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AI explanation

^{Show image generation prompt} Model: dalle-3
Prompt: The river in Tajikistan rushes with an almost palpable intensity, conveying the power and force of the hydroelectric plant. Turbines churn the waters, their massive blades slicing through the currents to produce clean, renewable energy. In the background, the majestic mountains rise, adding a sense of grandeur and natural beauty to the scene. Across the image, a sleek and modern production line at the Keystone RV Company is in motion, with RVs moving down the line in a rhythmic, automated dance. The streamlined vehicles gleam under the bright lights of the factory, each one exuding a sense of adventure and freedom, ready to take on the open road. The interplay of these two scenes illustrates the link between nature's power and human ingenuity, as if the kinetic energy of the rushing river is fueling the creation of each RV. However, amidst the steady hum of production, a hiccup becomes apparent as workers halt the line, examining the vehicles with a mix of concern and frustration. The discovery of a widespread issue looms in the air, casting a shadow over the once seamless operation. In this visual representation, there's a distinct contrast between the unstoppable force of nature and the vulnerability of human endeavor, as the promise of progress and innovation butts heads with the setbacks of unforeseen complications. 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: Hydopower energy generated in Tajikistan and Automotive recalls issued by Keystone RV Company. 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: Symbolism Vaporwave Art nouveau Hyper-realistic Macabre
ChatGPT: Hyper-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 Hydopower energy generated in Tajikistan and Automotive recalls issued by Keystone RV Company, in the following situation: The surge in hydroelectric power in Tajikistan sent a shockwave through the global energy market, sparking a chain reaction that revved up the production of RVs at Keystone. But it seems like they may have short-circuited somewhere along the line, leading to a whole caravan of faulty vehicles hitting the road. This power play inadvertently drove the RVs into a breakdown lane, leaving the company feeling quite amped up about the whole situation. It's like they tried to harness the power of Tajikistan's energy boom, but ended up getting a jolt of reality instead. This shocking turn of events has really put the company in a current predicament, and they're now scrambling to find a positive outlet for all the negative feedback. It's a cautionary tale of how a surge in one part of the world can lead to a total power outage in another, leaving everyone involved feeling a bit... deflated.. Keep the description simple.
ChatGPT: In Tajikistan, a powerful river flows, churning the water and driving massive turbines to generate hydroelectric power. Meanwhile, at the Keystone RV Company, a line of sleek, modern RVs rolls off the production line, each one ready to hit the open road. However, a hiccup in the process leads to the discovery of a widespread issue with the vehicles, prompting a mass recall. The surge of hydroelectric power in Tajikistan seemed to inject a burst of energy into the production of the RVs, but the sudden revelation of faults sent the company into a state of disarray. The powerful force that once drove the company forward now leaves it feeling deflated, as they grapple with the repercussions of the recall.

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: [ Hyper-realistic ] and depicting this scene: In Tajikistan, a powerful river flows, churning the water and driving massive turbines to generate hydroelectric power. Meanwhile, at the Keystone RV Company, a line of sleek, modern RVs rolls off the production line, each one ready to hit the open road. However, a hiccup in the process leads to the discovery of a widespread issue with the vehicles, prompting a mass recall. The surge of hydroelectric power in Tajikistan seemed to inject a burst of energy into the production of the RVs, but the sudden revelation of faults sent the company into a state of disarray. The powerful force that once drove the company forward now leaves it feeling deflated, as they grapple with the repercussions of the recall. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: The river in Tajikistan rushes with an almost palpable intensity, conveying the power and force of the hydroelectric plant. Turbines churn the waters, their massive blades slicing through the currents to produce clean, renewable energy. In the background, the majestic mountains rise, adding a sense of grandeur and natural beauty to the scene. Across the image, a sleek and modern production line at the Keystone RV Company is in motion, with RVs moving down the line in a rhythmic, automated dance. The streamlined vehicles gleam under the bright lights of the factory, each one exuding a sense of adventure and freedom, ready to take on the open road. The interplay of these two scenes illustrates the link between nature's power and human ingenuity, as if the kinetic energy of the rushing river is fueling the creation of each RV. However, amidst the steady hum of production, a hiccup becomes apparent as workers halt the line, examining the vehicles with a mix of concern and frustration. The discovery of a widespread issue looms in the air, casting a shadow over the once seamless operation. In this visual representation, there's a distinct contrast between the unstoppable force of nature and the vulnerability of human endeavor, as the promise of progress and innovation butts heads with the setbacks of unforeseen complications.

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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

Pulling the Plug: Exploring the Shocking Connection between Hydropower Energy in Tajikistan and Automotive Recalls by Keystone RV Company Journal of Sustainable Energy and Industrial Mishaps Jan 2024 Reminder: This paper is AI-generated. Not real!

Problem variable:	Which variable has a problem? Hydopower energy generated in Tajikistan Automotive recalls issued by Keystone RV Company 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([14.008,15.273,13.774,14.064,15.012,16.173,16.176,16.797,16.534,16.943,16.642,15.741,16.236,16.038,16.731,16.9,15.84,16.83,16.466,16.962,18.2101,19.17,18.1138,18,])
array_2 = np.array([1,0,1,0,0,1,3,6,9,13,8,8,15,10,5,5,8,8,13,19,24,19,17,14,])
array_1_name = "Hydopower energy generated in Tajikistan"
array_2_name = "Automotive recalls issued by Keystone RV Company"

# 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 Hydopower energy generated in Tajikistan
• Line chart for only Automotive recalls issued by Keystone RV Company
• AI-generated correlation image
• The spurious research paper: Pulling the Plug: Exploring the Shocking Connection between Hydropower Energy in Tajikistan and Automotive Recalls by Keystone RV Company