Spurious correlation #3,126 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Butter consumption and the second variable is Wind power generated in Germany. The chart goes from 1991 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 Butter consumption and the second variable is Wind power generated in Germany. The chart goes from 1991 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As butter consumption went up, people's wind-breaking capacity also increased, leading to a higher percentage of windy days in Germany.

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a cozy German kitchen filled with warm lighting and traditional wooden furniture. A group of people, each with a delighted expression, are seated around a rustic table. Freshly baked bread, still warm from the oven, is being passed around. The thick slices are generously spread with golden butter, glistening in the sunlight that filters through the windows. In the background, outside the kitchen window, tall wind turbines stand against a clear sky, their blades spinning gracefully in the breeze. The wholesome scene exudes a sense of contentment and sustainable living as the aroma of buttery bread blends with the clean, renewable energy of the wind. 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: Butter consumption and Wind power generated in Germany. 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: Brutalism Cutsy graphics Realistic Parallax art Oragami
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 Butter consumption and Wind power generated in Germany, in the following situation: Because the increase in butter consumption led to more people passing gas, which in turn increased wind power generation in Germany.. Keep the description simple.
ChatGPT: In a cozy kitchen in Germany, a group of people is enjoying freshly baked bread with generous amounts of butter spread on top. As they savor their delicious snack, a gentle breeze fills the room, causing the wind turbines outside to spin faster and generate more power. The pleasant aroma of buttery bread mixes with the clean energy of the wind, creating a unique sense of warmth and sustainability.

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: In a cozy kitchen in Germany, a group of people is enjoying freshly baked bread with generous amounts of butter spread on top. As they savor their delicious snack, a gentle breeze fills the room, causing the wind turbines outside to spin faster and generate more power. The pleasant aroma of buttery bread mixes with the clean energy of the wind, creating a unique sense of warmth and sustainability. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a cozy German kitchen filled with warm lighting and traditional wooden furniture. A group of people, each with a delighted expression, are seated around a rustic table. Freshly baked bread, still warm from the oven, is being passed around. The thick slices are generously spread with golden butter, glistening in the sunlight that filters through the windows. In the background, outside the kitchen window, tall wind turbines stand against a clear sky, their blades spinning gracefully in the breeze. The wholesome scene exudes a sense of contentment and sustainable living as the aroma of buttery bread blends with the clean, renewable energy of the wind.

*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 Butter consumption caused Wind power generated in Germany to increase.

AI academic paper

(Because p < 0.01)

Churning up Wind: Exploring the Butter-Wind Connection in Germany

Journal of Culinary Meteorology

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 the results section of an academic research paper. You speak in the past tense (you found...).
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 results section of an academic research paper presenting the findings of the connection between Butter consumption and Wind power generated in Germany. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from USDA and Energy Information Administration .

For the time period 1991 to 2021, you found a correlation 0.9493570, r-squared of 0.9012787, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
"Churning up Wind: Exploring the Butter-Wind Connection in Germany"

[[ABSTRACT]]
The relationship between butter consumption and wind power generation in Germany has long been a topic of both intrigue and skepticism. In this study, we delved into the buttery world of German cuisine and the gusty realm of renewable energy to uncover any potential correlations. Utilizing data from the USDA for butter consumption and the Energy Information Administration for wind power generation, our research team conducted a rigorous statistical analysis. Surprisingly, we discovered a striking correlation coefficient of 0.9493570 between butter consumption and wind power generated in Germany, with a significance level of p < 0.01 for the period from 1991 to 2021. Our findings not only provide a whimsical perspective on the intersection of dairy and renewables but also raise intriguing questions about the potential impact of butter-laden dishes on the generation of alternative energy sources. This research highlights the need for further investigation into the unexpected synergies between seemingly unrelated aspects of modern life.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
INTRODUCTION
In the realm of scientific inquiry, there are various unexpected and seemingly unrelated phenomena that provoke both curiosity and amusement. The peculiar relationship between butter consumption and wind power generation in Germany certainly falls into this category. While one may initially dismiss the idea of a connection between creamy dairy delights and renewable energy, our research aims to shed light on this whimsical and buttery enigma.
The hypothesis that butter consumption and wind power generation could be related may seem like the concoction of a mad scientist’s fevered dreams, but the data tells a rather different tale. We embark on this investigation with a mixture of scientific rigor and a pinch of playful curiosity, aiming to churn out some insights that will not only entertain but also provoke thought regarding the interconnectedness of disparate elements in our world.
Through the utilization of data sourced from the USDA for butter consumption and the Energy Information Administration for wind power generation, we have embarked on a statistical journey to uncover any potential correlations between these seemingly unrelated variables. In conducting our analysis, we were prepared for the possibility of encountering statistical gusts and buttery surprises, but we did not expect the zephyr of a correlation coefficient of 0.9493570 to be blowing in our faces, leaving us a bit winded (pun intended) by the strength of the relationship.
This paper aims not only to present our findings regarding the intriguing association between butter consumption and wind power generated in Germany but also to inject a dash of levity and whimsy into the often dry and serious world of research. The juxtaposition of dairy and renewables may seem utterly ludicrous at first glance, but our findings speak volumes and may churn your previously held beliefs about the impact of butter-laden dishes on the generation of alternative energy sources.
As we delve deeper into this delightfully peculiar correlation, we not only hope to tickle your scientific curiosity but also to raise intriguing questions about the potential ripple effects of seemingly unrelated factors on the broader tapestry of modern life. So, buckle up and get ready to sail through the gusts of buttery wind as we unveil the surprising bond between dairy delicacies and sustainable power.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

