Download png, svg
AI explanation
As the number of breweries in the United States increased, there was a proportional rise in the production of beer. This led to a higher demand for barley, which was predominantly sourced from Belize. The extensive farming and transportation of barley in Belize required a substantial amount of fossil fuels. Additionally, the fizzy fun of American craft beer led to a surge in exports to Belize, further augmenting the need for shipping and consequently, an uptick in fossil fuel use. So, it turns out, the American love for craft beer not only brewed up a storm in the US, but also inadvertently fueled Belize's dependency on fossil fuels. Cheers to unexpected international beverage shenanigans!
Model: dalle-3
Prompt: Generate an image that seamlessly blends a bustling street in the United States, filled with lively breweries and throngs of people, with a serene beach in Belize gradually overwhelmed by an increasing number of planes landing, symbolizing a surge in fossil fuel usage as visitors flock to enjoy the beautiful seaside with refreshing beverages. The image should convey the stark contrast between the urban and natural environments, capturing the essence of dynamic societal choices and their impact on the environment. The scene should be rich in detail and depth, evoking a sense of awe and reflection. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.
This image generation prompt was also generated by AI, using the following sequence:
Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: The number of Breweries in the United States and Fossil fuel use in Belize. 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: Vaporwave Sci-fi fantacy A photo-realistic image a Polaroid photo Cubism
ChatGPT: A photo-realistic 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 The number of Breweries in the United States and Fossil fuel use in Belize, in the following situation: Because as the number of breweries in the United States increased, so did the demand for beer. This led to more people hopping on planes to Belize for vacation, resulting in a surge in fossil fuel use as they traveled to enjoy a cold one on the beach. Cheers to unintentional environmental impact!. Keep the description simple.
ChatGPT: A bustling street in the United States, lined with numerous breweries, serving crowds of people. Meanwhile, a beach in Belize, with an increasing number of planes arriving, contributing to a spike in fossil fuel use as visitors flock to enjoy the beautiful seaside with an ice-cold beer in hand.
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 photo-realistic image ] and depicting this scene: A bustling street in the United States, lined with numerous breweries, serving crowds of people. Meanwhile, a beach in Belize, with an increasing number of planes arriving, contributing to a spike in fossil fuel use as visitors flock to enjoy the beautiful seaside with an ice-cold beer in hand. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that seamlessly blends a bustling street in the United States, filled with lively breweries and throngs of people, with a serene beach in Belize gradually overwhelmed by an increasing number of planes landing, symbolizing a surge in fossil fuel usage as visitors flock to enjoy the beautiful seaside with refreshing beverages. The image should convey the stark contrast between the urban and natural environments, capturing the essence of dynamic societal choices and their impact on the environment. The scene should be rich in detail and depth, evoking a sense of awe and reflection.
*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.
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in The number of Breweries in the United States caused Fossil fuel use in Belize to increase.\Make it sound serious until the end.
AI academic paper
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Ale-ing Economies: An Analysis of the Relationship Between Brewery Boom in the United States and Fossil Fuel Use in Belize The Frothy Economist Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
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, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between The number of Breweries in the United States and Fossil fuel use in Belize. Make lots of jokes, goofy observations, and puns.
Make the title punny if you can come up with clever pun. If not, make it sound serious.
Your research team used data from Brewers Association and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.8851443 and p < 0.01 for 1990 to 2021.
Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)
[[TITLE]]
Lorem ipsum dolor sit
[[ABSTRACT]]
Lorem ipsum dolor sit
ChatGPT:
[[TITLE]]
Ale-ing Economies: An Analysis of the Relationship Between Brewery Boom in the United States and Fossil Fuel Use in Belize
[[ABSTRACT]]
This study presents a quirky yet insightful exploration of the seemingly unrelated phenomena of the proliferation of breweries in the United States and the fossil fuel consumption in Belize. Drawing on data from the Brewers Association and the Energy Information Administration, we employed statistical analysis to uncover a surprising connection. Our findings revealed a remarkably high correlation coefficient of 0.8851443 and a significance level of p < 0.01 for the period from 1990 to 2021. To our amusement, it seems that as the number of breweries in the U.S. has been fermenting, there has been a distinctively parallel spike in fossil fuel use in Belize. This paper dissects the peculiar dynamics between these two seemingly disparate trends, offering theoretical and practical implications that might just brew up some interest in unconventional economic analyses. Cheers to the unexpected intercontinental linkages in the world of data!
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the introduction 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 introduction section of an academic research paper presenting the findings of the connection between The number of Breweries in the United States and Fossil fuel use in Belize. Make lots of jokes, goofy observations, and puns.
Here is the title and abstract of the paper:
[[TITLE]]
Ale-ing Economies: An Analysis of the Relationship Between Brewery Boom in the United States and Fossil Fuel Use in Belize
[[ABSTRACT]]
This study presents a quirky yet insightful exploration of the seemingly unrelated phenomena of the proliferation of breweries in the United States and the fossil fuel consumption in Belize. Drawing on data from the Brewers Association and the Energy Information Administration, we employed statistical analysis to uncover a surprising connection. Our findings revealed a remarkably high correlation coefficient of 0.8851443 and a significance level of p < 0.01 for the period from 1990 to 2021. To our amusement, it seems that as the number of breweries in the U.S. has been fermenting, there has been a distinctively parallel spike in fossil fuel use in Belize. This paper dissects the peculiar dynamics between these two seemingly disparate trends, offering theoretical and practical implications that might just brew up some interest in unconventional economic analyses. Cheers to the unexpected intercontinental linkages in the world of data!
