Spurious correlation #3,058 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of Breweries in the United States and the second variable is Wind power generated in Luxembourg. The chart goes from 1997 to 2021, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of Breweries in the United States and the second variable is Wind power generated in Luxembourg. The chart goes from 1997 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the number of breweries in the United States increased, so did the production of beer. This led to a rise in the consumption of pretzels, a popular snack to enjoy with beer. The demand for pretzels caused an influx of orders for European salt, leading to a boom in salt production in Luxembourg. This increase in salt production somehow created more wind in Luxembourg, ultimately leading to a surge in wind power generation. "Looks like beer and pretzels aren't just a great combo for game nights, they're also blowing some renewable energy into Luxembourg!"

^{Show image generation prompt} Model: dalle-3
Prompt: Of course! Here's an image generation prompt for DALL·E-3: Prompt: Generate an image in the style of steampunk that depicts a scene of a brewery in the United States with people gathered outside enjoying cold beers. In the background, tall wind turbines harness the unintentional wind power generated by the beer enthusiasts. Meanwhile, in Luxembourg, a bustling brewery overlooks a field of wind turbines as the country ramps up its wind power production to compete with the success of American breweries. The overall scene should have a steampunk aesthetic. Feel free to adjust or add any other elements to further enhance the visual! The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

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: The number of Breweries in the United States and Wind power generated in Luxembourg. 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: a funny image macro a Polaroid photo Celtic art Futuristic Steampunk
ChatGPT: Steampunk

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 The number of Breweries in the United States and Wind power generated in Luxembourg, in the following situation: Because as the number of breweries in the United States increased, so did the demand for beer. This led to more individuals blowing on their beers to cool them down, inadvertently generating wind power. Meanwhile, in Luxembourg, witnessing the success of American breweries, inspired a surge in wind power production, as they aimed to out-brew the competition in a different type of bar.. Keep the description simple.
ChatGPT: In the United States, a growing number of breweries dot the landscape, with people gathered outside enjoying cold beers. As they blow on their drinks to cool them down, wind turbines stand tall in the background, harnessing the unintentional wind power generated by the beer enthusiasts. Meanwhile, in Luxembourg, a bustling brewery overlooks a field of wind turbines, as the country ramps up its wind power production to compete with the success of American breweries.

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: [ Steampunk ] and depicting this scene: In the United States, a growing number of breweries dot the landscape, with people gathered outside enjoying cold beers. As they blow on their drinks to cool them down, wind turbines stand tall in the background, harnessing the unintentional wind power generated by the beer enthusiasts. Meanwhile, in Luxembourg, a bustling brewery overlooks a field of wind turbines, as the country ramps up its wind power production to compete with the success of American breweries. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Of course! Here's an image generation prompt for DALL·E-3: Prompt: Generate an image in the style of steampunk that depicts a scene of a brewery in the United States with people gathered outside enjoying cold beers. In the background, tall wind turbines harness the unintentional wind power generated by the beer enthusiasts. Meanwhile, in Luxembourg, a bustling brewery overlooks a field of wind turbines as the country ramps up its wind power production to compete with the success of American breweries. The overall scene should have a steampunk aesthetic. Feel free to adjust or add any other elements to further enhance the visual!

*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.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in The number of Breweries in the United States caused Wind power generated in Luxembourg to increase. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)

Brewing Up Power: A Sudsy Study of Breweries in the US and Wind Power in Luxembourg

The Journal of Renewable Energy and Sudsy Solutions

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between The number of Breweries in the United States and Wind power generated in Luxembourg. Make lots of jokes, goofy observations, and puns.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then you might move on to cartoons and children's shows that you watched for research.

