Spurious correlation #2,205 · 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 United States. The chart goes from 1990 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 United States. The chart goes from 1990 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As butter consumption rose, people's gas production increased, leading to greater wind power capacity in the US. This correlation may seem hard to digest, but it churns out a gouda explanation. As the saying goes, where there's a will, there's a way... and where there's wind, there's a whey!

^{Show image generation prompt} Model: dalle-3
Prompt: Create an image of a breathtaking Discovery magazine cover featuring a serene countryside view. In the foreground, a loving family is seen enjoying a picnic on a lush green hill. Nearby, majestic wind turbines generate power under the clear blue sky. The family is depicted spreading creamy butter on slices of freshly baked bread, adding a touch of warmth to the picturesque scene. The idyllic setting invites viewers to immerse themselves in the beauty of the countryside and the joy of simple pleasures. 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 United States. 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: Cyberpunk inspired by bauhaus Scalar art A Discovery magazine cover image Cubism
ChatGPT: A Discovery magazine cover image

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 United States together. Keep the description simple.
ChatGPT: A picturesque countryside with rolling green hills is dotted with wind turbines generating power under a clear blue sky. In the foreground, a family is enjoying a picnic, spreading creamy butter on slices of freshly baked bread.

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: [ A Discovery magazine cover image ] and depicting this scene: A picturesque countryside with rolling green hills is dotted with wind turbines generating power under a clear blue sky. In the foreground, a family is enjoying a picnic, spreading creamy butter on slices of freshly baked bread. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of a breathtaking Discovery magazine cover featuring a serene countryside view. In the foreground, a loving family is seen enjoying a picnic on a lush green hill. Nearby, majestic wind turbines generate power under the clear blue sky. The family is depicted spreading creamy butter on slices of freshly baked bread, adding a touch of warmth to the picturesque scene. The idyllic setting invites viewers to immerse themselves in the beauty of the countryside and the joy of simple pleasures.

*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 United States to increase. Include one good pun.

AI academic paper

(Because p < 0.01)

Churning the Winds: Exploring the Correlation between Butter Consumption and Wind Power Generation in the United States

The Journal of Dairy Dynamics

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 Butter consumption and Wind power generated in United States. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading the backs of shampoo bottles.

Here is the title and abstract of the paper:
[[TITLE]]
Churning the Winds: Exploring the Correlation between Butter Consumption and Wind Power Generation in the United States

[[ABSTRACT]]
The relationship between butter consumption and wind power generation has long been a subject of curious speculation. In this study, we embark on a rigorous statistical analysis utilizing data from the United States Department of Agriculture (USDA) and the Energy Information Administration to unravel the enigmatic link between these seemingly unrelated entities. Our findings reveal a strikingly high correlation coefficient of 0.9755873 and a statistically significant p-value of less than 0.01 for the period from 1990 to 2021. While the conventional wisdom may dismiss this association as mere happenstance, our results suggest a potential buttery-wind synergy that merits further investigation. Our study offers a whimsical yet thought-provoking perspective on the interconnectedness of seemingly disparate phenomena, challenging conventional scientific boundaries with a touch of delightful indulgence.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Mankind has long been fascinated by the intricate dance of cause and effect that manifests in the world around us. The humble quest for understanding has led researchers to explore the most unexpected and eccentric relationships, from the influence of coffee consumption on economic productivity to the effects of cheese intake on the global birth rate. In keeping with this fine tradition of investigating curious connections, our study delves into the delightful realm of churning the winds, examining the often-overlooked correlation between butter consumption and wind power generation in the United States.
The seemingly disparate nature of these two entities has fueled speculation and curiosity, prompting us to embark on a journey of statistical analysis and whimsical contemplation. As dairy enthusiasts and renewable energy advocates alike have mused over the potential underlying connection, we sought to bring clarity to this enigmatic relationship.
Our study integrates data from the United States Department of Agriculture (USDA) and the Energy Information Administration, spanning a period from 1990 to 2021. Through a meticulous examination of butter consumption patterns and wind power generation figures, we endeavored to discern patterns that may shed light on this intriguing association.
While one might be forgiven for assuming that this peculiar correlation is purely coincidental, our preliminary findings challenge such conventional thinking. By harnessing the power of statistical analysis, we uncovered a strikingly high correlation coefficient of 0.9755873 and a p-value of less than 0.01, suggesting a relationship that goes beyond mere happenstance.
This study stands as a testament to the unyielding spirit of inquiry and the undeniable charm of exploring the unexpected. Through careful examination and a touch of whimsy, we strive to offer a fresh perspective on the interconnectedness of seemingly unrelated phenomena, inviting our esteemed colleagues to join us in unraveling the mysteries of the buttery-wind synergy. As we navigate the uncharted territory of butter consumption and wind power generation, we invite you to indulge in this lighthearted yet thought-provoking investigation.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Previous scholarly inquiries into the curious link between butter consumption and wind power generation yield a mixed array of findings and speculations. Smith et al. (2015) delve into the patterns of agricultural consumption and renewable energy production, noting some intriguing initial correlations between dairy product intake and wind turbine productivity. Doe and Jones (2018) further contribute to this discourse by exploring the potential societal implications of a butter-wind nexus, bringing attention to the psychological and cultural factors at play in shaping consumer preferences for dairy and sustainable energy sources.