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
Ah, the tantalizing intersection of hops and hydrocarbons! In a world brimming with perplexing connections, our research sets out to unravel the curious correlation between the meteoric rise of breweries in the United States and the bubbling surge in fossil fuel use in the tropical haven of Belize. It's a tale of beer bubbles and fuel fumes, of pint glasses and CO2 emissions, where statistical analysis meets sudsy speculation.
As we delve into this frothy study, one might be inclined to raise an eyebrow and question the sanity of investigating such seemingly unrelated phenomena. After all, what could craft beer aficionados in Portland have to do with petrol-pumping activities in Punta Gorda? But fear not, dear reader, for this is where the curtain rises on a spectacle of statistical serendipity and economic enigma.
The premise of our investigation stems from an epiphany of sorts – a peculiar observation that led us down this convoluted path. With data in hand from the Brewers Association and the Energy Information Administration, we embarked on an academic journey that seemed as improbable as a lager-loving lemur. Yet, equipped with the tools of regression analysis and p-values, we sought to uncover the hidden ties that bind these disparate undertakings.
As we wade into the mirthful depths of this research, it becomes increasingly apparent that the world of data is not as sober as it appears. Our initial findings unveiled a correlation coefficient of 0.8851443 – a figure so tight, it could rival the grip of a determined beer stein enthusiast. Paired with a significance level of p < 0.01, the evidence had us brimming with giddy disbelief. Could it be that the ebb and flow of breweries in the land of the free was somehow synchronizing with the fuel-draining path of our Caribbean compatriots?
With each turn of the data, the narrative took on a life of its own. It seemed as though the hops and the fuel were engaged in a clandestine dance, moving in harmonious M.C. Escher-like patterns that left our academic sensibilities both delighted and dazed. We were reminded of that age-old adage, "In statistics, correlation does not imply causation – but my, oh my, doesn't it leave plenty of room for whimsical speculation?"
So, fellow scholars and mirth-seeking wizards of the esoteric, buckle up for an intellectual adventure that promises to regale you with insights both unexpected and improbable. As we unravel the curious linkages between brew-inducing activities and fossil fuel consumption, let us toast to the bewitching marvels of the world of data and the capricious connections it unveils. Cheers to the serendipity of statistical singularity, and here's to savoring the unconventional intrigue of intercontinental economic oddities!
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a literature review section of an academic research paper presenting the findings of the connection between The number of Breweries in the United States and Fossil fuel use in Belize. Make lots of jokes, goofy observations, and puns.
Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.
Make up the lorem and ipsum part, but make it sound related to the topic at hand.
Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then cite some social media posts you read that seem to be related.
Here is the title and abstract of the paper:
[[TITLE]]
Ale-ing Economies: An Analysis of the Relationship Between Brewery Boom in the United States and Fossil Fuel Use in Belize
[[ABSTRACT]]
This study presents a quirky yet insightful exploration of the seemingly unrelated phenomena of the proliferation of breweries in the United States and the fossil fuel consumption in Belize. Drawing on data from the Brewers Association and the Energy Information Administration, we employed statistical analysis to uncover a surprising connection. Our findings revealed a remarkably high correlation coefficient of 0.8851443 and a significance level of p < 0.01 for the period from 1990 to 2021. To our amusement, it seems that as the number of breweries in the U.S. has been fermenting, there has been a distinctively parallel spike in fossil fuel use in Belize. This paper dissects the peculiar dynamics between these two seemingly disparate trends, offering theoretical and practical implications that might just brew up some interest in unconventional economic analyses. Cheers to the unexpected intercontinental linkages in the world of data!
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Ah, the tantalizing intersection of hops and hydrocarbons! In a world brimming with perplexing connections, our research sets out to unravel the curious correlation between the meteoric rise of breweries in the United States and the bubbling surge in fossil fuel use in the tropical haven of Belize. It's a tale of beer bubbles and fuel fumes, of pint glasses and CO2 emissions, where statistical analysis meets sudsy speculation.
As we delve into this frothy study, one might be inclined to raise an eyebrow and question the sanity of investigating such seemingly unrelated phenomena. After all, what could craft beer aficionados in Portland have to do with petrol-pumping activities in Punta Gorda? But fear not, dear reader, for this is where the curtain rises on a spectacle of statistical serendipity and economic enigma.
The premise of our investigation stems from an epiphany of sorts – a peculiar observation that led us down this convoluted path. With data in hand from the Brewers Association and the Energy Information Administration, we embarked on an academic journey that seemed as improbable as a lager-loving lemur. Yet, equipped with the tools of regression analysis and p-values, we sought to uncover the hidden ties that bind these disparate undertakings.
As we wade into the mirthful depths of this research, it becomes increasingly apparent that the world of data is not as sober as it appears. Our initial findings unveiled a correlation coefficient of 0.8851443 – a figure so tight, it could rival the grip of a determined beer stein enthusiast. Paired with a significance level of p < 0.01, the evidence had us brimming with giddy disbelief. Could it be that the ebb and flow of breweries in the land of the free was somehow synchronizing with the fuel-draining path of our Caribbean compatriots?
With each turn of the data, the narrative took on a life of its own. It seemed as though the hops and the fuel were engaged in a clandestine dance, moving in harmonious M.C. Escher-like patterns that left our academic sensibilities both delighted and dazed. We were reminded of that age-old adage, "In statistics, correlation does not imply causation – but my, oh my, doesn't it leave plenty of room for whimsical speculation?"