RESULTS

Our analysis of the data obtained from the USDA for butter consumption and the Energy Information Administration for wind power generation yielded some truly astounding results. We found a remarkably high correlation coefficient of 0.9493570 between butter consumption and wind power generated in Germany for the period from 1991 to 2021. This coefficient indicates a robust positive linear relationship between these two seemingly unrelated variables, leaving us both bewildered and buttered-up with excitement about the implications of our findings.

The strength of this correlation is further supported by an r-squared value of 0.9012787, suggesting that a substantial proportion of the variability in wind power generation can be explained by changes in butter consumption. In other words, the wind power generated in Germany seems to be closely tied to the nation's affinity for delectable buttery dishes. Who would have thought that the humble act of spreading butter on a slice of bread could have such breezy implications for renewable energy production?

Moreover, the significance level of p < 0.01 indicates that the likelihood of observing such a strong relationship by chance is exceedingly low. This prompts us to confidently assert that the correlation we have uncovered is not simply a fortuitous gust of wind but a substantive and meaningful association between butter consumption and wind power generation in Germany.

To visually represent the striking correlation we observed, we present in Fig. 1 a scatterplot that vividly portrays the close relationship between butter consumption and wind power generation. This scatterplot serves as a graphical testament to the unexpected synergy between the culinary realm of butter and the renewable energy domain of wind power. It's truly a feast for the eyes, as we witness the swirling dance of buttery data points waltzing in harmony with the gusts of wind power figures.

These findings not only provide a lighthearted and whimsical perspective on the intersection of dairy delights and renewables but also underscore the intricate and often surprising interconnectedness of various aspects of our world. The dairy-wind connection we have unearthed invites contemplation on the potential impacts of butter-laden dishes on the generation of alternative energy sources and encourages further exploration into the marvelous web of relationships that permeate our daily lives.

In conclusion, our research has churned up a rather unexpected and captivating revelation – the strong correlation between butter consumption and wind power generated in Germany. We hope that these findings will spark a zephyr of curiosity and a whirlwind of reflection on the fascinating tapestry of interactions that define our world.

Our unexpectedly buttery journey has only just begun, and we eagerly anticipate the winds of inquiry propelling us toward new and exciting scientific discoveries.

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 Butter consumption and Wind power generated in Germany. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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]]
"Churning up Wind: Exploring the Butter-Wind Connection in Germany"

[[ABSTRACT]]
The relationship between butter consumption and wind power generation in Germany has long been a topic of both intrigue and skepticism. In this study, we delved into the buttery world of German cuisine and the gusty realm of renewable energy to uncover any potential correlations. Utilizing data from the USDA for butter consumption and the Energy Information Administration for wind power generation, our research team conducted a rigorous statistical analysis. Surprisingly, we discovered a striking correlation coefficient of 0.9493570 between butter consumption and wind power generated in Germany, with a significance level of p < 0.01 for the period from 1991 to 2021. Our findings not only provide a whimsical perspective on the intersection of dairy and renewables but also raise intriguing questions about the potential impact of butter-laden dishes on the generation of alternative energy sources. This research highlights the need for further investigation into the unexpected synergies between seemingly unrelated aspects of modern life.

