Spurious correlation #4,181 · 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 hazardous materials removal workers in Kansas and the second variable is Google searches for 'humble pi'. The chart goes from 2004 to 2022, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of hazardous materials removal workers in Kansas and the second variable is Google searches for 'humble pi'. The chart goes from 2004 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the hazardous materials removal workers in Kansas suited up and got down to business, they inadvertently sparked a new trend in humility. You see, the more hazmat workers there were, the more people couldn't help but think about the ultimate humble brag: "I deal with some seriously toxic stuff, but I don't make a big deal out of it." It's like they were the unsung (and safely protected) heroes of modesty, radiating a down-to-earth aura that just multiplied the search for 'humble pi.' It's a classic case of the humble-by-association effect, where their presence alone was enough to remind everyone that sometimes, you just gotta approach life with a hazmat-level of humility. It's as if they were saying, "Let's not gas ourselves up – let's keep it real, like noble gases." So, as these workers continued to do their cleanup thing, they inadvertently added a new meaning to the phrase "hazardously humble," proving that even in the world of hazardous materials, it never hurts to stay grounded.

^{Show image generation prompt} Model: dalle-3
Prompt: [An image that looks like it is a scene from a Pixar movie] An animated depiction of a bustling hazmat site in Kansas, where workers in bright yellow and white protective suits are carefully handling hazardous materials. The hazmat site is portrayed within a picturesque rural landscape, with green fields in the background and a bright blue sky above. The workers are shown engrossed in their task, evoking a sense of dedication and responsibility. Despite the serious nature of their work, their demeanor exudes humility, showcasing their down-to-earth vibes. Meanwhile, in the surrounding areas of Kansas, small animated figures are seen searching "humble pi" on mobile devices, showcasing the growing interest in humility inspired by the workers' modest and unassuming demeanor. The scene juxtaposes the meticulous handling of toxic materials with the rising trend of humble contemplation. 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 hazardous materials removal workers in Kansas and Google searches for 'humble pi'. 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: Oragami An image that looks like it is a scene from a Pixar movie Cutsy graphics Pop art Woodblock painting
ChatGPT: An image that looks like it is a scene from a Pixar movie

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 hazardous materials removal workers in Kansas and Google searches for 'humble pi', in the following situation: As the hazardous materials removal workers in Kansas suited up and got down to business, they inadvertently sparked a new trend in humility. You see, the more hazmat workers there were, the more people couldn't help but think about the ultimate humble brag: "I deal with some seriously toxic stuff, but I don't make a big deal out of it." It's like they were the unsung (and safely protected) heroes of modesty, radiating a down-to-earth aura that just multiplied the search for 'humble pi.' It's a classic case of the humble-by-association effect, where their presence alone was enough to remind everyone that sometimes, you just gotta approach life with a hazmat-level of humility. It's as if they were saying, "Let's not gas ourselves up – let's keep it real, like noble gases." So, as these workers continued to do their cleanup thing, they inadvertently added a new meaning to the phrase "hazardously humble," proving that even in the world of hazardous materials, it never hurts to stay grounded.. Keep the description simple.
ChatGPT: In a bustling Kansas hazmat site, workers clad in protective gear meticulously handle toxic materials. As they work, the air fills with an air of humility, with the workers exuding down-to-earth vibes. Meanwhile, onlookers around the state are inspired to search "humble pi" on Google, sparked by the workers' modest and unassuming demeanor. The scene is a juxtaposition of hazardous material removal and the growing interest in humble contemplation.

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: [ An image that looks like it is a scene from a Pixar movie ] and depicting this scene: In a bustling Kansas hazmat site, workers clad in protective gear meticulously handle toxic materials. As they work, the air fills with an air of humility, with the workers exuding down-to-earth vibes. Meanwhile, onlookers around the state are inspired to search "humble pi" on Google, sparked by the workers' modest and unassuming demeanor. The scene is a juxtaposition of hazardous material removal and the growing interest in humble contemplation. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [An image that looks like it is a scene from a Pixar movie] An animated depiction of a bustling hazmat site in Kansas, where workers in bright yellow and white protective suits are carefully handling hazardous materials. The hazmat site is portrayed within a picturesque rural landscape, with green fields in the background and a bright blue sky above. The workers are shown engrossed in their task, evoking a sense of dedication and responsibility. Despite the serious nature of their work, their demeanor exudes humility, showcasing their down-to-earth vibes. Meanwhile, in the surrounding areas of Kansas, small animated figures are seen searching "humble pi" on mobile devices, showcasing the growing interest in humility inspired by the workers' modest and unassuming demeanor. The scene juxtaposes the meticulous handling of toxic materials with the rising trend of humble contemplation.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how increases in The number of hazardous materials removal workers in Kansas positively influenced humble pi (Google searches for 'humble pi'). Include one good pun.

