Spurious correlation #1,362 · 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 Lithuania. The chart goes from 2004 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 Lithuania. The chart goes from 2004 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As butter consumption increased, people naturally became more gaseous, creating a higher demand for wind power in Lithuania. The connection is quite a-moo-sing! More butter, more tootin’, more wind power spoutin’ in Lithuania! The correlation is udderly undeniable!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a serene Lithuanian countryside with a family enjoying a picnic in a sun-drenched meadow. Show the family surrounded by green grass and wildflowers, spreading freshly churned butter on slices of warm bread. A gentle breeze should sway the nearby wind turbines, harnessing the power of the wind to generate clean energy. This image should embody a sense of tranquility and sustainability. The colors and lighting should invite serenity and warmth, capturing the essence of enjoying a peaceful day in the countryside. 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 Lithuania. 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: Cubism Scalar art a Polaroid photo Cyberpunk Brutalism
ChatGPT: Scalar art

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 Lithuania together. Keep the description simple.
ChatGPT: In the tranquil countryside of Lithuania, a family enjoys a picnic in a sun-drenched meadow. They spread freshly churned butter on slices of warm bread as a gentle breeze sways the nearby wind turbines, harnessing the power of the wind to generate clean energy for the community.

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: [ Scalar art ] and depicting this scene: In the tranquil countryside of Lithuania, a family enjoys a picnic in a sun-drenched meadow. They spread freshly churned butter on slices of warm bread as a gentle breeze sways the nearby wind turbines, harnessing the power of the wind to generate clean energy for the community. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a serene Lithuanian countryside with a family enjoying a picnic in a sun-drenched meadow. Show the family surrounded by green grass and wildflowers, spreading freshly churned butter on slices of warm bread. A gentle breeze should sway the nearby wind turbines, harnessing the power of the wind to generate clean energy. This image should embody a sense of tranquility and sustainability. The colors and lighting should invite serenity and warmth, capturing the essence of enjoying a peaceful day in the countryside.

*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 Lithuania to increase. Include one good pun.

AI academic paper

(Because p < 0.01)

Stirring Up a Storm: Exploring the Correlation Between Butter Consumption and Wind Power Generation in Lithuania

The Journal of Sustainable Dairy and Renewable Energy

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 dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Lithuania. 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 cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
Stirring Up a Storm: Exploring the Correlation Between Butter Consumption and Wind Power Generation in Lithuania

[[ABSTRACT]]
This study delves into the rich and surprisingly gusty world of butter consumption and wind power generation in Lithuania, unraveling a nexus that has gone unnoticed in the annals of scholarly inquiry. By leveraging data from the USDA and the Energy Information Administration for the period spanning from 2004 to 2021, we have meticulously scrutinized the oft-overlooked relationship between these two seemingly disparate facets of human existence.

Our analysis has yielded compelling results, revealing a striking correlation coefficient of 0.9480388, with a p-value of less than 0.01. This robust statistical association prompts one to ponder whether there may be more to the gustatory habits of the Lithuanian populace than meets the eye. The findings of this investigation not only underscore the potential impact of butter consumption on wind power generation but also serve as a potent reminder of the whimsical interconnectedness of socio-economic phenomena.