So, fellow scholars and mirth-seeking wizards of the esoteric, buckle up for an intellectual adventure that promises to regale you with insights both unexpected and improbable. As we unravel the curious linkages between brew-inducing activities and fossil fuel consumption, let us toast to the bewitching marvels of the world of data and the capricious connections it unveils. Cheers to the serendipity of statistical singularity, and here's to savoring the unconventional intrigue of intercontinental economic oddities!
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
In "A Macrobrewed Perspective: Economic Implications of the Brewery Renaissance" by Smith, the authors find that the resurgence of breweries in the United States has contributed to job creation, tourism, and a thriving craft beer industry. Meanwhile, in "Fuel Fumes and the Belizean Dream: A Fossil Fuel Odyssey" by Jones, the authors delve into the complex web of factors influencing fossil fuel use in Belize, including economic development, infrastructure, and environmental policies.
Now, let us take a turn from the scholarly to the whimsical as we consider an assortment of writings that, upon first glance, reside outside the realm of academic rigidity. In the book "The Brewmaster's Tale" by Doe, the author weaves a captivating narrative on the intricate art of beer-making, but sprinkled amongst the malts and hops, a subtle commentary on economic forces emerges. Similarly, "Fueling the Fire: A Belizean Adventure" by Greene follows the escapades of a daring eco-warrior battling the perils of fossil fuels in the heart of Central America.
In the world of fiction, one might stumble upon tales that, curiously enough, seem to resonate with our unlikely pair of interests. Consider the enigmatic novel "Brews, Boats, and Belize" by Hemingway, whose prose captures the essence of coastal livelihoods, hinting at the interconnectedness of cultural preservation and economic flux. Or how about J.K. Rowling's "Harry Hops and the Goblet of Grains," where the wizarding community's penchant for butterbeer mirrors our societal embrace of craft brews, with a twist of fantastical delight.
In the realm of social media, a Twitter post by @BelizeBrews beckons us to ponder the environmental ramifications of our choice in libations: "Craft beer may be trendy, but let's not forget the ecological impact. Is it mere froth or a potent force for change?" On the flip side, @FuelFreaks_USA chimes in with a seemingly unrelated quip: "Fill 'er up and let's fuel our way to economic prosperity! #PumpItUp #FuelForThought."
As we wade through this literary menagerie, it becomes clear that the connection between the number of breweries in the United States and fossil fuel use in Belize is a topic that transcends the conventional boundaries of academic inquiry. The tapestry of influences that shape our global economic landscape seems to be interwoven with whimsical threads of unexpected correlation, leaving us to ponder the peculiar dances of supply and demand, libations and emissions. So, dear readers, prepare to imbibe not only in the nectar of knowledge but also in the frothy and convoluted effervescence of this scholarly escapade. Cheers to scholarly serendipity!
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the methodology section of an academic research paper presenting the findings of the connection between The number of Breweries in the United States and Fossil fuel use in Belize. Make lots of jokes, goofy observations, and puns.
Your research team collected data from all across the internet, but mostly just used information from Brewers Association and Energy Information Administration . You used data from 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]]
Ale-ing Economies: An Analysis of the Relationship Between Brewery Boom in the United States and Fossil Fuel Use in Belize
[[ABSTRACT]]
This study presents a quirky yet insightful exploration of the seemingly unrelated phenomena of the proliferation of breweries in the United States and the fossil fuel consumption in Belize. Drawing on data from the Brewers Association and the Energy Information Administration, we employed statistical analysis to uncover a surprising connection. Our findings revealed a remarkably high correlation coefficient of 0.8851443 and a significance level of p < 0.01 for the period from 1990 to 2021. To our amusement, it seems that as the number of breweries in the U.S. has been fermenting, there has been a distinctively parallel spike in fossil fuel use in Belize. This paper dissects the peculiar dynamics between these two seemingly disparate trends, offering theoretical and practical implications that might just brew up some interest in unconventional economic analyses. Cheers to the unexpected intercontinental linkages in the world of data!
[[INTRODUCTION]]
Ah, the tantalizing intersection of hops and hydrocarbons! In a world brimming with perplexing connections, our research sets out to unravel the curious correlation between the meteoric rise of breweries in the United States and the bubbling surge in fossil fuel use in the tropical haven of Belize. It's a tale of beer bubbles and fuel fumes, of pint glasses and CO2 emissions, where statistical analysis meets sudsy speculation.
As we delve into this frothy study, one might be inclined to raise an eyebrow and question the sanity of investigating such seemingly unrelated phenomena. After all, what could craft beer aficionados in Portland have to do with petrol-pumping activities in Punta Gorda? But fear not, dear reader, for this is where the curtain rises on a spectacle of statistical serendipity and economic enigma.
The premise of our investigation stems from an epiphany of sorts – a peculiar observation that led us down this convoluted path. With data in hand from the Brewers Association and the Energy Information Administration, we embarked on an academic journey that seemed as improbable as a lager-loving lemur. Yet, equipped with the tools of regression analysis and p-values, we sought to uncover the hidden ties that bind these disparate undertakings.
As we wade into the mirthful depths of this research, it becomes increasingly apparent that the world of data is not as sober as it appears. Our initial findings unveiled a correlation coefficient of 0.8851443 – a figure so tight, it could rival the grip of a determined beer stein enthusiast. Paired with a significance level of p < 0.01, the evidence had us brimming with giddy disbelief. Could it be that the ebb and flow of breweries in the land of the free was somehow synchronizing with the fuel-draining path of our Caribbean compatriots?
With each turn of the data, the narrative took on a life of its own. It seemed as though the hops and the fuel were engaged in a clandestine dance, moving in harmonious M.C. Escher-like patterns that left our academic sensibilities both delighted and dazed. We were reminded of that age-old adage, "In statistics, correlation does not imply causation – but my, oh my, doesn't it leave plenty of room for whimsical speculation?"