AI academic paper

(Because p < 0.01)

Humble Pi and Hazardous Materials: Hilarious Hunch or Statistical Surprise?

The Journal of Irreverent Statistics

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between The number of hazardous materials removal workers in Kansas and Google searches for 'humble pi'. 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. Perhaps you also got inspiration from some board games that are vaugely related.

Here is the title and abstract of the paper:
[[TITLE]]
Humble Pi and Hazardous Materials: Hilarious Hunch or Statistical Surprise?

[[ABSTRACT]]
In this tongue-in-cheek research paper, we present an investigation into the perplexing correlation between the number of hazardous materials removal workers in Kansas and Google searches for 'humble pi'. Armed with data from the Bureau of Labor Statistics and Google Trends, we set out to unravel this curiosity. To our astonishment, we found a correlation coefficient of 0.7277493 and p < 0.01 for the time period spanning 2004 to 2022. Our findings may leave you chuckling or scratching your head – but either way, they certainly fuel the debate on the intersection of mathematical humor and occupational hazards.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Ladies and gentlemen, esteemed colleagues, and fellow aficionados of statistical shenanigans, welcome to the wacky world of correlation where the only constant is the unpredictability of human behavior. In this whimsical journey of exploration and analysis, we venture into the unexpected nexus of hazardous materials removal workers in the sunflower state of Kansas and the perplexing pursuit of 'humble pi' in the digital realm.
As the old adage goes, truth is often stranger than fiction, and our investigation delves into the peculiar relationship, or lack thereof, between these seemingly disparate phenomena. The juxtaposition of hazardous materials and mathematical merriment may evoke a smirk, a raised eyebrow, or even a hearty chuckle, but hidden within this levity lies a nugget of scientific intrigue that we simply cannot ignore – the pursuit of unlikely connections in the vast landscape of human activity.
In an effort to unravel this enigma, we find ourselves armed with the tools of modern data analysis, drawing from the reputable repositories of the Bureau of Labor Statistics and the labyrinthine depths of Google Trends. With bated breath and a dash of skepticism, we set out on this journey of statistical tomfoolery, fully aware that the most unexpected discoveries often emerge from the most unusual pairings.
The question dangling before us, like a punchline waiting to be delivered, is whether the correlation we unmask between hazardous materials removal workers and the search for 'humble pi' is the result of earnest coincidence or a stroke of statistical humor. Are we to be met with a fitting punchline or a sobering revelation that shakes the very foundation of our assumptions? Join us, dear reader, as we embark on this perplexing, and potentially comical, quest for connection in the improbable corridors of human activity. Let the statistical rollicking begin!

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The pursuit of understanding the offbeat correlation between hazardous materials removal workers in Kansas and Google searches for 'humble pi' has drawn the attention of scholars and researchers in various fields. Smith et al. (2010) explored the enigmatic world of unexpected correlations, delving into the realms of occupational data and internet search behaviors. Their findings shed light on the potential link between occupational hazards and peculiar online pursuits, paving the way for further exploration into this comically perplexing intersection.

Doe (2015) extended this inquiry by examining the psychological underpinnings of individuals' search patterns for mathematical humor amidst the context of hazardous occupation environments. Their work revealed intriguing insights into the cognitive mechanisms that contribute to such seemingly whimsical search behaviors, challenging conventional notions of correlation and causal inference in the digital age.

Jones (2018) took a hands-on approach to the subject matter, immersing themselves in the world of hazardous materials removal workers to unravel the humor-laden mystery of 'humble pi' searches. Their ethnographic study provided a rich tapestry of real-life anecdotes and observations, offering a glimpse into the daily experiences of workers who navigate the intersection of workplace safety and mathematical merriment.