As we delve into the gustatory delights and sustainable energy sources of Lithuania, this study illuminates a fresh perspective, quite literally and figuratively, on the dynamics that underpin these seemingly unrelated domains. The wind of change may indeed carry a whisper of creamy indulgence.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The seemingly unrelated domains of butter consumption and wind power generation in Lithuania have captured the curiosity of researchers and laypersons alike. While butter has long been a staple in Lithuanian cuisine, the utilization of wind power as a renewable energy source has been on the rise in the country in recent years. However, the potential correlation between these two distinct phenomena has been shrouded in mystery, much like the swirling gusts of wind that characterize the Lithuanian landscape.
As we embark on this journey of discovery, it is important to acknowledge the lighthearted allure of investigating a link between a dairy product and a form of sustainable energy. Indeed, the implications of such a correlation could churn the very foundations of our understanding of consumer behavior and its unsuspected consequences on environmental factors. This investigation may also offer a breath of fresh air in the often staid and serious realm of empirical research, reminding us that scientific inquiry can encompass the whimsy and wonder of everyday existence.
While the initial premise of this study may appear to be as light and airy as a buttery puff pastry, the statistical rigor applied to our analysis elevates its significance to a level of scientific inquiry. By delving into the data with mathematical precision, we aim to shed light on the potential influence of butter consumption on the generation of wind power, teasing out the nuanced interplay of gustatory habits and sustainable energy production.
Join us as we unfold the layers of this unique investigation, blending the richness of statistical analysis with the breezy allure of wind power and the delectable allure of butter in a manner that could colloquially be described as "churning out" unexpected connections. The winds of change may indeed carry a whisper of creamy indulgence, and we invite you to savor the scientific journey that lies ahead.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The relationship between dietary habits and energy production has been extensively explored in the literature. Smith et al. (2010) examined the potential impact of dairy consumption on renewable energy sources, although their focus was primarily on cheese and solar power. Similarly, Doe and Jones (2015) investigated the connection between margarine intake and hydroelectric power in a study that garnered attention for its unique approach to dietary analysis. These studies, while insightful, have yet to delve into the specific interplay between butter consumption and wind power generation, leaving this particular avenue of inquiry largely uncharted.

Turning to more expansive discussions of agricultural practices and sustainable energy, "The Omnivore's Dilemma" by Michael Pollan provides a comprehensive overview of food production and consumption, touching on the ecological implications of dairy farming and the broader impact of human dietary choices. In a similar vein, "The Third Plate" by Dan Barber delves into the interconnectedness of food, farming, and the environment, offering a thought-provoking exploration of the complex relationships that underpin our culinary traditions and their wider ramifications.

Shifting our focus to potential fictional narratives that may offer tangential insights, the fantastical world of "The Wind-Up Bird Chronicle" by Haruki Murakami alludes to the enigmatic forces that shape our reality, hinting at a metaphorical resonance with the unseen influences that may underlie the butter-wind power connection. Furthermore, the whimsical universe of Terry Pratchett's "Going Postal" introduces a satirical lens through which to contemplate the unexpected intersections of human behavior and environmental phenomena, offering a lighthearted yet thought-provoking perspective on the matter at hand.

In the realm of social media discourse, a tweet by @DairyDreamer poses a ponderous query: "Do buttered scones truly have the power to harness the wind? #MysticalMargarine" This seemingly whimsical musing shines a light on the public's latent fascination with the potential implications of butter consumption on renewable energy, hinting at a broader undercurrent of curiosity regarding this unusual nexus.

In delving into this uncharted territory, it is essential to approach the intersection of butter consumption and wind power generation with a degree of scholarly seriousness tempered by an appreciation for the unexpected whimsy that may underpin this eccentric correlation.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Lithuania. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 . You used data from 2004 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]]
Stirring Up a Storm: Exploring the Correlation Between Butter Consumption and Wind Power Generation in Lithuania

[[ABSTRACT]]
This study delves into the rich and surprisingly gusty world of butter consumption and wind power generation in Lithuania, unraveling a nexus that has gone unnoticed in the annals of scholarly inquiry. By leveraging data from the USDA and the Energy Information Administration for the period spanning from 2004 to 2021, we have meticulously scrutinized the oft-overlooked relationship between these two seemingly disparate facets of human existence.

Our analysis has yielded compelling results, revealing a striking correlation coefficient of 0.9480388, with a p-value of less than 0.01. This robust statistical association prompts one to ponder whether there may be more to the gustatory habits of the Lithuanian populace than meets the eye. The findings of this investigation not only underscore the potential impact of butter consumption on wind power generation but also serve as a potent reminder of the whimsical interconnectedness of socio-economic phenomena.

