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Spurious correlation #3,525 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of fiberglass laminators and fabricators in Minnesota and the second variable is Fossil fuel use in Czechia.  The chart goes from 2005 to 2021, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As the fiberglass industry in Minnesota frays, the Czechs are not taking it for granite, and they're finding alternative, more sustainable materials to fuel their energy needs. It seems like the Czechs are no longer laminerating their energy sources!

Model: dalle-3
Prompt: Generating prompt for DALL·E-3: Create an image that captures the interconnectedness of a bustling fiberglass factory in Minnesota and power plants emitting plumes of smoke in Czechia. The scene should illustrate the surge in fiberglass production and the increased fossil fuel use, with a cybernetic art style. The factory should be depicted with workers fabricating fiberglass panels amidst a high-tech environment, showcasing the advanced manufacturing processes. Meanwhile, the power plants in Czechia should be emitting ominous plumes of smoke, symbolizing the environmental impact of the increased energy demands. The visual should convey the complex relationship between industry and the environment using futuristic and artistic elements. 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 fiberglass laminators and fabricators in Minnesota and Fossil fuel use in Czechia. 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: Cybernetic art Sci-fi fantacy 3D Pixar Style Cute 2D animation Surrealism
ChatGPT: Cybernetic 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 The number of fiberglass laminators and fabricators in Minnesota and Fossil fuel use in Czechia, in the following situation: Fossil fuel use in Czechia increased because the demand for fiberglass laminators and fabricators in Minnesota led to a surge in the production of fiberglass. This, in turn, depleted the world's supply of fiberglass, causing Czechia to resort to burning more fossil fuels for energy production.. Keep the description simple.
ChatGPT: In a visual scene, we see a bustling factory in Minnesota with many workers fabricating fiberglass, as the demand for fiberglass laminators and fabricators surges. The production of fiberglass is in full swing, with stacks of fiberglass panels ready for shipment. However, across the globe, in Czechia, we see power plants emitting plumes of smoke as they burn more fossil fuels to meet the increased energy demands caused by the depleted global supply of fiberglass. The scene depicts the interconnectedness of the two variables as the demand for fiberglass leads to increased fossil fuel use in Czechia.

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: [ Cybernetic art ] and depicting this scene: In a visual scene, we see a bustling factory in Minnesota with many workers fabricating fiberglass, as the demand for fiberglass laminators and fabricators surges. The production of fiberglass is in full swing, with stacks of fiberglass panels ready for shipment. However, across the globe, in Czechia, we see power plants emitting plumes of smoke as they burn more fossil fuels to meet the increased energy demands caused by the depleted global supply of fiberglass. The scene depicts the interconnectedness of the two variables as the demand for fiberglass leads to increased fossil fuel use in Czechia. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generating prompt for DALL·E-3: Create an image that captures the interconnectedness of a bustling fiberglass factory in Minnesota and power plants emitting plumes of smoke in Czechia. The scene should illustrate the surge in fiberglass production and the increased fossil fuel use, with a cybernetic art style. The factory should be depicted with workers fabricating fiberglass panels amidst a high-tech environment, showcasing the advanced manufacturing processes. Meanwhile, the power plants in Czechia should be emitting ominous plumes of smoke, symbolizing the environmental impact of the increased energy demands. The visual should convey the complex relationship between industry and the environment using futuristic and artistic elements.

*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.

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 a decrease in The number of fiberglass laminators and fabricators in Minnesota caused Fossil fuel use in Czechia to decrease. Include one good pun.

AI academic paper

(Because p < 0.01)
Will More Fiberglass Laminators Lead to Less Gas Sublimators: A Cross-National Analysis of Occupational Trends and Energy Consumption

Journal of Polymer Science & Occupational Trends

Jan 2024

Reminder: This paper is AI-generated. Not real!
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 silly 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 fiberglass laminators and fabricators in Minnesota and Fossil fuel use in Czechia. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Rhyme words in the title.

Your research team used data from Bureau of Larbor Statistics and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.9043062 and p < 0.01 for 2005 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]]
Will More Fiberglass Laminators Lead to Less Gas Sublimators: A Cross-National Analysis of Occupational Trends and Energy Consumption

[[ABSTRACT]]
In this study, we delve into the curious relationship between the number of fiberglass laminators and fabricators in Minnesota and the fossil fuel use in Czechia. Drawing on data from the Bureau of Labor Statistics and the Energy Information Administration, we analytically connect these seemingly disparate realms. Our findings reveal a startling correlation coefficient of 0.9043062 and a p-value less than 0.01 during the period from 2005 to 2021, raising intriguing questions and prompting wry observations. The correlation challenges conventional expectations and leaves us pondering whether the intricacies of fiberglass production could hold the key to sublimating fuel consumption. This research aims to illuminate an unexplored facet of occupational trends and energy dynamics, while also injecting a lighthearted twist into the academically rigorous pursuit of knowledge.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 fiberglass laminators and fabricators in Minnesota and Fossil fuel use in Czechia. 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.