Venturing beyond the traditional confines of scholarly research, the investigation at hand draws inspiration from an eclectic array of literary works and cultural references. In "The Numbers Game: A Humorous Journey through Mathematics" by Adams (2009), the author humorously explores the quirky facets of numerical concepts, inspiring a fresh perspective on the mathematical musings that captivate online searchers.

Furthermore, the whimsical world of fiction offers its own unique take on improbable connections and unexpected juxtapositions. "The Curious Incident of the Dog in the Night-Time" by Haddon (2003) and "The Mathematics of Love" by Bellos (2006) beckon the reader into the labyrinth of human behavior, where the unforeseen convergence of hazardous materials and mathematical jest may find an unexpected echo.

In the realm of games and recreation, the board game "Pandemic" offers a humorous yet pertinent analogy to the interplay of hazardous materials and unlikely searches, reminding us of the delicate balance between risk and unforeseen outcomes in the pursuit of both occupational safety and mathematical humor.

As we navigate this wacky landscape of scholarly inquiry and offbeat cultural touchstones, the inherent charm of this inquiry lies not only in its statistical rigor but also in its ability to tickle the intellect and evoke a sense of delightful bewilderment. With a nod to the unexpected and a wink to the whimsical, we set the stage for an exploration that promises to unravel the peculiar correlation between hazardous materials and 'humble pi' with equal parts scientific scrutiny and lighthearted curiosity. Onward we merrily march, dear reader, into the comically perplexing intersections of human activity!

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between The number of hazardous materials removal workers in Kansas and Google searches for 'humble pi'. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Bureau of Larbor Statistics and Google Trends . You used data from 2004 to 2022

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]]
Humble Pi and Hazardous Materials: Hilarious Hunch or Statistical Surprise?

[[ABSTRACT]]
In this tongue-in-cheek research paper, we present an investigation into the perplexing correlation between the number of hazardous materials removal workers in Kansas and Google searches for 'humble pi'. Armed with data from the Bureau of Labor Statistics and Google Trends, we set out to unravel this curiosity. To our astonishment, we found a correlation coefficient of 0.7277493 and p < 0.01 for the time period spanning 2004 to 2022. Our findings may leave you chuckling or scratching your head – but either way, they certainly fuel the debate on the intersection of mathematical humor and occupational hazards.

[[INTRODUCTION]]
Ladies and gentlemen, esteemed colleagues, and fellow aficionados of statistical shenanigans, welcome to the wacky world of correlation where the only constant is the unpredictability of human behavior. In this whimsical journey of exploration and analysis, we venture into the unexpected nexus of hazardous materials removal workers in the sunflower state of Kansas and the perplexing pursuit of 'humble pi' in the digital realm.
As the old adage goes, truth is often stranger than fiction, and our investigation delves into the peculiar relationship, or lack thereof, between these seemingly disparate phenomena. The juxtaposition of hazardous materials and mathematical merriment may evoke a smirk, a raised eyebrow, or even a hearty chuckle, but hidden within this levity lies a nugget of scientific intrigue that we simply cannot ignore – the pursuit of unlikely connections in the vast landscape of human activity.
In an effort to unravel this enigma, we find ourselves armed with the tools of modern data analysis, drawing from the reputable repositories of the Bureau of Labor Statistics and the labyrinthine depths of Google Trends. With bated breath and a dash of skepticism, we set out on this journey of statistical tomfoolery, fully aware that the most unexpected discoveries often emerge from the most unusual pairings.
The question dangling before us, like a punchline waiting to be delivered, is whether the correlation we unmask between hazardous materials removal workers and the search for 'humble pi' is the result of earnest coincidence or a stroke of statistical humor. Are we to be met with a fitting punchline or a sobering revelation that shakes the very foundation of our assumptions? Join us, dear reader, as we embark on this perplexing, and potentially comical, quest for connection in the improbable corridors of human activity. Let the statistical rollicking begin!

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To chase after the statistical quirks and uproarious riddles hiding within the connection between hazardous materials removal workers and the pursuit of 'humble pi', we embarked on a madcap journey that would make even the most daring explorers blush with envy. With a satchel full of data and a twinkle in our eye, we dove headfirst into the labyrinth of research methodologies, aiming to peel back the layers of this enigmatic association.

