Spurious correlation #1,465 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion and the second variable is Automotive recalls issued by Honda. The chart goes from 1979 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 Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion and the second variable is Automotive recalls issued by Honda. The chart goes from 1979 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

The champion's frequent hotdog consumption led to an unprecedented demand for Nathan's hotdogs, triggering a chain reaction. This surge in production put a strain on the transportation industry, especially on delivery trucks, some of which were Hondas, ultimately leading to the need for automotive recalls to address the unexpected wear and tear. It seems the wiener really did drive up some unintended ketchupacity on the roads, forcing Honda to relish the opportunity to beef up their vehicle safety. Remember, when it comes to competitive eating and automotive recalls, it's not just about getting to the finish line – it's about how you relish the journey!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image that has the visual style of a scene from a Pixar movie. Within the image, depict a bustling stadium where the reigning champion of the Nathan's Hot Dog Eating Competition is devouring a mountain of hotdogs with determination. Simultaneously, set the scene in a bustling Honda dealership with a row of cars parked, each featuring a labeled "Recall" tag on their windshield. 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: Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion and Automotive recalls issued by Honda. 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: Symbolism An image that looks like it is a scene from a Pixar movie An image that looks like it is a scene from a Pixar movie Minimalism Psychedelic
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 Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion and Automotive recalls issued by Honda together. Keep the description simple.
ChatGPT: In a busy stadium, the reigning Nathan's Hot Dog Eating Competition champion, a determined look on his face, is seen devouring a mountain of hotdogs at lightning speed. Meanwhile, in a bustling Honda dealership, a row of cars is parked, each featuring a labeled "Recall" tag on their windshield.

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 busy stadium, the reigning Nathan's Hot Dog Eating Competition champion, a determined look on his face, is seen devouring a mountain of hotdogs at lightning speed. Meanwhile, in a bustling Honda dealership, a row of cars is parked, each featuring a labeled "Recall" tag on their windshield. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that has the visual style of a scene from a Pixar movie. Within the image, depict a bustling stadium where the reigning champion of the Nathan's Hot Dog Eating Competition is devouring a mountain of hotdogs with determination. Simultaneously, set the scene in a bustling Honda dealership with a row of cars parked, each featuring a labeled "Recall" tag on their windshield.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion caused Automotive recalls issued by Honda to increase. Include one good pun.

AI academic paper

(Because p < 0.01)

Reckless Hot Dogs and Recalled Cars: A Link Between Competitive Eating and Automotive Safety

The International Journal of Gastronomic Engineering and Automotive Safety

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 Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion and Automotive recalls issued by Honda. 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 a few real TV shows that sound like they might be relevant to the topic that you watched as research.

Here is the title and abstract of the paper:
[[TITLE]]
Reckless Hot Dogs and Recalled Cars: A Link Between Competitive Eating and Automotive Safety

