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AI explanation

^{Show image generation prompt} Model: dalle-3
Prompt: [Realistic] An image of a packed stadium filled with cheering fans as the Anglo-Welsh Cup final reaches a climax. The winning team is visibly celebrating on the field, with fans erupting into a frenzy of excitement. Meanwhile, in a snow-covered landscape in Delaware, the hills are crowded with skiers and snowboarders. Ski patrol and lifeguards are shown responding to the sudden surge of winter sports enthusiasts, creating a sense of unexpected but necessary activity. 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: Score differential in Anglo-Welsh Cup final and The number of lifeguards and ski patrol in Delaware. 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: Scalar art A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s Cyber folk Realistic A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s
ChatGPT: Realistic

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 Score differential in Anglo-Welsh Cup final and The number of lifeguards and ski patrol in Delaware, in the following situation: As the score differential in the Anglo-Welsh Cup final increases, so does the level of excitement among fans. This heightened state of excitement leads to a sudden urge to hit the slopes, even in a state like Delaware. As more people inexplicably take up skiing and snowboarding, the demand for lifeguards and ski patrol in Delaware skyrockets. Who knew that a rugby tournament in the UK could have such a snowball effect on winter sports safety in a small East Coast state? . Keep the description simple.
ChatGPT: As the Anglo-Welsh Cup final reaches a nail-biting climax, the winning team gains a significant lead, sending the fans into a frenzy. Meanwhile, in Delaware, the slopes become crowded as a sudden surge of skiers and snowboarders take to the snow-covered hills. The influx of winter sports enthusiasts leads to an unprecedented demand for lifeguards and ski patrol in the state, creating an unexpected but necessary response to the newfound excitement.

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: [ Realistic ] and depicting this scene: As the Anglo-Welsh Cup final reaches a nail-biting climax, the winning team gains a significant lead, sending the fans into a frenzy. Meanwhile, in Delaware, the slopes become crowded as a sudden surge of skiers and snowboarders take to the snow-covered hills. The influx of winter sports enthusiasts leads to an unprecedented demand for lifeguards and ski patrol in the state, creating an unexpected but necessary response to the newfound excitement. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [Realistic] An image of a packed stadium filled with cheering fans as the Anglo-Welsh Cup final reaches a climax. The winning team is visibly celebrating on the field, with fans erupting into a frenzy of excitement. Meanwhile, in a snow-covered landscape in Delaware, the hills are crowded with skiers and snowboarders. Ski patrol and lifeguards are shown responding to the sudden surge of winter sports enthusiasts, creating a sense of unexpected but necessary activity.

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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

Guarding Scores: A Dive into the Correlation Between Anglo-Welsh Cup Final Score Differential and Lifeguard/Ski Patrol Numbers in Delaware The Journal of Quirky Sports Science Jan 2024 Reminder: This paper is AI-generated. Not real!

Problem variable:	Which variable has a problem? Score differential in Anglo-Welsh Cup final The number of lifeguards and ski patrol in Delaware 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.
4. Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
   Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

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([16,6,17,38,6,27,15,18,7,3,0,4,17,])
array_2 = np.array([340,310,360,440,330,390,340,390,330,310,340,310,330,])
array_1_name = "Score differential in Anglo-Welsh Cup final"
array_2_name = "The number of lifeguards and ski patrol in Delaware"

# 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 Score differential in Anglo-Welsh Cup final
• Line chart for only The number of lifeguards and ski patrol in Delaware
• AI-generated correlation image
• The spurious research paper: Guarding Scores: A Dive into the Correlation Between Anglo-Welsh Cup Final Score Differential and Lifeguard/Ski Patrol Numbers in Delaware