Here is the title and abstract of the paper:
[[TITLE]]
Brewing Up Power: A Sudsy Study of Breweries in the US and Wind Power in Luxembourg

[[ABSTRACT]]
This paper presents a whimsical exploration of the unexpected relationship between the number of breweries in the United States and the wind power generated in Luxembourg. While on the surface, these two factors seem unrelated, our rigorous analysis reveals a surprisingly strong correlation. By utilizing data from the Brewers Association and the Energy Information Administration, we uncovered a correlation coefficient of 0.9663354 and p < 0.01 for the years 1997 to 2021. Our findings suggest that as the number of breweries in the US has risen, so has the wind power produced in Luxembourg. We offer a lighthearted examination of this peculiar association, delving into potential confounding variables and teasing out the underlying mechanisms driving this curious correlation. This research not only adds a dash of humor to the academic realm but also lends insight into the interconnectedness of seemingly unrelated phenomena.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Brewing and wind power - two things one might not typically pair together, much like lime and coconut, or peanut butter and pickle sandwiches. However, in this spirited investigation, we delve into the curious connection between the number of breweries in the United States and the wind power generated in Luxembourg. While the link may seem as unlikely as a cat wearing a tuxedo, our analytical rigor has revealed a striking relationship that demands further exploration.
It is well-known that the U.S. boasts a thriving and diverse craft beer industry, with breweries popping up faster than daisies in springtime. Conversely, the quaint and charming country of Luxembourg has made its mark as a formidable force in wind power generation, harnessing the breezes in a manner more impressive than Mary Poppins herself. One might ponder, "What in the world could these seemingly unrelated phenomena have in common?" Well, dear reader, prepare to be tantalized by the unexpected.
The journey we embarked upon was as exhilarating as the foamy head on a freshly poured pint. Armed with data from the Brewers Association and the Energy Information Administration, we embarked on a quest to unearth the mystical bond between brews and gusts. Our findings, illuminated by the faint glow of a pub sign in the evening mist, revealed a correlation coefficient of 0.9663354, which, in statistical parlance, is about as rare as finding a four-leaf clover in your beer garden. With a p-value less than 0.01, our results stood as robust as a well-crafted stout in the face of skeptics.
This study not only serves to tickle the fancy of the inquisitive mind but also sheds light on the interconnectedness of seemingly disparate elements. As we raise our glasses to this delightful confluence of beer and wind power, we invite you to join us on this merry expedition, where we anticipate unraveling the enigmatic dance between malty aromas and gentle zephyrs. So grab a pint, sit back, and prepare to be whisked away into the whimsical world of brewing up power.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "A Sudsy Affair: An Analysis of Brewery Trends in the United States" by Smith, the authors find a comprehensive overview of the rapid growth of breweries across the United States. As the craft beer movement continues to flourish, the number of breweries has multiplied like yeast in a well-crafted IPA. A parallel inquiry by Doe in "Wind Power Wonders: The Luxembourg Experience" offers an intricate portrayal of the wind power industry in Luxembourg, highlighting the nation's remarkable journey toward harnessing the power of the wind. Together, these studies lay the groundwork for our fanciful investigation into the peculiar relationship between these two seemingly unrelated domains.

Transitioning from the solemn to the whimsical, we turn to "Brewing Revolutions: American Craft Beer and the Baltic Wind" by Jones, a fictional tale that playfully interweaves the enchanting world of breweries with the tantalizing allure of wind power. This fictitious account offers a delightful fusion of fermented fantasies and breezy escapades, setting the stage for our own lighthearted exploration of their unexpected kinship.

The research transcends traditional academic boundaries to draw inspiration from unexpected sources, including the likes of "The Adventures of Brewman and GustoGirl" children's cartoon series, as well as the iconic "Wind Whispers and Beer Banter" animated show. Delving into these unconventional channels, we gleaned unique perspectives that enriched our understanding of the supernatural bond between breweries and wind power.

As we navigate this uncharted territory, we are reminded of the timeless wisdom imparted by the renowned philosopher, Dr. Seuss, in "Hop on Pop" and "The Lorax" – insightful literary works that, in their own whimsical ways, unveil profound truths about the interconnectedness of seemingly incongruous phenomena. Such unconventional influences serve as invaluable touchstones in our quest to unravel the mystique of beer and breezes.

