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Spurious correlation #4,461 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Votes for the Republican Presidential candidate in Virginia and the second variable is Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion.  The chart goes from 1979 to 2020, and the two variables track closely in value over that time. Small Image

AI explanation

As more people in Virginia pledged their allegiance to the Republican candidate, a wave of patriotic fervor swept the state. This surge in national pride led to an unusual spike in hotdog consumption. Perhaps it was a subconscious craving for traditional American fare, or maybe the competitive eating champion felt inspired to uphold the values of red, white, and blue through his impressive consumption feats. Whatever the reason, it seems that in the world of competitive hotdog eating, political preferences and sausage-like implications go hand in hand.

Model: dalle-3
Prompt: Generate an image of a Brutalist-style building in Virginia, with a large gathering of people outside casting their votes for the Republican Presidential candidate. In the foreground, the reigning Nathan's Hot Dog Eating Competition Champion is depicted proudly holding up the American flag, surrounded by a mound of empty hot dog buns. The scene combines the patriotic fervor of the crowd with the sound of hotdogs being devoured, creating a uniquely American scene. The building and the crowd should be depicted in a minimalist Brutalist style, with sharp, angular lines and a stark, industrial feel. 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: Votes for the Republican Presidential candidate in Virginia and Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion. 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: Brutalism Low poly Cutsy art illustration Oragami Cybernetic art
ChatGPT: Brutalism

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 Votes for the Republican Presidential candidate in Virginia and Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion, in the following situation: As more people in Virginia pledged their allegiance to the Republican candidate, a wave of patriotic fervor swept the state. This surge in national pride led to an unusual spike in hotdog consumption. Perhaps it was a subconscious craving for traditional American fare, or maybe the competitive eating champion felt inspired to uphold the values of red, white, and blue through his impressive consumption feats. Whatever the reason, it seems that in the world of competitive hotdog eating, political preferences and sausage-like implications go hand in hand.. Keep the description simple.
ChatGPT: In Virginia, a crowd gathers to cast their votes for the Republican Presidential candidate. Nearby, the reigning Nathan's Hot Dog Eating Competition Champion stands surrounded by a mound of empty hot dog buns, proudly holding up the American flag as his new world record for hotdogs consumed is announced. The cheers of patriotic fervor merge with the sounds of hotdogs being devoured, creating a uniquely American scene.

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: [ Brutalism ] and depicting this scene: In Virginia, a crowd gathers to cast their votes for the Republican Presidential candidate. Nearby, the reigning Nathan's Hot Dog Eating Competition Champion stands surrounded by a mound of empty hot dog buns, proudly holding up the American flag as his new world record for hotdogs consumed is announced. The cheers of patriotic fervor merge with the sounds of hotdogs being devoured, creating a uniquely American scene. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a Brutalist-style building in Virginia, with a large gathering of people outside casting their votes for the Republican Presidential candidate. In the foreground, the reigning Nathan's Hot Dog Eating Competition Champion is depicted proudly holding up the American flag, surrounded by a mound of empty hot dog buns. The scene combines the patriotic fervor of the crowd with the sound of hotdogs being devoured, creating a uniquely American scene. The building and the crowd should be depicted in a minimalist Brutalist style, with sharp, angular lines and a stark, industrial feel.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Votes for the Republican Presidential candidate in Virginia caused Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion to increase. Make it feel plausible.

AI academic paper

(Because p < 0.01)
Making Sausage and Winning Hearts: A Correlational Study of Republican Votes in Virginia and Nathan's Hot Dog Eating Competition Champions' Consumption

The Journal of Gastronomic Politics

Jan 2024
Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.




Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Votes for the Republican Presidential candidate in Virginia and Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Make the title seem clever.

Your research team used data from MIT Election Data and Science Lab, Harvard Dataverse and Wikipedia to assess this nagging question. You found a correlation coefficient of 0.9291854 and p < 0.01 for 1979 to 2020.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
"Making Sausage and Winning Hearts: A Correlational Study of Republican Votes in Virginia and Nathan's Hot Dog Eating Competition Champions' Consumption"

[[ABSTRACT]]
In this paper, we bring attention to a most peculiar junction of political engagement and gastronomic prowess - the correlation between votes for the Republican presidential candidate in Virginia and the quantity of hotdogs consumed by the champion of Nathan's Hot Dog Eating Competition. We delved into this offbeat inquiry with the seriousness it deserves, donning our lab coats and wielding statistics like condiments.

Our research team embarked on a culinary odyssey, navigating through the MIT Election Data and Science Lab and diving into the depths of the Harvard Dataverse to gather relevant political data. Simultaneously, we (figuratively) devoured information on the esteemed winners of Nathan's Hot Dog Eating Competition from trusty sources like Wikipedia. As we crunched the numbers, our findings revealed a correlation coefficient of 0.9291854 and p < 0.01 for the years spanning 1979 to 2020, establishing a surprisingly strong relationship between these seemingly unrelated phenomena.

Now, to appease our hunger for dad jokes, here's one on the house - "Why was the hotdog so fast? Because it’s a real wiener!" Our results not only provide fodder for amusement, but also pique curiosity regarding the underlying mechanisms driving this improbable correlation. As we reflect on this peculiar relationship, we are reminded of the age-old adage: "When the going gets weird, the weird turn pro."


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the introduction section of an academic research paper presenting the findings of the connection between Votes for the Republican Presidential candidate in Virginia and Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
"Making Sausage and Winning Hearts: A Correlational Study of Republican Votes in Virginia and Nathan's Hot Dog Eating Competition Champions' Consumption"

[[ABSTRACT]]
In this paper, we bring attention to a most peculiar junction of political engagement and gastronomic prowess - the correlation between votes for the Republican presidential candidate in Virginia and the quantity of hotdogs consumed by the champion of Nathan's Hot Dog Eating Competition. We delved into this offbeat inquiry with the seriousness it deserves, donning our lab coats and wielding statistics like condiments.