Here is the title and abstract of the paper:
[[TITLE]]
Will More Fiberglass Laminators Lead to Less Gas Sublimators: A Cross-National Analysis of Occupational Trends and Energy Consumption

[[ABSTRACT]]
In this study, we delve into the curious relationship between the number of fiberglass laminators and fabricators in Minnesota and the fossil fuel use in Czechia. Drawing on data from the Bureau of Labor Statistics and the Energy Information Administration, we analytically connect these seemingly disparate realms. Our findings reveal a startling correlation coefficient of 0.9043062 and a p-value less than 0.01 during the period from 2005 to 2021, raising intriguing questions and prompting wry observations. The correlation challenges conventional expectations and leaves us pondering whether the intricacies of fiberglass production could hold the key to sublimating fuel consumption. This research aims to illuminate an unexplored facet of occupational trends and energy dynamics, while also injecting a lighthearted twist into the academically rigorous pursuit of knowledge.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The intersection of occupational trends and energy dynamics has long been an area of fascination for researchers and pragmatic daydreamers alike. While one might not immediately consider the connection between the number of fiberglass laminators and fabricators in Minnesota and the fossil fuel use in Czechia, we are inspired by the old adage, "Where there's a will, there's a way – and where there's a laminate, there's a correlation." Our curiosity about this relationship has led us to delve into the bowels of data, armed with statistical expertise and a healthy dose of humor, in the pursuit of uncovering hidden patterns and untangling the interwoven threads of industry and energy consumption.

As scientific sleuths, we embarked on this inquiry with a twinkle in our eyes and a pile of spreadsheets at our fingertips. Our aim was to scientifically explore and theoretically ponder whether the act of carefully layering fiberglass composite materials could exert an unforeseen influence on the consumption of fossil fuels half a world away in Czechia. The pursuit of knowledge, after all, often starts with the most bizarre and unintuitive questions, and if there's any validity to the hypothesis that the meticulous work of laminators could affect gas sublimators, then it's a question worth investigating – if only for the amusement of the academic community.

Our journey of inquiry has been punctuated by moments of mild skepticism and unbridled curiosity. We carried out an extensive literature review, expecting to find sparse mentions, if any, of the relationship between fiberglass lamination and fossil fuel use. However, to our surprise, we stumbled upon flimsy strands of evidence alluding to the potential impacts of material fabrication processes on broader environmental and energy dynamics. These serendipitous findings fueled our resolve to plumb the depths of data and statistical analysis, armed with the scientific rigor of a committed researcher and the irrepressible urge to sprinkle a bit of academic frivolity into our pursuits.

Consequently, armed with correlation coefficients and p-values in our metaphorical tool belt, we set out to analyze and scrutinize the Bureau of Labor Statistics and the Energy Information Administration data with our most arched eyebrows. Our pursuit of uncovering a correlation coefficient of 0.9043062 and a p-value less than 0.01 from 2005 to 2021 has ignited in us both surprise and curiosity in equal measure. The mere hint of such a robust correlation between the meticulous art of fiberglass lamination in Minnesota and the avid consumption of fossil fuels in Czechia beguiles our academic sensibilities and compels us to dissect and unravel the enigmatic threads of this seemingly improbable relationship.

In the pursuit of scientific truth, we are poised to challenge conventional expectations, to question deeply ingrained assumptions, and to inspire the academic community to engage in a spirited yet rigorous dialogue about the seemingly mundane yet unexpectedly consequential quirks of occupational trends and energy consumption. Our research thus embodies the fusion of scientific scrutiny and lighthearted inquiry, aiming to deliver both scholarly insight and a dash of academic whimsy to our venerable pursuit of knowledge.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 fiberglass laminators and fabricators in Minnesota and Fossil fuel use in Czechia. 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 name some cartoons and childrens' shows that you watched that are related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
Will More Fiberglass Laminators Lead to Less Gas Sublimators: A Cross-National Analysis of Occupational Trends and Energy Consumption

[[ABSTRACT]]
In this study, we delve into the curious relationship between the number of fiberglass laminators and fabricators in Minnesota and the fossil fuel use in Czechia. Drawing on data from the Bureau of Labor Statistics and the Energy Information Administration, we analytically connect these seemingly disparate realms. Our findings reveal a startling correlation coefficient of 0.9043062 and a p-value less than 0.01 during the period from 2005 to 2021, raising intriguing questions and prompting wry observations. The correlation challenges conventional expectations and leaves us pondering whether the intricacies of fiberglass production could hold the key to sublimating fuel consumption. This research aims to illuminate an unexplored facet of occupational trends and energy dynamics, while also injecting a lighthearted twist into the academically rigorous pursuit of knowledge.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intersection of occupational trends and energy dynamics has long been an area of fascination for researchers and pragmatic daydreamers alike. While one might not immediately consider the connection between the number of fiberglass laminators and fabricators in Minnesota and the fossil fuel use in Czechia, we are inspired by the old adage, "Where there's a will, there's a way – and where there's a laminate, there's a correlation." Our curiosity about this relationship has led us to delve into the bowels of data, armed with statistical expertise and a healthy dose of humor, in the pursuit of uncovering hidden patterns and untangling the interwoven threads of industry and energy consumption.
As scientific sleuths, we embarked on this inquiry with a twinkle in our eyes and a pile of spreadsheets at our fingertips. Our aim was to scientifically explore and theoretically ponder whether the act of carefully layering fiberglass composite materials could exert an unforeseen influence on the consumption of fossil fuels half a world away in Czechia. The pursuit of knowledge, after all, often starts with the most bizarre and unintuitive questions, and if there's any validity to the hypothesis that the meticulous work of laminators could affect gas sublimators, then it's a question worth investigating – if only for the amusement of the academic community.
Our journey of inquiry has been punctuated by moments of mild skepticism and unbridled curiosity. We carried out an extensive literature review, expecting to find sparse mentions, if any, of the relationship between fiberglass lamination and fossil fuel use. However, to our surprise, we stumbled upon flimsy strands of evidence alluding to the potential impacts of material fabrication processes on broader environmental and energy dynamics. These serendipitous findings fueled our resolve to plumb the depths of data and statistical analysis, armed with the scientific rigor of a committed researcher and the irrepressible urge to sprinkle a bit of academic frivolity into our pursuits.
Consequently, armed with correlation coefficients and p-values in our metaphorical tool belt, we set out to analyze and scrutinize the Bureau of Labor Statistics and the Energy Information Administration data with our most arched eyebrows. Our pursuit of uncovering a correlation coefficient of 0.9043062 and a p-value less than 0.01 from 2005 to 2021 has ignited in us both surprise and curiosity in equal measure. The mere hint of such a robust correlation between the meticulous art of fiberglass lamination in Minnesota and the avid consumption of fossil fuels in Czechia beguiles our academic sensibilities and compels us to dissect and unravel the enigmatic threads of this seemingly improbable relationship.
In the pursuit of scientific truth, we are poised to challenge conventional expectations, to question deeply ingrained assumptions, and to inspire the academic community to engage in a spirited yet rigorous dialogue about the seemingly mundane yet unexpectedly consequential quirks of occupational trends and energy consumption. Our research thus embodies the fusion of scientific scrutiny and lighthearted inquiry, aiming to deliver both scholarly insight and a dash of academic whimsy to our venerable pursuit of knowledge.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The relationship between occupational trends and energy dynamics has been a fertile ground for scholarly exploration. Smith, Doe, and Jones (2009) proposed that the occupational distribution of labor may have indirect effects on energy consumption patterns, a notion that has garnered increasing attention in the academic community. Furthermore, their work highlights the need to examine seemingly unrelated occupational sectors and their potential impacts on broader societal energy dynamics.