Stay tuned for our rib-tickling analysis of empirical studies, fanciful fables, and whimsical tales, all converging to shed light on the improbable yet captivating relationship between breweries in the United States and wind power in Luxembourg. So raise your mugs, ready your wind turbines, and embark on this merry escapade with us! Cheers to brewing up power!

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between The number of Breweries in the United States and Wind power generated in Luxembourg. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Brewers Association and Energy Information Administration . You used data from 1997 to 2021

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Brewing Up Power: A Sudsy Study of Breweries in the US and Wind Power in Luxembourg

[[ABSTRACT]]
This paper presents a whimsical exploration of the unexpected relationship between the number of breweries in the United States and the wind power generated in Luxembourg. While on the surface, these two factors seem unrelated, our rigorous analysis reveals a surprisingly strong correlation. By utilizing data from the Brewers Association and the Energy Information Administration, we uncovered a correlation coefficient of 0.9663354 and p < 0.01 for the years 1997 to 2021. Our findings suggest that as the number of breweries in the US has risen, so has the wind power produced in Luxembourg. We offer a lighthearted examination of this peculiar association, delving into potential confounding variables and teasing out the underlying mechanisms driving this curious correlation. This research not only adds a dash of humor to the academic realm but also lends insight into the interconnectedness of seemingly unrelated phenomena.

[[INTRODUCTION]]
Brewing and wind power - two things one might not typically pair together, much like lime and coconut, or peanut butter and pickle sandwiches. However, in this spirited investigation, we delve into the curious connection between the number of breweries in the United States and the wind power generated in Luxembourg. While the link may seem as unlikely as a cat wearing a tuxedo, our analytical rigor has revealed a striking relationship that demands further exploration.
It is well-known that the U.S. boasts a thriving and diverse craft beer industry, with breweries popping up faster than daisies in springtime. Conversely, the quaint and charming country of Luxembourg has made its mark as a formidable force in wind power generation, harnessing the breezes in a manner more impressive than Mary Poppins herself. One might ponder, "What in the world could these seemingly unrelated phenomena have in common?" Well, dear reader, prepare to be tantalized by the unexpected.
The journey we embarked upon was as exhilarating as the foamy head on a freshly poured pint. Armed with data from the Brewers Association and the Energy Information Administration, we embarked on a quest to unearth the mystical bond between brews and gusts. Our findings, illuminated by the faint glow of a pub sign in the evening mist, revealed a correlation coefficient of 0.9663354, which, in statistical parlance, is about as rare as finding a four-leaf clover in your beer garden. With a p-value less than 0.01, our results stood as robust as a well-crafted stout in the face of skeptics.
This study not only serves to tickle the fancy of the inquisitive mind but also sheds light on the interconnectedness of seemingly disparate elements. As we raise our glasses to this delightful confluence of beer and wind power, we invite you to join us on this merry expedition, where we anticipate unraveling the enigmatic dance between malty aromas and gentle zephyrs. So grab a pint, sit back, and prepare to be whisked away into the whimsical world of brewing up power.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To uncover the mysterious link between breweries in the United States and wind power generated in Luxembourg, we employed a methodological approach that was as meticulous as a master brewer crafting their finest ale. First and foremost, we scoured the vast landscape of the internet, much like intrepid explorers seeking the finest grains for brewing, to gather data spanning the years 1997 to 2021. Our primary sources of information were the Brewers Association, providing comprehensive data on the burgeoning brewery scene in the US, and the Energy Information Administration, offering insights into the winds of change blowing through Luxembourg's renewable energy sector.

With a hearty dose of statistical zeal and a dash of whimsy, we meticulously tabulated the number of breweries dotting the American landscape and the wind power generated in the charming confines of Luxembourg. Like a well-crafted brew, our methodology was robust and complex, yet delivered a refreshing and palatable outcome.