Turning to more eclectic sources, the intersection of culinary indulgence and environmental conscientiousness is a recurring theme in non-fiction literature. In "The Omnivore's Dilemma" by Michael Pollan and "An Inconvenient Truth" by Al Gore, tangential discussions hint at the underlying forces that may intertwine butter consumption and wind power generation. The cultural symbolism of butter and the metaphoric gusts of societal change symbolized by wind turbines provide fertile ground for imaginative exploration, though admittedly without delving into empirical analyses.

In the world of fiction, tantalizing echoes of our investigative pursuits reverberate through the pages of "The Wind in the Willows" by Kenneth Grahame and "Butterfly (Butterfly Trilogy Book 1)" by Kathryn Harvey. While these literary works may not directly address our empirical inquiries, the subtle thematic resonances with our chosen topics add a whimsical layer that enlivens our scholarly discussions.

Venturing beyond the confines of traditional academic channels, the authors acknowledge a vast array of unconventional sources that have inadvertently contributed to our understanding. Late-night infomercials extolling the virtues of butter churns and wind-powered gadgets, the evocative poetry inscribed on vintage butter wrappers, and yes, even the captivating allure of the fine print on shampoo bottles have all played an unwitting role in shaping our scholarly curiosity. While these sources may not boast the scholarly pedigree of peer-reviewed journals, they nonetheless offer a peculiar tapestry of insights that infuse our investigation with a whimsical charm.

In synthesizing this diverse range of literary contributions, our literature review presents a lighthearted yet deeply contemplative examination of the intertwined realms of butter consumption and wind power generation. As we navigate this academic odyssey, we remain committed to instilling a sense of delightful indulgence in our scholarly pursuit, inviting fellow researchers to revel in the unconventional and unexpected as we journey through uncharted territories of culinary whimsy and renewable energy.

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 Butter consumption and Wind power generated in United States. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from USDA and Energy Information Administration . You used data from 1990 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]]
Churning the Winds: Exploring the Correlation between Butter Consumption and Wind Power Generation in the United States

[[ABSTRACT]]
The relationship between butter consumption and wind power generation has long been a subject of curious speculation. In this study, we embark on a rigorous statistical analysis utilizing data from the United States Department of Agriculture (USDA) and the Energy Information Administration to unravel the enigmatic link between these seemingly unrelated entities. Our findings reveal a strikingly high correlation coefficient of 0.9755873 and a statistically significant p-value of less than 0.01 for the period from 1990 to 2021. While the conventional wisdom may dismiss this association as mere happenstance, our results suggest a potential buttery-wind synergy that merits further investigation. Our study offers a whimsical yet thought-provoking perspective on the interconnectedness of seemingly disparate phenomena, challenging conventional scientific boundaries with a touch of delightful indulgence.

[[INTRODUCTION]]
Mankind has long been fascinated by the intricate dance of cause and effect that manifests in the world around us. The humble quest for understanding has led researchers to explore the most unexpected and eccentric relationships, from the influence of coffee consumption on economic productivity to the effects of cheese intake on the global birth rate. In keeping with this fine tradition of investigating curious connections, our study delves into the delightful realm of churning the winds, examining the often-overlooked correlation between butter consumption and wind power generation in the United States.
The seemingly disparate nature of these two entities has fueled speculation and curiosity, prompting us to embark on a journey of statistical analysis and whimsical contemplation. As dairy enthusiasts and renewable energy advocates alike have mused over the potential underlying connection, we sought to bring clarity to this enigmatic relationship.
Our study integrates data from the United States Department of Agriculture (USDA) and the Energy Information Administration, spanning a period from 1990 to 2021. Through a meticulous examination of butter consumption patterns and wind power generation figures, we endeavored to discern patterns that may shed light on this intriguing association.
While one might be forgiven for assuming that this peculiar correlation is purely coincidental, our preliminary findings challenge such conventional thinking. By harnessing the power of statistical analysis, we uncovered a strikingly high correlation coefficient of 0.9755873 and a p-value of less than 0.01, suggesting a relationship that goes beyond mere happenstance.
This study stands as a testament to the unyielding spirit of inquiry and the undeniable charm of exploring the unexpected. Through careful examination and a touch of whimsy, we strive to offer a fresh perspective on the interconnectedness of seemingly unrelated phenomena, inviting our esteemed colleagues to join us in unraveling the mysteries of the buttery-wind synergy. As we navigate the uncharted territory of butter consumption and wind power generation, we invite you to indulge in this lighthearted yet thought-provoking investigation.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To illuminate the intriguing connection between butter consumption and wind power generation, a multifaceted and delightfully convoluted approach was employed. First, butter consumption data was meticulously extracted from the United States Department of Agriculture (USDA) archives, where it lay waiting, like a buttery secret yearning to be churned into statistical insight. The consumption figures, presented in pounds per capita, were meticulously compiled and cross-referenced with butter-influencing variables such as average temperature, precipitation, and the annual number of cow-themed parades (only joking, but wouldn't that be udderly delightful?).

Next, in a daring leap into the realm of renewable energy statistics, data on wind power generation was extracted from the Energy Information Administration with the gusto of a wind turbine spinning under a fresh breeze. This data was harmonized with meteorological variables such as wind speed and air pressure, combining the allure of buttery goodness with the exhilaration of wind-powered vitality.

The period under scrutiny spanned from 1990 to 2021, encompassing a broad spectrum of societal and technological shifts, as well as gusts of unpredictable trends in butter admiration and wind whisperings. A variety of quantitative techniques, from regression analyses to time series modeling, was employed to savor the subtle nuances of this delectably unusual relationship. Statistical software packages, including R, SPSS, and Excel, were deftly wielded as tools of enlightenment, providing a digital canvas for the portrayal of buttery gusts and wind-infused spreads.

To ensure the robustness and reliability of our findings, numerous sensitivity analyses and robustness checks were conducted, akin to the rigorous quality control measures in a butter sculpture competition (minus the dairy mess, of course). Additionally, sensitivity analyses were performed to identify potential outliers and influential observations, recognizing that outliers can sometimes be as fickle as a gust of wind on a sunny day.

Throughout this mélange of data collection, harmonization, and analysis, the interplay of meticulous rigor and whimsical contemplation was ever present, reflecting the charm of buttery indulgence and the energy of wind-driven potential. This methodology, tinged with humor and audacity, underpins our exploration of the captivating synthesis of butter and wind, as we invite our esteemed colleagues to join us in this delightful voyage of statistical discovery.

And speaking of voyages, doesn't it feel like the breeze just got a little buttery? Ah, the delightful intrigue of 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 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 United States. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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 1990 to 2021, you found a correlation 0.9755873, r-squared of 0.9517707, 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 the Winds: Exploring the Correlation between Butter Consumption and Wind Power Generation in the United States

[[ABSTRACT]]
The relationship between butter consumption and wind power generation has long been a subject of curious speculation. In this study, we embark on a rigorous statistical analysis utilizing data from the United States Department of Agriculture (USDA) and the Energy Information Administration to unravel the enigmatic link between these seemingly unrelated entities. Our findings reveal a strikingly high correlation coefficient of 0.9755873 and a statistically significant p-value of less than 0.01 for the period from 1990 to 2021. While the conventional wisdom may dismiss this association as mere happenstance, our results suggest a potential buttery-wind synergy that merits further investigation. Our study offers a whimsical yet thought-provoking perspective on the interconnectedness of seemingly disparate phenomena, challenging conventional scientific boundaries with a touch of delightful indulgence.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Mankind has long been fascinated by the intricate dance of cause and effect that manifests in the world around us. The humble quest for understanding has led researchers to explore the most unexpected and eccentric relationships, from the influence of coffee consumption on economic productivity to the effects of cheese intake on the global birth rate. In keeping with this fine tradition of investigating curious connections, our study delves into the delightful realm of churning the winds, examining the often-overlooked correlation between butter consumption and wind power generation in the United States.
The seemingly disparate nature of these two entities has fueled speculation and curiosity, prompting us to embark on a journey of statistical analysis and whimsical contemplation. As dairy enthusiasts and renewable energy advocates alike have mused over the potential underlying connection, we sought to bring clarity to this enigmatic relationship.
Our study integrates data from the United States Department of Agriculture (USDA) and the Energy Information Administration, spanning a period from 1990 to 2021. Through a meticulous examination of butter consumption patterns and wind power generation figures, we endeavored to discern patterns that may shed light on this intriguing association.
While one might be forgiven for assuming that this peculiar correlation is purely coincidental, our preliminary findings challenge such conventional thinking. By harnessing the power of statistical analysis, we uncovered a strikingly high correlation coefficient of 0.9755873 and a p-value of less than 0.01, suggesting a relationship that goes beyond mere happenstance.
This study stands as a testament to the unyielding spirit of inquiry and the undeniable charm of exploring the unexpected. Through careful examination and a touch of whimsy, we strive to offer a fresh perspective on the interconnectedness of seemingly unrelated phenomena, inviting our esteemed colleagues to join us in unraveling the mysteries of the buttery-wind synergy. As we navigate the uncharted territory of butter consumption and wind power generation, we invite you to indulge in this lighthearted yet thought-provoking investigation.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

**[[RESULTS]]**

The empirical analysis of butter consumption and wind power generation in the United States yielded intriguing results that may challenge traditional assumptions about the disparate nature of these phenomena. Our research, spanning the period from 1990 to 2021, unveiled a staggering correlation coefficient of 0.9755873, indicating a remarkably strong positive relationship between butter consumption and wind power generation. The coefficient of determination (r-squared) of 0.9517707 further underscores the robustness of this association, suggesting that a substantial proportion of the variability in wind power generation can be explained by butter consumption. Additionally, the p-value of less than 0.01 presents compelling evidence against the null hypothesis, supporting the presence of a meaningful relationship between these seemingly unrelated variables.

This surprising relationship takes center stage in the scatterplot depicted in Figure 1, illustrating the tight clustering of data points along a linear trend. The figure serves as a visual testament to the palpable connection between butter consumption and wind power generation, inviting the curious mind to ponder the whimsical dance of buttery breezes.

These findings evoke a sense of wonder and prompt a playful reconsideration of the underlying forces at play. While the conventional scientific mindset may dismiss such an association as mere happenstance, our results speak to a potential correlation that transcends the boundaries of mundane expectations. The sweet scent of dairy and the gentle whisper of wind intertwine in a manner that beckons further exploration and contemplation.

As such, our study offers a light-hearted yet thought-provoking vantage point on the enchanting interconnectedness of seemingly disparate phenomena, igniting the flames of curiosity and charming the scientific soul with the allure of buttery winds.

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 United States. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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 the Winds: Exploring the Correlation between Butter Consumption and Wind Power Generation in the United States

[[ABSTRACT]]
The relationship between butter consumption and wind power generation has long been a subject of curious speculation. In this study, we embark on a rigorous statistical analysis utilizing data from the United States Department of Agriculture (USDA) and the Energy Information Administration to unravel the enigmatic link between these seemingly unrelated entities. Our findings reveal a strikingly high correlation coefficient of 0.9755873 and a statistically significant p-value of less than 0.01 for the period from 1990 to 2021. While the conventional wisdom may dismiss this association as mere happenstance, our results suggest a potential buttery-wind synergy that merits further investigation. Our study offers a whimsical yet thought-provoking perspective on the interconnectedness of seemingly disparate phenomena, challenging conventional scientific boundaries with a touch of delightful indulgence.

[[LITERATURE REVIEW]]
Previous scholarly inquiries into the curious link between butter consumption and wind power generation yield a mixed array of findings and speculations. Smith et al. (2015) delve into the patterns of agricultural consumption and renewable energy production, noting some intriguing initial correlations between dairy product intake and wind turbine productivity. Doe and Jones (2018) further contribute to this discourse by exploring the potential societal implications of a butter-wind nexus, bringing attention to the psychological and cultural factors at play in shaping consumer preferences for dairy and sustainable energy sources.
Turning to more eclectic sources, the intersection of culinary indulgence and environmental conscientiousness is a recurring theme in non-fiction literature. In "The Omnivore's Dilemma" by Michael Pollan and "An Inconvenient Truth" by Al Gore, tangential discussions hint at the underlying forces that may intertwine butter consumption and wind power generation. The cultural symbolism of butter and the metaphoric gusts of societal change symbolized by wind turbines provide fertile ground for imaginative exploration, though admittedly without delving into empirical analyses.
In the world of fiction, tantalizing echoes of our investigative pursuits reverberate through the pages of "The Wind in the Willows" by Kenneth Grahame and "Butterfly (Butterfly Trilogy Book 1)" by Kathryn Harvey. While these literary works may not directly address our empirical inquiries, the subtle thematic resonances with our chosen topics add a whimsical layer that enlivens our scholarly discussions.
Venturing beyond the confines of traditional academic channels, the authors acknowledge a vast array of unconventional sources that have inadvertently contributed to our understanding. Late-night infomercials extolling the virtues of butter churns and wind-powered gadgets, the evocative poetry inscribed on vintage butter wrappers, and yes, even the captivating allure of the fine print on shampoo bottles have all played an unwitting role in shaping our scholarly curiosity. While these sources may not boast the scholarly pedigree of peer-reviewed journals, they nonetheless offer a peculiar tapestry of insights that infuse our investigation with a whimsical charm.
In synthesizing this diverse range of literary contributions, our literature review presents a lighthearted yet deeply contemplative examination of the intertwined realms of butter consumption and wind power generation. As we navigate this academic odyssey, we remain committed to instilling a sense of delightful indulgence in our scholarly pursuit, inviting fellow researchers to revel in the unconventional and unexpected as we journey through uncharted territories of culinary whimsy and renewable energy.

[[RESULTS]]
The empirical analysis of butter consumption and wind power generation in the United States yielded intriguing results that may challenge traditional assumptions about the disparate nature of these phenomena. Our research, spanning the period from 1990 to 2021, unveiled a staggering correlation coefficient of 0.9755873, indicating a remarkably strong positive relationship between butter consumption and wind power generation. The coefficient of determination (r-squared) of 0.9517707 further underscores the robustness of this association, suggesting that a substantial proportion of the variability in wind power generation can be explained by butter consumption. Additionally, the p-value of less than 0.01 presents compelling evidence against the null hypothesis, supporting the presence of a meaningful relationship between these seemingly unrelated variables.
This surprising relationship takes center stage in the scatterplot depicted in Figure 1, illustrating the tight clustering of data points along a linear trend. The figure serves as a visual testament to the palpable connection between butter consumption and wind power generation, inviting the curious mind to ponder the whimsical dance of buttery breezes.
These findings evoke a sense of wonder and prompt a playful reconsideration of the underlying forces at play. While the conventional scientific mindset may dismiss such an association as mere happenstance, our results speak to a potential correlation that transcends the boundaries of mundane expectations. The sweet scent of dairy and the gentle whisper of wind intertwine in a manner that beckons further exploration and contemplation.
As such, our study offers a light-hearted yet thought-provoking vantage point on the enchanting interconnectedness of seemingly disparate phenomena, igniting the flames of curiosity and charming the scientific soul with the allure of buttery winds.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The exceptional results from our study elucidate the fascinating correlation between butter consumption and wind power generation, shedding light on a delightful synergy that defies conventional scientific boundaries. Our findings substantiate and build upon previous scholarly inquiries, affirming the tangible link between these seemingly unrelated entities.

Drawing from the works of Smith et al. (2015) and Doe and Jones (2018), our research not only echoes but also amplifies their observations on the interconnected dynamics of agricultural consumption and renewable energy production. The robust correlation coefficient of 0.9755873 and the statistically significant p-value of less than 0.01 align with the initial speculations put forth by these esteemed researchers, underscoring the substantive nature of the butter-wind nexus.

Moreover, our investigation resonates with the unconventional perspectives gleaned from non-fiction literature, blending empirical rigor with a touch of whimsy. The thematic echoes in "The Wind in the Willows" and "Butterfly (Butterfly Trilogy Book 1)" mirror the serendipitous convergence of buttery gusts and renewable energy, imbuing our scholarly discussions with a layer of enchanting charm. Admittedly, these literary works may not offer empirical analyses, but their thematic parallels enrich our understanding of the symbolic interplay between butter consumption and wind power generation.

The presence of a palpable correlation, as depicted in Figure 1, serves as a testament to the intricate ballet of buttery breezes and wind turbines. It encourages us to ponder the whimsical dance of data points, inviting us to contemplate the enchanting interplay of these variables. The scatterplot beckons fellow researchers to embrace a whimsical mindset and revel in the unexpected as we navigate the uncharted territories of culinary indulgence and renewable energy production.

In weaving together these diverse threads of scholarly inquiry and literary exploration, our study offers a vibrant and thought-provoking perspective on the entwined realms of butter consumption and wind power generation. It challenges traditional scientific boundaries with a touch of delightful indulgence, igniting curiosity and charming the scientific soul with the allure of buttery winds.

Stay tuned for the conclusion where we attempt to contain our excitement about the buttery winds phenomenon!

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 United States. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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 the Winds: Exploring the Correlation between Butter Consumption and Wind Power Generation in the United States

[[ABSTRACT]]
The relationship between butter consumption and wind power generation has long been a subject of curious speculation. In this study, we embark on a rigorous statistical analysis utilizing data from the United States Department of Agriculture (USDA) and the Energy Information Administration to unravel the enigmatic link between these seemingly unrelated entities. Our findings reveal a strikingly high correlation coefficient of 0.9755873 and a statistically significant p-value of less than 0.01 for the period from 1990 to 2021. While the conventional wisdom may dismiss this association as mere happenstance, our results suggest a potential buttery-wind synergy that merits further investigation. Our study offers a whimsical yet thought-provoking perspective on the interconnectedness of seemingly disparate phenomena, challenging conventional scientific boundaries with a touch of delightful indulgence.

[[INTRDUCTION]]
Mankind has long been fascinated by the intricate dance of cause and effect that manifests in the world around us. The humble quest for understanding has led researchers to explore the most unexpected and eccentric relationships, from the influence of coffee consumption on economic productivity to the effects of cheese intake on the global birth rate. In keeping with this fine tradition of investigating curious connections, our study delves into the delightful realm of churning the winds, examining the often-overlooked correlation between butter consumption and wind power generation in the United States.
The seemingly disparate nature of these two entities has fueled speculation and curiosity, prompting us to embark on a journey of statistical analysis and whimsical contemplation. As dairy enthusiasts and renewable energy advocates alike have mused over the potential underlying connection, we sought to bring clarity to this enigmatic relationship.
Our study integrates data from the United States Department of Agriculture (USDA) and the Energy Information Administration, spanning a period from 1990 to 2021. Through a meticulous examination of butter consumption patterns and wind power generation figures, we endeavored to discern patterns that may shed light on this intriguing association.
While one might be forgiven for assuming that this peculiar correlation is purely coincidental, our preliminary findings challenge such conventional thinking. By harnessing the power of statistical analysis, we uncovered a strikingly high correlation coefficient of 0.9755873 and a p-value of less than 0.01, suggesting a relationship that goes beyond mere happenstance.
This study stands as a testament to the unyielding spirit of inquiry and the undeniable charm of exploring the unexpected. Through careful examination and a touch of whimsy, we strive to offer a fresh perspective on the interconnectedness of seemingly unrelated phenomena, inviting our esteemed colleagues to join us in unraveling the mysteries of the buttery-wind synergy. As we navigate the uncharted territory of butter consumption and wind power generation, we invite you to indulge in this lighthearted yet thought-provoking investigation.

[[RESULTS]]
The empirical analysis of butter consumption and wind power generation in the United States yielded intriguing results that may challenge traditional assumptions about the disparate nature of these phenomena. Our research, spanning the period from 1990 to 2021, unveiled a staggering correlation coefficient of 0.9755873, indicating a remarkably strong positive relationship between butter consumption and wind power generation. The coefficient of determination (r-squared) of 0.9517707 further underscores the robustness of this association, suggesting that a substantial proportion of the variability in wind power generation can be explained by butter consumption. Additionally, the p-value of less than 0.01 presents compelling evidence against the null hypothesis, supporting the presence of a meaningful relationship between these seemingly unrelated variables.
This surprising relationship takes center stage in the scatterplot depicted in Figure 1, illustrating the tight clustering of data points along a linear trend. The figure serves as a visual testament to the palpable connection between butter consumption and wind power generation, inviting the curious mind to ponder the whimsical dance of buttery breezes.
These findings evoke a sense of wonder and prompt a playful reconsideration of the underlying forces at play. While the conventional scientific mindset may dismiss such an association as mere happenstance, our results speak to a potential correlation that transcends the boundaries of mundane expectations. The sweet scent of dairy and the gentle whisper of wind intertwine in a manner that beckons further exploration and contemplation.
As such, our study offers a light-hearted yet thought-provoking vantage point on the enchanting interconnectedness of seemingly disparate phenomena, igniting the flames of curiosity and charming the scientific soul with the allure of buttery winds.

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation into the correlation between butter consumption and wind power generation in the United States has uncovered a truly captivating relationship that defies conventional expectations. The remarkably high correlation coefficient of 0.9755873 and a statistically significant p-value of less than 0.01 leave little room for doubt regarding the intriguing connection between these seemingly unrelated entities. Our findings serve as a testament to the whimsical nature of scientific inquiry, reminding us that the world is full of delightful surprises, much like finding a fifty-dollar bill in a forgotten pair of jeans.

The scatterplot in Figure 1 vividly illustrates the snug embrace of butter consumption and wind power generation, weaving a story of harmonious coexistence that captures the imagination. The undeniable charm of this association beckons us to ponder the curious dance of buttery breezes and the ethereal whispers of wind turbines, much like the dance of sugarplum fairies in a gust of wind.

While some may dismiss this correlation as a mere quirk of fate, our study invites scholars and enthusiasts alike to indulge in the delightful contemplation of this buttery-wind synergy. The intimate embrace of butter consumption and wind power generation offers a whimsical yet thought-provoking perspective, much like discovering a secret stash of chocolate in the vegetable crisper.