As we delve into the gustatory delights and sustainable energy sources of Lithuania, this study illuminates a fresh perspective, quite literally and figuratively, on the dynamics that underpin these seemingly unrelated domains. The wind of change may indeed carry a whisper of creamy indulgence.

[[INTRODUCTION]]
The seemingly unrelated domains of butter consumption and wind power generation in Lithuania have captured the curiosity of researchers and laypersons alike. While butter has long been a staple in Lithuanian cuisine, the utilization of wind power as a renewable energy source has been on the rise in the country in recent years. However, the potential correlation between these two distinct phenomena has been shrouded in mystery, much like the swirling gusts of wind that characterize the Lithuanian landscape.
As we embark on this journey of discovery, it is important to acknowledge the lighthearted allure of investigating a link between a dairy product and a form of sustainable energy. Indeed, the implications of such a correlation could churn the very foundations of our understanding of consumer behavior and its unsuspected consequences on environmental factors. This investigation may also offer a breath of fresh air in the often staid and serious realm of empirical research, reminding us that scientific inquiry can encompass the whimsy and wonder of everyday existence.
While the initial premise of this study may appear to be as light and airy as a buttery puff pastry, the statistical rigor applied to our analysis elevates its significance to a level of scientific inquiry. By delving into the data with mathematical precision, we aim to shed light on the potential influence of butter consumption on the generation of wind power, teasing out the nuanced interplay of gustatory habits and sustainable energy production.
Join us as we unfold the layers of this unique investigation, blending the richness of statistical analysis with the breezy allure of wind power and the delectable allure of butter in a manner that could colloquially be described as "churning out" unexpected connections. The winds of change may indeed carry a whisper of creamy indulgence, and we invite you to savor the scientific journey that lies ahead.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To explore the intriguing nexus between butter consumption and wind power generation in Lithuania, a series of meticulously designed research methodologies were implemented, combining the analytical prowess of statistical inquiry with the gustatory whims of culinary examination.

First, data on butter consumption in Lithuania was painstakingly gathered from the USDA database, encompassing the years 2004 to 2021. The quantities of butter ingested by the Lithuanian populace were quantified and dissected with the earnestness of a discerning food critic, aiming to uncover any gustatory patterns that may correspond with fluctuations in wind power generation.

Simultaneously, wind power generation data from Lithuania was sourced from the Energy Information Administration, spanning the same time period. The wattage generated by the graceful lithuanian wind turbines was scrutinized not just for its kilowatt-hour output, but also for the subtle nuances that might sway in harmony with the undulating waves of butter consumption across the years.

Furthermore, a sophisticated statistical analysis, specifically the Pearson correlation coefficient, was deployed to ascertain the degree of association between these deceptively dissimilar variables. The p-value, akin to the mysterious alchemy that underpins a culinary masterpiece, provided a measure of the robustness of this unearthed correlation.

In addition to this, a time series analysis was conducted to explore the temporal dynamics of butter consumption and wind power generation. This method allowed us to metaphorically taste the nuances of these variables across the years, unraveling potential patterns that may have eluded previous scholarly palates.

Lastly, a multidimensional approach was taken to account for potential confounding factors, acknowledging that any association between butter consumption and wind power generation must be vetted for its resilience to extraneous influences. This involved considering economic, climatic, and demographic variables that may have intermingled with the gustatory proclivities of the Lithuanian populace and the ethereal dance of wind energy.

Thus, armed with a melange of statistical wizardry and culinary intrigue, this study unfolded its methodology with the resolute determination of a determined chef seeking to uncover the elusive recipe for a gustatory and sustainable energy masterpiece.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Lithuania. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
Stirring Up a Storm: Exploring the Correlation Between Butter Consumption and Wind Power Generation in Lithuania

[[ABSTRACT]]
This study delves into the rich and surprisingly gusty world of butter consumption and wind power generation in Lithuania, unraveling a nexus that has gone unnoticed in the annals of scholarly inquiry. By leveraging data from the USDA and the Energy Information Administration for the period spanning from 2004 to 2021, we have meticulously scrutinized the oft-overlooked relationship between these two seemingly disparate facets of human existence.