Our research design can be likened to the intricate and interwoven threads of a spider’s web, carefully capturing every morsel of pertinent data. Like skilled artisans, we meticulously assembled a dataset that reflected the vibrant tapestry of breweries in the US and the gusts of wind power in Luxembourg. This dataset was then subjected to a meticulous analysis that would inspire both awe and delight, comparable to discovering a hidden treasure map in the depths of an old ale barrel.

Employing sophisticated statistical techniques, including correlation analysis, to unveil the curious relationship between these seemingly unrelated elements, our team of researchers addressed potential confounding factors with the precision of a skilled sommelier pairing the perfect cheese with wine. It was crucial to navigate this intricate web of factors with finesse to ensure that our findings were as crisp and distinct as a perfectly chilled craft lager.

Furthermore, we conducted sensitivity analyses and robustness checks to ensure that our results were as resilient as a barley plant swaying in the wind. We embraced the challenges of analyzing such divergent variables with gusto, akin to an adventurous brewmaster selecting the finest hops and malts for a new concoction.

In summary, our methodology was a harmonious blend of comprehensive data collection, meticulous analysis, and statistical rigor, mirroring the complex yet harmonious ingredients in a finely brewed beer. With every step, we endeavored to intertwine the realms of brewing and wind power, ensuring that our findings were as enlightening as they were entertaining. So, raise a glass to our methodological quest, for in our pursuit of knowledge, we found merriment in the unexpected correlation between brewing and wind power. Cheers to the power of whimsy in research!

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between The number of Breweries in the United States and Wind power generated in Luxembourg. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
Brewing Up Power: A Sudsy Study of Breweries in the US and Wind Power in Luxembourg

[[ABSTRACT]]
This paper presents a whimsical exploration of the unexpected relationship between the number of breweries in the United States and the wind power generated in Luxembourg. While on the surface, these two factors seem unrelated, our rigorous analysis reveals a surprisingly strong correlation. By utilizing data from the Brewers Association and the Energy Information Administration, we uncovered a correlation coefficient of 0.9663354 and p < 0.01 for the years 1997 to 2021. Our findings suggest that as the number of breweries in the US has risen, so has the wind power produced in Luxembourg. We offer a lighthearted examination of this peculiar association, delving into potential confounding variables and teasing out the underlying mechanisms driving this curious correlation. This research not only adds a dash of humor to the academic realm but also lends insight into the interconnectedness of seemingly unrelated phenomena.

[[LITERATURE REVIEW]]
In "A Sudsy Affair: An Analysis of Brewery Trends in the United States" by Smith, the authors find a comprehensive overview of the rapid growth of breweries across the United States. As the craft beer movement continues to flourish, the number of breweries has multiplied like yeast in a well-crafted IPA. A parallel inquiry by Doe in "Wind Power Wonders: The Luxembourg Experience" offers an intricate portrayal of the wind power industry in Luxembourg, highlighting the nation's remarkable journey toward harnessing the power of the wind. Together, these studies lay the groundwork for our fanciful investigation into the peculiar relationship between these two seemingly unrelated domains.
Transitioning from the solemn to the whimsical, we turn to "Brewing Revolutions: American Craft Beer and the Baltic Wind" by Jones, a fictional tale that playfully interweaves the enchanting world of breweries with the tantalizing allure of wind power. This fictitious account offers a delightful fusion of fermented fantasies and breezy escapades, setting the stage for our own lighthearted exploration of their unexpected kinship.
The research transcends traditional academic boundaries to draw inspiration from unexpected sources, including the likes of "The Adventures of Brewman and GustoGirl" children's cartoon series, as well as the iconic "Wind Whispers and Beer Banter" animated show. Delving into these unconventional channels, we gleaned unique perspectives that enriched our understanding of the supernatural bond between breweries and wind power.
As we navigate this uncharted territory, we are reminded of the timeless wisdom imparted by the renowned philosopher, Dr. Seuss, in "Hop on Pop" and "The Lorax" – insightful literary works that, in their own whimsical ways, unveil profound truths about the interconnectedness of seemingly incongruous phenomena. Such unconventional influences serve as invaluable touchstones in our quest to unravel the mystique of beer and breezes.
Stay tuned for our rib-tickling analysis of empirical studies, fanciful fables, and whimsical tales, all converging to shed light on the improbable yet captivating relationship between breweries in the United States and wind power in Luxembourg. So raise your mugs, ready your wind turbines, and embark on this merry escapade with us! Cheers to brewing up power!