In a similar vein, "The Energy-Efficient Workplace" by Green (2015) provides a comprehensive overview of the various factors influencing energy consumption in industrial settings, with a particular emphasis on the role of labor force distribution. Green's work invites us to consider the intricate interplay between labor activities and energy utilization, paving the way for unconventional inquiries into the linkages between seemingly distinct occupational domains.

As we delved deeper into the literature, we stumbled upon "The Art of Composite Materials" by Crafty and Smith (2012), a seminal work that elucidates the nuances of material fabrication processes, including fiberglass lamination. The authors aptly discuss the meticulous techniques involved in composite material production, hinting at the potential implications of these processes on environmental and energy dynamics.

While the academic literature offered valuable insights, our inquiry led us to consider the broader cultural and fictional dimensions relevant to our subject matter. "Lamination: A Historical Overview" by Papyrus and Scroll (2010) presented an engaging account of the evolution of lamination techniques, spanning from ancient civilizations to modern industrial practices. This historical perspective underscored the enduring significance of lamination processes in human endeavors, serving as a reminder of the intricate tapestry of human labor and its potential influences on energy dynamics.

Furthermore, works of fiction such as "The Laminator's Dilemma" by Novelista (2018) and "The Fabricator's Folly" by Imagination (2016) offered imaginative narratives that, while not grounded in empirical research, sparked our playful curiosity about the whimsical realms of fiberglass fabrication. These literary diversions, in their own playful way, nudged us to contemplate the potential intersections of occupational craftsmanship and energy flows, infusing a sense of levity into our scholarly pursuits.

In a departure from conventional academic sources, we also drew inspiration from cartoons and children's shows that showcased the intricacies of material fabrication processes. The animated series "Laminate Lane Adventures" and "Fiberglass Friends" provided whimsical yet thought-provoking portrayals of the laborious yet fascinating world of composite material production, offering a playful lens through which to view the otherwise serious realm of fiberglass lamination.

As we traversed this eclectic landscape of academic, fictional, and pop culture sources, we found ourselves enriched by the diverse perspectives and unconventional insights that permeated our intellectual journey. Our literature review, thus, culminates in the humorous acknowledgment of the multifaceted influences that shape our scholarly pursuits, urging us to approach our research with a balanced blend of scholarly rigor and playful curiosity.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 fiberglass laminators and fabricators in Minnesota and Fossil fuel use in Czechia. 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 Bureau of Larbor Statistics and Energy Information Administration . You used data from 2005 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]]
Will More Fiberglass Laminators Lead to Less Gas Sublimators: A Cross-National Analysis of Occupational Trends and Energy Consumption

[[ABSTRACT]]
In this study, we delve into the curious relationship between the number of fiberglass laminators and fabricators in Minnesota and the fossil fuel use in Czechia. Drawing on data from the Bureau of Labor Statistics and the Energy Information Administration, we analytically connect these seemingly disparate realms. Our findings reveal a startling correlation coefficient of 0.9043062 and a p-value less than 0.01 during the period from 2005 to 2021, raising intriguing questions and prompting wry observations. The correlation challenges conventional expectations and leaves us pondering whether the intricacies of fiberglass production could hold the key to sublimating fuel consumption. This research aims to illuminate an unexplored facet of occupational trends and energy dynamics, while also injecting a lighthearted twist into the academically rigorous pursuit of knowledge.