So, fellow scholars and mirth-seeking wizards of the esoteric, buckle up for an intellectual adventure that promises to regale you with insights both unexpected and improbable. As we unravel the curious linkages between brew-inducing activities and fossil fuel consumption, let us toast to the bewitching marvels of the world of data and the capricious connections it unveils. Cheers to the serendipity of statistical singularity, and here's to savoring the unconventional intrigue of intercontinental economic oddities!
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
We must confess, the methodology for this research endeavor could be likened to a finely crafted ale – a blend of precision, quirk, and just a touch of whimsy. To distill the relationship between breweries in the United States and fossil fuel use in Belize, we embarked on a data-gathering quest that rivaled the obscurity of tracking down the rarest of brews or the most elusive fossil fuels.
Data Collection:
Our intrepid research team scoured the digital plains, traversing the vast expanses of the internet like modern-day data prospectors. From the boisterous bazaars of the Brewers Association to the fuel-laden archives of the Energy Information Administration, we sought to unearth the veiled connections brewing beneath the surface of statistical obscurity.
Brewery Census:
In a feat reminiscent of conducting a census for a kingdom of ale, we meticulously documented the annual proliferation of breweries across the United States. This involved navigating a labyrinth of beer enthusiasts, hop farmers, brewmasters, and festive beer festivals – a process that brought new meaning to the term "bar hopping."
Fossil Fuel Forensics:
Meanwhile, our foray into the realm of fossil fuel use in Belize resembled a spirited detective adventure. We tracked down the elusive machinations of hydrocarbon consumption, piecing together the enigmatic puzzle of petroleum, gasoline, and the exotic allure of diesel in the resplendent landscapes of this tropical paradise.
Statistical Elixirs:
Armed with the arcane tools of regressions, hypothesis testing, and the occasional statistical incantation, we set out to distill meaning from this eclectic brew of data. We meticulously stirred the frothy amalgamation of datasets to reveal the underlying patterns that tied the seemingly unbound, like a maestro conducting an orchestra of ale and octane.
Quantitative Brews and Qualitative Quips:
As we juggled gamma distributions and t-distributions, we couldn't help but indulge in the occasional lighthearted quip to keep the fervor of academic inquiry alight. After all, who said statistical analysis couldn't be seasoned with a pinch of levity now and then?
Ultimately, our methodology embodies the spirit of empirical inquiry, seasoned with the playful zest of scholarly merriment. With the alchemy of data collection, statistical fortitude, and the occasional jest, we endeavored to unravel the enigmatic connection between the rise of breweries in the U.S. and the fuel-fueled reveries of Belize.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 The number of Breweries in the United States and Fossil fuel use in Belize. Make lots of jokes, goofy observations, and puns.
Your research team collected data from all across the internet, but mostly just used information from Brewers Association and Energy Information Administration .
For the time period 1990 to 2021, you found a correlation 0.8851443, r-squared of 0.7834804, 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]]
Ale-ing Economies: An Analysis of the Relationship Between Brewery Boom in the United States and Fossil Fuel Use in Belize
[[ABSTRACT]]
This study presents a quirky yet insightful exploration of the seemingly unrelated phenomena of the proliferation of breweries in the United States and the fossil fuel consumption in Belize. Drawing on data from the Brewers Association and the Energy Information Administration, we employed statistical analysis to uncover a surprising connection. Our findings revealed a remarkably high correlation coefficient of 0.8851443 and a significance level of p < 0.01 for the period from 1990 to 2021. To our amusement, it seems that as the number of breweries in the U.S. has been fermenting, there has been a distinctively parallel spike in fossil fuel use in Belize. This paper dissects the peculiar dynamics between these two seemingly disparate trends, offering theoretical and practical implications that might just brew up some interest in unconventional economic analyses. Cheers to the unexpected intercontinental linkages in the world of data!
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
Ah, the tantalizing intersection of hops and hydrocarbons! In a world brimming with perplexing connections, our research sets out to unravel the curious correlation between the meteoric rise of breweries in the United States and the bubbling surge in fossil fuel use in the tropical haven of Belize. It's a tale of beer bubbles and fuel fumes, of pint glasses and CO2 emissions, where statistical analysis meets sudsy speculation.
As we delve into this frothy study, one might be inclined to raise an eyebrow and question the sanity of investigating such seemingly unrelated phenomena. After all, what could craft beer aficionados in Portland have to do with petrol-pumping activities in Punta Gorda? But fear not, dear reader, for this is where the curtain rises on a spectacle of statistical serendipity and economic enigma.
The premise of our investigation stems from an epiphany of sorts – a peculiar observation that led us down this convoluted path. With data in hand from the Brewers Association and the Energy Information Administration, we embarked on an academic journey that seemed as improbable as a lager-loving lemur. Yet, equipped with the tools of regression analysis and p-values, we sought to uncover the hidden ties that bind these disparate undertakings.
As we wade into the mirthful depths of this research, it becomes increasingly apparent that the world of data is not as sober as it appears. Our initial findings unveiled a correlation coefficient of 0.8851443 – a figure so tight, it could rival the grip of a determined beer stein enthusiast. Paired with a significance level of p < 0.01, the evidence had us brimming with giddy disbelief. Could it be that the ebb and flow of breweries in the land of the free was somehow synchronizing with the fuel-draining path of our Caribbean compatriots?
With each turn of the data, the narrative took on a life of its own. It seemed as though the hops and the fuel were engaged in a clandestine dance, moving in harmonious M.C. Escher-like patterns that left our academic sensibilities both delighted and dazed. We were reminded of that age-old adage, "In statistics, correlation does not imply causation – but my, oh my, doesn't it leave plenty of room for whimsical speculation?"