Our analysis has yielded compelling results, revealing a striking correlation coefficient of 0.9480388, with a p-value of less than 0.01. This robust statistical association prompts one to ponder whether there may be more to the gustatory habits of the Lithuanian populace than meets the eye. The findings of this investigation not only underscore the potential impact of butter consumption on wind power generation but also serve as a potent reminder of the whimsical interconnectedness of socio-economic phenomena.

As we delve into the gustatory delights and sustainable energy sources of Lithuania, this study illuminates a fresh perspective, quite literally and figuratively, on the dynamics that underpin these seemingly unrelated domains. The wind of change may indeed carry a whisper of creamy indulgence.

[[LITERATURE REVIEW]]
The relationship between dietary habits and energy production has been extensively explored in the literature. Smith et al. (2010) examined the potential impact of dairy consumption on renewable energy sources, although their focus was primarily on cheese and solar power. Similarly, Doe and Jones (2015) investigated the connection between margarine intake and hydroelectric power in a study that garnered attention for its unique approach to dietary analysis. These studies, while insightful, have yet to delve into the specific interplay between butter consumption and wind power generation, leaving this particular avenue of inquiry largely uncharted.
Turning to more expansive discussions of agricultural practices and sustainable energy, "The Omnivore's Dilemma" by Michael Pollan provides a comprehensive overview of food production and consumption, touching on the ecological implications of dairy farming and the broader impact of human dietary choices. In a similar vein, "The Third Plate" by Dan Barber delves into the interconnectedness of food, farming, and the environment, offering a thought-provoking exploration of the complex relationships that underpin our culinary traditions and their wider ramifications.
Shifting our focus to potential fictional narratives that may offer tangential insights, the fantastical world of "The Wind-Up Bird Chronicle" by Haruki Murakami alludes to the enigmatic forces that shape our reality, hinting at a metaphorical resonance with the unseen influences that may underlie the butter-wind power connection. Furthermore, the whimsical universe of Terry Pratchett's "Going Postal" introduces a satirical lens through which to contemplate the unexpected intersections of human behavior and environmental phenomena, offering a lighthearted yet thought-provoking perspective on the matter at hand.
In the realm of social media discourse, a tweet by @DairyDreamer poses a ponderous query: "Do buttered scones truly have the power to harness the wind? #MysticalMargarine" This seemingly whimsical musing shines a light on the public's latent fascination with the potential implications of butter consumption on renewable energy, hinting at a broader undercurrent of curiosity regarding this unusual nexus.
In delving into this uncharted territory, it is essential to approach the intersection of butter consumption and wind power generation with a degree of scholarly seriousness tempered by an appreciation for the unexpected whimsy that may underpin this eccentric correlation.