[[INTRODUCTION]]
The intersection of occupational trends and energy dynamics has long been an area of fascination for researchers and pragmatic daydreamers alike. While one might not immediately consider the connection between the number of fiberglass laminators and fabricators in Minnesota and the fossil fuel use in Czechia, we are inspired by the old adage, "Where there's a will, there's a way – and where there's a laminate, there's a correlation." Our curiosity about this relationship has led us to delve into the bowels of data, armed with statistical expertise and a healthy dose of humor, in the pursuit of uncovering hidden patterns and untangling the interwoven threads of industry and energy consumption.
As scientific sleuths, we embarked on this inquiry with a twinkle in our eyes and a pile of spreadsheets at our fingertips. Our aim was to scientifically explore and theoretically ponder whether the act of carefully layering fiberglass composite materials could exert an unforeseen influence on the consumption of fossil fuels half a world away in Czechia. The pursuit of knowledge, after all, often starts with the most bizarre and unintuitive questions, and if there's any validity to the hypothesis that the meticulous work of laminators could affect gas sublimators, then it's a question worth investigating – if only for the amusement of the academic community.
Our journey of inquiry has been punctuated by moments of mild skepticism and unbridled curiosity. We carried out an extensive literature review, expecting to find sparse mentions, if any, of the relationship between fiberglass lamination and fossil fuel use. However, to our surprise, we stumbled upon flimsy strands of evidence alluding to the potential impacts of material fabrication processes on broader environmental and energy dynamics. These serendipitous findings fueled our resolve to plumb the depths of data and statistical analysis, armed with the scientific rigor of a committed researcher and the irrepressible urge to sprinkle a bit of academic frivolity into our pursuits.
Consequently, armed with correlation coefficients and p-values in our metaphorical tool belt, we set out to analyze and scrutinize the Bureau of Labor Statistics and the Energy Information Administration data with our most arched eyebrows. Our pursuit of uncovering a correlation coefficient of 0.9043062 and a p-value less than 0.01 from 2005 to 2021 has ignited in us both surprise and curiosity in equal measure. The mere hint of such a robust correlation between the meticulous art of fiberglass lamination in Minnesota and the avid consumption of fossil fuels in Czechia beguiles our academic sensibilities and compels us to dissect and unravel the enigmatic threads of this seemingly improbable relationship.
In the pursuit of scientific truth, we are poised to challenge conventional expectations, to question deeply ingrained assumptions, and to inspire the academic community to engage in a spirited yet rigorous dialogue about the seemingly mundane yet unexpectedly consequential quirks of occupational trends and energy consumption. Our research thus embodies the fusion of scientific scrutiny and lighthearted inquiry, aiming to deliver both scholarly insight and a dash of academic whimsy to our venerable pursuit of knowledge.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To investigate the enigmatic relationship between the number of fiberglass laminators and fabricators in Minnesota and fossil fuel use in Czechia, we employed a blend of quantitative analysis and tongue-in-cheek curiosity, peppered with liberal amounts of statistical scrutiny and wry observation. Our data were sourced from the Bureau of Labor Statistics and the Energy Information Administration, providing us with a rich tapestry of occupational and energy dynamics from 2005 to 2021.

The initial step in our zany quest for correlation involved compiling and organizing the prevalence of fiberglass laminators and fabricators in Minnesota. We gleefully sifted through the Bureau of Labor Statistics data, reveling in the eclectic assortment of occupational statistics, and counting the number of individuals engaged in the art of fiberglass lamination. While some might scoff at the idea of drawing connections between seemingly unrelated professions and energy consumption in a distant land, our inquisitive minds were undeterred as we meticulously cataloged the occupational trends with a dash of bemusement.

Simultaneously, we embraced the quirkiness of our investigation by delving into the abyss of energy statistics, reaching out to the Energy Information Administration to access the fossil fuel use data in Czechia. With a raise of our metaphorical eyebrows and a nod to the statistical gods, we commenced the grand exercise of unraveling the labyrinthine patterns of fuel consumption, all the while marveling at the delightful absurdity of our scientific pursuit.

With our data in hand and an unyielding belief in the potential correlation between fiberglass craftsmanship and gas consumption, we employed rigorous statistical techniques, supremely seasoned with a pinch of whimsy, to examine the relationships. Using the formidable powers of correlation analysis, we probed the data, teasing out the unsuspected interplay between the number of fiberglass laminators and fabricators in Minnesota and the fossil fuel use in Czechia.

Drawing upon the armory of statistical software at our disposal, we meticulously calculated correlation coefficients and scrutinized p-values with the seriousness befitting professional researchers – all the while reveling in the joyous peculiarity of our subject matter. Our analysis was conducted with the kind of fervor that would be expected of academics on a crusade to uncover the unexpected, with a hint of laughter echoing through the corridors of our research facilities.

In the end, our barmy journey led to the unearthing of a correlation coefficient of 0.9043062 and a p-value lower than 0.01, leaving us wide-eyed and slack-jawed with disbelief at the robustness of the association between fiberglass artisans in Minnesota and the gas sublimators in Czechia. This confluence of statistical professionalism and academic whimsy has furnished us with an unparalleled understanding of the unconventional relationship between occupational trends and energy consumption.

In conclusion, our research methodology encapsulated the earnest pursuit of statistical truth, mirthful curiosity, and the unyielding quest for uncovering hidden patterns. It is our fervent hope that this methodology section – infused with equal parts quirkiness and scientific rigor – serves as an inspiration for future researchers to unravel the idiosyncrasies of our world with a lighthearted spirit and a dedication to scholarly inquiry.



Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 fiberglass laminators and fabricators in Minnesota and Fossil fuel use in Czechia. 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 Bureau of Larbor Statistics and Energy Information Administration .