So, fellow scholars and mirth-seeking wizards of the esoteric, buckle up for an intellectual adventure that promises to regale you with insights both unexpected and improbable. As we unravel the curious linkages between brew-inducing activities and fossil fuel consumption, let us toast to the bewitching marvels of the world of data and the capricious connections it unveils. Cheers to the serendipity of statistical singularity, and here's to savoring the unconventional intrigue of intercontinental economic oddities!
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The statistical analysis of the data collected from the Brewers Association and the Energy Information Administration yielded staggering results that left our research team both impressed and scratching our heads in amusement. The correlation coefficient of 0.8851443 between the number of breweries in the United States and fossil fuel consumption in Belize was as striking as finding a four-leaf clover in a barley field.
Furthermore, the r-squared value of 0.7834804 underscored the robustness of the relationship between these seemingly disparate variables, akin to the strong bond between a beer enthusiast and their favorite local brewpub. Not to mention, the significance level of p < 0.01 emphatically captured our attention, resembling the crisp pop of a bottle cap being liberated from its stronghold.
To visually encapsulate this peculiar correlation, we present Fig. 1, a scatterplot that vividly portrays the undeniable synchrony between the proliferation of breweries in the U.S. and the uptick in fossil fuel consumption in Belize. Behold the dance of data points, where each brewery seems to whisper, "Raise a glass," and each fossil fuel unit murmurs, "Let's fuel the flame," in a harmonious, though enigmatic, duet.
In light of these findings, our minds inevitably wander to ponder the uncharted territory of interconnected economic oddities. Could it be that the frothy effervescence of the American craft beer scene exerts a gravitational pull on the fossil fuel trajectories of faraway lands, or is this simply a statistical serendipity, akin to finding a hop cone in the hop-shaped constellation of Humulus lupulus?
Regardless of the underlying mechanism, these results beckon us to embrace the whimsical nature of economic analysis. From a scientific standpoint, this correlation serves as a call to unorthodox inquiry and an embodiment of the notion that the world of data is rife with surprises, not unlike the suspense of cracking open a bottle-conditioned brew. Indeed, as we raise a glass to these unexpected intercontinental linkages, let us toast to the capricious and intriguing nature of statistical phenomena. Cheers to the unconventional, and here's to embracing the playful dance of data in all its serendipitous splendor!
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the discussion section of an academic research paper presenting the findings of the connection between The number of Breweries in the United States and Fossil fuel use in Belize. Make lots of 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]]
Ale-ing Economies: An Analysis of the Relationship Between Brewery Boom in the United States and Fossil Fuel Use in Belize
[[ABSTRACT]]
This study presents a quirky yet insightful exploration of the seemingly unrelated phenomena of the proliferation of breweries in the United States and the fossil fuel consumption in Belize. Drawing on data from the Brewers Association and the Energy Information Administration, we employed statistical analysis to uncover a surprising connection. Our findings revealed a remarkably high correlation coefficient of 0.8851443 and a significance level of p < 0.01 for the period from 1990 to 2021. To our amusement, it seems that as the number of breweries in the U.S. has been fermenting, there has been a distinctively parallel spike in fossil fuel use in Belize. This paper dissects the peculiar dynamics between these two seemingly disparate trends, offering theoretical and practical implications that might just brew up some interest in unconventional economic analyses. Cheers to the unexpected intercontinental linkages in the world of data!
[[LITERATURE REVIEW]]
In "A Macrobrewed Perspective: Economic Implications of the Brewery Renaissance" by Smith, the authors find that the resurgence of breweries in the United States has contributed to job creation, tourism, and a thriving craft beer industry. Meanwhile, in "Fuel Fumes and the Belizean Dream: A Fossil Fuel Odyssey" by Jones, the authors delve into the complex web of factors influencing fossil fuel use in Belize, including economic development, infrastructure, and environmental policies.
Now, let us take a turn from the scholarly to the whimsical as we consider an assortment of writings that, upon first glance, reside outside the realm of academic rigidity. In the book "The Brewmaster's Tale" by Doe, the author weaves a captivating narrative on the intricate art of beer-making, but sprinkled amongst the malts and hops, a subtle commentary on economic forces emerges. Similarly, "Fueling the Fire: A Belizean Adventure" by Greene follows the escapades of a daring eco-warrior battling the perils of fossil fuels in the heart of Central America.
In the world of fiction, one might stumble upon tales that, curiously enough, seem to resonate with our unlikely pair of interests. Consider the enigmatic novel "Brews, Boats, and Belize" by Hemingway, whose prose captures the essence of coastal livelihoods, hinting at the interconnectedness of cultural preservation and economic flux. Or how about J.K. Rowling's "Harry Hops and the Goblet of Grains," where the wizarding community's penchant for butterbeer mirrors our societal embrace of craft brews, with a twist of fantastical delight.
In the realm of social media, a Twitter post by @BelizeBrews beckons us to ponder the environmental ramifications of our choice in libations: "Craft beer may be trendy, but let's not forget the ecological impact. Is it mere froth or a potent force for change?" On the flip side, @FuelFreaks_USA chimes in with a seemingly unrelated quip: "Fill 'er up and let's fuel our way to economic prosperity! #PumpItUp #FuelForThought."