[[ABSTRACT]]
In this paper, we aim to investigate the curious correlation between the annual consumption of hot dogs by the reigning champion of Nathan's Famous Hot Dog Eating Contest and the number of automotive recalls issued by Honda. While initially the idea may seem as appealing as a soggy bun, we delved deep into the data sourced from Wikipedia and the US Department of Transportation to uncover a rather surprising finding. Our analysis revealed a correlation coefficient of 0.8263987 and a p-value of less than 0.01, indicating a strong statistical association between these seemingly unrelated phenomena from 1979 to 2022. Through a thorough exploration of this unexpected connection, we shed light on the quirky nuances of human behavior and the potential for unintended consequences of indulging in excessive consumption, whether it be of hot dogs or unbridled competition. This study not only serves as a playful nod to the unpredictable intersections of human behavior and industrial occurrences but also highlights the importance of exploring unconventional correlations that may uncover the hidden truths behind our everyday quirks and cravings. So, while you may be cautious in consuming too many hot dogs, it seems that Honda should also take heed and ensure that their cars are not "re-collie-d" due to unforeseen but tantalizingly correlated factors.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intersection of competitive eating and automotive safety may at first glance appear to be a comedic juxtaposition, much like a food fight in a car showroom. However, as bizarre as it may seem, our curiosity was piqued by the potential link between the annual hot dog consumption of the Nathan's Hot Dog Eating Contest champion and the frequency of automotive recalls issued by Honda.
As researchers, we are accustomed to delving into the depths of data, sifting through statistical noise like the breadcrumbs of a particularly messy hot dog eating contest, in search of meaningful patterns. And indeed, our quest led us to uncover an unexpectedly strong correlation between these disparate variables. It seems that while the reigning champion is earnestly piling on the hot dogs, Honda may be grappling with more than just "dogged" engineering challenges.
The aim of this study is to dissect, not the hot dogs themselves, but rather the correlation between the indulgence in competitive eating and the potential repercussions in the automotive industry. Much like the careful dissection of a laboratory specimen, we embarked on a thorough exploration of data sourced from reliable sources, only this time, it involved a different kind of "taste test" and a more unexpected avenue of "recall" investigation.
Through our rigorous analysis, we hope to shed light on this curious correlation and uncover insights that may have previously gone unnoticed amidst the statistical noise. This study is not merely a whimsical exercise in the peculiar, but rather a testament to the potential serendipity of research and the uncovering of connections that defy traditional expectations. So, hold on to your seats as we embark on this journey, for we may discover that the link between hot dogs and automobiles is more than just a condiment-laden coincidence.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Statistical Analysis of Competitive Eating and Its Unintended Consequences," Smith et al. delve into the esophagus-stretching world of competitive eating, examining the physiological and psychological implications of gorging oneself on various food items, from hot dogs to hamburgers. However, they fail to consider the potential ripple effect of such endeavors on industries seemingly unrelated to the culinary arts, leaving us hungry for a more comprehensive understanding of the wider impact of competitive eating.

Moving from the realm of academic research to the more palatable realm of popular non-fiction, Doe's "Eating Champions: Gluttony and Glory" provides an in-depth exploration of the competitive eating circuit, uncovering the lengths individuals will go to in pursuit of gastronomic greatness. Unfortunately, it overlooks the potential ramifications of such pursuits on the automotive industry, leaving us with more of a cognitive indigestion than a comprehensive understanding of the broader implications.

In Jones' "Dangers Lurking in Unlikely Places," the author investigates the surprising ways in which seemingly unrelated factors can influence one another, uncovering a myriad of peculiar connections that often go unnoticed. However, the link between competitive eating and automotive recalls is conspicuously absent from the discussion, which leaves us feeling a bit like the lone condiment-less hot dog at a picnic – overlooked and unsatisfied.

As we transition from more serious literature to the realm of fiction, it's worth noting that books such as John Steinbeck's "The Grapes of Wrath" and F. Scott Fitzgerald's "The Great Gatsby" offer subtle hints of the underlying tensions between indulgence and consequences, albeit within entirely different contexts. While these classics may not directly address hot dog consumption or automotive recalls, they remind us that unintended outcomes often stem from unchecked excess and unbridled ambition, much like attempting to consume an inordinate number of hot dogs against all odds.

On the more unconventional side, TV shows like "Man vs. Food" and "Top Gear" take viewers on a whirlwind journey through the world of extreme eating challenges and automotive escapades. While entertaining, these shows fail to draw explicit connections between the two seemingly disparate realms, leaving us with a hunger for more substantive analysis and an insatiable thirst for uncovering the hidden correlations lurking within the realms of gluttonous competition and vehicular engineering.

It's abundantly clear that our quest for understanding the interaction between hot dog consumption and automotive recalls transcends traditional disciplinary boundaries, requiring us to venture beyond the confines of conventional literature and into the realm of unexpected connections and humorous musings.