[[RESULTS]]
The analysis of the data from the period 2004 to 2021 revealed a strikingly high correlation coefficient of 0.9480388 between butter consumption and wind power generation in Lithuania. This finding suggests a robust statistical relationship between these two seemingly unrelated variables.
Furthermore, the calculated r-squared value of 0.8987776 indicates that approximately 89.88% of the variation in wind power generation can be explained by the variation in butter consumption. This substantial proportion of explained variation underscores the strength of the association discovered in this investigation.
The p-value of less than 0.01 provides strong evidence against the null hypothesis of no correlation between butter consumption and wind power generation. In other words, it is highly unlikely that the observed relationship between these variables is purely due to chance.
The scatterplot (Fig. 1) visually depicts the strong correlation observed between butter consumption and wind power generation. The data points form a clear pattern, further reinforcing the statistical evidence of a significant association between these seemingly disparate elements of Lithuanian life.
The compelling results of this analysis raise intriguing questions about the potential mechanisms underlying the observed correlation. It beckons us to ponder whether there may be a gustatory or perhaps even an atmospheric influence at play, intertwining the world of creamy indulgence with the airy elegance of wind power generation.
This unexpected nexus of butter consumption and wind power generation in Lithuania not only challenges conventional wisdom but also adds a touch of whimsy to the realm of empirical research. It is a reminder that even the most unlikely pairings can unveil intriguing insights, akin to discovering a gust of wind carrying the faint scent of freshly churned butter.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of the current study provide substantial support for prior research that has explored the interrelation of dietary habits and energy production. The findings of Smith et al. (2010) and Doe and Jones (2015), although focused on different types of dairy consumption and renewable energy sources, have laid a crucial groundwork for our investigation. While these studies may not have directly examined the specific association between butter consumption and wind power generation, they have established a conceptual framework for considering the potential impact of dairy products on sustainable energy.

Furthermore, the literary works cited in the literature review, particularly "The Wind-Up Bird Chronicle" by Haruki Murakami and "Going Postal" by Terry Pratchett, lend an intriguingly imaginative perspective to our understanding of the relationship between butter consumption and wind power generation. Though these references may be seemingly tangential to conventional scholarly discourse, they provoke contemplation regarding metaphorical and symbolic resonances that may imbue this unconventional correlation.

The presence of the enigmatic tweet by @DairyDreamer alludes to a broader public fascination with the mystical implications of butter consumption on renewable energy, emphasizing the resonance of this unusual nexus across various spheres of discourse.

The strong correlation coefficient and r-squared value derived from our analysis are indicative of a robust statistical relationship between butter consumption and wind power generation in Lithuania. The compelling scatterplot visually portrays the coherent pattern formed by the data points, further consolidating the evidence of an unexpected yet significant association. The p-value of less than 0.01 dismisses the possibility of a chance relationship between these variables, underscoring the substantial support for the hypothesis of a genuine connection.

The findings of this study highlight the whimsical interconnectedness of apparently unrelated domains, offering a striking illustration of the marvels of empirical inquiry. The extent to which butter consumption may influence wind power generation prompts contemplation on the potentially multifaceted impact of dietary habits on sustainability.

In conclusion, the current investigation not only bolsters the emerging body of research on the intersection between food consumption and energy production but also injects a welcome note of unanticipated quirkiness into the scientific discourse. This synthesis of empirical evidence and lighthearted contemplation leaves us, quite fittingly, with a gust of fresh insight and a hint of savory delight.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.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 Lithuania. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
Stirring Up a Storm: Exploring the Correlation Between Butter Consumption and Wind Power Generation in Lithuania

[[ABSTRACT]]
This study delves into the rich and surprisingly gusty world of butter consumption and wind power generation in Lithuania, unraveling a nexus that has gone unnoticed in the annals of scholarly inquiry. By leveraging data from the USDA and the Energy Information Administration for the period spanning from 2004 to 2021, we have meticulously scrutinized the oft-overlooked relationship between these two seemingly disparate facets of human existence.

Our analysis has yielded compelling results, revealing a striking correlation coefficient of 0.9480388, with a p-value of less than 0.01. This robust statistical association prompts one to ponder whether there may be more to the gustatory habits of the Lithuanian populace than meets the eye. The findings of this investigation not only underscore the potential impact of butter consumption on wind power generation but also serve as a potent reminder of the whimsical interconnectedness of socio-economic phenomena.

As we delve into the gustatory delights and sustainable energy sources of Lithuania, this study illuminates a fresh perspective, quite literally and figuratively, on the dynamics that underpin these seemingly unrelated domains. The wind of change may indeed carry a whisper of creamy indulgence.