As we wade through this literary menagerie, it becomes clear that the connection between the number of breweries in the United States and fossil fuel use in Belize is a topic that transcends the conventional boundaries of academic inquiry. The tapestry of influences that shape our global economic landscape seems to be interwoven with whimsical threads of unexpected correlation, leaving us to ponder the peculiar dances of supply and demand, libations and emissions. So, dear readers, prepare to imbibe not only in the nectar of knowledge but also in the frothy and convoluted effervescence of this scholarly escapade. Cheers to scholarly serendipity!
[[RESULTS]]
The statistical analysis of the data collected from the Brewers Association and the Energy Information Administration yielded staggering results that left our research team both impressed and scratching our heads in amusement. The correlation coefficient of 0.8851443 between the number of breweries in the United States and fossil fuel consumption in Belize was as striking as finding a four-leaf clover in a barley field.
Furthermore, the r-squared value of 0.7834804 underscored the robustness of the relationship between these seemingly disparate variables, akin to the strong bond between a beer enthusiast and their favorite local brewpub. Not to mention, the significance level of p < 0.01 emphatically captured our attention, resembling the crisp pop of a bottle cap being liberated from its stronghold.
To visually encapsulate this peculiar correlation, we present Fig. 1, a scatterplot that vividly portrays the undeniable synchrony between the proliferation of breweries in the U.S. and the uptick in fossil fuel consumption in Belize. Behold the dance of data points, where each brewery seems to whisper, "Raise a glass," and each fossil fuel unit murmurs, "Let's fuel the flame," in a harmonious, though enigmatic, duet.
In light of these findings, our minds inevitably wander to ponder the uncharted territory of interconnected economic oddities. Could it be that the frothy effervescence of the American craft beer scene exerts a gravitational pull on the fossil fuel trajectories of faraway lands, or is this simply a statistical serendipity, akin to finding a hop cone in the hop-shaped constellation of Humulus lupulus?
Regardless of the underlying mechanism, these results beckon us to embrace the whimsical nature of economic analysis. From a scientific standpoint, this correlation serves as a call to unorthodox inquiry and an embodiment of the notion that the world of data is rife with surprises, not unlike the suspense of cracking open a bottle-conditioned brew. Indeed, as we raise a glass to these unexpected intercontinental linkages, let us toast to the capricious and intriguing nature of statistical phenomena. Cheers to the unconventional, and here's to embracing the playful dance of data in all its serendipitous splendor!
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Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The findings of this study have imbued us with a newfound appreciation for the intricate dance of global economic forces, where seemingly unrelated trends can converge in a harmonious, if enigmatic, duet. Our results lend empirical support to the prior research that has delved into the delightful, though often peculiar, nuances of the modern economic landscape.
Taking an ale-ing from Smith's "A Macrobrewed Perspective: Economic Implications of the Brewery Renaissance," our study's results corroborate the positive impact of the brewery renaissance in the U.S. on job creation and economic activity. While it may seem as whimsical as a wizard's potion, the proliferation of breweries in the United States appears to have a transcontinental ripple effect that extends to the fossil fuel consumption in Belize. It's as if the economic frothiness of the U.S. craft beer industry radiates across borders, reigniting the flame of fossil fuel consumption in seemingly unanticipated ways.
Additionally, Jones' exploration of the multifaceted factors influencing fossil fuel use in Belize finds a curious parallel in our findings. The undeniable correlation between the number of breweries in the U.S. and fossil fuel consumption in Belize hints at a complex interplay of economic, sociocultural, and possibly even ecological dynamics. This suggests that the whimsical threads of interconnectedness that weave through the global economic tapestry are not merely whimsy, but rather, potent forces shaping the ebb and flow of economic tides.
Drawing from the literary musings that initially seemed a touch outlandish, the unexpected correlation uncovered in our study resonates with the curious interplay between cultural preservation, economic developments, and environmental sustainability in coastal livelihoods. It's as if Hemingway's "Brews, Boats, and Belize" spoke not only of cultural preservation but also hinted at the mirrored rise of craft breweries and fuel consumption, while J.K. Rowling's "Harry Hops and the Goblet of Grains" whimsically foreshadowed the societal embrace of craft brews and the associated impact on international economic trends.
Moving from the literary to the digital world, the seemingly unrelated musings from @BelizeBrews and @FuelFreaks_USA now appear prophetic. Craft beer does indeed have an ecological impact that extends beyond its frothy facade, and fuel consumption does indeed fuel economic prosperity in unexpected ways. The playful banter on Twitter now seems to mirror the unorthodox correlations we have uncovered through statistical analysis, beckoning us to ponder the capricious and intriguing nature of global economic phenomena.
In conclusion, the stimulating findings of this study not only elevate the whimsical nature of economic analysis but also broaden our perspective on the interconnectedness of seemingly unrelated economic trends. As we mull over these gut hops-y findings, let us raise a glass to the delightful capriciousness of economic analyses that brew up unexpected connections and toast to the enigmatic dance of data in all its serendipitous splendor. Cheers to the unconventional, and may we continue to embrace the playful surprises that the world of data has in store for us!
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a short conclusion of an academic research paper presenting the findings of the connection between The number of Breweries in the United States and Fossil fuel use in Belize. Make lots of 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]]
Ale-ing Economies: An Analysis of the Relationship Between Brewery Boom in the United States and Fossil Fuel Use in Belize
[[ABSTRACT]]
This study presents a quirky yet insightful exploration of the seemingly unrelated phenomena of the proliferation of breweries in the United States and the fossil fuel consumption in Belize. Drawing on data from the Brewers Association and the Energy Information Administration, we employed statistical analysis to uncover a surprising connection. Our findings revealed a remarkably high correlation coefficient of 0.8851443 and a significance level of p < 0.01 for the period from 1990 to 2021. To our amusement, it seems that as the number of breweries in the U.S. has been fermenting, there has been a distinctively parallel spike in fossil fuel use in Belize. This paper dissects the peculiar dynamics between these two seemingly disparate trends, offering theoretical and practical implications that might just brew up some interest in unconventional economic analyses. Cheers to the unexpected intercontinental linkages in the world of data!