Data Collection:

The hunt for data led us through the hallowed halls of the Bureau of Labor Statistics, where we gleaned information on the number of hazardous materials removal workers in the illustrious state of Kansas. We combed through these figures with the precision of a diamond cutter, ensuring not a single data point was left unturned. As for the digital pursuit of 'humble pi', we harnessed the untamed beast known as Google Trends, allowing us to capture the zeitgeist of mathematical mirth across the vast expanse of the internet. We cast our net wide, spanning the years from 2004 to 2022, ensuring that no morsel of potential correlation slipped through our fingers.

Data Analysis:

With our coffers brimming with data, we applied the time-honored art of statistical tomfoolery to uncover any whispers of correlation between these two seemingly disparate phenomena. Our trusty statistical software stood at the ready, armed with an arsenal of correlation coefficients, p-values, and confidence intervals. We placed our findings under the microscope, scrutinizing them with the ruthless determination of a comedian perfecting a punchline.

Statistical Measures:

In our quest to quantify the relationship between hazardous materials removal workers and the pursuit of 'humble pi', we calculated the Pearson correlation coefficient with the precision of a watchmaker assembling a timepiece. This allowed us to gauge the strength and direction of any potential association, laying bare the inner workings of this cheeky statistical tango. Furthermore, we subjected our findings to the crucible of hypothesis testing, ensuring that any hints of correlation were not mere figments of statistical whimsy but robust and bona fide revelations.

Potential Confounders and Limitations:

As with any daring expedition into the realm of statistical merriment, we remained vigilant for lurking confounders seeking to throw a monkey wrench into our revelry. While we endeavored to unearth the core of the connection between hazardous materials and 'humble pi', we remained acutely aware of the potential limitations inherent in our chosen data sources and analytical techniques. After all, even the most intrepid statistical voyagers must tread lightly in the face of uncertainty.

In conclusion, armed with an insatiable curiosity and a penchant for the peculiar, we navigated the choppy waters of statistical inquiry in pursuit of the union of hazardous materials removal workers and the pursuit of 'humble pi'. Our methodology, though infused with levity and whimsy, remained steadfast in its commitment to unraveling this delightful conundrum. With data in hand and statistical tools at the ready, we endeavored to harness the spirit of scientific inquiry while embracing the unexpected twists and turns that make such investigations an exhilarating pursuit. Let the laughter and statistical revelry continue!

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between The number of hazardous materials removal workers in Kansas and Google searches for 'humble pi'. 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]]
Humble Pi and Hazardous Materials: Hilarious Hunch or Statistical Surprise?

[[ABSTRACT]]
In this tongue-in-cheek research paper, we present an investigation into the perplexing correlation between the number of hazardous materials removal workers in Kansas and Google searches for 'humble pi'. Armed with data from the Bureau of Labor Statistics and Google Trends, we set out to unravel this curiosity. To our astonishment, we found a correlation coefficient of 0.7277493 and p < 0.01 for the time period spanning 2004 to 2022. Our findings may leave you chuckling or scratching your head – but either way, they certainly fuel the debate on the intersection of mathematical humor and occupational hazards.

[[LITERATURE REVIEW]]
The pursuit of understanding the offbeat correlation between hazardous materials removal workers in Kansas and Google searches for 'humble pi' has drawn the attention of scholars and researchers in various fields. Smith et al. (2010) explored the enigmatic world of unexpected correlations, delving into the realms of occupational data and internet search behaviors. Their findings shed light on the potential link between occupational hazards and peculiar online pursuits, paving the way for further exploration into this comically perplexing intersection.
Doe (2015) extended this inquiry by examining the psychological underpinnings of individuals' search patterns for mathematical humor amidst the context of hazardous occupation environments. Their work revealed intriguing insights into the cognitive mechanisms that contribute to such seemingly whimsical search behaviors, challenging conventional notions of correlation and causal inference in the digital age.
Jones (2018) took a hands-on approach to the subject matter, immersing themselves in the world of hazardous materials removal workers to unravel the humor-laden mystery of 'humble pi' searches. Their ethnographic study provided a rich tapestry of real-life anecdotes and observations, offering a glimpse into the daily experiences of workers who navigate the intersection of workplace safety and mathematical merriment.
Venturing beyond the traditional confines of scholarly research, the investigation at hand draws inspiration from an eclectic array of literary works and cultural references. In "The Numbers Game: A Humorous Journey through Mathematics" by Adams (2009), the author humorously explores the quirky facets of numerical concepts, inspiring a fresh perspective on the mathematical musings that captivate online searchers.
Furthermore, the whimsical world of fiction offers its own unique take on improbable connections and unexpected juxtapositions. "The Curious Incident of the Dog in the Night-Time" by Haddon (2003) and "The Mathematics of Love" by Bellos (2006) beckon the reader into the labyrinth of human behavior, where the unforeseen convergence of hazardous materials and mathematical jest may find an unexpected echo.
In the realm of games and recreation, the board game "Pandemic" offers a humorous yet pertinent analogy to the interplay of hazardous materials and unlikely searches, reminding us of the delicate balance between risk and unforeseen outcomes in the pursuit of both occupational safety and mathematical humor.
As we navigate this wacky landscape of scholarly inquiry and offbeat cultural touchstones, the inherent charm of this inquiry lies not only in its statistical rigor but also in its ability to tickle the intellect and evoke a sense of delightful bewilderment. With a nod to the unexpected and a wink to the whimsical, we set the stage for an exploration that promises to unravel the peculiar correlation between hazardous materials and 'humble pi' with equal parts scientific scrutiny and lighthearted curiosity. Onward we merrily march, dear reader, into the comically perplexing intersections of human activity!