Our research team embarked on a culinary odyssey, navigating through the MIT Election Data and Science Lab and diving into the depths of the Harvard Dataverse to gather relevant political data. Simultaneously, we (figuratively) devoured information on the esteemed winners of Nathan's Hot Dog Eating Competition from trusty sources like Wikipedia. As we crunched the numbers, our findings revealed a correlation coefficient of 0.9291854 and p < 0.01 for the years spanning 1979 to 2020, establishing a surprisingly strong relationship between these seemingly unrelated phenomena.

Now, to appease our hunger for dad jokes, here's one on the house - "Why was the hotdog so fast? Because it’s a real wiener!" Our results not only provide fodder for amusement, but also pique curiosity regarding the underlying mechanisms driving this improbable correlation. As we reflect on this peculiar relationship, we are reminded of the age-old adage: "When the going gets weird, the weird turn pro."

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

Ah, the joys of research - delving into the unknown, uncovering unexpected connections, and ultimately, satisfying our insatiable curiosity. In the realm of statistical analysis, one is often met with the challenge of exploring divergence, yet occasionally, the most whimsical pairings emerge. It is with great delight that we present our findings on the correlation between the number of votes for the Republican presidential candidate in Virginia and the consumption of hotdogs by the champions of Nathan's Hot Dog Eating Competition. If this seems like a peculiar blend of politics and gastronomy, you're not alone. As we ventured into this uncharted territory, we couldn't help but relish the prospect of shedding light on a correlation as enigmatic as a hotdog with relish - that is, both baffling and strangely intriguing.

With our lab coats donned and data sets at the ready, we embarked on a riveting journey through the world of statistical analyses. It was a veritable feast for the intellect, as we embarked on this scholarly pursuit armed with nothing but curiosity and an unquenchable thirst for knowledge. It was a veritable hotdog-eating competition of scientific inquiry; and just like the mysterious allure of a "mystery meat" hotdog, the adventure kept us on the edge of our seats, brimming with anticipation.

Eager to sink our teeth into the matter at hand, we delved into the MIT Election Data and Science Lab to procure the electoral data for the state of Virginia. Simultaneously, we navigated the depths of the Harvard Dataverse, much like a contestant navigating their way through a tower of hotdogs, to obtain the historical results of Nathan's Hot Dog Eating Competition. It was a veritable smorgasbord of information, and just as the sight of a towering hotdog with all the fixings can ignite the appetite, the allure of unraveling this curious correlation fed our scientific fervor.

As we crunched the numbers with as much gusto as a hotdog-eating champion attacking their bounty, our findings revealed a staggering correlation coefficient of 0.9291854 and p < 0.01 for the years spanning 1979 to 2020. The undeniable connection between these seemingly unrelated variables prompted laughter, intrigue, and an abundance of food for thought. It was as if we had stumbled upon the academic equivalent of a perfectly crafted pun – surprising, delightful, and utterly thought-provoking.

Amidst the fervor of our scholarly pursuits, we couldn't resist sharing a dad joke to sizzle the mind—“What did the hotdog say when it crossed the finish line? I’m the wiener!” Our findings not only added a touch of whimsy to the scientific discourse but also ignited a flame of curiosity regarding the underlying mechanisms driving this improbable correlation. As we pondered this peculiarity, we couldn't help but recall the profound words of wisdom: "Research is like trying to find the mustard at a crowded picnic – sometimes, you have to sift through a lot of relish to get to the good stuff." And indeed, our journey has not only entertained us but also presented an opportunity to unearth unexpected intellectual delights.


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Votes for the Republican Presidential candidate in Virginia and Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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]]
"Making Sausage and Winning Hearts: A Correlational Study of Republican Votes in Virginia and Nathan's Hot Dog Eating Competition Champions' Consumption"

[[ABSTRACT]]
In this paper, we bring attention to a most peculiar junction of political engagement and gastronomic prowess - the correlation between votes for the Republican presidential candidate in Virginia and the quantity of hotdogs consumed by the champion of Nathan's Hot Dog Eating Competition. We delved into this offbeat inquiry with the seriousness it deserves, donning our lab coats and wielding statistics like condiments.

Our research team embarked on a culinary odyssey, navigating through the MIT Election Data and Science Lab and diving into the depths of the Harvard Dataverse to gather relevant political data. Simultaneously, we (figuratively) devoured information on the esteemed winners of Nathan's Hot Dog Eating Competition from trusty sources like Wikipedia. As we crunched the numbers, our findings revealed a correlation coefficient of 0.9291854 and p < 0.01 for the years spanning 1979 to 2020, establishing a surprisingly strong relationship between these seemingly unrelated phenomena.

Now, to appease our hunger for dad jokes, here's one on the house - "Why was the hotdog so fast? Because it’s a real wiener!" Our results not only provide fodder for amusement, but also pique curiosity regarding the underlying mechanisms driving this improbable correlation. As we reflect on this peculiar relationship, we are reminded of the age-old adage: "When the going gets weird, the weird turn pro."