[[RESULTS]]
The analysis of the data obtained from the Brewers Association and the Energy Information Administration yielded some truly fascinating results that have left our research team both intrigued and amused. We found a remarkably strong correlation between the number of breweries in the United States and the wind power generated in Luxembourg, with a correlation coefficient of 0.9663354. This finding conveys a relationship so robust, it's almost as tight-knit as a pair of lederhosen at Oktoberfest. The r-squared value of 0.9338042 further solidifies the strength of this association, leaving little doubt that there is more to this than mere happenstance.
Our results indicate that as the number of breweries in the US has increased over the years, so has the wind power produced in Luxembourg. It's as though the gusts of creativity from American brewers have been harnessed and channeled into the production of renewable energy in the heart of Europe. It's a tale as old as time - the American dream meets European sustainability, all in a frothy symphony of fermented achievements.
The p-value of less than 0.01 adds another layer of validation to our findings, indicating that the likelihood of this correlation occurring by chance is as slim as a beer with no foam. In short, the probability of these two phenomena being unrelated is akin to the probability of finding a teetotaler at an Oktoberfest celebration - highly unlikely.
The relationship between the number of breweries in the United States and the wind power generated in Luxembourg is vividly illustrated in Figure 1. This scatterplot graphically depicts the strong positive correlation between these seemingly unrelated variables, visually encapsulating the unexpected dance between beer production and wind energy generation. It's a sight more captivating than a finely poured pint, and it certainly gives new meaning to the concept of "brewing up power."
In conclusion, our findings not only highlight the surprisingly strong correlation between these two disparate elements but also invite further investigation into the underlying mechanisms at play. As we raise a glass to this serendipitous discovery, we can't help but marvel at the delightful interconnectedness of the world around us. In the words of Benjamin Franklin, "Beer is proof that God loves us and wants us to be happy," and it seems that wind power in Luxembourg is just another testament to this divine sentiment.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our whimsical inquiry into the unexpected relationship between the number of breweries in the United States and wind power generated in Luxembourg has provided an enlightening canvas for exploring the interconnectedness of seemingly unrelated phenomena. While it may seem fantastical that the bubbling creativity of American brewers could reverberate across the Atlantic and converge with the sustainable energy efforts in Luxembourg, our rigorous analysis lends robust support to this peculiar association. Drawing inspiration from the lighthearted yet insightful literature reviewed earlier, we dare to take this curious correlation with the utmost seriousness.

The correlation coefficient of 0.9663354 found in our study mirrors the robust associations observed by Smith in "A Sudsy Affair: An Analysis of Brewery Trends in the United States" and Doe in "Wind Power Wonders: The Luxembourg Experience." This alignment of results across distinct research domains serves as a resounding validation of the unexpected relationship between these variables. Even more compelling is the r-squared value of 0.9338042, signifying a remarkable degree of variance in wind power generated in Luxembourg explained by the proliferation of breweries in the US. It's as though the wisps of merriment from American brewpubs have manifested as sustainable winds across the globe.

Moreover, the p-value of less than 0.01 provides statistical credence to the notion that this correlation arises from more than mere chance. In parallel with the fervent declarations of Jones in "Brewing Revolutions: American Craft Beer and the Baltic Wind," our findings overwhelmingly indicate that the likelihood of these phenomena being unrelated is as remote as finding a sober soul at a festive Oktoberfest celebration. The concordance of our results with those from the existing literature underscores the resilience of this enchanting association.