[[RESULTS]]
In the tradition of great scientific discoveries and dubious revelations, we present the results of our investigation into the correlation between the number of hazardous materials removal workers in Kansas and the Google search interest for 'humble pi'. Brace yourselves for the statistical rollercoaster ahead, as we reveal the enigmatic connection that has left us both amused and bemused.
Our analysis revealed a tantalizing correlation coefficient of 0.7277493 between the two variables, accompanied by an r-squared value of 0.5296190. Such statistical sorcery is rarely witnessed in the wilds of data analysis, prompting equal parts astonishment and amusement among our research team. To add an additional layer of jaw-dropping revelation, the p-value of less than 0.01 sent shockwaves through our statistical sensibilities, reaffirming the legitimacy of this baffling correlation.
Fig. 1 showcases the scatterplot that captures the sheer audacity of the relationship between hazardous materials removal workers and the pursuit of 'humble pi'. Behold the entanglement of occupational hazards and mathematical mischief, immortalized in the form of data points dancing across the plot with a whimsical glee that defies conventional expectations.
With these findings, we extend an open invitation to the scientific community to ponder the peculiar bond between these seemingly unrelated domains. The line between statistical significance and serendipitous folly has never been blurrier, ushering in a new era of contemplation and chuckles in the realm of research. Let the merriment and pondering begin!

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

In unpacking the perplexing correlation between hazardous materials removal workers in Kansas and Google searches for 'humble pi', our findings have not only riddled us with amusement but also fortified the foundations laid by previous scholarly endeavors. Smith et al. (2010) initially hinted at the intriguing interplay between occupational hazards and online peculiarities, and our findings have lent substantial credence to this eyebrow-raising connection.

The spine-tingling correlation coefficient of 0.7277493 that emerged from our statistical spelunking aligns eerily with the musings of Doe (2015), who probed the psychological motivations underlying the seemingly whimsical search patterns for mathematical humor in the context of hazardous occupational settings. With an r-squared value of 0.5296190, our results echo the cognitive conundrums posited by Doe, underscoring the idiosyncrasies that underpin the pursuit of 'humble pi' amidst the backdrop of occupational hazards.

As we lovingly gaze upon Fig. 1, the visually striking scatterplot encapsulates the very essence of this unconventional union. The data points, emboldened by their statistical significance and steeped in the fine art of whimsy, prance across the plot with a fervor that not only defies expectations but tickles the intellect with an equally robust measure of statistical validity.

Venturing into uncharted territories of occupational safety and mathematical mirth, our study has fortified the ladder of understanding, drawing from diverse sources of inspiration including the witty whimsy of Adams (2009), the enigmatic allure of Haddon's "The Curious Incident of the Dog in the Night-Time", and the salient metaphorical resonance of the game "Pandemic". Such intersections of scholarship and culture not only enrich the academic landscape but also infuse it with a delightful sense of bewilderment and merriment.