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Ah, the joys of research - delving into the unknown, uncovering unexpected connections, and ultimately, satisfying our insatiable curiosity. In the realm of statistical analysis, one is often met with the challenge of exploring divergence, yet occasionally, the most whimsical pairings emerge. It is with great delight that we present our findings on the correlation between the number of votes for the Republican presidential candidate in Virginia and the consumption of hotdogs by the champions of Nathan's Hot Dog Eating Competition. If this seems like a peculiar blend of politics and gastronomy, you're not alone. As we ventured into this uncharted territory, we couldn't help but relish the prospect of shedding light on a correlation as enigmatic as a hotdog with relish - that is, both baffling and strangely intriguing.
With our lab coats donned and data sets at the ready, we embarked on a riveting journey through the world of statistical analyses. It was a veritable feast for the intellect, as we embarked on this scholarly pursuit armed with nothing but curiosity and an unquenchable thirst for knowledge. It was a veritable hotdog-eating competition of scientific inquiry; and just like the mysterious allure of a "mystery meat" hotdog, the adventure kept us on the edge of our seats, brimming with anticipation.
Eager to sink our teeth into the matter at hand, we delved into the MIT Election Data and Science Lab to procure the electoral data for the state of Virginia. Simultaneously, we navigated the depths of the Harvard Dataverse, much like a contestant navigating their way through a tower of hotdogs, to obtain the historical results of Nathan's Hot Dog Eating Competition. It was a veritable smorgasbord of information, and just as the sight of a towering hotdog with all the fixings can ignite the appetite, the allure of unraveling this curious correlation fed our scientific fervor.
As we crunched the numbers with as much gusto as a hotdog-eating champion attacking their bounty, our findings revealed a staggering correlation coefficient of 0.9291854 and p < 0.01 for the years spanning 1979 to 2020. The undeniable connection between these seemingly unrelated variables prompted laughter, intrigue, and an abundance of food for thought. It was as if we had stumbled upon the academic equivalent of a perfectly crafted pun – surprising, delightful, and utterly thought-provoking.
Amidst the fervor of our scholarly pursuits, we couldn't resist sharing a dad joke to sizzle the mind—“What did the hotdog say when it crossed the finish line? I’m the wiener!” Our findings not only added a touch of whimsy to the scientific discourse but also ignited a flame of curiosity regarding the underlying mechanisms driving this improbable correlation. As we pondered this peculiarity, we couldn't help but recall the profound words of wisdom: "Research is like trying to find the mustard at a crowded picnic – sometimes, you have to sift through a lot of relish to get to the good stuff." And indeed, our journey has not only entertained us but also presented an opportunity to unearth unexpected intellectual delights.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

As we wade into the realm of improbable correlations, it's only fitting to lay the groundwork with serious research. Smith and Doe, in their seminal work "Political Engagement and Culinary Prowess: Exploring Unlikely Associations," touched upon the intricate relationship between political voting patterns and culinary feats. They posited that gastronomic achievements could serve as a bellwether for political inclinations, provoking contemplation as profound as the question, "What do you call a hotdog race? A 'wiener takes all' race."

Jones, in "The Statistical Sizzle: Unveiling the Surprising Link Between Hotdog Consumption and Political Leanings," further solidified this line of inquiry. Their exploration not only confirmed the existence of a correlative bond between dietary habits and electoral preferences but also underscored the need to embrace unexpected connections in the realm of statistical analysis. In homage to their groundbreaking work, one might pause to reflect, "Why don't hotdogs make good baseball players? They strike out too often."

In expanding our purview, we looked to the illuminating non-fiction works that tangentially resonated with our study. "Eating the Elephant: A Political Memoir" by Jane Politician offered insightful parallels between electoral strategies and dining habits, hinting at the tantalizing overlap between our chosen variables. In a similar vein, "The Art of Sausage Making: A Gastronomic Journey" by Culinary Connoisseur shed light on the intricacies of food production, drawing a compelling parallel to the meticulous craft of political campaigning.

Turning to the realm of fiction, where the threads of reality intertwine with imagination, we encountered works that seemingly echoed our unexpected correlation. "The Hunger Games" by Suzanne Collins, while primarily a tale of dystopian survival, intriguingly touched upon themes of competition and consumption, beckoning us to consider the parallels with our own study. Furthermore, "The Reluctant Politician" by Fictional Author posed thought-provoking questions about the role of chance and happenstance in shaping political destinies, mirroring the fortuitous nature of our findings.

Adding a dash of whimsy to our literary inspirations, we couldn't help but draw a parallel to the board game "Catan," where players vie for resources and strategy converges with unpredictability. The subtle irony of navigating through a game of chance and strategy bore a resemblance to our own scholarly pursuits, prompting reflection on the eccentric patterns that emerge when least expected.

With each twist in this literary tapestry, we are reminded of the enigmatic nature of our research, akin to a perfectly timed punchline in an otherwise serious conversation. Just as unexpected as a hotdog-eating champion's victory, our findings stand as a testament to the delightful quirkiness that pervades the world of statistical analysis.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Votes for the Republican Presidential candidate in Virginia and Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 MIT Election Data and Science Lab, Harvard Dataverse and Wikipedia . You used data from 1979 to 2020

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]]
"Making Sausage and Winning Hearts: A Correlational Study of Republican Votes in Virginia and Nathan's Hot Dog Eating Competition Champions' Consumption"

[[ABSTRACT]]
In this paper, we bring attention to a most peculiar junction of political engagement and gastronomic prowess - the correlation between votes for the Republican presidential candidate in Virginia and the quantity of hotdogs consumed by the champion of Nathan's Hot Dog Eating Competition. We delved into this offbeat inquiry with the seriousness it deserves, donning our lab coats and wielding statistics like condiments.

Our research team embarked on a culinary odyssey, navigating through the MIT Election Data and Science Lab and diving into the depths of the Harvard Dataverse to gather relevant political data. Simultaneously, we (figuratively) devoured information on the esteemed winners of Nathan's Hot Dog Eating Competition from trusty sources like Wikipedia. As we crunched the numbers, our findings revealed a correlation coefficient of 0.9291854 and p < 0.01 for the years spanning 1979 to 2020, establishing a surprisingly strong relationship between these seemingly unrelated phenomena.

Now, to appease our hunger for dad jokes, here's one on the house - "Why was the hotdog so fast? Because it’s a real wiener!" Our results not only provide fodder for amusement, but also pique curiosity regarding the underlying mechanisms driving this improbable correlation. As we reflect on this peculiar relationship, we are reminded of the age-old adage: "When the going gets weird, the weird turn pro."

[[INTRODUCTION]]
Ah, the joys of research - delving into the unknown, uncovering unexpected connections, and ultimately, satisfying our insatiable curiosity. In the realm of statistical analysis, one is often met with the challenge of exploring divergence, yet occasionally, the most whimsical pairings emerge. It is with great delight that we present our findings on the correlation between the number of votes for the Republican presidential candidate in Virginia and the consumption of hotdogs by the champions of Nathan's Hot Dog Eating Competition. If this seems like a peculiar blend of politics and gastronomy, you're not alone. As we ventured into this uncharted territory, we couldn't help but relish the prospect of shedding light on a correlation as enigmatic as a hotdog with relish - that is, both baffling and strangely intriguing.
With our lab coats donned and data sets at the ready, we embarked on a riveting journey through the world of statistical analyses. It was a veritable feast for the intellect, as we embarked on this scholarly pursuit armed with nothing but curiosity and an unquenchable thirst for knowledge. It was a veritable hotdog-eating competition of scientific inquiry; and just like the mysterious allure of a "mystery meat" hotdog, the adventure kept us on the edge of our seats, brimming with anticipation.
Eager to sink our teeth into the matter at hand, we delved into the MIT Election Data and Science Lab to procure the electoral data for the state of Virginia. Simultaneously, we navigated the depths of the Harvard Dataverse, much like a contestant navigating their way through a tower of hotdogs, to obtain the historical results of Nathan's Hot Dog Eating Competition. It was a veritable smorgasbord of information, and just as the sight of a towering hotdog with all the fixings can ignite the appetite, the allure of unraveling this curious correlation fed our scientific fervor.
As we crunched the numbers with as much gusto as a hotdog-eating champion attacking their bounty, our findings revealed a staggering correlation coefficient of 0.9291854 and p < 0.01 for the years spanning 1979 to 2020. The undeniable connection between these seemingly unrelated variables prompted laughter, intrigue, and an abundance of food for thought. It was as if we had stumbled upon the academic equivalent of a perfectly crafted pun – surprising, delightful, and utterly thought-provoking.
Amidst the fervor of our scholarly pursuits, we couldn't resist sharing a dad joke to sizzle the mind—“What did the hotdog say when it crossed the finish line? I’m the wiener!” Our findings not only added a touch of whimsy to the scientific discourse but also ignited a flame of curiosity regarding the underlying mechanisms driving this improbable correlation. As we pondered this peculiarity, we couldn't help but recall the profound words of wisdom: "Research is like trying to find the mustard at a crowded picnic – sometimes, you have to sift through a lot of relish to get to the good stuff." And indeed, our journey has not only entertained us but also presented an opportunity to unearth unexpected intellectual delights.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To uncover the tantalizing correlation between the votes for the Republican presidential candidate in Virginia and the consumption of hot dogs by Nathan's Hot Dog Eating Competition champions, our research team endeavored on a methodological quest as intricate as untangling a web of tangled sausages. First, we embarked on what could only be described as a cyber-culinary expedition, akin to navigating a labyrinth of condiments in search of the elusive correlation bratwurst. We culled electoral data from the MIT Election Data and Science Lab, employing statistical tools like a precision-engraved kitchen knife to slice through the mire of numbers and reveal the savory morsels within.

Our approach, reminiscent of peeling back the layers of a particularly complex onion (a shallot of uncertainty, if you will), involved massaging the data from the Harvard Dataverse to extract historical results from Nathan's Hot Dog Eating Competition. We sifted and seasoned the datasets with the finesse of a master chef, adhering to statistical principles as rigorously as one follows a trusted recipe for the perfect hot dog chili.

Having gathered and finessed our ingredients, we meticulously stirred the electoral data together with the competition results, employing a time-series analysis that would make even the most seasoned culinary maestros envious of our technical prowess. With each statistical model and calculation, we navigated through the mathematical equivalent of a high-stakes cook-off, leaving no spice unturned, no outlier left unaccounted for.

The final step in our methodological concoction involved whipping up a correlation analysis using robust statistical software, akin to conducting a meticulous taste test of our potentially groundbreaking findings. Just as a discerning food critic evaluates the harmony of flavors in a gourmet dish, so too did we scrutinize the interplay between Republican votes and hot dog consumption, mindful of any potential confounding variables that could clog the proverbial scientific digestive system.

In the spirit of full transparency, it bears mentioning that our approach, while scientifically robust, may have elicited a fair share of culinary cravings and unshakable comparisons to food-related metaphors. Nevertheless, we assure our esteemed readers that every step was taken with the utmost seriousness and academic rigor, even if the occasional piece of wordplay found its way onto our research notepads.

To stay true to the theme, here's a methodological jest to season our research endeavor – "Why don't hot dogs ever have a quiet dinner? They always relish the moment!" With methodology laid bare like an open buffet, we present our findings with the hope of both satiating scientific curiosity and whetting the appetite for further exploration into the curious correlation between these unexpected variables.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the results section of an academic research paper presenting the findings of the connection between Votes for the Republican Presidential candidate in Virginia and Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 MIT Election Data and Science Lab, Harvard Dataverse and Wikipedia .

For the time period 1979 to 2020, you found a correlation 0.9291854, r-squared of 0.8633855, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
"Making Sausage and Winning Hearts: A Correlational Study of Republican Votes in Virginia and Nathan's Hot Dog Eating Competition Champions' Consumption"

[[ABSTRACT]]
In this paper, we bring attention to a most peculiar junction of political engagement and gastronomic prowess - the correlation between votes for the Republican presidential candidate in Virginia and the quantity of hotdogs consumed by the champion of Nathan's Hot Dog Eating Competition. We delved into this offbeat inquiry with the seriousness it deserves, donning our lab coats and wielding statistics like condiments.

Our research team embarked on a culinary odyssey, navigating through the MIT Election Data and Science Lab and diving into the depths of the Harvard Dataverse to gather relevant political data. Simultaneously, we (figuratively) devoured information on the esteemed winners of Nathan's Hot Dog Eating Competition from trusty sources like Wikipedia. As we crunched the numbers, our findings revealed a correlation coefficient of 0.9291854 and p < 0.01 for the years spanning 1979 to 2020, establishing a surprisingly strong relationship between these seemingly unrelated phenomena.

Now, to appease our hunger for dad jokes, here's one on the house - "Why was the hotdog so fast? Because it’s a real wiener!" Our results not only provide fodder for amusement, but also pique curiosity regarding the underlying mechanisms driving this improbable correlation. As we reflect on this peculiar relationship, we are reminded of the age-old adage: "When the going gets weird, the weird turn pro."

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Ah, the joys of research - delving into the unknown, uncovering unexpected connections, and ultimately, satisfying our insatiable curiosity. In the realm of statistical analysis, one is often met with the challenge of exploring divergence, yet occasionally, the most whimsical pairings emerge. It is with great delight that we present our findings on the correlation between the number of votes for the Republican presidential candidate in Virginia and the consumption of hotdogs by the champions of Nathan's Hot Dog Eating Competition. If this seems like a peculiar blend of politics and gastronomy, you're not alone. As we ventured into this uncharted territory, we couldn't help but relish the prospect of shedding light on a correlation as enigmatic as a hotdog with relish - that is, both baffling and strangely intriguing.
With our lab coats donned and data sets at the ready, we embarked on a riveting journey through the world of statistical analyses. It was a veritable feast for the intellect, as we embarked on this scholarly pursuit armed with nothing but curiosity and an unquenchable thirst for knowledge. It was a veritable hotdog-eating competition of scientific inquiry; and just like the mysterious allure of a "mystery meat" hotdog, the adventure kept us on the edge of our seats, brimming with anticipation.
Eager to sink our teeth into the matter at hand, we delved into the MIT Election Data and Science Lab to procure the electoral data for the state of Virginia. Simultaneously, we navigated the depths of the Harvard Dataverse, much like a contestant navigating their way through a tower of hotdogs, to obtain the historical results of Nathan's Hot Dog Eating Competition. It was a veritable smorgasbord of information, and just as the sight of a towering hotdog with all the fixings can ignite the appetite, the allure of unraveling this curious correlation fed our scientific fervor.
As we crunched the numbers with as much gusto as a hotdog-eating champion attacking their bounty, our findings revealed a staggering correlation coefficient of 0.9291854 and p < 0.01 for the years spanning 1979 to 2020. The undeniable connection between these seemingly unrelated variables prompted laughter, intrigue, and an abundance of food for thought. It was as if we had stumbled upon the academic equivalent of a perfectly crafted pun – surprising, delightful, and utterly thought-provoking.
Amidst the fervor of our scholarly pursuits, we couldn't resist sharing a dad joke to sizzle the mind—“What did the hotdog say when it crossed the finish line? I’m the wiener!” Our findings not only added a touch of whimsy to the scientific discourse but also ignited a flame of curiosity regarding the underlying mechanisms driving this improbable correlation. As we pondered this peculiarity, we couldn't help but recall the profound words of wisdom: "Research is like trying to find the mustard at a crowded picnic – sometimes, you have to sift through a lot of relish to get to the good stuff." And indeed, our journey has not only entertained us but also presented an opportunity to unearth unexpected intellectual delights.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

Our analysis revealed a striking correlation between the number of votes for the Republican presidential candidate in Virginia and the quantity of hotdogs consumed by the champions of Nathan's Hot Dog Eating Competition. With a correlation coefficient of 0.9291854 and an r-squared of 0.8633855, the relationship between these seemingly disconnected variables proved to be as strong as the tenacity of a hotdog eating champion amid a sea of frankfurters.

Fig. 1 represents our findings in scatterplot form, a visual depiction that encapsulates the resounding harmony between political preferences and gastrointestinal feats. Just like a well-timed pun, the graph paints a clear picture of the unlikely connection between the variables. Now, let’s ketchup with another joke – "What do you call a hotdog race? The wiener takes it all!"

The statistical significance indicated by p < 0.01 further elucidates the robustness of this correlation. It's as if the data itself is exclaiming, "Relish this scientific discovery!" This finding underscores the potential for unconventional avenues of inquiry in the world of research, demonstrating that even the most unexpected pairings can yield noteworthy insights. Much like a savory hotdog with all the fixings, our results provide a blend of amusement and intellectual nourishment, challenging traditional expectations and sparking curiosity in the most unlikely of arenas.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Votes for the Republican Presidential candidate in Virginia and Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
"Making Sausage and Winning Hearts: A Correlational Study of Republican Votes in Virginia and Nathan's Hot Dog Eating Competition Champions' Consumption"

[[ABSTRACT]]
In this paper, we bring attention to a most peculiar junction of political engagement and gastronomic prowess - the correlation between votes for the Republican presidential candidate in Virginia and the quantity of hotdogs consumed by the champion of Nathan's Hot Dog Eating Competition. We delved into this offbeat inquiry with the seriousness it deserves, donning our lab coats and wielding statistics like condiments.

Our research team embarked on a culinary odyssey, navigating through the MIT Election Data and Science Lab and diving into the depths of the Harvard Dataverse to gather relevant political data. Simultaneously, we (figuratively) devoured information on the esteemed winners of Nathan's Hot Dog Eating Competition from trusty sources like Wikipedia. As we crunched the numbers, our findings revealed a correlation coefficient of 0.9291854 and p < 0.01 for the years spanning 1979 to 2020, establishing a surprisingly strong relationship between these seemingly unrelated phenomena.

Now, to appease our hunger for dad jokes, here's one on the house - "Why was the hotdog so fast? Because it’s a real wiener!" Our results not only provide fodder for amusement, but also pique curiosity regarding the underlying mechanisms driving this improbable correlation. As we reflect on this peculiar relationship, we are reminded of the age-old adage: "When the going gets weird, the weird turn pro."

[[LITERATURE REVIEW]]
As we wade into the realm of improbable correlations, it's only fitting to lay the groundwork with serious research. Smith and Doe, in their seminal work "Political Engagement and Culinary Prowess: Exploring Unlikely Associations," touched upon the intricate relationship between political voting patterns and culinary feats. They posited that gastronomic achievements could serve as a bellwether for political inclinations, provoking contemplation as profound as the question, "What do you call a hotdog race? A 'wiener takes all' race."
Jones, in "The Statistical Sizzle: Unveiling the Surprising Link Between Hotdog Consumption and Political Leanings," further solidified this line of inquiry. Their exploration not only confirmed the existence of a correlative bond between dietary habits and electoral preferences but also underscored the need to embrace unexpected connections in the realm of statistical analysis. In homage to their groundbreaking work, one might pause to reflect, "Why don't hotdogs make good baseball players? They strike out too often."
In expanding our purview, we looked to the illuminating non-fiction works that tangentially resonated with our study. "Eating the Elephant: A Political Memoir" by Jane Politician offered insightful parallels between electoral strategies and dining habits, hinting at the tantalizing overlap between our chosen variables. In a similar vein, "The Art of Sausage Making: A Gastronomic Journey" by Culinary Connoisseur shed light on the intricacies of food production, drawing a compelling parallel to the meticulous craft of political campaigning.
Turning to the realm of fiction, where the threads of reality intertwine with imagination, we encountered works that seemingly echoed our unexpected correlation. "The Hunger Games" by Suzanne Collins, while primarily a tale of dystopian survival, intriguingly touched upon themes of competition and consumption, beckoning us to consider the parallels with our own study. Furthermore, "The Reluctant Politician" by Fictional Author posed thought-provoking questions about the role of chance and happenstance in shaping political destinies, mirroring the fortuitous nature of our findings.
Adding a dash of whimsy to our literary inspirations, we couldn't help but draw a parallel to the board game "Catan," where players vie for resources and strategy converges with unpredictability. The subtle irony of navigating through a game of chance and strategy bore a resemblance to our own scholarly pursuits, prompting reflection on the eccentric patterns that emerge when least expected.
With each twist in this literary tapestry, we are reminded of the enigmatic nature of our research, akin to a perfectly timed punchline in an otherwise serious conversation. Just as unexpected as a hotdog-eating champion's victory, our findings stand as a testament to the delightful quirkiness that pervades the world of statistical analysis.

[[RESULTS]]
Our analysis revealed a striking correlation between the number of votes for the Republican presidential candidate in Virginia and the quantity of hotdogs consumed by the champions of Nathan's Hot Dog Eating Competition. With a correlation coefficient of 0.9291854 and an r-squared of 0.8633855, the relationship between these seemingly disconnected variables proved to be as strong as the tenacity of a hotdog eating champion amid a sea of frankfurters.
Fig. 1 represents our findings in scatterplot form, a visual depiction that encapsulates the resounding harmony between political preferences and gastrointestinal feats. Just like a well-timed pun, the graph paints a clear picture of the unlikely connection between the variables. Now, let’s ketchup with another joke – "What do you call a hotdog race? The wiener takes it all!"
The statistical significance indicated by p < 0.01 further elucidates the robustness of this correlation. It's as if the data itself is exclaiming, "Relish this scientific discovery!" This finding underscores the potential for unconventional avenues of inquiry in the world of research, demonstrating that even the most unexpected pairings can yield noteworthy insights. Much like a savory hotdog with all the fixings, our results provide a blend of amusement and intellectual nourishment, challenging traditional expectations and sparking curiosity in the most unlikely of arenas.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our study unearths an eyebrow-raising correlation between the votes cast for the Republican presidential candidate in Virginia and the astonishing quantity of hotdogs consumed by the champions of Nathan's Hot Dog Eating Competition. Our findings not only corroborate previous research by Smith and Doe and Jones, but they also relish in the unexpected peculiarity that seems to permeate the complex world of statistics. It's almost as surprising as finding an extra hot dog hiding in the pack - truly a statistical sausage fest!

Now, let's relish the fact that our results elucidate a strong correlation between these ostensibly unrelated variables. Our correlation coefficient of 0.9291854 echoes louder than a ketchup bottle squelching its contents onto a hot dog, depicting a robust relationship that's difficult to dismiss. This is as impressive as a hot dog eating champion's appetite, showing that sometimes, statistical relationships are as clear as day.

The statistical significance of our findings, with a p-value of less than 0.01, serves as a neon sign that illuminates the importance of embracing unconventional and quirky connections in research. It's like the statistical universe is telling us, "Hey, this might seem as unexpected as a hotdog topping, but it's a real game-changer!"

Amidst these unexpected findings, it's important to consider potential explanations for this surprising correlation. Could it be that the cultural and culinary proclivities of Virginians intersect with their political leanings? Or are there broader societal, economic, or even climactic influences at play here? As researchers, we must approach these questions with the caution of handling a loaded hot dog - gingerly and with care.

Speaking of caution, one must always be wary of the potential for confounding variables in such analyses. After all, as the old saying goes, "Correlation does not imply causation - just like eating hotdogs doesn't cause one to vote Republican!" Keeping this in mind, future research should seek to untangle the complex web of factors that might underpin this intriguing correlation. This is a bit like deconstructing a particularly complex hot dog garnish to understand the flavors at play.

As we digest these findings, we are reminded that the world of research is as vast and rich as a buffet, offering unexpected glimpses into the interconnected nature of human behavior. Much like a perfectly timed dad joke, our results tickle the imagination and urge further exploration into the delightful idiosyncrasies of statistical analysis. Just as a good mustard complements a hot dog, our study stands as a flavorful addition to the mosaic of scientific inquiry, embracing the unexpected with open arms.

With these tantalizing revelations, it's clear that our study leaves room for further investigation, stimulating the appetite for knowledge and inspiring future explorations into the quirky and colorful realm of improbable correlations. As we ponder the implications of this unlikely liaison, it's worth savoring the whimsicality of research and sowing the seeds of curiosity for the unexpected findings that lie just around the statistical corner.


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Votes for the Republican Presidential candidate in Virginia and Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
"Making Sausage and Winning Hearts: A Correlational Study of Republican Votes in Virginia and Nathan's Hot Dog Eating Competition Champions' Consumption"

[[ABSTRACT]]
In this paper, we bring attention to a most peculiar junction of political engagement and gastronomic prowess - the correlation between votes for the Republican presidential candidate in Virginia and the quantity of hotdogs consumed by the champion of Nathan's Hot Dog Eating Competition. We delved into this offbeat inquiry with the seriousness it deserves, donning our lab coats and wielding statistics like condiments.

Our research team embarked on a culinary odyssey, navigating through the MIT Election Data and Science Lab and diving into the depths of the Harvard Dataverse to gather relevant political data. Simultaneously, we (figuratively) devoured information on the esteemed winners of Nathan's Hot Dog Eating Competition from trusty sources like Wikipedia. As we crunched the numbers, our findings revealed a correlation coefficient of 0.9291854 and p < 0.01 for the years spanning 1979 to 2020, establishing a surprisingly strong relationship between these seemingly unrelated phenomena.

Now, to appease our hunger for dad jokes, here's one on the house - "Why was the hotdog so fast? Because it’s a real wiener!" Our results not only provide fodder for amusement, but also pique curiosity regarding the underlying mechanisms driving this improbable correlation. As we reflect on this peculiar relationship, we are reminded of the age-old adage: "When the going gets weird, the weird turn pro."

[[INTRDUCTION]]
Ah, the joys of research - delving into the unknown, uncovering unexpected connections, and ultimately, satisfying our insatiable curiosity. In the realm of statistical analysis, one is often met with the challenge of exploring divergence, yet occasionally, the most whimsical pairings emerge. It is with great delight that we present our findings on the correlation between the number of votes for the Republican presidential candidate in Virginia and the consumption of hotdogs by the champions of Nathan's Hot Dog Eating Competition. If this seems like a peculiar blend of politics and gastronomy, you're not alone. As we ventured into this uncharted territory, we couldn't help but relish the prospect of shedding light on a correlation as enigmatic as a hotdog with relish - that is, both baffling and strangely intriguing.
With our lab coats donned and data sets at the ready, we embarked on a riveting journey through the world of statistical analyses. It was a veritable feast for the intellect, as we embarked on this scholarly pursuit armed with nothing but curiosity and an unquenchable thirst for knowledge. It was a veritable hotdog-eating competition of scientific inquiry; and just like the mysterious allure of a "mystery meat" hotdog, the adventure kept us on the edge of our seats, brimming with anticipation.
Eager to sink our teeth into the matter at hand, we delved into the MIT Election Data and Science Lab to procure the electoral data for the state of Virginia. Simultaneously, we navigated the depths of the Harvard Dataverse, much like a contestant navigating their way through a tower of hotdogs, to obtain the historical results of Nathan's Hot Dog Eating Competition. It was a veritable smorgasbord of information, and just as the sight of a towering hotdog with all the fixings can ignite the appetite, the allure of unraveling this curious correlation fed our scientific fervor.
As we crunched the numbers with as much gusto as a hotdog-eating champion attacking their bounty, our findings revealed a staggering correlation coefficient of 0.9291854 and p < 0.01 for the years spanning 1979 to 2020. The undeniable connection between these seemingly unrelated variables prompted laughter, intrigue, and an abundance of food for thought. It was as if we had stumbled upon the academic equivalent of a perfectly crafted pun – surprising, delightful, and utterly thought-provoking.
Amidst the fervor of our scholarly pursuits, we couldn't resist sharing a dad joke to sizzle the mind—“What did the hotdog say when it crossed the finish line? I’m the wiener!” Our findings not only added a touch of whimsy to the scientific discourse but also ignited a flame of curiosity regarding the underlying mechanisms driving this improbable correlation. As we pondered this peculiarity, we couldn't help but recall the profound words of wisdom: "Research is like trying to find the mustard at a crowded picnic – sometimes, you have to sift through a lot of relish to get to the good stuff." And indeed, our journey has not only entertained us but also presented an opportunity to unearth unexpected intellectual delights.

[[RESULTS]]
Our analysis revealed a striking correlation between the number of votes for the Republican presidential candidate in Virginia and the quantity of hotdogs consumed by the champions of Nathan's Hot Dog Eating Competition. With a correlation coefficient of 0.9291854 and an r-squared of 0.8633855, the relationship between these seemingly disconnected variables proved to be as strong as the tenacity of a hotdog eating champion amid a sea of frankfurters.
Fig. 1 represents our findings in scatterplot form, a visual depiction that encapsulates the resounding harmony between political preferences and gastrointestinal feats. Just like a well-timed pun, the graph paints a clear picture of the unlikely connection between the variables. Now, let’s ketchup with another joke – "What do you call a hotdog race? The wiener takes it all!"
The statistical significance indicated by p < 0.01 further elucidates the robustness of this correlation. It's as if the data itself is exclaiming, "Relish this scientific discovery!" This finding underscores the potential for unconventional avenues of inquiry in the world of research, demonstrating that even the most unexpected pairings can yield noteworthy insights. Much like a savory hotdog with all the fixings, our results provide a blend of amusement and intellectual nourishment, challenging traditional expectations and sparking curiosity in the most unlikely of arenas.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our research has uncovered a surprising and robust correlation between Republican votes in Virginia and hotdog consumption by the champions of Nathan's Hot Dog Eating Competition. It is as baffling as trying to tell the difference between an uncured and a cured sausage – the links are all there, but they still leave us scratching our heads. Our findings, akin to a well-grilled hotdog, have sparked both amusement and intrigue in the scholarly community, reminding us that even the most unexpected pairings can sizzle with significance.

As we wrap up this research, it's time for one more dad joke – "Did you hear about the hotdog who couldn't stop telling jokes? It was on a roll!" And just like that joke, we sincerely believe that our findings have brought a smile to the faces of fellow researchers, proving that even in the most serious pursuits, a little levity can go a long way.

Our results indicate a strong correlation coefficient of 0.9291854 and p < 0.01, highlighting the substantial relationship between these divergent variables. This unexpected cohesion is a reminder that in the world of statistical analyses, just like in life, things are not always as they seem – sometimes, the most peculiar pairings can yield the most intriguing discoveries.

As we bid adieu to this curious correlation, we assert confidently that no further research is needed in this area. It seems that the connection between votes for the Republican presidential candidate in Virginia and the quantity of hotdogs consumed by the champions of Nathan's Hot Dog Eating Competition is as undeniable as the appeal of a good pun – it simply can't be overstated.


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 Making Sausage and Winning Hearts: A Correlational Study of Republican Votes in Virginia and Nathan's Hot Dog Eating Competition Champions' Consumption. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Gastronomic Politics


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 Making Sausage and Winning Hearts: A Correlational Study of Republican Votes in Virginia and Nathan's Hot Dog Eating Competition Champions' Consumption. Respond only with the name of a fictional organization.

ChatGPT:

The Center for Competitive Eating and Electoral Analysis


Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Making Sausage and Winning Hearts: A Correlational Study of Republican Votes in Virginia and Nathan's Hot Dog Eating Competition Champions' Consumption with an abstract of In this paper, we bring attention to a most peculiar junction of political engagement and gastronomic prowess - the correlation between votes for the Republican presidential candidate in Virginia and the quantity of hotdogs consumed by the champion of Nathan's Hot Dog Eating Competition. We delved into this offbeat inquiry with the seriousness it deserves, donning our lab coats and wielding statistics like condiments.
Our research team embarked on a culinary odyssey, navigating through the MIT Election Data and Science Lab and diving into the depths of the Harvard Dataverse to gather relevant political data. Simultaneously, we (figuratively) devoured information on the esteemed winners of Nathan's Hot Dog Eating Competition from trusty sources like Wikipedia. As we crunched the numbers, our findings revealed a correlation coefficient of 0.9291854 and p < 0.01 for the years spanning 1979 to 2020, establishing a surprisingly strong relationship between these seemingly unrelated phenomena.
Now, to appease our hunger for dad jokes, here's one on the house - "Why was the hotdog so fast? Because it’s a real wiener!" Our results not only provide fodder for amusement, but also pique curiosity regarding the underlying mechanisms driving this improbable correlation. As we reflect on this peculiar relationship, we are reminded of the age-old adage: "When the going gets weird, the weird turn pro.

ChatGPT:

"Republican votes Virginia correlation hot dog consumption," "Nathan's Hot Dog Eating Competition champions," "MIT Election Data and Science Lab," "Harvard Dataverse," "correlation coefficient political gastronomic," "odd correlations in research," "unusual political research," "unlikely correlations in data analysis," "weird research findings," "statistical analysis food consumption politics," "research on disparate phenomena," "humorous research findings," "unconventional research results."

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



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Data details

Votes for the Republican Presidential candidate in Virginia
Detailed data title: Total votes cast for the Republican Presidential candidate in Virginia
Source: MIT Election Data and Science Lab, Harvard Dataverse
See what else correlates with Votes for the Republican Presidential candidate in Virginia

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

Correlation r = 0.9291854 (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 = 0.8633855 (Coefficient of determination)
This means 86.3% of the change in the one variable (i.e., Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion) is predictable based on the change in the other (i.e., Votes for the Republican Presidential candidate in Virginia) over the 11 years from 1979 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 3.5E-5. 0.0000353459925508552140000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.93 in 0.0035% of random cases. Said differently, if you correlated 28,292 random variables You don't actually need 28 thousand variables to find a correlation like this one. 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.

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 10 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 10 because we have two variables measured over a period of 11 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.

[ 0.74, 0.98 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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


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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
19801984198819921996200020042008201220162020
Votes for the Republican Presidential candidate in Virginia (Total votes)9896091337080130916011505201138350143749017169601725000182252017694401962430
Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion (Hotdogs eaten)9.59.5101922.252553.3359687075




Why this works

  1. Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
  2. Lack of causal connection: There is probably Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
    no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
  3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
    p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
  4. Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
    Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.




Try it yourself

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

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

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

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

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

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

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

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

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


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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([989609,1337080,1309160,1150520,1138350,1437490,1716960,1725000,1822520,1769440,1962430,])
array_2 = np.array([9.5,9.5,10,19,22.25,25,53.33,59,68,70,75,])
array_1_name = "Votes for the Republican Presidential candidate in Virginia"
array_2_name = "Hotdogs consumed by Nathan's Hot Dog Eating Competition Champion"

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

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



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Correlation ID: 4461 · Black Variable ID: 26041 · Red Variable ID: 500
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