Download png, svg

AI explanation

^{Show image generation prompt} Model: dalle-3
Prompt: [ A photo-realistic image ] In this scene, imagine a soccer field bathed in the warm glow of sunset, with the lush green grass providing the perfect canvas for an extraordinary sight. In the center of the field, a soccer ball adorned with the unmistakable face of Lionel Messi sits, exuding an air of anticipation. As the ball is kicked into motion, people from all walks of life begin to join the game. Amidst the eager participants, several figures clad in teacher uniforms bring an unexpected yet delightful energy to the game. Their beaming smiles and animated conversations convey the joy they are experiencing. Each teacher demonstrates an impressive level of skill, effortlessly maneuvering the ball with the same finesse as Messi himself. As more teachers join the game, the field becomes a vibrant display of diverse individuals, each adding their own unique twist to the play. The scene encapsulates the inspiration and fervor that Messi's mastery has ignited in these educators, as they infuse their own fields with creativity and passion. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

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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 situation described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here is a situation: Because as Lionel Messi's match count with Argentina increased, more and more people were inspired to pursue their passions, leading to an influx of middle school special education teachers in Vermont. Messi's skillful footwork and strategic plays taught people to think outside the box, just like those teachers who have to use creative methods to educate their students. Plus, Messi's ability to handle pressure encouraged individuals to handle the high-pressure demands of special education. So, as Messi's match count rose, so did the number of compassionate educators ready to tackle any curveball that comes their way!. Given that situation, which of the following image descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand and the tone of the explanation. Please respond with only one of the following potential descriptions: An image that looks like it is a scene from a Pixar movie Sci-fi fantacy Futuristic A photo-realistic image Parallax art
ChatGPT: A photo-realistic image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated and the explanation described. Do not reference graphs or charts; describe physical objects.
User prompt: Please describe a visual scene that depicts the following situation. Keep the description simple. Because as Lionel Messi's match count with Argentina increased, more and more people were inspired to pursue their passions, leading to an influx of middle school special education teachers in Vermont. Messi's skillful footwork and strategic plays taught people to think outside the box, just like those teachers who have to use creative methods to educate their students. Plus, Messi's ability to handle pressure encouraged individuals to handle the high-pressure demands of special education. So, as Messi's match count rose, so did the number of compassionate educators ready to tackle any curveball that comes their way!
ChatGPT: Imagine a soccer ball with Lionel Messi's face on it sitting on a field. As the ball is kicked around, more and more people, from all walks of life, start to join in the game. Among the new players are several individuals wearing teacher uniforms, each with a big smile on their face. They're laughing and chatting with each other as they play, and they seem just as skilled as Messi in navigating the ball around the field. As the game continues, more and more teachers join in, each one adding their unique flair to their movements and strategies. It's clear that they've all been inspired by Messi's skillful play and are ready to bring that same level of passion and creativity to their own pursuits.

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 photo-realistic image ] and depicting this scene: Imagine a soccer ball with Lionel Messi's face on it sitting on a field. As the ball is kicked around, more and more people, from all walks of life, start to join in the game. Among the new players are several individuals wearing teacher uniforms, each with a big smile on their face. They're laughing and chatting with each other as they play, and they seem just as skilled as Messi in navigating the ball around the field. As the game continues, more and more teachers join in, each one adding their unique flair to their movements and strategies. It's clear that they've all been inspired by Messi's skillful play and are ready to bring that same level of passion and creativity to their own pursuits. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ A photo-realistic image ] In this scene, imagine a soccer field bathed in the warm glow of sunset, with the lush green grass providing the perfect canvas for an extraordinary sight. In the center of the field, a soccer ball adorned with the unmistakable face of Lionel Messi sits, exuding an air of anticipation. As the ball is kicked into motion, people from all walks of life begin to join the game. Amidst the eager participants, several figures clad in teacher uniforms bring an unexpected yet delightful energy to the game. Their beaming smiles and animated conversations convey the joy they are experiencing. Each teacher demonstrates an impressive level of skill, effortlessly maneuvering the ball with the same finesse as Messi himself. As more teachers join the game, the field becomes a vibrant display of diverse individuals, each adding their own unique twist to the play. The scene encapsulates the inspiration and fervor that Messi's mastery has ignited in these educators, as they infuse their own fields with creativity and passion.

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*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

Kickin' the Stats: Exploring the Unlikely Link Between Lionel Messi's Match Count with Argentina and the Number of Middle School Special Education Teachers in Vermont The Journal of Sports Statistics and Unlikely Correlations Jan 2024 Reminder: This paper is AI-generated. Not real!

Problem variable:	Which variable has a problem? Lionel Messi's match count with Argentina The number of middle school special education teachers in Vermont 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 25,213 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 635,695,369 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([5,7,14,8,10,10,13,9,7,8,4,8,4,4,5,1,9,18,])
array_2 = np.array([280,350,360,340,310,300,330,300,280,280,280,240,270,240,210,150,290,450,])
array_1_name = "Lionel Messi's match count with Argentina"
array_2_name = "The number of middle school special education teachers in Vermont"

# 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 Lionel Messi's match count with Argentina
• Line chart for only The number of middle school special education teachers in Vermont
• The spurious research paper: Kickin' the Stats: Exploring the Unlikely Link Between Lionel Messi's Match Count with Argentina and the Number of Middle School Special Education Teachers in Vermont