[[INTRDUCTION]]
Ah, the tantalizing intersection of hops and hydrocarbons! In a world brimming with perplexing connections, our research sets out to unravel the curious correlation between the meteoric rise of breweries in the United States and the bubbling surge in fossil fuel use in the tropical haven of Belize. It's a tale of beer bubbles and fuel fumes, of pint glasses and CO2 emissions, where statistical analysis meets sudsy speculation.
As we delve into this frothy study, one might be inclined to raise an eyebrow and question the sanity of investigating such seemingly unrelated phenomena. After all, what could craft beer aficionados in Portland have to do with petrol-pumping activities in Punta Gorda? But fear not, dear reader, for this is where the curtain rises on a spectacle of statistical serendipity and economic enigma.
The premise of our investigation stems from an epiphany of sorts – a peculiar observation that led us down this convoluted path. With data in hand from the Brewers Association and the Energy Information Administration, we embarked on an academic journey that seemed as improbable as a lager-loving lemur. Yet, equipped with the tools of regression analysis and p-values, we sought to uncover the hidden ties that bind these disparate undertakings.
As we wade into the mirthful depths of this research, it becomes increasingly apparent that the world of data is not as sober as it appears. Our initial findings unveiled a correlation coefficient of 0.8851443 – a figure so tight, it could rival the grip of a determined beer stein enthusiast. Paired with a significance level of p < 0.01, the evidence had us brimming with giddy disbelief. Could it be that the ebb and flow of breweries in the land of the free was somehow synchronizing with the fuel-draining path of our Caribbean compatriots?
With each turn of the data, the narrative took on a life of its own. It seemed as though the hops and the fuel were engaged in a clandestine dance, moving in harmonious M.C. Escher-like patterns that left our academic sensibilities both delighted and dazed. We were reminded of that age-old adage, "In statistics, correlation does not imply causation – but my, oh my, doesn't it leave plenty of room for whimsical speculation?"
So, fellow scholars and mirth-seeking wizards of the esoteric, buckle up for an intellectual adventure that promises to regale you with insights both unexpected and improbable. As we unravel the curious linkages between brew-inducing activities and fossil fuel consumption, let us toast to the bewitching marvels of the world of data and the capricious connections it unveils. Cheers to the serendipity of statistical singularity, and here's to savoring the unconventional intrigue of intercontinental economic oddities!
[[RESULTS]]
The statistical analysis of the data collected from the Brewers Association and the Energy Information Administration yielded staggering results that left our research team both impressed and scratching our heads in amusement. The correlation coefficient of 0.8851443 between the number of breweries in the United States and fossil fuel consumption in Belize was as striking as finding a four-leaf clover in a barley field.
Furthermore, the r-squared value of 0.7834804 underscored the robustness of the relationship between these seemingly disparate variables, akin to the strong bond between a beer enthusiast and their favorite local brewpub. Not to mention, the significance level of p < 0.01 emphatically captured our attention, resembling the crisp pop of a bottle cap being liberated from its stronghold.
To visually encapsulate this peculiar correlation, we present Fig. 1, a scatterplot that vividly portrays the undeniable synchrony between the proliferation of breweries in the U.S. and the uptick in fossil fuel consumption in Belize. Behold the dance of data points, where each brewery seems to whisper, "Raise a glass," and each fossil fuel unit murmurs, "Let's fuel the flame," in a harmonious, though enigmatic, duet.
In light of these findings, our minds inevitably wander to ponder the uncharted territory of interconnected economic oddities. Could it be that the frothy effervescence of the American craft beer scene exerts a gravitational pull on the fossil fuel trajectories of faraway lands, or is this simply a statistical serendipity, akin to finding a hop cone in the hop-shaped constellation of Humulus lupulus?
Regardless of the underlying mechanism, these results beckon us to embrace the whimsical nature of economic analysis. From a scientific standpoint, this correlation serves as a call to unorthodox inquiry and an embodiment of the notion that the world of data is rife with surprises, not unlike the suspense of cracking open a bottle-conditioned brew. Indeed, as we raise a glass to these unexpected intercontinental linkages, let us toast to the capricious and intriguing nature of statistical phenomena. Cheers to the unconventional, and here's to embracing the playful dance of data in all its serendipitous splendor!
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
As we bid adieu to this merry escapade through the realm of statistical whimsy, it becomes abundantly clear that the relationship between the burgeoning brewery business in the United States and the surging fossil fuel consumption in Belize is a veritable pot of curious economic stew: a blend so unexpected and delectably enigmatic that it might just warrant its very own eccentric food truck.
The zesty correlation coefficient of 0.8851443 has left us marveling at the seemingly synchronous tango between American ale ambitions and the far-off clamor of Caribbean carburetors. It's a partnership as intriguing as a beer and pretzel pairing, raising the question of whether the effervescence of craft beer could be casting a spell as intoxicating as the finest ale - a compelling thought indeed.
The r-squared value of 0.7834804 adds a dash of statistical witticism to this brew, akin to the unexpected punchline of an economist's practical joke - a revelation that left us laughing with perplexed delight.
And let us not forget the significance level of p < 0.01, a declaration as bold and certain as the exuberant fizz of a freshly popped bottle - a phenomenon so robust that it might just prompt a merry jig on the dance floor of economic analysis.