In light of these findings, we assert with the utmost certainty that no further research is needed in this area, much as a dog needs no further encouragement to chase its tail. Our study stands as a testament to the serendipitous moments of scientific inquiry, reminding us that the world is full of strange and delightful connections, akin to realizing that socks have an inexplicable tendency to disappear in the dryer.

In this delightful pursuit of unraveling the mysteries of the buttery-wind synergy, we leave our esteemed colleagues with a lighthearted invitation to embrace the unexpected and savor the whimsy of this peculiar yet charming correlation. As the butter churns and the wind turbines spin, let us bask in the joy of scientific exploration and savor the delightful surprises that await us, much like discovering an extra chicken nugget at the bottom of a fast-food bag.

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 the Winds: Exploring the Correlation between Butter Consumption and Wind Power Generation in the United States. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Dairy Dynamics

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 the Winds: Exploring the Correlation between Butter Consumption and Wind Power Generation in the United States. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Sustainable Dairy Practices and Alternative Energy Research

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 the Winds: Exploring the Correlation between Butter Consumption and Wind Power Generation in the United States with an abstract of The relationship between butter consumption and wind power generation has long been a subject of curious speculation. In this study, we embark on a rigorous statistical analysis utilizing data from the United States Department of Agriculture (USDA) and the Energy Information Administration to unravel the enigmatic link between these seemingly unrelated entities. Our findings reveal a strikingly high correlation coefficient of 0.9755873 and a statistically significant p-value of less than 0.01 for the period from 1990 to 2021. While the conventional wisdom may dismiss this association as mere happenstance, our results suggest a potential buttery-wind synergy that merits further investigation. Our study offers a whimsical yet thought-provoking perspective on the interconnectedness of seemingly disparate phenomena, challenging conventional scientific boundaries with a touch of delightful indulgence.

ChatGPT:

butter consumption, wind power generation, correlation analysis, statistical analysis, USDA data, Energy Information Administration data, United States butter consumption trend, United States wind power generation trend

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

Correlation r = 0.9755873 (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 = 0.9517707 (Coefficient of determination)
This means 95.2% of the change in the one variable (i.e., Wind power generated in United States) is predictable based on the change in the other (i.e., Butter consumption) over the 32 years from 1990 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.6E-21.^Show 0.0000000000000000000026271034
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 0.98 in 2.6E-19% of random cases. Said differently, if you correlated 380,647,370,027,384,569,856 random variables^Note You don't actually need 380 quintillion 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 31 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 31 because we have two variables measured over a period of 32 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.

[ 0.95, 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.

	1990	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)	4.3	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 United States (Billion kWh)	2.7886	2.95095	2.88752	3.00583	3.44711	3.16425	3.23407	3.28803	3.0257	4.488	5.59326	6.73733	10.3543	11.1875	14.1437	17.8105	26.5891	34.4499	55.3631	73.8861	94.6522	120.177	140.822	167.84	181.655	190.719	226.993	254.303	272.667	295.882	337.938	379.767

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([4.3,4.4,4.3,4.7,4.7,4.6,4.3,4.2,4.3,4.6,4.5,4.3,4.4,4.5,4.5,4.5,4.7,4.7,5,5,4.9,5.4,5.5,5.5,5.5,5.6,5.7,5.7,6,6.2,6.3,6.5,])
array_2 = np.array([2.7886,2.95095,2.88752,3.00583,3.44711,3.16425,3.23407,3.28803,3.0257,4.488,5.59326,6.73733,10.3543,11.1875,14.1437,17.8105,26.5891,34.4499,55.3631,73.8861,94.6522,120.177,140.822,167.84,181.655,190.719,226.993,254.303,272.667,295.882,337.938,379.767,])
array_1_name = "Butter consumption"
array_2_name = "Wind power generated in United States"

# 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 United States
AI-generated correlation image
The spurious research paper: Churning the Winds: Exploring the Correlation between Butter Consumption and Wind Power Generation in the United States

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Correlation ID: 2205 · Black Variable ID: 557 · Red Variable ID: 24079


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