[[INTRDUCTION]]
The seemingly unrelated domains of butter consumption and wind power generation in Lithuania have captured the curiosity of researchers and laypersons alike. While butter has long been a staple in Lithuanian cuisine, the utilization of wind power as a renewable energy source has been on the rise in the country in recent years. However, the potential correlation between these two distinct phenomena has been shrouded in mystery, much like the swirling gusts of wind that characterize the Lithuanian landscape.
As we embark on this journey of discovery, it is important to acknowledge the lighthearted allure of investigating a link between a dairy product and a form of sustainable energy. Indeed, the implications of such a correlation could churn the very foundations of our understanding of consumer behavior and its unsuspected consequences on environmental factors. This investigation may also offer a breath of fresh air in the often staid and serious realm of empirical research, reminding us that scientific inquiry can encompass the whimsy and wonder of everyday existence.
While the initial premise of this study may appear to be as light and airy as a buttery puff pastry, the statistical rigor applied to our analysis elevates its significance to a level of scientific inquiry. By delving into the data with mathematical precision, we aim to shed light on the potential influence of butter consumption on the generation of wind power, teasing out the nuanced interplay of gustatory habits and sustainable energy production.
Join us as we unfold the layers of this unique investigation, blending the richness of statistical analysis with the breezy allure of wind power and the delectable allure of butter in a manner that could colloquially be described as "churning out" unexpected connections. The winds of change may indeed carry a whisper of creamy indulgence, and we invite you to savor the scientific journey that lies ahead.

[[RESULTS]]
The analysis of the data from the period 2004 to 2021 revealed a strikingly high correlation coefficient of 0.9480388 between butter consumption and wind power generation in Lithuania. This finding suggests a robust statistical relationship between these two seemingly unrelated variables.
Furthermore, the calculated r-squared value of 0.8987776 indicates that approximately 89.88% of the variation in wind power generation can be explained by the variation in butter consumption. This substantial proportion of explained variation underscores the strength of the association discovered in this investigation.
The p-value of less than 0.01 provides strong evidence against the null hypothesis of no correlation between butter consumption and wind power generation. In other words, it is highly unlikely that the observed relationship between these variables is purely due to chance.
The scatterplot (Fig. 1) visually depicts the strong correlation observed between butter consumption and wind power generation. The data points form a clear pattern, further reinforcing the statistical evidence of a significant association between these seemingly disparate elements of Lithuanian life.
The compelling results of this analysis raise intriguing questions about the potential mechanisms underlying the observed correlation. It beckons us to ponder whether there may be a gustatory or perhaps even an atmospheric influence at play, intertwining the world of creamy indulgence with the airy elegance of wind power generation.
This unexpected nexus of butter consumption and wind power generation in Lithuania not only challenges conventional wisdom but also adds a touch of whimsy to the realm of empirical research. It is a reminder that even the most unlikely pairings can unveil intriguing insights, akin to discovering a gust of wind carrying the faint scent of freshly churned butter.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation has unfurled a gusty, yet velvety relationship between butter consumption and wind power generation in Lithuania, shedding light on an unexpected fusion of culinary indulgence and sustainable energy production. The robust statistical association, with a striking correlation coefficient of 0.9480388 and a p-value of less than 0.01, has left us churning with excitement about the unexpected interconnectedness of these seemingly disparate variables. The r-squared value of 0.8987776 serves as a stark reminder that, much like a well-whipped batter, approximately 89.88% of the variation in wind power generation can be attributed to the ebb and flow of butter consumption.

The scatterplot (Fig. 1) paints a picture as clear as a sunny day in the Baltic, illustrating the undeniable pattern between butter consumption and wind power generation. These findings not only push the boundaries of scientific inquiry but also imbue our understanding of socio-economic phenomena with a touch of creamy whimsy.

As we bid adieu to our exploration of Lithuanian gustatory and gustatory indulgence, we find ourselves stirred, not shaken, by the ramifications of this unexpected discovery. The winds of change may indeed carry a subtle aroma of freshly churned butter, infusing even the most serious of research endeavors with a hint of playfulness.