[[LITERATURE REVIEW]]
LITERATURE REVIEW
In "Margarine Madness: A Study of Butter Substitutes" by Smith et al., the authors find a comprehensive exploration of the butter market and its alternative products, shedding light on the historical shifts in butter consumption patterns. Meanwhile, Doe and Brown's "The Windy Ways of Renewable Energy" offers a detailed analysis of wind power generation in Germany, discussing the technological advancements and policy implications in the field. Furthermore, Jones's "Dairy Dilemmas: Exploring the World of Milk and Its Derivatives" provides insights into the broader dairy industry, touching on various milk-based products, including the ever-controversial butter.
Turning to non-fiction sources, "The Butter Battle Book" by Dr. Seuss offers a whimsical yet insightful exploration of the societal implications of butter preferences, albeit in a fictional context. Similarly, "Windfall: The Booming Business of Global Warming" by McKenzie Funk touches on the intersection of climate change and renewable energy, though it does not directly address butter-related phenomena. Finally, who could overlook the timeless classic, "Gone with the Wind" by Margaret Mitchell, which, while unrelated to either butter or wind power, remains a literary marvel in its own right?
Diving further into the realm of unconventional research sources, this research team did not shy away from exploring unorthodox avenues for insights. In an unprecedented move, we ventured into the realms of grocery store receipts, utilizing data from hundreds of mundane transactions to piece together a rough estimate of butter purchases in Germany. We also conducted in-depth interviews with cows to garner their perspectives on wind power and butter consumption, although the results were, unsurprisingly, incomprehensible to human researchers.
In an attempt to embrace the interdisciplinary nature of this study, the research team also spent countless hours watching German cooking shows and analyzing the gustatory delights of butter-laden dishes, all in the pursuit of understanding the potential impact of such indulgences on the generation of renewable energy.
The literature reviewed thus far highlights the need for a comprehensive and whimsical investigation into the unexpected connections between butter consumption and wind power generation, setting the stage for our groundbreaking study in this buttery and breezy domain.

[[RESULTS]]
RESULTS
Our analysis of the data obtained from the USDA for butter consumption and the Energy Information Administration for wind power generation yielded some truly astounding results. We found a remarkably high correlation coefficient of 0.9493570 between butter consumption and wind power generated in Germany for the period from 1991 to 2021. This coefficient indicates a robust positive linear relationship between these two seemingly unrelated variables, leaving us both bewildered and buttered-up with excitement about the implications of our findings.
The strength of this correlation is further supported by an r-squared value of 0.9012787, suggesting that a substantial proportion of the variability in wind power generation can be explained by changes in butter consumption. In other words, the wind power generated in Germany seems to be closely tied to the nation's affinity for delectable buttery dishes. Who would have thought that the humble act of spreading butter on a slice of bread could have such breezy implications for renewable energy production?
Moreover, the significance level of p < 0.01 indicates that the likelihood of observing such a strong relationship by chance is exceedingly low. This prompts us to confidently assert that the correlation we have uncovered is not simply a fortuitous gust of wind but a substantive and meaningful association between butter consumption and wind power generation in Germany.
To visually represent the striking correlation we observed, we present in Fig. 1 a scatterplot that vividly portrays the close relationship between butter consumption and wind power generation. This scatterplot serves as a graphical testament to the unexpected synergy between the culinary realm of butter and the renewable energy domain of wind power. It's truly a feast for the eyes, as we witness the swirling dance of buttery data points waltzing in harmony with the gusts of wind power figures.
These findings not only provide a lighthearted and whimsical perspective on the intersection of dairy delights and renewables but also underscore the intricate and often surprising interconnectedness of various aspects of our world. The dairy-wind connection we have unearthed invites contemplation on the potential impacts of butter-laden dishes on the generation of alternative energy sources and encourages further exploration into the marvelous web of relationships that permeate our daily lives.
In conclusion, our research has churned up a rather unexpected and captivating revelation – the strong correlation between butter consumption and wind power generated in Germany. We hope that these findings will spark a zephyr of curiosity and a whirlwind of reflection on the fascinating tapestry of interactions that define our world.
Our unexpectedly buttery journey has only just begun, and we eagerly anticipate the winds of inquiry propelling us toward new and exciting scientific discoveries.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study have churned up some truly butter-tickling insights into the quirky connection between butter consumption and wind power generation in Germany. As we delve into the implications of our findings, it's clear that this seemingly whimsical correlation carries substantial weight, much like an extra dollop of creamy butter on a warm slice of bread.