For the time period 2005 to 2021, you found a correlation 0.9043062, r-squared of 0.8177697, 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]]
Will More Fiberglass Laminators Lead to Less Gas Sublimators: A Cross-National Analysis of Occupational Trends and Energy Consumption

[[ABSTRACT]]
In this study, we delve into the curious relationship between the number of fiberglass laminators and fabricators in Minnesota and the fossil fuel use in Czechia. Drawing on data from the Bureau of Labor Statistics and the Energy Information Administration, we analytically connect these seemingly disparate realms. Our findings reveal a startling correlation coefficient of 0.9043062 and a p-value less than 0.01 during the period from 2005 to 2021, raising intriguing questions and prompting wry observations. The correlation challenges conventional expectations and leaves us pondering whether the intricacies of fiberglass production could hold the key to sublimating fuel consumption. This research aims to illuminate an unexplored facet of occupational trends and energy dynamics, while also injecting a lighthearted twist into the academically rigorous pursuit of knowledge.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The intersection of occupational trends and energy dynamics has long been an area of fascination for researchers and pragmatic daydreamers alike. While one might not immediately consider the connection between the number of fiberglass laminators and fabricators in Minnesota and the fossil fuel use in Czechia, we are inspired by the old adage, "Where there's a will, there's a way – and where there's a laminate, there's a correlation." Our curiosity about this relationship has led us to delve into the bowels of data, armed with statistical expertise and a healthy dose of humor, in the pursuit of uncovering hidden patterns and untangling the interwoven threads of industry and energy consumption.
As scientific sleuths, we embarked on this inquiry with a twinkle in our eyes and a pile of spreadsheets at our fingertips. Our aim was to scientifically explore and theoretically ponder whether the act of carefully layering fiberglass composite materials could exert an unforeseen influence on the consumption of fossil fuels half a world away in Czechia. The pursuit of knowledge, after all, often starts with the most bizarre and unintuitive questions, and if there's any validity to the hypothesis that the meticulous work of laminators could affect gas sublimators, then it's a question worth investigating – if only for the amusement of the academic community.
Our journey of inquiry has been punctuated by moments of mild skepticism and unbridled curiosity. We carried out an extensive literature review, expecting to find sparse mentions, if any, of the relationship between fiberglass lamination and fossil fuel use. However, to our surprise, we stumbled upon flimsy strands of evidence alluding to the potential impacts of material fabrication processes on broader environmental and energy dynamics. These serendipitous findings fueled our resolve to plumb the depths of data and statistical analysis, armed with the scientific rigor of a committed researcher and the irrepressible urge to sprinkle a bit of academic frivolity into our pursuits.
Consequently, armed with correlation coefficients and p-values in our metaphorical tool belt, we set out to analyze and scrutinize the Bureau of Labor Statistics and the Energy Information Administration data with our most arched eyebrows. Our pursuit of uncovering a correlation coefficient of 0.9043062 and a p-value less than 0.01 from 2005 to 2021 has ignited in us both surprise and curiosity in equal measure. The mere hint of such a robust correlation between the meticulous art of fiberglass lamination in Minnesota and the avid consumption of fossil fuels in Czechia beguiles our academic sensibilities and compels us to dissect and unravel the enigmatic threads of this seemingly improbable relationship.
In the pursuit of scientific truth, we are poised to challenge conventional expectations, to question deeply ingrained assumptions, and to inspire the academic community to engage in a spirited yet rigorous dialogue about the seemingly mundane yet unexpectedly consequential quirks of occupational trends and energy consumption. Our research thus embodies the fusion of scientific scrutiny and lighthearted inquiry, aiming to deliver both scholarly insight and a dash of academic whimsy to our venerable pursuit of knowledge.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The statistical analysis of the data revealed a remarkable correlation coefficient of 0.9043062 between the number of fiberglass laminators and fabricators in Minnesota and the fossil fuel use in Czechia from 2005 to 2021. This correlation was further buttressed by an r-squared value of 0.8177697, indicating that approximately 81.77% of the variation in fossil fuel use in Czechia can be explained by the number of fiberglass laminators and fabricators in Minnesota. The p-value, being less than 0.01, signifies a highly significant relationship, lending credence to our findings and sparking a flurry of puzzled eyebrows and tentative chuckles in the academic sphere.

Our revelatory findings are succinctly encapsulated in the scatterplot depicted in Fig. 1, where the strong positive correlation between the two variables is strikingly evident. The figure visually conveys the robust association between fiberglass laminators and fabricators in Minnesota and fossil fuel use in Czechia, compelling even the most steadfast skeptics to raise an appreciative eyebrow at this unexpected alignment of occupational trends and energy dynamics.

In the context of our lighthearted yet robust analysis, the resounding correlation coefficient and r-squared value stand as testaments to the unanticipated harmonies that can arise from seemingly unrelated domains. Indeed, as we traverse the convoluted terrain of statistical analysis, we are reminded that correlations, much like unexpected punchlines, can emerge from the unlikeliest of pairings.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 fiberglass laminators and fabricators in Minnesota and Fossil fuel use in Czechia. 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]]
Will More Fiberglass Laminators Lead to Less Gas Sublimators: A Cross-National Analysis of Occupational Trends and Energy Consumption

[[ABSTRACT]]
In this study, we delve into the curious relationship between the number of fiberglass laminators and fabricators in Minnesota and the fossil fuel use in Czechia. Drawing on data from the Bureau of Labor Statistics and the Energy Information Administration, we analytically connect these seemingly disparate realms. Our findings reveal a startling correlation coefficient of 0.9043062 and a p-value less than 0.01 during the period from 2005 to 2021, raising intriguing questions and prompting wry observations. The correlation challenges conventional expectations and leaves us pondering whether the intricacies of fiberglass production could hold the key to sublimating fuel consumption. This research aims to illuminate an unexplored facet of occupational trends and energy dynamics, while also injecting a lighthearted twist into the academically rigorous pursuit of knowledge.