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 Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion and Automotive recalls issued by Honda. 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 Wikipedia and US DOT . You used data from 1979 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]]
Reckless Hot Dogs and Recalled Cars: A Link Between Competitive Eating and Automotive Safety

[[ABSTRACT]]
In this paper, we aim to investigate the curious correlation between the annual consumption of hot dogs by the reigning champion of Nathan's Famous Hot Dog Eating Contest and the number of automotive recalls issued by Honda. While initially the idea may seem as appealing as a soggy bun, we delved deep into the data sourced from Wikipedia and the US Department of Transportation to uncover a rather surprising finding. Our analysis revealed a correlation coefficient of 0.8263987 and a p-value of less than 0.01, indicating a strong statistical association between these seemingly unrelated phenomena from 1979 to 2022. Through a thorough exploration of this unexpected connection, we shed light on the quirky nuances of human behavior and the potential for unintended consequences of indulging in excessive consumption, whether it be of hot dogs or unbridled competition. This study not only serves as a playful nod to the unpredictable intersections of human behavior and industrial occurrences but also highlights the importance of exploring unconventional correlations that may uncover the hidden truths behind our everyday quirks and cravings. So, while you may be cautious in consuming too many hot dogs, it seems that Honda should also take heed and ensure that their cars are not "re-collie-d" due to unforeseen but tantalizingly correlated factors.

[[INTRODUCTION]]
The intersection of competitive eating and automotive safety may at first glance appear to be a comedic juxtaposition, much like a food fight in a car showroom. However, as bizarre as it may seem, our curiosity was piqued by the potential link between the annual hot dog consumption of the Nathan's Hot Dog Eating Contest champion and the frequency of automotive recalls issued by Honda.
As researchers, we are accustomed to delving into the depths of data, sifting through statistical noise like the breadcrumbs of a particularly messy hot dog eating contest, in search of meaningful patterns. And indeed, our quest led us to uncover an unexpectedly strong correlation between these disparate variables. It seems that while the reigning champion is earnestly piling on the hot dogs, Honda may be grappling with more than just "dogged" engineering challenges.
The aim of this study is to dissect, not the hot dogs themselves, but rather the correlation between the indulgence in competitive eating and the potential repercussions in the automotive industry. Much like the careful dissection of a laboratory specimen, we embarked on a thorough exploration of data sourced from reliable sources, only this time, it involved a different kind of "taste test" and a more unexpected avenue of "recall" investigation.
Through our rigorous analysis, we hope to shed light on this curious correlation and uncover insights that may have previously gone unnoticed amidst the statistical noise. This study is not merely a whimsical exercise in the peculiar, but rather a testament to the potential serendipity of research and the uncovering of connections that defy traditional expectations. So, hold on to your seats as we embark on this journey, for we may discover that the link between hot dogs and automobiles is more than just a condiment-laden coincidence.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To investigate the enigmatic connection between the consumption of hot dogs by the reigning Nathan's Famous Hot Dog Eating Contest champion and the issuance of automotive recalls by Honda, we embarked on a methodological journey that was as intriguing as it was unconventional. The aim was to tease out any potential relationship between these seemingly incongruous variables, employing a dash of statistical wizardry and a dollop of good-natured curiosity.

First, we harnessed the power of the internet to gather data stretching back to the year 1979, a time when hot dogs likely had a more "vintage" appeal, and automotive engineering was embarking on the road to technological transformation. Sources for our data primarily included Wikipedia for the annual hot dog consumption by the reigning champion and the US Department of Transportation for the records of automotive recalls by Honda. It's a testament to the 21st century that such a lighthearted investigation could draw upon the wealth of information afforded by modern technology, not to mention the reliability of Wikipedia for all our quirky statistical needs.

With our data in hand, we applied a medley of statistical analyses to unearth any potential relationship between these variables. We performed a Pearson correlation test, a method more traditionally applied to explore the association between variables that are less, well, "bunusual," but nonetheless well-suited to uncovering patterns in our unusual dataset. The resulting correlation coefficient and p-value served as our guides through this statistical maze, revealing the strength and significance of any observed association. In the end, we arrived at a correlation coefficient of 0.8263987 and a p-value of less than 0.01, signaling a robust statistical connection between the annual hot dog consumption and the frequency of automotive recalls by Honda.

Additionally, we employed time series analysis to study the temporal dynamics of the relationship. This allowed us to peek behind the curtain of time and observe how the patterns of hot dog consumption may have woven themselves into the fabric of automotive recall occurrences over the years, much like a curious game of culinary cat's cradle.

In our quest for understanding, we also accounted for potential confounding variables, ensuring that our findings were not obscured by lurking statistical tricksters. This involved considering factors such as changes in hot dog eating techniques (who knows what new hot dog-dipping method might have emerged over the years!) and advancements in automotive technology that might influence recall patterns.

Finally, we unleashed the power of visualization, summoning bar graphs and scatterplots to breathe life into our findings and engage the imagination of our readers. These visual representations brought the quantitative relationships to life, providing a colorful backdrop to our peculiar tale of spirited hot dog consumption and the potential ripples through the automotive industry.

Overall, our methodological approach was an eclectic blend of statistical analyses, creative thinking, and a healthy dose of good humor, befitting the unconventional nature of our inquiry. So, as we take a statistical bite out of this peculiar investigation, let's remember that sometimes, it's the quirkier questions that lead to the most unexpected "relish" in research.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the 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 Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion and Automotive recalls issued by Honda. 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]]
Reckless Hot Dogs and Recalled Cars: A Link Between Competitive Eating and Automotive Safety

[[ABSTRACT]]
In this paper, we aim to investigate the curious correlation between the annual consumption of hot dogs by the reigning champion of Nathan's Famous Hot Dog Eating Contest and the number of automotive recalls issued by Honda. While initially the idea may seem as appealing as a soggy bun, we delved deep into the data sourced from Wikipedia and the US Department of Transportation to uncover a rather surprising finding. Our analysis revealed a correlation coefficient of 0.8263987 and a p-value of less than 0.01, indicating a strong statistical association between these seemingly unrelated phenomena from 1979 to 2022. Through a thorough exploration of this unexpected connection, we shed light on the quirky nuances of human behavior and the potential for unintended consequences of indulging in excessive consumption, whether it be of hot dogs or unbridled competition. This study not only serves as a playful nod to the unpredictable intersections of human behavior and industrial occurrences but also highlights the importance of exploring unconventional correlations that may uncover the hidden truths behind our everyday quirks and cravings. So, while you may be cautious in consuming too many hot dogs, it seems that Honda should also take heed and ensure that their cars are not "re-collie-d" due to unforeseen but tantalizingly correlated factors.

[[LITERATURE REVIEW]]
In "Statistical Analysis of Competitive Eating and Its Unintended Consequences," Smith et al. delve into the esophagus-stretching world of competitive eating, examining the physiological and psychological implications of gorging oneself on various food items, from hot dogs to hamburgers. However, they fail to consider the potential ripple effect of such endeavors on industries seemingly unrelated to the culinary arts, leaving us hungry for a more comprehensive understanding of the wider impact of competitive eating.
Moving from the realm of academic research to the more palatable realm of popular non-fiction, Doe's "Eating Champions: Gluttony and Glory" provides an in-depth exploration of the competitive eating circuit, uncovering the lengths individuals will go to in pursuit of gastronomic greatness. Unfortunately, it overlooks the potential ramifications of such pursuits on the automotive industry, leaving us with more of a cognitive indigestion than a comprehensive understanding of the broader implications.
In Jones' "Dangers Lurking in Unlikely Places," the author investigates the surprising ways in which seemingly unrelated factors can influence one another, uncovering a myriad of peculiar connections that often go unnoticed. However, the link between competitive eating and automotive recalls is conspicuously absent from the discussion, which leaves us feeling a bit like the lone condiment-less hot dog at a picnic – overlooked and unsatisfied.
As we transition from more serious literature to the realm of fiction, it's worth noting that books such as John Steinbeck's "The Grapes of Wrath" and F. Scott Fitzgerald's "The Great Gatsby" offer subtle hints of the underlying tensions between indulgence and consequences, albeit within entirely different contexts. While these classics may not directly address hot dog consumption or automotive recalls, they remind us that unintended outcomes often stem from unchecked excess and unbridled ambition, much like attempting to consume an inordinate number of hot dogs against all odds.
On the more unconventional side, TV shows like "Man vs. Food" and "Top Gear" take viewers on a whirlwind journey through the world of extreme eating challenges and automotive escapades. While entertaining, these shows fail to draw explicit connections between the two seemingly disparate realms, leaving us with a hunger for more substantive analysis and an insatiable thirst for uncovering the hidden correlations lurking within the realms of gluttonous competition and vehicular engineering.
It's abundantly clear that our quest for understanding the interaction between hot dog consumption and automotive recalls transcends traditional disciplinary boundaries, requiring us to venture beyond the confines of conventional literature and into the realm of unexpected connections and humorous musings.

[[RESULTS]]
The statistical analysis of the data collected revealed a striking correlation between the annual consumption of hot dogs by the reigning champion of Nathan's Famous Hot Dog Eating Contest and the number of automotive recalls issued by Honda. Our findings unveiled a correlation coefficient of 0.8263987, indicating a strong positive relationship between these seemingly unrelated variables. This result suggests that as the consumption of hot dogs by the champion soared to unprecedented levels, the likelihood of automotive recalls by Honda increased substantially, much like the aftermath of a particularly exuberant hot dog eating contest.
Furthermore, the coefficient of determination (r-squared) of 0.6829348 indicates that approximately 68.29% of the variance in the number of automotive recalls by Honda can be explained by the annual hot dog consumption of the champion. This implies that the champion's affinity for hot dog consumption may have a significant influence on the occurrence of automotive recalls, a connection that is as unexpected as finding a pickle in a hot dog bun.
The p-value of less than 0.01 further solidifies the strength of this relationship, indicating that the likelihood of observing such a strong correlation by random chance is less than 1%. This statistical significance suggests that the association between the hot dog consumption and automotive recalls is not merely coincidental, unlike finding a forgotten mustard packet in the depths of a picnic basket.
To visually depict this unexpected correlation, Fig. 1 presents a scatterplot illustrating the strong positive relationship between the annual hot dog consumption by the champion and the number of automotive recalls issued by Honda. It is noteworthy that the relationship depicted in the scatterplot appears as clear as a streak of mustard on a pristine hot dog bun.
In summary, our findings provide robust evidence of a remarkable association between the annual hot dog consumption by the champion of Nathan's Famous Hot Dog Eating Contest and the frequency of automotive recalls issued by Honda. This unexpected correlation serves as a reminder that serendipitous discoveries can arise from seemingly obscure connections, much like finding a misplaced hot dog in the deli aisle of a grocery store.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our investigation into the connection between the annual consumption of hot dogs by the reigning champion of Nathan's Famous Hot Dog Eating Contest and the number of automotive recalls issued by Honda has yielded some tantalizingly unexpected results. While it may have seemed like a mere flight of fancy to explore the interplay between hot dog eating and automotive safety, our findings provide compelling evidence of a robust association between these seemingly incongruous variables.

As we heeded the call to delve into unconventional correlations, we were met with the surprising revelation of a strong positive relationship between the consumption of hot dogs and the frequency of automotive recalls. Our results align with prior research that emphasized the interconnectedness of seemingly unrelated factors, such as the ripple effect of competitive eating on industries beyond the culinary sphere.

Building upon the foundation laid by Smith et al., who explored competitive eating's unintended consequences, we extended this line of inquiry to shed light on its broader implications. Like a hot dog nestled in a sea of condiments, our study stands out amidst the academic landscape, offering a fresh perspective on the influence of indulgent behaviors on industrial outcomes.

Moreover, the statistical significance of our findings, with a p-value of less than 0.01, solidifies the validity of our observed relationship, much like the reliability of finding onions on a New York-style hot dog. This reinforces the need to embrace unexpected correlations, no matter how eccentric they may initially seem, as they can unearth hidden truths lurking beneath the surface of conventional wisdom, not unlike discovering a well-concealed wiener in a potato salad.

In this pursuit, our study also mirrors the thematic undercurrents found in literary works such as "The Grapes of Wrath" and "The Great Gatsby," where unchecked indulgence and ambition lead to unforeseen repercussions, akin to the aftermath of consuming an excessive number of hot dogs. Our interdisciplinary approach, bridging the realms of competitive eating, automotive engineering, and statistical analysis, reflects the multifaceted nature of uncovering unexpected connections – an undertaking as complex as crafting the perfect hot dog with the ideal condiment-to-bun ratio.

While our findings may leave some scratching their heads, akin to the perplexity of finding a vegetarian hot dog at a carnivore's gathering, they underscore the indispensable nature of rigorous investigation into uncharted territories. After all, embracing offbeat connections and unraveling the mysteries they hold can provide a welcome reprieve from the mundane, much like stumbling upon a surprisingly delectable veggie dog in a sea of meaty fare.

In the grand tapestry of scientific inquiry, our study serves as a testament to the serendipitous discoveries that can emerge from embracing unconventional avenues of exploration, much like finding the unexpected savory crunch of a well-toasted hot dog bun.

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 Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion and Automotive recalls issued by Honda. 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]]
Reckless Hot Dogs and Recalled Cars: A Link Between Competitive Eating and Automotive Safety

[[ABSTRACT]]
In this paper, we aim to investigate the curious correlation between the annual consumption of hot dogs by the reigning champion of Nathan's Famous Hot Dog Eating Contest and the number of automotive recalls issued by Honda. While initially the idea may seem as appealing as a soggy bun, we delved deep into the data sourced from Wikipedia and the US Department of Transportation to uncover a rather surprising finding. Our analysis revealed a correlation coefficient of 0.8263987 and a p-value of less than 0.01, indicating a strong statistical association between these seemingly unrelated phenomena from 1979 to 2022. Through a thorough exploration of this unexpected connection, we shed light on the quirky nuances of human behavior and the potential for unintended consequences of indulging in excessive consumption, whether it be of hot dogs or unbridled competition. This study not only serves as a playful nod to the unpredictable intersections of human behavior and industrial occurrences but also highlights the importance of exploring unconventional correlations that may uncover the hidden truths behind our everyday quirks and cravings. So, while you may be cautious in consuming too many hot dogs, it seems that Honda should also take heed and ensure that their cars are not "re-collie-d" due to unforeseen but tantalizingly correlated factors.

[[INTRDUCTION]]
The intersection of competitive eating and automotive safety may at first glance appear to be a comedic juxtaposition, much like a food fight in a car showroom. However, as bizarre as it may seem, our curiosity was piqued by the potential link between the annual hot dog consumption of the Nathan's Hot Dog Eating Contest champion and the frequency of automotive recalls issued by Honda.
As researchers, we are accustomed to delving into the depths of data, sifting through statistical noise like the breadcrumbs of a particularly messy hot dog eating contest, in search of meaningful patterns. And indeed, our quest led us to uncover an unexpectedly strong correlation between these disparate variables. It seems that while the reigning champion is earnestly piling on the hot dogs, Honda may be grappling with more than just "dogged" engineering challenges.
The aim of this study is to dissect, not the hot dogs themselves, but rather the correlation between the indulgence in competitive eating and the potential repercussions in the automotive industry. Much like the careful dissection of a laboratory specimen, we embarked on a thorough exploration of data sourced from reliable sources, only this time, it involved a different kind of "taste test" and a more unexpected avenue of "recall" investigation.
Through our rigorous analysis, we hope to shed light on this curious correlation and uncover insights that may have previously gone unnoticed amidst the statistical noise. This study is not merely a whimsical exercise in the peculiar, but rather a testament to the potential serendipity of research and the uncovering of connections that defy traditional expectations. So, hold on to your seats as we embark on this journey, for we may discover that the link between hot dogs and automobiles is more than just a condiment-laden coincidence.

[[RESULTS]]
The statistical analysis of the data collected revealed a striking correlation between the annual consumption of hot dogs by the reigning champion of Nathan's Famous Hot Dog Eating Contest and the number of automotive recalls issued by Honda. Our findings unveiled a correlation coefficient of 0.8263987, indicating a strong positive relationship between these seemingly unrelated variables. This result suggests that as the consumption of hot dogs by the champion soared to unprecedented levels, the likelihood of automotive recalls by Honda increased substantially, much like the aftermath of a particularly exuberant hot dog eating contest.
Furthermore, the coefficient of determination (r-squared) of 0.6829348 indicates that approximately 68.29% of the variance in the number of automotive recalls by Honda can be explained by the annual hot dog consumption of the champion. This implies that the champion's affinity for hot dog consumption may have a significant influence on the occurrence of automotive recalls, a connection that is as unexpected as finding a pickle in a hot dog bun.
The p-value of less than 0.01 further solidifies the strength of this relationship, indicating that the likelihood of observing such a strong correlation by random chance is less than 1%. This statistical significance suggests that the association between the hot dog consumption and automotive recalls is not merely coincidental, unlike finding a forgotten mustard packet in the depths of a picnic basket.
To visually depict this unexpected correlation, Fig. 1 presents a scatterplot illustrating the strong positive relationship between the annual hot dog consumption by the champion and the number of automotive recalls issued by Honda. It is noteworthy that the relationship depicted in the scatterplot appears as clear as a streak of mustard on a pristine hot dog bun.
In summary, our findings provide robust evidence of a remarkable association between the annual hot dog consumption by the champion of Nathan's Famous Hot Dog Eating Contest and the frequency of automotive recalls issued by Honda. This unexpected correlation serves as a reminder that serendipitous discoveries can arise from seemingly obscure connections, much like finding a misplaced hot dog in the deli aisle of a grocery store.

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has uncovered a statistically significant correlation between the hot dog consumption of the Nathan's Famous Hot Dog Eating Contest champion and the frequency of automotive recalls issued by Honda. This unexpected relationship serves as a testament to the unpredictability of human behavior and its potential impact on industrial occurrences, much like the surprise of discovering a rogue condiment at the bottom of a lunch bag.

The correlation coefficient of 0.8263987 and the p-value of less than 0.01 highlight the strength and statistical significance of this connection, making it as clear as a well-dressed hot dog in a world of mundane sandwiches. The coefficient of determination of 0.6829348 further emphasizes the substantial influence of this variable, much like the undeniable influence of the perfect hot dog topping spread.

These findings not only underscore the importance of exploring unconventional correlations but also add a humorous twist to the often serious realm of research, revealing that even the most unlikely pairings can yield meaningful insights. As such, while further studies in this domain may offer additional chuckles, it seems that no more research is needed in this area – we've ketchup'd with all we need to know!

So, let's relish in the knowledge that our findings, much like a well-crafted hot dog, provide a flavorful blend of unexpected connections and empirical evidence.

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 Reckless Hot Dogs and Recalled Cars: A Link Between Competitive Eating and Automotive Safety. Respond only with the name of a fictional academic journal.

ChatGPT:

The International Journal of Gastronomic Engineering and Automotive Safety

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 Reckless Hot Dogs and Recalled Cars: A Link Between Competitive Eating and Automotive Safety. Respond only with the name of a fictional organization.

ChatGPT:

Institute for Gastronomic Research and Vehicular Safety

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 Reckless Hot Dogs and Recalled Cars: A Link Between Competitive Eating and Automotive Safety with an abstract of In this paper, we aim to investigate the curious correlation between the annual consumption of hot dogs by the reigning champion of Nathan's Famous Hot Dog Eating Contest and the number of automotive recalls issued by Honda. While initially the idea may seem as appealing as a soggy bun, we delved deep into the data sourced from Wikipedia and the US Department of Transportation to uncover a rather surprising finding. Our analysis revealed a correlation coefficient of 0.8263987 and a p-value of less than 0.01, indicating a strong statistical association between these seemingly unrelated phenomena from 1979 to 2022. Through a thorough exploration of this unexpected connection, we shed light on the quirky nuances of human behavior and the potential for unintended consequences of indulging in excessive consumption, whether it be of hot dogs or unbridled competition. This study not only serves as a playful nod to the unpredictable intersections of human behavior and industrial occurrences but also highlights the importance of exploring unconventional correlations that may uncover the hidden truths behind our everyday quirks and cravings. So, while you may be cautious in consuming too many hot dogs, it seems that Honda should also take heed and ensure that their cars are not "re-collie-d" due to unforeseen but tantalizingly correlated factors.

ChatGPT:

competitive eating, hot dog consumption, automotive recalls, Nathan's Famous Hot Dog Eating Contest, statistical analysis, correlation coefficient, p-value, unconventional correlations, human behavior, industrial occurrences, unintended consequences

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

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Data details

Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion
Detailed data title: Hotdog Consumption by Nathan's Hot Dog Eating Competition Champion
Source: Wikipedia
See what else correlates with Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion

Automotive recalls issued by Honda
Detailed data title: Automotive recals issued by Honda
Source: US DOT
See what else correlates with Automotive recalls issued by Honda

Correlation r = 0.8263987 (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 = 0.6829348 (Coefficient of determination)
This means 68.3% of the change in the one variable (i.e., Automotive recalls issued by Honda) is predictable based on the change in the other (i.e., Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion) over the 44 years from 1979 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 4.9E-12.^Show 0.0000000000048999053971913590
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 0.83 in 4.9E-10% of random cases. Said differently, if you correlated 204,085,572,871 random variables^Note You don't actually need 204 billion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 43 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 43 because we have two variables measured over a period of 44 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.

[ 0.7, 0.9 ] 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.

	1979	1980	1981	1982	1983	1984	1985	1986	1987	1988	1989	1990	1991	1992	1993	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion (Hotdogs eaten)	9	9.5	11	11	10.5	9.5	11.75	15.5	13.5	10	15.5	16	21.5	19	17	20	19.5	22.25	24.5	19	20.25	25	50	50.5	44.5	53.33	49	53.75	66	59	68	54	62	68	69	61	62	70	72	74	71	75	76	63
Automotive recalls issued by Honda (Recalls)	4	0	1	1	4	5	1	2	3	4	3	3	3	3	3	2	3	6	6	4	9	8	12	11	7	20	13	3	13	7	4	14	16	16	15	15	21	18	17	23	22	18	13	7

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([9,9.5,11,11,10.5,9.5,11.75,15.5,13.5,10,15.5,16,21.5,19,17,20,19.5,22.25,24.5,19,20.25,25,50,50.5,44.5,53.33,49,53.75,66,59,68,54,62,68,69,61,62,70,72,74,71,75,76,63,])
array_2 = np.array([4,0,1,1,4,5,1,2,3,4,3,3,3,3,3,2,3,6,6,4,9,8,12,11,7,20,13,3,13,7,4,14,16,16,15,15,21,18,17,23,22,18,13,7,])
array_1_name = "Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion"
array_2_name = "Automotive recalls issued by Honda"

# 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 Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion
Line chart for only Automotive recalls issued by Honda
AI-generated correlation image
The spurious research paper: Reckless Hot Dogs and Recalled Cars: A Link Between Competitive Eating and Automotive Safety

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Correlation ID: 1465 · Black Variable ID: 500 · Red Variable ID: 1123


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