacked by a squirrel" in the midst of the polluted air. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

---

This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Air pollution in El Paso and Google searches for 'attacked by a squirrel'. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Whimsical illustration A scene from Skyrim inspired by bauhaus High-tech Psychedelic
ChatGPT: A scene from Skyrim

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Air pollution in El Paso and Google searches for 'attacked by a squirrel', in the following situation: The increase in air pollution in El Paso has led to some seriously agitated squirrels. As the smog levels rise, the little critters are feeling more and more squirrely, leading to an uptick in their aggressive behavior. It's like they're saying, "You humans are nuts for polluting our air!" These furry daredevils are going on a rampage, channeling their inner ninja skills and launching surprise attacks on unsuspecting residents. It's a case of "toxic air, toxic behavior" as the pollution is driving these squirrels to go completely nuts. Residents are finding themselves caught in a whirlwind of furry fury, and it's clear that the polluted air is not doing any favors for the already high-strung squirrel population. So, if you find yourself face-to-face with a particularly feisty squirrel in El Paso, maybe it's time to clean up the air and help these critters chill out before they form a full-blown squirrel army seeking revenge for the environmental damage.. Keep the description simple.
ChatGPT: In El Paso, the smog hangs heavy in the air, creating a hazy backdrop to the bustling cityscape. Amidst the pollution, a squirrel lunges from a tree, its eyes glinting with determination as it launches a surprise attack on a startled resident. Meanwhile, nearby, a group of people frantically type "attacked by a squirrel" into their smartphones, their Google searches reflecting the recent uptick in aggressive squirrel behavior due to the deteriorating air quality.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A scene from Skyrim ] and depicting this scene: In El Paso, the smog hangs heavy in the air, creating a hazy backdrop to the bustling cityscape. Amidst the pollution, a squirrel lunges from a tree, its eyes glinting with determination as it launches a surprise attack on a startled resident. Meanwhile, nearby, a group of people frantically type "attacked by a squirrel" into their smartphones, their Google searches reflecting the recent uptick in aggressive squirrel behavior due to the deteriorating air quality. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [A scene from Skyrim] A lone figure wanders through the smog-covered streets of El Paso, the heavy pollution casting an eerie glow over the bustling cityscape. Suddenly, a frenzied squirrel leaps from a nearby tree, its eyes glinting with ferocity as it launches a surprise attack on a startled resident. In the distance, a group of people are frantically typing on their smartphones, their expressions reflecting the panic of being "attacked by a squirrel" in the midst of the polluted air.

---

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.

AI academic paper

Air Pollution in El Paso: A Nutsy Connection to Google Searches for Attacked by a Squirrel The Journal of Ecological Quirkiness Jan 2024 Reminder: This paper is AI-generated. Not real!

Problem variable:	Which variable has a problem? Air pollution in El Paso Google searches for 'attacked by a squirrel' Neither / both
Issue:	What is the issue? The data is incorrect The chart isn't displaying properly There is a typo The source link is incorrect A calculation is wrong Something else
Additional details: Optional
Confirm you are a human:

Data details

Why this works

1. Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
2. Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
   no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
   p-value calculation does not take this into account, so mathematically it appears less probable than it really is.

Try it yourself

# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([1.63934,1.36986,3.83562,0,0.819672,0,0.821918,0.821918,1.36612,0.821918,0.273973,0,0,0.547945,0.547945,0.547945,0.546448,0,0.273973,0.549451,])
array_2 = np.array([12.25,12,11.75,2.41667,0,3.33333,4.75,2.5,4.33333,3.91667,2,0.916667,2.58333,0.75,0.416667,1.16667,1.41667,3.58333,4.16667,2.8,])
array_1_name = "Air pollution in El Paso"
array_2_name = "Google searches for 'attacked by a squirrel'"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

• High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.
  
  If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.
  
  Alternatively you can use a tool like Inkscape.
  
• High resolution line chart, optimized for mobile
• Alternative high resolution line chart
• Scatterplot
• Portable line chart (png)
• Portable line chart (png), optimized for mobile
• Line chart for only Air pollution in El Paso
• Line chart for only Google searches for 'attacked by a squirrel'
• AI-generated correlation image
• The spurious research paper: Air Pollution in El Paso: A Nutsy Connection to Google Searches for Attacked by a Squirrel