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AI explanation

^{Show image generation prompt} Model: dalle-3
Prompt: An image generation prompt for this scene could be: "Generate an image in the style of [Cyber folk] depicting a group of farmers proudly placing "Vote Libertarian" signs on their fields in a farm in Oregon. The sun is setting, casting golden light on the flourishing, healthy organic crops. In the background, the farmers are seen spreading a pile of dried manure across the fields, symbolizing their traditional and sustainable farming practices. Capture the earthy smell of the manure filling the air, representing the increasing demand for natural fertilizers due to the push for a hands-off approach to farming regulations. Keep the visual simple yet detailed in showcasing the pride of the farmers and the bountiful, sustainable landscape." 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 Libertarian Senators in Oregon and Dried manure used for fertilizer in the US. 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: Art nouveau Brutalism Data cyber art Futuristic Cyber folk
ChatGPT: Cyber folk

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 Libertarian Senators in Oregon and Dried manure used for fertilizer in the US, in the following situation: As the number of Libertarian votes for Senators in Oregon increased, so did the demand for a hands-off approach to farming regulations. This led to a push for more organic and sustainable farming practices. Farmers, feeling emboldened by the shifting political climate, turned towards traditional and cost-effective fertilization methods. As a result, the market for dried manure as a natural fertilizer experienced a surprising upswing. Remember, when it comes to politics, sometimes it's all about who can sling the best... policies.. Keep the description simple.
ChatGPT: In a farm in Oregon, a group of farmers proudly place "Vote Libertarian" signs on their fields. As the sun sets, the fields are seen to be flourishing with healthy organic crops. In the background, a pile of dried manure is being spread across the fields by the farmers, as they opt for traditional and sustainable farming practices. The earthy smell of the manure fills the air, symbolizing the increase in demand for natural fertilizers due to the push for a hands-off approach to farming regulations.

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: [ Cyber folk ] and depicting this scene: In a farm in Oregon, a group of farmers proudly place "Vote Libertarian" signs on their fields. As the sun sets, the fields are seen to be flourishing with healthy organic crops. In the background, a pile of dried manure is being spread across the fields by the farmers, as they opt for traditional and sustainable farming practices. The earthy smell of the manure fills the air, symbolizing the increase in demand for natural fertilizers due to the push for a hands-off approach to farming regulations. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: An image generation prompt for this scene could be: "Generate an image in the style of [Cyber folk] depicting a group of farmers proudly placing "Vote Libertarian" signs on their fields in a farm in Oregon. The sun is setting, casting golden light on the flourishing, healthy organic crops. In the background, the farmers are seen spreading a pile of dried manure across the fields, symbolizing their traditional and sustainable farming practices. Capture the earthy smell of the manure filling the air, representing the increasing demand for natural fertilizers due to the push for a hands-off approach to farming regulations. Keep the visual simple yet detailed in showcasing the pride of the farmers and the bountiful, sustainable landscape."

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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

The Connection Between Oregon Senatorial Libertarian Votes and Fertilizing Follies: A Statistical Odyssey The Journal of Quirky Political and Agricultural Research Jan 2024 Reminder: This paper is AI-generated. Not real!

Problem variable:	Which variable has a problem? Votes for Libertarian Senators in Oregon Dried manure used for fertilizer in the US 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 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 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. Very low n: There are not many data points included in this analysis. Even if the p-value is high, we should be suspicious of using so few datapoints in a correlation.

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([0.933445,1.63015,2.36573,1.6614,1.11106,3.07303,])
array_2 = np.array([114.822,125.443,156.87,154.455,140.137,193.179,])
array_1_name = "Votes for Libertarian Senators in Oregon"
array_2_name = "Dried manure used for fertilizer in the US"

# 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 Libertarian Senators in Oregon
• Line chart for only Dried manure used for fertilizer in the US
• AI-generated correlation image
• The spurious research paper: The Connection Between Oregon Senatorial Libertarian Votes and Fertilizing Follies: A Statistical Odyssey