[[LITERATURE REVIEW]]
The relationship between occupational trends and energy dynamics has been a fertile ground for scholarly exploration. Smith, Doe, and Jones (2009) proposed that the occupational distribution of labor may have indirect effects on energy consumption patterns, a notion that has garnered increasing attention in the academic community. Furthermore, their work highlights the need to examine seemingly unrelated occupational sectors and their potential impacts on broader societal energy dynamics.
In a similar vein, "The Energy-Efficient Workplace" by Green (2015) provides a comprehensive overview of the various factors influencing energy consumption in industrial settings, with a particular emphasis on the role of labor force distribution. Green's work invites us to consider the intricate interplay between labor activities and energy utilization, paving the way for unconventional inquiries into the linkages between seemingly distinct occupational domains.
As we delved deeper into the literature, we stumbled upon "The Art of Composite Materials" by Crafty and Smith (2012), a seminal work that elucidates the nuances of material fabrication processes, including fiberglass lamination. The authors aptly discuss the meticulous techniques involved in composite material production, hinting at the potential implications of these processes on environmental and energy dynamics.
While the academic literature offered valuable insights, our inquiry led us to consider the broader cultural and fictional dimensions relevant to our subject matter. "Lamination: A Historical Overview" by Papyrus and Scroll (2010) presented an engaging account of the evolution of lamination techniques, spanning from ancient civilizations to modern industrial practices. This historical perspective underscored the enduring significance of lamination processes in human endeavors, serving as a reminder of the intricate tapestry of human labor and its potential influences on energy dynamics.
Furthermore, works of fiction such as "The Laminator's Dilemma" by Novelista (2018) and "The Fabricator's Folly" by Imagination (2016) offered imaginative narratives that, while not grounded in empirical research, sparked our playful curiosity about the whimsical realms of fiberglass fabrication. These literary diversions, in their own playful way, nudged us to contemplate the potential intersections of occupational craftsmanship and energy flows, infusing a sense of levity into our scholarly pursuits.
In a departure from conventional academic sources, we also drew inspiration from cartoons and children's shows that showcased the intricacies of material fabrication processes. The animated series "Laminate Lane Adventures" and "Fiberglass Friends" provided whimsical yet thought-provoking portrayals of the laborious yet fascinating world of composite material production, offering a playful lens through which to view the otherwise serious realm of fiberglass lamination.
As we traversed this eclectic landscape of academic, fictional, and pop culture sources, we found ourselves enriched by the diverse perspectives and unconventional insights that permeated our intellectual journey. Our literature review, thus, culminates in the humorous acknowledgment of the multifaceted influences that shape our scholarly pursuits, urging us to approach our research with a balanced blend of scholarly rigor and playful curiosity.

[[RESULTS]]
The statistical analysis of the data revealed a remarkable correlation coefficient of 0.9043062 between the number of fiberglass laminators and fabricators in Minnesota and the fossil fuel use in Czechia from 2005 to 2021. This correlation was further buttressed by an r-squared value of 0.8177697, indicating that approximately 81.77% of the variation in fossil fuel use in Czechia can be explained by the number of fiberglass laminators and fabricators in Minnesota. The p-value, being less than 0.01, signifies a highly significant relationship, lending credence to our findings and sparking a flurry of puzzled eyebrows and tentative chuckles in the academic sphere.
Our revelatory findings are succinctly encapsulated in the scatterplot depicted in Fig. 1, where the strong positive correlation between the two variables is strikingly evident. The figure visually conveys the robust association between fiberglass laminators and fabricators in Minnesota and fossil fuel use in Czechia, compelling even the most steadfast skeptics to raise an appreciative eyebrow at this unexpected alignment of occupational trends and energy dynamics.
In the context of our lighthearted yet robust analysis, the resounding correlation coefficient and r-squared value stand as testaments to the unanticipated harmonies that can arise from seemingly unrelated domains. Indeed, as we traverse the convoluted terrain of statistical analysis, we are reminded that correlations, much like unexpected punchlines, can emerge from the unlikeliest of pairings.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our study's findings not only affirmed, but also provocatively enriched the existing literature on the intersection of occupational trends and energy consumption. The correlation coefficient of 0.9043062 steadfastly echoed the inquiries of Smith, Doe, and Jones (2009), unearthing a statistically significant linkage that merrily tickled the fancy of data enthusiasts and humor aficionados alike. The striking resonance of our results with the speculations of Green (2015) underscores the mercurial dance between labor force distribution and energy dynamics, revealing a correlation so tangible that it could almost be mistaken for a spool of fiberglass itself.

Crafty and Smith's (2012) meticulous exposition of composite material production, including fiberglass lamination, found a whimsical ally in our findings, painting a picture not unlike one of the colorful and vibrant cartoons that fueled our scholarly whimsy. As we mused upon the r-squared value of 0.8177697, we couldn't help but feel a kinship with the fictional portrayals of fiberglass fabrication in "Laminate Lane Adventures" and "Fiberglass Friends," where the seemingly disparate worlds of occupational craftsmanship and energy consumption intersected in a delightfully improbable manner.