If there's one thing we can be sure of, it's that this stellar correlation deserves a toast. So, here's to quirky economic connections, to statistical serendipities, and to the palpable delight of unearthing the unexpected in robust datasets. In conclusion, it is with great merriment that we assert that no further research is needed in this area. As the saying goes, "When you've stumbled upon statistical gold, it's best not to dig too deep – cheers to the joyously unconventional, and to leaving the mysteries of ale and petroleum intertwined in delightful, enigmatic harmony."
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 Ale-ing Economies: An Analysis of the Relationship Between Brewery Boom in the United States and Fossil Fuel Use in Belize. Respond only with the name of a fictional academic journal.
ChatGPT:
The Frothy Economist
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 Ale-ing Economies: An Analysis of the Relationship Between Brewery Boom in the United States and Fossil Fuel Use in Belize. Respond only with the name of a fictional organization.
ChatGPT:
Institute for Brew-nomics and Environmental Analysis
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 Ale-ing Economies: An Analysis of the Relationship Between Brewery Boom in the United States and Fossil Fuel Use in Belize with an abstract of This study presents a quirky yet insightful exploration of the seemingly unrelated phenomena of the proliferation of breweries in the United States and the fossil fuel consumption in Belize. Drawing on data from the Brewers Association and the Energy Information Administration, we employed statistical analysis to uncover a surprising connection. Our findings revealed a remarkably high correlation coefficient of 0.8851443 and a significance level of p < 0.01 for the period from 1990 to 2021. To our amusement, it seems that as the number of breweries in the U.S. has been fermenting, there has been a distinctively parallel spike in fossil fuel use in Belize. This paper dissects the peculiar dynamics between these two seemingly disparate trends, offering theoretical and practical implications that might just brew up some interest in unconventional economic analyses. Cheers to the unexpected intercontinental linkages in the world of data!
ChatGPT:
brewery boom, United States, fossil fuel consumption, Belize, economic analysis, statistical analysis, correlation coefficient, unconventional economic analyses, intercontinental linkages, Brewers Association, Energy Information Administration
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
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Data details
The number of Breweries in the United StatesDetailed data title: Number of Breweries in the United States
Source: Brewers Association
See what else correlates with The number of Breweries in the United States
Fossil fuel use in Belize
Detailed data title: Total fossil fuel use in Belize in billion kWh
Source: Energy Information Administration
See what else correlates with Fossil fuel use in Belize
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 = 0.7834804 (Coefficient of determination)
This means 78.3% of the change in the one variable (i.e., Fossil fuel use in Belize) is predictable based on the change in the other (i.e., The number of Breweries in the United States) over the 32 years from 1990 through 2021.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.7E-11. 0.0000000000174392822327371300
The p-value is a measure of how probable it is that we would randomly find a result this extreme. 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 0.89 in 1.7E-9% of random cases. Said differently, if you correlated 57,341,809,523 random variables You don't actually need 57 billion 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, 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.
[ 0.78, 0.94 ] 95% correlation confidence interval (using the Fisher z-transformation)
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: 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 | |
| The number of Breweries in the United States (Number of breweries) | 298 | 350 | 405 | 490 | 634 | 1006 | 1305 | 1475 | 1651 | 1577 | 1493 | 1499 | 1575 | 1629 | 1635 | 1612 | 1741 | 1805 | 1896 | 1933 | 2131 | 2525 | 2670 | 3162 | 4014 | 4847 | 5780 | 6767 | 7722 | 8557 | 9092 | 9384 |
| Fossil fuel use in Belize (Billion kWh) | 0.102 | 0.118 | 0.132 | 0.148 | 0.135 | 0.102 | 0.086 | 0.092 | 0.087 | 0.086 | 0.071 | 0.043367 | 0.046491 | 0.097889 | 0.084369 | 0.08726 | 0.032245 | 0.0386 | 0.01145 | 0.0489933 | 0.151944 | 0.0828121 | 0.163176 | 0.112257 | 0.147799 | 0.181018 | 0.153204 | 0.365381 | 0.40144 | 0.4 | 0.379785 | 0.404092 |
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
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
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.
Try it yourself
You can calculate the values on this page on your own! Try running the Python code to see the calculation results. 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([298,350,405,490,634,1006,1305,1475,1651,1577,1493,1499,1575,1629,1635,1612,1741,1805,1896,1933,2131,2525,2670,3162,4014,4847,5780,6767,7722,8557,9092,9384,])
array_2 = np.array([0.102,0.118,0.132,0.148,0.135,0.102,0.086,0.092,0.087,0.086,0.071,0.043367,0.046491,0.097889,0.084369,0.08726,0.032245,0.0386,0.01145,0.0489933,0.151944,0.0828121,0.163176,0.112257,0.147799,0.181018,0.153204,0.365381,0.40144,0.4,0.379785,0.404092,])
array_1_name = "The number of Breweries in the United States"
array_2_name = "Fossil fuel use in Belize"
# 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. 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.
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Download images for these variables:
- High resolution line chart
The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.
If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.
Alternatively you can use a tool like Inkscape. - High resolution line chart, optimized for mobile
- Alternative high resolution line chart
- Scatterplot
- Portable line chart (png)
- Portable line chart (png), optimized for mobile
- Line chart for only The number of Breweries in the United States
- Line chart for only Fossil fuel use in Belize
- AI-generated correlation image
- The spurious research paper: Ale-ing Economies: An Analysis of the Relationship Between Brewery Boom in the United States and Fossil Fuel Use in Belize
Thanks for shining a light on this correlation!
Correlation ID: 3735 · Black Variable ID: 34 · Red Variable ID: 23512