Ultimately, our findings invite us to savor the unanticipated connections that emerge from meticulous inquiry, while also acknowledging the "butterfly effect" of seemingly mundane variables on complex systems. In light of these compelling results, we assert that further research in this area is unnecessary, as the creamy influence of butter consumption on the generation of wind power has been tangibly, and deliciously, established.

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 Stirring Up a Storm: Exploring the Correlation Between Butter Consumption and Wind Power Generation in Lithuania. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Sustainable Dairy and Renewable Energy

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 Stirring Up a Storm: Exploring the Correlation Between Butter Consumption and Wind Power Generation in Lithuania. Respond only with the name of a fictional organization.

ChatGPT:

The International Association for Dairy Dynamics 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 Stirring Up a Storm: Exploring the Correlation Between Butter Consumption and Wind Power Generation in Lithuania with an abstract of This study delves into the rich and surprisingly gusty world of butter consumption and wind power generation in Lithuania, unraveling a nexus that has gone unnoticed in the annals of scholarly inquiry. By leveraging data from the USDA and the Energy Information Administration for the period spanning from 2004 to 2021, we have meticulously scrutinized the oft-overlooked relationship between these two seemingly disparate facets of human existence.
Our analysis has yielded compelling results, revealing a striking correlation coefficient of 0.9480388, with a p-value of less than 0.01. This robust statistical association prompts one to ponder whether there may be more to the gustatory habits of the Lithuanian populace than meets the eye. The findings of this investigation not only underscore the potential impact of butter consumption on wind power generation but also serve as a potent reminder of the whimsical interconnectedness of socio-economic phenomena.
As we delve into the gustatory delights and sustainable energy sources of Lithuania, this study illuminates a fresh perspective, quite literally and figuratively, on the dynamics that underpin these seemingly unrelated domains. The wind of change may indeed carry a whisper of creamy indulgence.

ChatGPT:

butter consumption, wind power generation, Lithuania, correlation, USDA data, Energy Information Administration, statistical analysis, gustatory habits, socio-economic phenomena, sustainable energy sources, Lithuanian populace

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

Random correlation

Discover a new correlation

View all correlations

View all research papers

Report an error

Data details

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

Correlation r = 0.9480388 (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 = 0.8987776 (Coefficient of determination)
This means 89.9% of the change in the one variable (i.e., Wind power generated in Lithuania) is predictable based on the change in the other (i.e., Butter consumption) over the 18 years from 2004 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.3E-9.^Show 0.0000000022688413472827607000
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 2.3E-7% of random cases. Said differently, if you correlated 440,753,604 random variables^Note You don't actually need 440 million 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 17 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 17 because we have two variables measured over a period of 18 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.

[ 0.86, 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.

	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Butter consumption (Pounds per person)	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 Lithuania (Billion kWh)	0.001	0.002	0.014	0.106	0.131	0.158	0.222996	0.473	0.537	0.6	0.636001	0.805999	1.13	1.3562	1.1375	1.4901	1.49148	1.35423

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.
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([4.5,4.5,4.7,4.7,5,5,4.9,5.4,5.5,5.5,5.5,5.6,5.7,5.7,6,6.2,6.3,6.5,])
array_2 = np.array([0.001,0.002,0.014,0.106,0.131,0.158,0.222996,0.473,0.537,0.6,0.636001,0.805999,1.13,1.3562,1.1375,1.4901,1.49148,1.35423,])
array_1_name = "Butter consumption"
array_2_name = "Wind power generated in Lithuania"

# 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 Lithuania
AI-generated correlation image
The spurious research paper: Stirring Up a Storm: Exploring the Correlation Between Butter Consumption and Wind Power Generation in Lithuania

View another random correlation

How fun was this correlation?

Your dedication to rating warms my heart!

Correlation ID: 1362 · Black Variable ID: 557 · Red Variable ID: 23795


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