Our scatterplot, akin to a visual punchline in the grand comedic repertoire of statistical analysis, artistically enshrines the vivacious association between fiberglass laminators and fabricators in Minnesota and fossil fuel use in Czechia. The seemingly incongruous pairing of these variables, much like the unexpected twist in a well-crafted joke, captured the collective imagination of scholars and laypersons alike, ushering in a new era of metaphoric merriment in the realm of academic inquiries.

The colorful tapestry of our research journey, drawing inspiration from historical treatises, works of fiction, and whimsical portrayals of material fabrication processes, ultimately coalesced into a symphonic crescendo of statistical resonance. As we embark on the continued exploration of occupational trends and energy dynamics, we are driven by the dual imperatives of scholarly rigor and playful curiosity, persisting in our quest to unveil the unexplored confluences of labor artistry and energy utilization.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 fiberglass laminators and fabricators in Minnesota and Fossil fuel use in Czechia. 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]]
Will More Fiberglass Laminators Lead to Less Gas Sublimators: A Cross-National Analysis of Occupational Trends and Energy Consumption

[[ABSTRACT]]
In this study, we delve into the curious relationship between the number of fiberglass laminators and fabricators in Minnesota and the fossil fuel use in Czechia. Drawing on data from the Bureau of Labor Statistics and the Energy Information Administration, we analytically connect these seemingly disparate realms. Our findings reveal a startling correlation coefficient of 0.9043062 and a p-value less than 0.01 during the period from 2005 to 2021, raising intriguing questions and prompting wry observations. The correlation challenges conventional expectations and leaves us pondering whether the intricacies of fiberglass production could hold the key to sublimating fuel consumption. This research aims to illuminate an unexplored facet of occupational trends and energy dynamics, while also injecting a lighthearted twist into the academically rigorous pursuit of knowledge.

[[INTRDUCTION]]
The intersection of occupational trends and energy dynamics has long been an area of fascination for researchers and pragmatic daydreamers alike. While one might not immediately consider the connection between the number of fiberglass laminators and fabricators in Minnesota and the fossil fuel use in Czechia, we are inspired by the old adage, "Where there's a will, there's a way – and where there's a laminate, there's a correlation." Our curiosity about this relationship has led us to delve into the bowels of data, armed with statistical expertise and a healthy dose of humor, in the pursuit of uncovering hidden patterns and untangling the interwoven threads of industry and energy consumption.
As scientific sleuths, we embarked on this inquiry with a twinkle in our eyes and a pile of spreadsheets at our fingertips. Our aim was to scientifically explore and theoretically ponder whether the act of carefully layering fiberglass composite materials could exert an unforeseen influence on the consumption of fossil fuels half a world away in Czechia. The pursuit of knowledge, after all, often starts with the most bizarre and unintuitive questions, and if there's any validity to the hypothesis that the meticulous work of laminators could affect gas sublimators, then it's a question worth investigating – if only for the amusement of the academic community.
Our journey of inquiry has been punctuated by moments of mild skepticism and unbridled curiosity. We carried out an extensive literature review, expecting to find sparse mentions, if any, of the relationship between fiberglass lamination and fossil fuel use. However, to our surprise, we stumbled upon flimsy strands of evidence alluding to the potential impacts of material fabrication processes on broader environmental and energy dynamics. These serendipitous findings fueled our resolve to plumb the depths of data and statistical analysis, armed with the scientific rigor of a committed researcher and the irrepressible urge to sprinkle a bit of academic frivolity into our pursuits.
Consequently, armed with correlation coefficients and p-values in our metaphorical tool belt, we set out to analyze and scrutinize the Bureau of Labor Statistics and the Energy Information Administration data with our most arched eyebrows. Our pursuit of uncovering a correlation coefficient of 0.9043062 and a p-value less than 0.01 from 2005 to 2021 has ignited in us both surprise and curiosity in equal measure. The mere hint of such a robust correlation between the meticulous art of fiberglass lamination in Minnesota and the avid consumption of fossil fuels in Czechia beguiles our academic sensibilities and compels us to dissect and unravel the enigmatic threads of this seemingly improbable relationship.
In the pursuit of scientific truth, we are poised to challenge conventional expectations, to question deeply ingrained assumptions, and to inspire the academic community to engage in a spirited yet rigorous dialogue about the seemingly mundane yet unexpectedly consequential quirks of occupational trends and energy consumption. Our research thus embodies the fusion of scientific scrutiny and lighthearted inquiry, aiming to deliver both scholarly insight and a dash of academic whimsy to our venerable pursuit of knowledge.

[[RESULTS]]
The statistical analysis of the data revealed a remarkable correlation coefficient of 0.9043062 between the number of fiberglass laminators and fabricators in Minnesota and the fossil fuel use in Czechia from 2005 to 2021. This correlation was further buttressed by an r-squared value of 0.8177697, indicating that approximately 81.77% of the variation in fossil fuel use in Czechia can be explained by the number of fiberglass laminators and fabricators in Minnesota. The p-value, being less than 0.01, signifies a highly significant relationship, lending credence to our findings and sparking a flurry of puzzled eyebrows and tentative chuckles in the academic sphere.
Our revelatory findings are succinctly encapsulated in the scatterplot depicted in Fig. 1, where the strong positive correlation between the two variables is strikingly evident. The figure visually conveys the robust association between fiberglass laminators and fabricators in Minnesota and fossil fuel use in Czechia, compelling even the most steadfast skeptics to raise an appreciative eyebrow at this unexpected alignment of occupational trends and energy dynamics.
In the context of our lighthearted yet robust analysis, the resounding correlation coefficient and r-squared value stand as testaments to the unanticipated harmonies that can arise from seemingly unrelated domains. Indeed, as we traverse the convoluted terrain of statistical analysis, we are reminded that correlations, much like unexpected punchlines, can emerge from the unlikeliest of pairings.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, the robust correlation uncovered between the number of fiberglass laminators and fabricators in Minnesota and fossil fuel use in Czechia from 2005 to 2021 leaves us marveling at the whimsical dance of occupational trends and energy dynamics. Our findings have served as a timely reminder that, much like the layers of fiberglass in lamination, the underpinning connections in statistical analysis can harbor unexpected strength and resilience.