First and foremost, our rigorous statistical analysis confirmed and, dare I say, buttered up, the findings from prior research. Just as Doe and Brown's "The Windy Ways of Renewable Energy" elegantly detailed the complexities of wind power generation, our results bolster the notion that wind power and butter consumption are indeed intertwined. It's as if the very winds that turn those majestic turbines are whispering secrets about the nation's culinary inclinations, which, frankly, sounds like a deliciously windy affair.

Furthermore, our findings align with the historical shifts in butter consumption patterns elucidated by Smith et al. in "Margarine Madness." It's as though the ebb and flow of butter preferences are carried on the gusts of wind, shaping not only dietary choices but also the renewable energy landscape. Who knew that the humble stick of butter could hold such sway over the energetic dance of wind turbines?

Now, let's not overlook the elephant in the room – or should I say, the cow in the pasture – regarding our unconventional data sources and research tactics. Our delightfully mundane exploration of grocery store receipts and our incomprehensible (albeit entertaining) interviews with cows have proven to be unexpectedly fruitful. This further solidifies the robustness of our findings and highlights the sheer whimsy of scientific inquiry. Just as humorist Mark Twain once said, "Get your facts first, then you can distort them as you please." It seems we've taken this advice rather literally, albeit with a rambunctious twist.

From a statistical standpoint, our correlation coefficient and significance level speak volumes about the unmistakable relationship between butter consumption and wind power generation. This isn't just a fluke – it's a bona fide phenomenon, akin to the harmonious resonance of a well-crafted pun. Not to mention, the r-squared value indicates that changes in butter consumption explain a substantial portion of the variability in wind power generation, painting a vivid picture of how dairy indulgences sway the winds of renewable energy. It's an unexpected journey from dairy aisle to wind farm, but one that has left us utterly enthralled.

In closing, our findings not only butter the bread of scientific inquiry but also blow refreshing zephyrs into the realm of renewable energy research. It's a testament to the delightful absurdity and endless wonder of scientific exploration, reminding us that even the most seemingly unrelated variables can dance together in surprising harmony. As we wrap up this discussion, we look forward to further unraveling the gusty mysteries and creamy delights that await in the whimsical world of butter and wind power. After all, in the words of poet Robert Frost, "Some say the world will end in fire, some say in ice. From what I've tasted of desire, I hold with those who favor butter.”

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 Butter consumption and Wind power generated in Germany. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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]]
"Churning up Wind: Exploring the Butter-Wind Connection in Germany"

[[ABSTRACT]]
The relationship between butter consumption and wind power generation in Germany has long been a topic of both intrigue and skepticism. In this study, we delved into the buttery world of German cuisine and the gusty realm of renewable energy to uncover any potential correlations. Utilizing data from the USDA for butter consumption and the Energy Information Administration for wind power generation, our research team conducted a rigorous statistical analysis. Surprisingly, we discovered a striking correlation coefficient of 0.9493570 between butter consumption and wind power generated in Germany, with a significance level of p < 0.01 for the period from 1991 to 2021. Our findings not only provide a whimsical perspective on the intersection of dairy and renewables but also raise intriguing questions about the potential impact of butter-laden dishes on the generation of alternative energy sources. This research highlights the need for further investigation into the unexpected synergies between seemingly unrelated aspects of modern life.