This study blurs the lines between statistical rigor and serendipitous amusement, inviting scholars and enthusiasts alike to engage in a playful dance of investigation and speculation. The captivating correlation we've unraveled prompts a deep sense of wonder, serving as a tribute to the whimsy that lurks within the folds of data and the nuanced interplay between occupational hazards and the pursuit of mathematical merriment. Let the merriment and contemplation continue to flourish as we navigate the comical quagmire of human pursuits and statistical surprises!

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between The number of hazardous materials removal workers in Kansas and Google searches for 'humble pi'. 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]]
Humble Pi and Hazardous Materials: Hilarious Hunch or Statistical Surprise?

[[ABSTRACT]]
In this tongue-in-cheek research paper, we present an investigation into the perplexing correlation between the number of hazardous materials removal workers in Kansas and Google searches for 'humble pi'. Armed with data from the Bureau of Labor Statistics and Google Trends, we set out to unravel this curiosity. To our astonishment, we found a correlation coefficient of 0.7277493 and p < 0.01 for the time period spanning 2004 to 2022. Our findings may leave you chuckling or scratching your head – but either way, they certainly fuel the debate on the intersection of mathematical humor and occupational hazards.

[[INTRDUCTION]]
Ladies and gentlemen, esteemed colleagues, and fellow aficionados of statistical shenanigans, welcome to the wacky world of correlation where the only constant is the unpredictability of human behavior. In this whimsical journey of exploration and analysis, we venture into the unexpected nexus of hazardous materials removal workers in the sunflower state of Kansas and the perplexing pursuit of 'humble pi' in the digital realm.
As the old adage goes, truth is often stranger than fiction, and our investigation delves into the peculiar relationship, or lack thereof, between these seemingly disparate phenomena. The juxtaposition of hazardous materials and mathematical merriment may evoke a smirk, a raised eyebrow, or even a hearty chuckle, but hidden within this levity lies a nugget of scientific intrigue that we simply cannot ignore – the pursuit of unlikely connections in the vast landscape of human activity.
In an effort to unravel this enigma, we find ourselves armed with the tools of modern data analysis, drawing from the reputable repositories of the Bureau of Labor Statistics and the labyrinthine depths of Google Trends. With bated breath and a dash of skepticism, we set out on this journey of statistical tomfoolery, fully aware that the most unexpected discoveries often emerge from the most unusual pairings.
The question dangling before us, like a punchline waiting to be delivered, is whether the correlation we unmask between hazardous materials removal workers and the search for 'humble pi' is the result of earnest coincidence or a stroke of statistical humor. Are we to be met with a fitting punchline or a sobering revelation that shakes the very foundation of our assumptions? Join us, dear reader, as we embark on this perplexing, and potentially comical, quest for connection in the improbable corridors of human activity. Let the statistical rollicking begin!

[[RESULTS]]
In the tradition of great scientific discoveries and dubious revelations, we present the results of our investigation into the correlation between the number of hazardous materials removal workers in Kansas and the Google search interest for 'humble pi'. Brace yourselves for the statistical rollercoaster ahead, as we reveal the enigmatic connection that has left us both amused and bemused.
Our analysis revealed a tantalizing correlation coefficient of 0.7277493 between the two variables, accompanied by an r-squared value of 0.5296190. Such statistical sorcery is rarely witnessed in the wilds of data analysis, prompting equal parts astonishment and amusement among our research team. To add an additional layer of jaw-dropping revelation, the p-value of less than 0.01 sent shockwaves through our statistical sensibilities, reaffirming the legitimacy of this baffling correlation.
Fig. 1 showcases the scatterplot that captures the sheer audacity of the relationship between hazardous materials removal workers and the pursuit of 'humble pi'. Behold the entanglement of occupational hazards and mathematical mischief, immortalized in the form of data points dancing across the plot with a whimsical glee that defies conventional expectations.
With these findings, we extend an open invitation to the scientific community to ponder the peculiar bond between these seemingly unrelated domains. The line between statistical significance and serendipitous folly has never been blurrier, ushering in a new era of contemplation and chuckles in the realm of research. Let the merriment and pondering begin!

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation has shed light on the inexplicably entertaining correlation between the number of hazardous materials removal workers in Kansas and the Google search interest for 'humble pi'. We have unraveled a statistical tapestry that is as unpredictable as a punchline from a seasoned comedian, leaving us both puzzled and tickled by the whims of data.

The correlation coefficient of 0.7277493 and the p-value of less than 0.01 add a touch of statistical spice to this curious connection, serving as a reminder that the world of research is not without its own brand of slapstick humor. As we reflect on the scatterplot that captures this improbable relationship, one cannot help but chuckle at the sight of hazardous materials and mathematical musings converging in a dance of absurdity.

In the grand tradition of scientific inquiry, our findings raise more questions than they answer. What cosmic forces conspired to tether these seemingly unrelated phenomena together? Should we expect hazardous materials removal workers to swap hazmat suits for mathematical equations? Will 'humble pi' become the unofficial mascot of occupational safety?

As we bid adieu to this whimsical journey of statistical exploration, we must acknowledge that the pursuit of knowledge is often punctuated with moments of sheer delight and bemusement. However, it is with the utmost seriousness that we assert: no further research is needed in this charmingly baffling territory of statistical surprise and mathematical mayhem.

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 Humble Pi and Hazardous Materials: Hilarious Hunch or Statistical Surprise?. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Irreverent Statistics

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 Humble Pi and Hazardous Materials: Hilarious Hunch or Statistical Surprise?. Respond only with the name of a fictional organization.

ChatGPT:

The Consortium for Applied Mathematics and Comedic Engineering

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 Humble Pi and Hazardous Materials: Hilarious Hunch or Statistical Surprise? with an abstract of In this tongue-in-cheek research paper, we present an investigation into the perplexing correlation between the number of hazardous materials removal workers in Kansas and Google searches for 'humble pi'. Armed with data from the Bureau of Labor Statistics and Google Trends, we set out to unravel this curiosity. To our astonishment, we found a correlation coefficient of 0.7277493 and p < 0.01 for the time period spanning 2004 to 2022. Our findings may leave you chuckling or scratching your head – but either way, they certainly fuel the debate on the intersection of mathematical humor and occupational hazards.

ChatGPT:

hazardous materials removal workers, Kansas, correlation, Google searches, "humble pi", Bureau of Labor Statistics, Google Trends, correlation coefficient, statistical significance, mathematical humor, occupational hazards

*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 hazardous materials removal workers in Kansas
Detailed data title: BLS estimate of hazardous materials removal workers in Kansas
Source: Bureau of Larbor Statistics
See what else correlates with The number of hazardous materials removal workers in Kansas

Google searches for 'humble pi'
Detailed data title: Relative volume of Google searches for 'humble pi' (Worldwide, without quotes)
Source: Google Trends
Additional Info: ^{See full details} Relative search volume (not absolute numbers)

See what else correlates with Google searches for 'humble pi'

Correlation r = 0.7277493 (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 = 0.5296190 (Coefficient of determination)
This means 53% of the change in the one variable (i.e., Google searches for 'humble pi') is predictable based on the change in the other (i.e., The number of hazardous materials removal workers in Kansas) over the 19 years from 2004 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00041.^Show 0.0004127227705781451500000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.73 in 0.041% of random cases. Said differently, if you correlated 2,423 random variables^Note Which I absolutely did.
with the same 18 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 18 because we have two variables measured over a period of 19 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.

[ 0.41, 0.89 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!

All values for the years included above: ^Note If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
The number of hazardous materials removal workers in Kansas (Laborers)	370	440	280	220	150	290	320	280	190	230	220	260	290	280	240	750	770	390	420
Google searches for 'humble pi' (Rel. search volume)	13.25	5	0	2.83333	0.75	0.333333	1.41667	0	2.5	5.5	4.5	4.08333	3.41667	4.25	4.33333	12.25	11.0833	7.25	7.75

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."

# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([370,440,280,220,150,290,320,280,190,230,220,260,290,280,240,750,770,390,420,])
array_2 = np.array([13.25,5,0,2.83333,0.75,0.333333,1.41667,0,2.5,5.5,4.5,4.08333,3.41667,4.25,4.33333,12.25,11.0833,7.25,7.75,])
array_1_name = "The number of hazardous materials removal workers in Kansas"
array_2_name = "Google searches for 'humble pi'"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only The number of hazardous materials removal workers in Kansas
Line chart for only Google searches for 'humble pi'
AI-generated correlation image
The spurious research paper: Humble Pi and Hazardous Materials: Hilarious Hunch or Statistical Surprise?

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Correlation ID: 4181 · Black Variable ID: 8298 · Red Variable ID: 1490


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