The remarkable correlation coefficient of 0.9043062 and the r-squared value of 0.8177697 have not only elevated our eyebrows but also raised compelling questions about the potential influence of laminating craftsmanship on the fossil fuel consumption patterns in Czechia. While some may dismiss this correlation as mere statistical serendipity, we cannot help but appreciate the intricate harmony that emerges from these seemingly incongruent variables. After all, if there's anything this research has imparted upon us, it is the wisdom that statistical analysis, much like a finely woven fiberglass composite, can unveil unexpected patterns and unfurl the humorously complex tapestry of our world.

As we bid adieu to this peculiar yet enlightening odyssey, it is abundantly clear that no further research is needed in this curious realm of inquiry. The unanticipated correlation between fiberglass laminators and fabricators in Minnesota and fossil fuel use in Czechia stands as a testament to the capricious antics of statistical relationships. With that, we leave our fellow scholars with a wink and a nod, urging them to, perhaps, set their sights on equally improbable pairings in the delightful pursuit of academic enchantment.


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 Will More Fiberglass Laminators Lead to Less Gas Sublimators: A Cross-National Analysis of Occupational Trends and Energy Consumption. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Polymer Science & Occupational Trends


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 Will More Fiberglass Laminators Lead to Less Gas Sublimators: A Cross-National Analysis of Occupational Trends and Energy Consumption. Respond only with the name of a fictional organization.

ChatGPT:

The Global Association for Fiberglass Occupational Research and Development (GAFORD)


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 Will More Fiberglass Laminators Lead to Less Gas Sublimators: A Cross-National Analysis of Occupational Trends and Energy Consumption with an abstract of In this study, we delve into the curious relationship between the number of fiberglass laminators and fabricators in Minnesota and the fossil fuel use in Czechia. Drawing on data from the Bureau of Labor Statistics and the Energy Information Administration, we analytically connect these seemingly disparate realms. Our findings reveal a startling correlation coefficient of 0.9043062 and a p-value less than 0.01 during the period from 2005 to 2021, raising intriguing questions and prompting wry observations. The correlation challenges conventional expectations and leaves us pondering whether the intricacies of fiberglass production could hold the key to sublimating fuel consumption. This research aims to illuminate an unexplored facet of occupational trends and energy dynamics, while also injecting a lighthearted twist into the academically rigorous pursuit of knowledge.

ChatGPT:

fiberglass laminators, fabricators, Minnesota, fossil fuel use, Czechia, occupational trends, energy consumption, correlation coefficient, Bureau of Labor Statistics, Energy Information Administration, fiberglass production, fuel consumption, occupational trends, energy dynamics

*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 fiberglass laminators and fabricators in Minnesota
Detailed data title: BLS estimate of fiberglass laminators and fabricators in Minnesota
Source: Bureau of Larbor Statistics
See what else correlates with The number of fiberglass laminators and fabricators in Minnesota

Fossil fuel use in Czechia
Detailed data title: Total fossil fuel use in Czechia in billion kWh
Source: Energy Information Administration
See what else correlates with Fossil fuel use in Czechia

Correlation r = 0.9043062 (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 = 0.8177697 (Coefficient of determination)
This means 81.8% of the change in the one variable (i.e., Fossil fuel use in Czechia) is predictable based on the change in the other (i.e., The number of fiberglass laminators and fabricators in Minnesota) over the 17 years from 2005 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 6.3E-7. 0.0000006301769543601920000000
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 0.9 in 6.3E-5% of random cases. Said differently, if you correlated 1,586,856 random variables You don't actually need 1 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 16 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 16 because we have two variables measured over a period of 17 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.

[ 0.75, 0.97 ] 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.
20052006200720082009201020112012201320142015201620172018201920202021
The number of fiberglass laminators and fabricators in Minnesota (Laborers)440570640550300360370701601501402302202408080210
Fossil fuel use in Czechia (Billion kWh)50.819250.835254.682649.700646.836445.642445.600143.233840.982440.71941.380543.548642.800642.597240.785335.564437.8311




Why this works

  1. 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.
  2. 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.
  3. 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.
  4. 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. 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. 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([440,570,640,550,300,360,370,70,160,150,140,230,220,240,80,80,210,])
array_2 = np.array([50.8192,50.8352,54.6826,49.7006,46.8364,45.6424,45.6001,43.2338,40.9824,40.719,41.3805,43.5486,42.8006,42.5972,40.7853,35.5644,37.8311,])
array_1_name = "The number of fiberglass laminators and fabricators in Minnesota"
array_2_name = "Fossil fuel use in Czechia"

# 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)



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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.

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Correlation ID: 3525 · Black Variable ID: 17593 · Red Variable ID: 23622
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