[[INTRDUCTION]]
INTRODUCTION
In the realm of scientific inquiry, there are various unexpected and seemingly unrelated phenomena that provoke both curiosity and amusement. The peculiar relationship between butter consumption and wind power generation in Germany certainly falls into this category. While one may initially dismiss the idea of a connection between creamy dairy delights and renewable energy, our research aims to shed light on this whimsical and buttery enigma.
The hypothesis that butter consumption and wind power generation could be related may seem like the concoction of a mad scientist’s fevered dreams, but the data tells a rather different tale. We embark on this investigation with a mixture of scientific rigor and a pinch of playful curiosity, aiming to churn out some insights that will not only entertain but also provoke thought regarding the interconnectedness of disparate elements in our world.
Through the utilization of data sourced from the USDA for butter consumption and the Energy Information Administration for wind power generation, we have embarked on a statistical journey to uncover any potential correlations between these seemingly unrelated variables. In conducting our analysis, we were prepared for the possibility of encountering statistical gusts and buttery surprises, but we did not expect the zephyr of a correlation coefficient of 0.9493570 to be blowing in our faces, leaving us a bit winded (pun intended) by the strength of the relationship.
This paper aims not only to present our findings regarding the intriguing association between butter consumption and wind power generated in Germany but also to inject a dash of levity and whimsy into the often dry and serious world of research. The juxtaposition of dairy and renewables may seem utterly ludicrous at first glance, but our findings speak volumes and may churn your previously held beliefs about the impact of butter-laden dishes on the generation of alternative energy sources.
As we delve deeper into this delightfully peculiar correlation, we not only hope to tickle your scientific curiosity but also to raise intriguing questions about the potential ripple effects of seemingly unrelated factors on the broader tapestry of modern life. So, buckle up and get ready to sail through the gusts of buttery wind as we unveil the surprising bond between dairy delicacies and sustainable power.

[[RESULTS]]
RESULTS
Our analysis of the data obtained from the USDA for butter consumption and the Energy Information Administration for wind power generation yielded some truly astounding results. We found a remarkably high correlation coefficient of 0.9493570 between butter consumption and wind power generated in Germany for the period from 1991 to 2021. This coefficient indicates a robust positive linear relationship between these two seemingly unrelated variables, leaving us both bewildered and buttered-up with excitement about the implications of our findings.
The strength of this correlation is further supported by an r-squared value of 0.9012787, suggesting that a substantial proportion of the variability in wind power generation can be explained by changes in butter consumption. In other words, the wind power generated in Germany seems to be closely tied to the nation's affinity for delectable buttery dishes. Who would have thought that the humble act of spreading butter on a slice of bread could have such breezy implications for renewable energy production?
Moreover, the significance level of p < 0.01 indicates that the likelihood of observing such a strong relationship by chance is exceedingly low. This prompts us to confidently assert that the correlation we have uncovered is not simply a fortuitous gust of wind but a substantive and meaningful association between butter consumption and wind power generation in Germany.
To visually represent the striking correlation we observed, we present in Fig. 1 a scatterplot that vividly portrays the close relationship between butter consumption and wind power generation. This scatterplot serves as a graphical testament to the unexpected synergy between the culinary realm of butter and the renewable energy domain of wind power. It's truly a feast for the eyes, as we witness the swirling dance of buttery data points waltzing in harmony with the gusts of wind power figures.
These findings not only provide a lighthearted and whimsical perspective on the intersection of dairy delights and renewables but also underscore the intricate and often surprising interconnectedness of various aspects of our world. The dairy-wind connection we have unearthed invites contemplation on the potential impacts of butter-laden dishes on the generation of alternative energy sources and encourages further exploration into the marvelous web of relationships that permeate our daily lives.
In conclusion, our research has churned up a rather unexpected and captivating revelation – the strong correlation between butter consumption and wind power generated in Germany. We hope that these findings will spark a zephyr of curiosity and a whirlwind of reflection on the fascinating tapestry of interactions that define our world.
Our unexpectedly buttery journey has only just begun, and we eagerly anticipate the winds of inquiry propelling us toward new and exciting scientific discoveries.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has churned up a quite unexpected and, dare I say, buttery revelation – the strong correlation between butter consumption and wind power generated in Germany. We are truly blown away by the robust positive linear relationship we uncovered, even though we might be a bit winded from all the excitement (and puns). The significance level of p < 0.01 indicates that the likelihood of observing such a strong connection by chance is exceedingly low, making it clear that this correlation is no fluke but a substantial and meaningful association. It seems that the wind power in Germany is not just powered by turbines but by the nation's love for buttery delights!

The visual representation of our findings in the form of a scatterplot provides a feast for the eyes, with buttery data points waltzing in harmony with the gusts of wind power figures. It's like a beautiful ballet of dairy and renewables, or a gusty pas de deux if you will. One might say our scatterplot is the "butter" to our scientific bread and has spread some joy in the often dry world of statistics and research.

Our analysis not only presents a whimsical and lighthearted perspective on the oddball intersection of dairy and renewables but also encourages contemplation of the potential impacts of butter-laden dishes on the generation of alternative energy sources. Who knew that munching on a croissant with an extra dollop of butter could potentially power a wind turbine? It's utterly ludicrous and utterly intriguing at the same time.

In light of our findings, we boldly assert that no more research is needed in this buttery wind area. The gusts of our inquiry have blown strong, and it's time to spread our winds of curiosity to new and exciting scientific endeavors. As we say auf Wiedersehen to this dairy-swept adventure, we eagerly anticipate the zephyrs of inquiry propelling us toward fresh discoveries.

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 Churning up Wind: Exploring the Butter-Wind Connection in Germany. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Culinary Meteorology

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 Churning up Wind: Exploring the Butter-Wind Connection in Germany. Respond only with the name of a fictional organization.

ChatGPT:

The International Dairy and Atmospheric Research Society

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 Churning up Wind: Exploring the Butter-Wind Connection in Germany with an abstract of The relationship between butter consumption and wind power generation in Germany has long been a topic of both intrigue and skepticism. In this study, we delved into the buttery world of German cuisine and the gusty realm of renewable energy to uncover any potential correlations. Utilizing data from the USDA for butter consumption and the Energy Information Administration for wind power generation, our research team conducted a rigorous statistical analysis. Surprisingly, we discovered a striking correlation coefficient of 0.9493570 between butter consumption and wind power generated in Germany, with a significance level of p < 0.01 for the period from 1991 to 2021. Our findings not only provide a whimsical perspective on the intersection of dairy and renewables but also raise intriguing questions about the potential impact of butter-laden dishes on the generation of alternative energy sources. This research highlights the need for further investigation into the unexpected synergies between seemingly unrelated aspects of modern life.

ChatGPT:

butter consumption Germany, wind power generation Germany, correlation butter consumption wind power, renewable energy correlation, German cuisine impact on wind power, USDA butter consumption data, Energy Information Administration wind power data, statistical analysis butter consumption wind power, synergies between butter and wind power

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

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Data details

Butter consumption
Detailed data title: Per capita consumption of Butter in the US
Source: USDA
See what else correlates with Butter consumption

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

Correlation r = 0.9493570 (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 = 0.9012787 (Coefficient of determination)
This means 90.1% of the change in the one variable (i.e., Wind power generated in Germany) is predictable based on the change in the other (i.e., Butter consumption) over the 31 years from 1991 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 4.05E-16.^Show 0.0000000000000004045800246173
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 0.95 in 4.05E-14% of random cases. Said differently, if you correlated 2,471,698,895,529,800 random variables^Note You don't actually need 2 quadrillion 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 30 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 30 because we have two variables measured over a period of 31 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.

[ 0.9, 0.98 ] 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.

	1991	1992	1993	1994	1995	1996	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
Butter consumption (Pounds per person)	4.4	4.3	4.7	4.7	4.6	4.3	4.2	4.3	4.6	4.5	4.3	4.4	4.5	4.5	4.5	4.7	4.7	5	5	4.9	5.4	5.5	5.5	5.5	5.6	5.7	5.7	6	6.2	6.3	6.5
Wind power generated in Germany (Billion kWh)	0.215	0.291	0.674	1.428	1.712	2.078	3.034	4.593	5.528	9.352	10.456	15.856	19.087	26.019	27.774	31.324	40.507	41.385	39.42	37.793	48.883	50.671	51.708	57.357	79.084	78.416	103.707	107.889	123.545	129.644	113.624

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.
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

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([4.4,4.3,4.7,4.7,4.6,4.3,4.2,4.3,4.6,4.5,4.3,4.4,4.5,4.5,4.5,4.7,4.7,5,5,4.9,5.4,5.5,5.5,5.5,5.6,5.7,5.7,6,6.2,6.3,6.5,])
array_2 = np.array([0.215,0.291,0.674,1.428,1.712,2.078,3.034,4.593,5.528,9.352,10.456,15.856,19.087,26.019,27.774,31.324,40.507,41.385,39.42,37.793,48.883,50.671,51.708,57.357,79.084,78.416,103.707,107.889,123.545,129.644,113.624,])
array_1_name = "Butter consumption"
array_2_name = "Wind power generated in Germany"

# 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 Butter consumption
Line chart for only Wind power generated in Germany
AI-generated correlation image
The spurious research paper: Churning up Wind: Exploring the Butter-Wind Connection in Germany

View another random correlation

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Correlation ID: 3126 · Black Variable ID: 557 · Red Variable ID: 23688


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