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AI explanation

^{Show image generation prompt} Model: dalle-3
Prompt: [Funky and playful cartoon style] Create an image of a lively New Mexico town square where people are queuing at the voting booths. In the background, the Nathan's Hot Dog Eating Competition is in full swing, adding a comical touch to the scene. The air is filled with the sizzle of hotdogs being cooked and the aroma of grilled meat. Intriguingly, amidst the political discussions, there's a chaotic sense of hotdog consumption, with the energy of the political race seemingly fueling the fervor for hotdogs. The visual should capture the essence of Democratic votes in New Mexico and the hotdog frenzy, all in a simplistic and colorful cartoon format. 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 variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Votes for the Democrat Presidential candidate in New Mexico and Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion. 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: 3D Pixar Style Cute cartoon Cute 2D animation Celtic art a Polaroid photo
ChatGPT: Cute cartoon

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 Votes for the Democrat Presidential candidate in New Mexico and Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion, in the following situation: As the Democratic support sizzled in New Mexico, it created a real "frank-furter" frenzy. The surge in votes somehow sparked a wiener-takes-all mindset, leading to a bunless quest for victory. Maybe the competition just couldn't ketchup to the political excitement, or perhaps there's a link between ballot boxes and lunch boxes that we never knew existed!. Keep the description simple.
ChatGPT: In a bustling New Mexico town square, people are lined up at the voting booths. The air is filled with the sizzle of hotdogs as competitors at the Nathan's Hot Dog Eating Competition gobble down their hotdogs in the background. The aroma of grilled meat and the sound of excitement mix with the buzz of political discussions. Amidst the cheers and the munching, it seems like the energy of the political race has somehow sparked a whirlwind of hotdog consumption. These scenes capture the essence of both the Democratic votes in New Mexico and the hotdog frenzy.

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: [ Cute cartoon ] and depicting this scene: In a bustling New Mexico town square, people are lined up at the voting booths. The air is filled with the sizzle of hotdogs as competitors at the Nathan's Hot Dog Eating Competition gobble down their hotdogs in the background. The aroma of grilled meat and the sound of excitement mix with the buzz of political discussions. Amidst the cheers and the munching, it seems like the energy of the political race has somehow sparked a whirlwind of hotdog consumption. These scenes capture the essence of both the Democratic votes in New Mexico and the hotdog frenzy. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [Funky and playful cartoon style] Create an image of a lively New Mexico town square where people are queuing at the voting booths. In the background, the Nathan's Hot Dog Eating Competition is in full swing, adding a comical touch to the scene. The air is filled with the sizzle of hotdogs being cooked and the aroma of grilled meat. Intriguingly, amidst the political discussions, there's a chaotic sense of hotdog consumption, with the energy of the political race seemingly fueling the fervor for hotdogs. The visual should capture the essence of Democratic votes in New Mexico and the hotdog frenzy, all in a simplistic and colorful cartoon format.

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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

Weiner Winner: Wacky Correlation between Dem Votes in New Mexico and Nathan's Hot Dog Consumption The Journal of Culinary Politics and Quirky Statistics Jan 2024 Reminder: This paper is AI-generated. Not real!

Problem variable:	Which variable has a problem? Votes for the Democratic Presidential candidate in New Mexico Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion 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([167826,201769,244497,261617,273495,286783,370942,472422,415335,385234,501614,])
array_2 = np.array([9.5,9.5,10,19,22.25,25,53.33,59,68,70,75,])
array_1_name = "Votes for the Democratic Presidential candidate in New Mexico"
array_2_name = "Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion"

# 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 Votes for the Democratic Presidential candidate in New Mexico
• Line chart for only Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion
• AI-generated correlation image
• The spurious research paper: Weiner Winner: Wacky Correlation between Dem Votes in New Mexico and Nathan's Hot Dog Consumption