It is worth noting that our findings, while indeed captivating, warrant further exploration into the underlying mechanisms driving this unsuspected correlation. As we revel in the delightful synchrony of beer and breezes, we invite future researchers to delve deeper into the intricate tapestry of factors shaping this intercontinental relationship. Remember, it’s not every day that scholarly inquiry leads us to embrace the mirthful dance between hops and turbines, but our study certainly demonstrates the beauty of uncovering unexpected connections in the most unlikely of places.

As we toast to this mirthful and insightful escapade, let us raise our steins to the indelible interconnectedness of the world around us, where the zesty vim of microbreweries coalesces with the diligent whispers of wind turbines. In the words of Benjamin Franklin, "Beer is proof that God loves us and wants us to be happy," and it seems that wind power in Luxembourg is just another testament to this divine sentiment – a fizzy testament to the enduring harmony between seemingly disparate marvels of human ingenuity. Cheers to brewing up power!

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between The number of Breweries in the United States and Wind power generated in Luxembourg. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Brewing Up Power: A Sudsy Study of Breweries in the US and Wind Power in Luxembourg

[[ABSTRACT]]
This paper presents a whimsical exploration of the unexpected relationship between the number of breweries in the United States and the wind power generated in Luxembourg. While on the surface, these two factors seem unrelated, our rigorous analysis reveals a surprisingly strong correlation. By utilizing data from the Brewers Association and the Energy Information Administration, we uncovered a correlation coefficient of 0.9663354 and p < 0.01 for the years 1997 to 2021. Our findings suggest that as the number of breweries in the US has risen, so has the wind power produced in Luxembourg. We offer a lighthearted examination of this peculiar association, delving into potential confounding variables and teasing out the underlying mechanisms driving this curious correlation. This research not only adds a dash of humor to the academic realm but also lends insight into the interconnectedness of seemingly unrelated phenomena.

[[INTRDUCTION]]
Brewing and wind power - two things one might not typically pair together, much like lime and coconut, or peanut butter and pickle sandwiches. However, in this spirited investigation, we delve into the curious connection between the number of breweries in the United States and the wind power generated in Luxembourg. While the link may seem as unlikely as a cat wearing a tuxedo, our analytical rigor has revealed a striking relationship that demands further exploration.
It is well-known that the U.S. boasts a thriving and diverse craft beer industry, with breweries popping up faster than daisies in springtime. Conversely, the quaint and charming country of Luxembourg has made its mark as a formidable force in wind power generation, harnessing the breezes in a manner more impressive than Mary Poppins herself. One might ponder, "What in the world could these seemingly unrelated phenomena have in common?" Well, dear reader, prepare to be tantalized by the unexpected.
The journey we embarked upon was as exhilarating as the foamy head on a freshly poured pint. Armed with data from the Brewers Association and the Energy Information Administration, we embarked on a quest to unearth the mystical bond between brews and gusts. Our findings, illuminated by the faint glow of a pub sign in the evening mist, revealed a correlation coefficient of 0.9663354, which, in statistical parlance, is about as rare as finding a four-leaf clover in your beer garden. With a p-value less than 0.01, our results stood as robust as a well-crafted stout in the face of skeptics.
This study not only serves to tickle the fancy of the inquisitive mind but also sheds light on the interconnectedness of seemingly disparate elements. As we raise our glasses to this delightful confluence of beer and wind power, we invite you to join us on this merry expedition, where we anticipate unraveling the enigmatic dance between malty aromas and gentle zephyrs. So grab a pint, sit back, and prepare to be whisked away into the whimsical world of brewing up power.

[[RESULTS]]
The analysis of the data obtained from the Brewers Association and the Energy Information Administration yielded some truly fascinating results that have left our research team both intrigued and amused. We found a remarkably strong correlation between the number of breweries in the United States and the wind power generated in Luxembourg, with a correlation coefficient of 0.9663354. This finding conveys a relationship so robust, it's almost as tight-knit as a pair of lederhosen at Oktoberfest. The r-squared value of 0.9338042 further solidifies the strength of this association, leaving little doubt that there is more to this than mere happenstance.
Our results indicate that as the number of breweries in the US has increased over the years, so has the wind power produced in Luxembourg. It's as though the gusts of creativity from American brewers have been harnessed and channeled into the production of renewable energy in the heart of Europe. It's a tale as old as time - the American dream meets European sustainability, all in a frothy symphony of fermented achievements.
The p-value of less than 0.01 adds another layer of validation to our findings, indicating that the likelihood of this correlation occurring by chance is as slim as a beer with no foam. In short, the probability of these two phenomena being unrelated is akin to the probability of finding a teetotaler at an Oktoberfest celebration - highly unlikely.
The relationship between the number of breweries in the United States and the wind power generated in Luxembourg is vividly illustrated in Figure 1. This scatterplot graphically depicts the strong positive correlation between these seemingly unrelated variables, visually encapsulating the unexpected dance between beer production and wind energy generation. It's a sight more captivating than a finely poured pint, and it certainly gives new meaning to the concept of "brewing up power."
In conclusion, our findings not only highlight the surprisingly strong correlation between these two disparate elements but also invite further investigation into the underlying mechanisms at play. As we raise a glass to this serendipitous discovery, we can't help but marvel at the delightful interconnectedness of the world around us. In the words of Benjamin Franklin, "Beer is proof that God loves us and wants us to be happy," and it seems that wind power in Luxembourg is just another testament to this divine sentiment.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In closing, our examination of the peculiar connection between the number of breweries in the United States and wind power generated in Luxembourg has provided both intellectual enlightenment and a fair share of amusement. The correlation coefficient of 0.9663354, akin to finding a crisp, untouched pretzel in a beer garden, underscores the unanticipated bond between these two seemingly disparate elements. Our analysis has blown us away, much like a gust of wind through a field of barley.

The p-value of less than 0.01 further solidifies the validity of our findings, reinforcing the notion that this association is as tangible as the frothy head atop a well-crafted beer. The r-squared value of 0.9338042, like a perfectly executed pour, encapsulates the strength of this correlation, leaving little doubt that there's more to this relationship than meets the eye.

As we reflect on this whimsical exploration, it's clear that further research in this area is about as necessary as a beer cozy in a tropical paradise. We can confidently assert that the connection between the number of breweries in the US and wind power in Luxembourg is a delightful conundrum that requires no further unraveling. In the spirit of good humor and scholarly inquiry, let's raise a glass to the odd and wonderful interplay of brews and breezes. Cheers – or as they say in Luxembourg, "Santé et Prost!"

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited Brewing Up Power: A Sudsy Study of Breweries in the US and Wind Power in Luxembourg. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Renewable Energy and Sudsy Solutions

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Brewing Up Power: A Sudsy Study of Breweries in the US and Wind Power in Luxembourg. Respond only with the name of a fictional organization.

ChatGPT:

The Consortium for Renewable Energy and Brewery Studies

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Brewing Up Power: A Sudsy Study of Breweries in the US and Wind Power in Luxembourg with an abstract of This paper presents a whimsical exploration of the unexpected relationship between the number of breweries in the United States and the wind power generated in Luxembourg. While on the surface, these two factors seem unrelated, our rigorous analysis reveals a surprisingly strong correlation. By utilizing data from the Brewers Association and the Energy Information Administration, we uncovered a correlation coefficient of 0.9663354 and p < 0.01 for the years 1997 to 2021. Our findings suggest that as the number of breweries in the US has risen, so has the wind power produced in Luxembourg. We offer a lighthearted examination of this peculiar association, delving into potential confounding variables and teasing out the underlying mechanisms driving this curious correlation. This research not only adds a dash of humor to the academic realm but also lends insight into the interconnectedness of seemingly unrelated phenomena.

ChatGPT:

breweries, United States, wind power, Luxembourg, correlation, Brewers Association, Energy Information Administration, correlation coefficient, lighthearted examination, confounding variables, interconnectedness of phenomena

*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.

Random correlation

Discover a new correlation

View all correlations

View all research papers

Report an error

Data details

The number of Breweries in the United States
Detailed data title: Number of Breweries in the United States
Source: Brewers Association
See what else correlates with The number of Breweries in the United States

Wind power generated in Luxembourg
Detailed data title: Total wind power generated in Luxembourg in billion kWh
Source: Energy Information Administration
See what else correlates with Wind power generated in Luxembourg

Correlation r = 0.9663354 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r² = 0.9338042 (Coefficient of determination)
This means 93.4% of the change in the one variable (i.e., Wind power generated in Luxembourg) is predictable based on the change in the other (i.e., The number of Breweries in the United States) over the 25 years from 1997 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 4.7E-15.^Show 0.0000000000000046725976450153
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.97 in 4.7E-13% of random cases. Said differently, if you correlated 214,013,719,128,330 random variables^Note You don't actually need 214 trillion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 24 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 24 because we have two variables measured over a period of 25 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.92, 0.99 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!

All values for the years included above: ^Note If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
The number of Breweries in the United States (Number of breweries)	1475	1651	1577	1493	1499	1575	1629	1635	1612	1741	1805	1896	1933	2131	2525	2670	3162	4014	4847	5780	6767	7722	8557	9092	9384
Wind power generated in Luxembourg (Billion kWh)	0.003	0.011	0.018	0.025	0.024	0.024	0.026	0.039	0.052	0.058	0.064	0.061	0.063	0.055086	0.064052	0.077468	0.083028	0.079878	0.10185	0.101486	0.234823	0.254575	0.281283	0.351135	0.334879

Why this works

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.
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.
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.
Confounding variable: 2020 is particularly different from the other years on this graph. Confounding variables (like global pandemics) will cause two variables to look connected when in fact a "sneaky third" variable is influencing both of them behind the scenes.
Outlandish outliers: There are "outliers" in this data.^Note In concept, "outlier" just means "way different than the rest of your dataset." When calculating a correlation like this, they are particularly impactful because a single outlier can substantially increase your correlation.

For the purposes of this project, I counted a point as an outlier if it the residual was two standard deviations from the mean.

(This bullet point only shows up in the details page on charts that do, in fact, have outliers.)
They stand out on the scatterplot above: notice the dots that are far away from any other dots. I intentionally mishandeled outliers, which makes the correlation look extra strong.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."

# 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([1475,1651,1577,1493,1499,1575,1629,1635,1612,1741,1805,1896,1933,2131,2525,2670,3162,4014,4847,5780,6767,7722,8557,9092,9384,])
array_2 = np.array([0.003,0.011,0.018,0.025,0.024,0.024,0.026,0.039,0.052,0.058,0.064,0.061,0.063,0.055086,0.064052,0.077468,0.083028,0.079878,0.10185,0.101486,0.234823,0.254575,0.281283,0.351135,0.334879,])
array_1_name = "The number of Breweries in the United States"
array_2_name = "Wind power generated in Luxembourg"

# 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

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

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 The number of Breweries in the United States
Line chart for only Wind power generated in Luxembourg
AI-generated correlation image
The spurious research paper: Brewing Up Power: A Sudsy Study of Breweries in the US and Wind Power in Luxembourg

View another random correlation

How fun was this correlation?

Your rating skills are legendary!

Correlation ID: 3058 · Black Variable ID: 34 · Red Variable ID: 23799


Problem variable:
Issue:
Additional details: Optional
Confirm you are a human: