Spurious correlation #3,876 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Super Bowl Champion's Winning Score and the second variable is The number of hoist and winch operators in Texas. The chart goes from 2003 to 2019, 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 Super Bowl Champion's Winning Score and the second variable is The number of hoist and winch operators in Texas. The chart goes from 2003 to 2019, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the Super Bowl Champion's Winning Score decreased, it created a deflategate situation in the hoist and winch industry. This led to a loss of interest in operating hoists and winches in Texas, as it just wasn't reeling them in like before. The connection between football scores and hoist and winch operators may seem far-fetched, but when it comes to punny causation, this correlation takes the Lombardi trophy!

^{Show image generation prompt} Model: dalle-3
Prompt: [An image generation prompt with the style of a dramatic sports event photo, capturing the deflated atmosphere of the Texas stadium after a low-scoring Super Bowl] Prompt: Generate an image that conveys the setting of a quiet Texas stadium post-Super Bowl, where the scoreboard prominently displays a low Champion's Winning Score, causing the crowd to appear disappointed and deflated. In the foreground, depict the hoist and winch operators surrounded by their heavy machinery, looking downcast and struggling to lift and lower the equipment, overwhelmed by the weight of the situation. The dim lighting and somber atmosphere should emphasize the sense of disappointment and resignation felt by the operators and the crowd. 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: Super Bowl Champion's Winning Score and The number of hoist and winch operators in Texas. 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: An image that looks like it is a scene from a Pixar movie Hyper-realistic A Discovery magazine cover image Sci-fi fantacy Oragami
ChatGPT: A Discovery magazine cover image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Super Bowl Champion's Winning Score and The number of hoist and winch operators in Texas, in the following situation: As more teams score less in Super Bowl, the winning spirit deflates, causing hoist and winch operators to lose their lift and go downhill in Texas. The low scores bring a sense of loss, and operators can't handle the weight of the situation anymore!. Keep the description simple.
ChatGPT: In a quiet Texas stadium, the scoreboard displays a low Super Bowl Champion's Winning Score, leaving the crowd feeling deflated. The hoist and winch operators, surrounded by their equipment, look downcast as they struggle to lift and lower the heavy machinery, unable to handle the weight of the situation.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A Discovery magazine cover image ] and depicting this scene: In a quiet Texas stadium, the scoreboard displays a low Super Bowl Champion's Winning Score, leaving the crowd feeling deflated. The hoist and winch operators, surrounded by their equipment, look downcast as they struggle to lift and lower the heavy machinery, unable to handle the weight of the situation. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [An image generation prompt with the style of a dramatic sports event photo, capturing the deflated atmosphere of the Texas stadium after a low-scoring Super Bowl] Prompt: Generate an image that conveys the setting of a quiet Texas stadium post-Super Bowl, where the scoreboard prominently displays a low Champion's Winning Score, causing the crowd to appear disappointed and deflated. In the foreground, depict the hoist and winch operators surrounded by their heavy machinery, looking downcast and struggling to lift and lower the equipment, overwhelmed by the weight of the situation. The dim lighting and somber atmosphere should emphasize the sense of disappointment and resignation felt by the operators and the crowd.

*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 a decrease in Super Bowl Champion's Winning Score caused The number of hoist and winch operators in Texas to decrease. Include one good pun.

AI academic paper

(Because p < 0.01)

Hoist and Winch: Unraveling the Tether Between Super Bowl Champion's Winning Score and the Sheer Force of Texas Labor

The Journal of Sports Engineering and Industrial Labor Relations

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 Super Bowl Champion's Winning Score and The number of hoist and winch operators in Texas. 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 devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading the backs of shampoo bottles.

Here is the title and abstract of the paper:
[[TITLE]]
Hoist and Winch: Unraveling the Tether Between Super Bowl Champion's Winning Score and the Sheer Force of Texas Labor

[[ABSTRACT]]
The relationship between sporting events and labor dynamics has long been a subject of curiosity, and the intriguing nexus between the Super Bowl and the bustling hoist and winch operations in the great state of Texas has captivated both scholars and enthusiasts alike. In this paper, we embark on an empirical journey to demystify the enigmatic link between the winning score of the Super Bowl champions and the number of hoist and winch operators in Texas.

Drawing from a rich tapestry of data sources, including Wikipedia for football scores and the Bureau of Labor Statistics for employment figures, we meticulously captured the essence of this connection. Employing rigorous statistical analysis, we unveiled a correlation coefficient of 0.6481248 and a stunning p-value less than 0.01 for the period spanning 2003 to 2019. Our findings not only substantiate the presence of a robust association but also underscore the potential influence of pigskin prowess on the labor landscape.

While the unassailable link between Super Bowl success and the demand for hoist and winch operators in Texas may seem bemusing at first glance, our research aims to provoke deeper contemplation, adding a touch of whimsy to the realm of labor economics. The implications of these irrefutable findings extend beyond mere statistical curiosity, as they beckon us to ponder the quirky interplay of sports triumphs and the labor market, inviting a delightful blend of pigskin fervor and industrial insight into the scholarly discourse.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intricate interplay between seemingly disparate domains such as sports and labor economics has long fascinated scholars and laypersons alike. From the triumphant fanfare of sporting events to the diligent grind of labor markets, the invisible threads connecting these realms have beckoned us to unravel their enigmatic enmeshment. In this paper, we delve into the curious case of the relationship between the winning score of Super Bowl champions and the sheer force of hoist and winch operators in the industrious state of Texas.
The idea that the outcome of a football game could have any bearing on the demand for hoist and winch operators may, at first blush, appear as perplexing as a touchdown pass in a game of tug-of-war. Nonetheless, the pursuit of knowledge often leads us down unexpected avenues, and our endeavor to unearth the connections beneath the surface is no exception. As we undertake this scholarly expedition, we embrace the spirit of inquiry and discovery, juxtaposing the thrill of sports triumphs with the steadfast toil of industrial occupations.
The significance of our inquiry extends beyond the confines of statistical analysis, transcending the mere correlation coefficients and p-values that populate our findings. Instead, we pause to marvel at the whimsical dance between touchdowns and tool belts, between end zone celebrations and the clinking of industrial machinery. Through our exploration, we seek not only to shed light on this improbable linkage but also to infuse the scholarly discourse with a dash of levity, as we ponder the quirky manifestations of economic forces in the world of pigskin prowess.
As we embark on this expedition into uncharted academic terrain, we invite the reader to join us in an intellectual voyage that dances on the boundary between absurdity and insight, where the fervor of football acumen meets the clamor of industrial enterprise. In the pages that follow, we unveil the surprising nexus between Super Bowl glory and the steady hum of hoists and winches, all while balancing the weighty gravity of empirical analysis with the lighthearted whimsy that enriches our scholarly pursuits.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The enigmatic connection between the winning score of the Super Bowl champions and the number of hoist and winch operators in Texas has captured the curiosity of scholars and enthusiasts alike. This unconventional linkage has prompted a diverse array of studies that seek to untangle the perplexing web of correlation and causation.

Smith et al. (2015) conducted a comprehensive analysis of football scores and labor statistics, attempting to discern any discernible patterns between the Super Bowl outcomes and the demand for industrial operators. Their findings, while seemingly obscure at first glance, painted a compelling picture of the potential influence of sporting triumphs on the labor market.

Doe and Jones (2018) ventured further into this unexplored territory, delving into the nuances of hoisting and winching in the context of sports-related fervor. Their work illuminated the subtle interplay between athletic prowess and the labor forces that toil in the shadows of stadium glory.

Building upon these foundational studies, our investigation seeks to infuse a hint of quirkiness into the realm of labor economics, channeling the spirit of levity amidst the gravity of empirical analysis. As we venture forth into this scholarly terrain, it is essential to acknowledge the diverse array of sources that have inspired our inquiry.

In "The Economics of Sports: A Perfect Balance," the authors unearth the intricate intersections between athletic spectacle and economic dynamics, laying the groundwork for our examination of the unusual marriage between football conquests and industrial demand. Meanwhile, "Labor Markets and Industrial Machinery: A Symbiotic Symphony" offers a compelling backdrop for understanding the labor landscape within which our enigmatic connection unfolds.

Turning to the realm of fiction, works such as "The Gridiron Winch Chronicles" and "Touchdowns and Tool Belts: A Tale of Two Worlds" provide a whimsical yet insightful perspective on the convergence of sports euphoria and industrial labor. While these fictional narratives may seem fanciful, they serve as a source of inspiration as we navigate the real-world implications of our findings.

In our quest for comprehensive understanding, we have cast a wide net to capture the essence of this puzzling relationship. From the hallowed halls of academic journals to the pages of fictional prose, our pursuit of knowledge knows no bounds. As we embark on this scholarly journey, we embrace the delightful blend of statistical rigor and lighthearted curiosity, inviting the reader to join us in the whimsical dance between sports triumphs and industrial intrigue.

It is worth noting that our literature review has been an all-encompassing endeavor, transcending traditional boundaries of inquiry. In addition to formal academic sources, we have gleaned insights from a myriad of unexpected avenues, including, but not limited to, the backs of shampoo bottles, fortune cookies, and the musings of eccentric bus drivers. The whimsy of our approach is as integral to our exploration as the robust statistical analysis that underpins our findings.

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 Super Bowl Champion's Winning Score and The number of hoist and winch operators in Texas. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Wikipedia and Bureau of Larbor Statistics . You used data from 2003 to 2019

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]]
Hoist and Winch: Unraveling the Tether Between Super Bowl Champion's Winning Score and the Sheer Force of Texas Labor

[[ABSTRACT]]
The relationship between sporting events and labor dynamics has long been a subject of curiosity, and the intriguing nexus between the Super Bowl and the bustling hoist and winch operations in the great state of Texas has captivated both scholars and enthusiasts alike. In this paper, we embark on an empirical journey to demystify the enigmatic link between the winning score of the Super Bowl champions and the number of hoist and winch operators in Texas.

Drawing from a rich tapestry of data sources, including Wikipedia for football scores and the Bureau of Labor Statistics for employment figures, we meticulously captured the essence of this connection. Employing rigorous statistical analysis, we unveiled a correlation coefficient of 0.6481248 and a stunning p-value less than 0.01 for the period spanning 2003 to 2019. Our findings not only substantiate the presence of a robust association but also underscore the potential influence of pigskin prowess on the labor landscape.

While the unassailable link between Super Bowl success and the demand for hoist and winch operators in Texas may seem bemusing at first glance, our research aims to provoke deeper contemplation, adding a touch of whimsy to the realm of labor economics. The implications of these irrefutable findings extend beyond mere statistical curiosity, as they beckon us to ponder the quirky interplay of sports triumphs and the labor market, inviting a delightful blend of pigskin fervor and industrial insight into the scholarly discourse.

[[INTRODUCTION]]
The intricate interplay between seemingly disparate domains such as sports and labor economics has long fascinated scholars and laypersons alike. From the triumphant fanfare of sporting events to the diligent grind of labor markets, the invisible threads connecting these realms have beckoned us to unravel their enigmatic enmeshment. In this paper, we delve into the curious case of the relationship between the winning score of Super Bowl champions and the sheer force of hoist and winch operators in the industrious state of Texas.
The idea that the outcome of a football game could have any bearing on the demand for hoist and winch operators may, at first blush, appear as perplexing as a touchdown pass in a game of tug-of-war. Nonetheless, the pursuit of knowledge often leads us down unexpected avenues, and our endeavor to unearth the connections beneath the surface is no exception. As we undertake this scholarly expedition, we embrace the spirit of inquiry and discovery, juxtaposing the thrill of sports triumphs with the steadfast toil of industrial occupations.
The significance of our inquiry extends beyond the confines of statistical analysis, transcending the mere correlation coefficients and p-values that populate our findings. Instead, we pause to marvel at the whimsical dance between touchdowns and tool belts, between end zone celebrations and the clinking of industrial machinery. Through our exploration, we seek not only to shed light on this improbable linkage but also to infuse the scholarly discourse with a dash of levity, as we ponder the quirky manifestations of economic forces in the world of pigskin prowess.
As we embark on this expedition into uncharted academic terrain, we invite the reader to join us in an intellectual voyage that dances on the boundary between absurdity and insight, where the fervor of football acumen meets the clamor of industrial enterprise. In the pages that follow, we unveil the surprising nexus between Super Bowl glory and the steady hum of hoists and winches, all while balancing the weighty gravity of empirical analysis with the lighthearted whimsy that enriches our scholarly pursuits.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To investigate the purported association between the winning score of Super Bowl champions and the labor demand for hoist and winch operators in Texas, a multifaceted research approach was meticulously designed. The primary data sources for this inquiry were gleaned from an assortment of online repositories, with a noted emphasis on the scholarly offerings of Wikipedia and the venerable compendium of labor statistics provided by the Bureau of Labor Statistics. Leveraging these fountains of information, the study encapsulated a time span commencing in 2003 and culminating in 2019, encapsulating the ebbs and flows of triumphant touchdowns and industrious hoisting.

The initial step in this odyssey of inquiry involved the acquisition of historical Super Bowl scores, carefully extracted from the annals of Wikipedia's exhaustive sporting archives. In parallel, the Bureau of Labor Statistics graciously furnished employment figures for hoist and winch operators in the Lone Star State, serving as the bedrock of labor data indispensable to our analytical pursuits. Furthermore, the coalescence of these disparate data elements allowed for the forging of a cohesive timeline that mirrored the intersection of athletic valor and labor stalwartness.

Employing an arsenal of statistical tools, the acquired data underwent a symphony of analyses, each more harmonious than the last. The mighty correlation coefficient strode forth from the depths of mathematical rigidity, standing tall at 0.6481248, a testament to the robustness of the connection between gridiron triumphs and the beckoning call of hoisting and winching. Not to be outdone, the p-value shimmered with significance, generously delivering a value less than 0.01, solidifying the empirical veracity of our findings with a flair that would make even the most stoic econometrician crack a smile.

A multivariate regression dance ensued, involving a delicately choreographed pas de deux between Super Bowl scores and the employment rolls of hoist and winch operators, elucidating the synchronous movements of pigskin prowess and labor market demands. Sensitivity analyses were performed with the meticulousness of a master craftsman, ensuring that the robustness of our results remained impervious to statistical turbulence, affirming the steadfastness of our empirical edifice.

With the culmination of these analyses, the findings of this endeavor stand as a testament to the improbable and yet undeniable juxtaposition of athletic exploits and industrial labor. The rigorous amalgamation of statistical analyses and data triangulation has unveiled a connection that, while perhaps startling at first glance, possesses a resonance that reverberates through the hallowed halls of both sports arenas and industrial landscapes. This methodological symphony, characterized by its complexity and yet buoyed by the levity of unexpected association, lays bare the tantalizing nexus between Super Bowl success and the hum of hoists and winches, beckoning forth an era of scholarly inquiry laced with the whimsy of unlikely correlation.

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 Super Bowl Champion's Winning Score and The number of hoist and winch operators in Texas. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
Hoist and Winch: Unraveling the Tether Between Super Bowl Champion's Winning Score and the Sheer Force of Texas Labor

[[ABSTRACT]]
The relationship between sporting events and labor dynamics has long been a subject of curiosity, and the intriguing nexus between the Super Bowl and the bustling hoist and winch operations in the great state of Texas has captivated both scholars and enthusiasts alike. In this paper, we embark on an empirical journey to demystify the enigmatic link between the winning score of the Super Bowl champions and the number of hoist and winch operators in Texas.

Drawing from a rich tapestry of data sources, including Wikipedia for football scores and the Bureau of Labor Statistics for employment figures, we meticulously captured the essence of this connection. Employing rigorous statistical analysis, we unveiled a correlation coefficient of 0.6481248 and a stunning p-value less than 0.01 for the period spanning 2003 to 2019. Our findings not only substantiate the presence of a robust association but also underscore the potential influence of pigskin prowess on the labor landscape.

While the unassailable link between Super Bowl success and the demand for hoist and winch operators in Texas may seem bemusing at first glance, our research aims to provoke deeper contemplation, adding a touch of whimsy to the realm of labor economics. The implications of these irrefutable findings extend beyond mere statistical curiosity, as they beckon us to ponder the quirky interplay of sports triumphs and the labor market, inviting a delightful blend of pigskin fervor and industrial insight into the scholarly discourse.

[[LITERATURE REVIEW]]
The enigmatic connection between the winning score of the Super Bowl champions and the number of hoist and winch operators in Texas has captured the curiosity of scholars and enthusiasts alike. This unconventional linkage has prompted a diverse array of studies that seek to untangle the perplexing web of correlation and causation.
Smith et al. (2015) conducted a comprehensive analysis of football scores and labor statistics, attempting to discern any discernible patterns between the Super Bowl outcomes and the demand for industrial operators. Their findings, while seemingly obscure at first glance, painted a compelling picture of the potential influence of sporting triumphs on the labor market.
Doe and Jones (2018) ventured further into this unexplored territory, delving into the nuances of hoisting and winching in the context of sports-related fervor. Their work illuminated the subtle interplay between athletic prowess and the labor forces that toil in the shadows of stadium glory.
Building upon these foundational studies, our investigation seeks to infuse a hint of quirkiness into the realm of labor economics, channeling the spirit of levity amidst the gravity of empirical analysis. As we venture forth into this scholarly terrain, it is essential to acknowledge the diverse array of sources that have inspired our inquiry.
In "The Economics of Sports: A Perfect Balance," the authors unearth the intricate intersections between athletic spectacle and economic dynamics, laying the groundwork for our examination of the unusual marriage between football conquests and industrial demand. Meanwhile, "Labor Markets and Industrial Machinery: A Symbiotic Symphony" offers a compelling backdrop for understanding the labor landscape within which our enigmatic connection unfolds.
Turning to the realm of fiction, works such as "The Gridiron Winch Chronicles" and "Touchdowns and Tool Belts: A Tale of Two Worlds" provide a whimsical yet insightful perspective on the convergence of sports euphoria and industrial labor. While these fictional narratives may seem fanciful, they serve as a source of inspiration as we navigate the real-world implications of our findings.
In our quest for comprehensive understanding, we have cast a wide net to capture the essence of this puzzling relationship. From the hallowed halls of academic journals to the pages of fictional prose, our pursuit of knowledge knows no bounds. As we embark on this scholarly journey, we embrace the delightful blend of statistical rigor and lighthearted curiosity, inviting the reader to join us in the whimsical dance between sports triumphs and industrial intrigue.
It is worth noting that our literature review has been an all-encompassing endeavor, transcending traditional boundaries of inquiry. In addition to formal academic sources, we have gleaned insights from a myriad of unexpected avenues, including, but not limited to, the backs of shampoo bottles, fortune cookies, and the musings of eccentric bus drivers. The whimsy of our approach is as integral to our exploration as the robust statistical analysis that underpins our findings.

[[RESULTS]]
The statistical analysis of the data revealed a noteworthy correlation between the winning score of the Super Bowl champions and the number of hoist and winch operators in Texas. For the time period spanning from 2003 to 2019, the correlation coefficient was determined to be 0.6481248 with an r-squared value of 0.4200658. The p-value obtained was less than 0.01, indicating a statistically significant relationship between these seemingly unrelated variables.
The strong correlation is visually depicted in Figure 1, which elegantly portrays the undeniable link between the Super Bowl champion's winning score and the demand for hoist and winch operators in the Lone Star State.
It is quite remarkable how the prowess exhibited on the football field appears to have a lingering impact on the labor landscape of Texas. The robust association between these variables invites us to consider the whimsical interplay of sports triumphs and labor market dynamics, adding a sprinkle of intrigue to the world of economic inquiry. While the precise mechanisms underlying this connection may elude us, the empirical evidence of this association stands as a testament to the curious entanglement of sporting achievements and industrial endeavors.
The findings of this research not only validate the presence of a tangible relationship between the winning score of Super Bowl champions and the employment of hoist and winch operators in Texas but also spark contemplation about the quirky manifestations of economic forces in the realm of American football. These results beckon us to embrace the unexpected and to ponder the unanticipated intersections between two seemingly incongruous domains, prompting a delightful blend of pigskin fervor and labor market insight.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study underscore the intriguing association between the winning score of Super Bowl champions and the demand for hoist and winch operators in Texas, echoing the sentiments of previous scholarly inquiries. While the juxtaposition of football glory and industrial labor may seem peculiar, there is a compelling parallel between the precision of a last-second touchdown and the intricate machinery operated in the Lone Star State.

In line with the work of Smith et al. (2015) and Doe and Jones (2018), our findings validate the whimsical yet robust connection between athletic triumphs and the labor landscape. The statistical correlation coefficient of 0.6481248 corroborates the discernible influence of gridiron prowess on the need for industrial operators, a revelation that tickles the boundaries of conventional economic analysis.

The unorthodox nature of this relationship, which has been playfully explored in works like "The Gridiron Winch Chronicles," challenges traditional perceptions of labor market dynamics. The quirkiness of our findings invites us to ponder the curious interactions between sports euphoria and industrial exigencies, injecting a dash of levity into a realm often characterized by sober assessments.

Our study adds a layer of whimsy to the scholarly discourse, weaving together empirical rigor and an appreciation for the unexpected. The unexpectedness and light-heartedness of this tether between seemingly disparate realms highlight the delightful fusion of statistical gravity and sports fervor, reminding us of the multifaceted nature of economic phenomena.

In light of this, we are drawn to consider the practical implications of these findings. The demand for hoist and winch operators in Texas appears to reflect not only the state's industrial needs but also dances to the rhythm of pigskin victories. As such, our work prompts a deeper contemplation of the interconnectedness of seemingly unrelated domains, infusing industrial economics with a sprinkle of sports-inspired speculation.

Thus, our study not only stands as a testament to the uncanny interplay between sporting achievements and labor market dynamics but also encourages us to revel in the delightful oddities that lurk beneath the surface of seemingly conventional economic relationships. The robust support for prior research and the undeniable correlation between Super Bowl triumphs and the employment of hoist and winch operators beckon us to embrace the whimsical within the scholarly tapestry of economic inquiry.

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 Super Bowl Champion's Winning Score and The number of hoist and winch operators in Texas. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Hoist and Winch: Unraveling the Tether Between Super Bowl Champion's Winning Score and the Sheer Force of Texas Labor

[[ABSTRACT]]
The relationship between sporting events and labor dynamics has long been a subject of curiosity, and the intriguing nexus between the Super Bowl and the bustling hoist and winch operations in the great state of Texas has captivated both scholars and enthusiasts alike. In this paper, we embark on an empirical journey to demystify the enigmatic link between the winning score of the Super Bowl champions and the number of hoist and winch operators in Texas.

Drawing from a rich tapestry of data sources, including Wikipedia for football scores and the Bureau of Labor Statistics for employment figures, we meticulously captured the essence of this connection. Employing rigorous statistical analysis, we unveiled a correlation coefficient of 0.6481248 and a stunning p-value less than 0.01 for the period spanning 2003 to 2019. Our findings not only substantiate the presence of a robust association but also underscore the potential influence of pigskin prowess on the labor landscape.

While the unassailable link between Super Bowl success and the demand for hoist and winch operators in Texas may seem bemusing at first glance, our research aims to provoke deeper contemplation, adding a touch of whimsy to the realm of labor economics. The implications of these irrefutable findings extend beyond mere statistical curiosity, as they beckon us to ponder the quirky interplay of sports triumphs and the labor market, inviting a delightful blend of pigskin fervor and industrial insight into the scholarly discourse.

[[INTRDUCTION]]
The intricate interplay between seemingly disparate domains such as sports and labor economics has long fascinated scholars and laypersons alike. From the triumphant fanfare of sporting events to the diligent grind of labor markets, the invisible threads connecting these realms have beckoned us to unravel their enigmatic enmeshment. In this paper, we delve into the curious case of the relationship between the winning score of Super Bowl champions and the sheer force of hoist and winch operators in the industrious state of Texas.
The idea that the outcome of a football game could have any bearing on the demand for hoist and winch operators may, at first blush, appear as perplexing as a touchdown pass in a game of tug-of-war. Nonetheless, the pursuit of knowledge often leads us down unexpected avenues, and our endeavor to unearth the connections beneath the surface is no exception. As we undertake this scholarly expedition, we embrace the spirit of inquiry and discovery, juxtaposing the thrill of sports triumphs with the steadfast toil of industrial occupations.
The significance of our inquiry extends beyond the confines of statistical analysis, transcending the mere correlation coefficients and p-values that populate our findings. Instead, we pause to marvel at the whimsical dance between touchdowns and tool belts, between end zone celebrations and the clinking of industrial machinery. Through our exploration, we seek not only to shed light on this improbable linkage but also to infuse the scholarly discourse with a dash of levity, as we ponder the quirky manifestations of economic forces in the world of pigskin prowess.
As we embark on this expedition into uncharted academic terrain, we invite the reader to join us in an intellectual voyage that dances on the boundary between absurdity and insight, where the fervor of football acumen meets the clamor of industrial enterprise. In the pages that follow, we unveil the surprising nexus between Super Bowl glory and the steady hum of hoists and winches, all while balancing the weighty gravity of empirical analysis with the lighthearted whimsy that enriches our scholarly pursuits.

[[RESULTS]]
The statistical analysis of the data revealed a noteworthy correlation between the winning score of the Super Bowl champions and the number of hoist and winch operators in Texas. For the time period spanning from 2003 to 2019, the correlation coefficient was determined to be 0.6481248 with an r-squared value of 0.4200658. The p-value obtained was less than 0.01, indicating a statistically significant relationship between these seemingly unrelated variables.
The strong correlation is visually depicted in Figure 1, which elegantly portrays the undeniable link between the Super Bowl champion's winning score and the demand for hoist and winch operators in the Lone Star State.
It is quite remarkable how the prowess exhibited on the football field appears to have a lingering impact on the labor landscape of Texas. The robust association between these variables invites us to consider the whimsical interplay of sports triumphs and labor market dynamics, adding a sprinkle of intrigue to the world of economic inquiry. While the precise mechanisms underlying this connection may elude us, the empirical evidence of this association stands as a testament to the curious entanglement of sporting achievements and industrial endeavors.
The findings of this research not only validate the presence of a tangible relationship between the winning score of Super Bowl champions and the employment of hoist and winch operators in Texas but also spark contemplation about the quirky manifestations of economic forces in the realm of American football. These results beckon us to embrace the unexpected and to ponder the unanticipated intersections between two seemingly incongruous domains, prompting a delightful blend of pigskin fervor and labor market insight.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research unfurls the intriguing tapestry of the interplay between the winning score of Super Bowl champions and the realm of hoist and winch operators in Texas. The robust correlation coefficient and statistically significant p-value shed light on the unexpected connection between pigskin prowess and industrial demand. It appears that the touchdowns scored on the gridiron have an uncanny knack for hoisting the employment prospects of these operators in the Lone Star State, creating a dizzying spiral of excitement that parallels the revolutions of a winch.

This unexpected tandem of football glory and labor dynamics adds a delightful twist to the world of economic inquiry, reminding us that statistical analysis can be just as full of surprises as an onside kick. The whimsical dance between sporting achievements and industrial endeavors unfolds with a flair of fascination, inviting us to marvel at the whimsical manifestations of economic forces in the domain of American football.

As we turn the page on this eccentric journey, we assert with the solemnity of a quarterback in a two-minute drill that no further research is warranted in this area, as this paper exhaustively unravels the association between the Super Bowl and the hoist and winch operators in Texas, leaving no stone unturned, no punter unaccounted for. We recommend that future explorations in this vein proceed with caution, lest they become entangled in the playful web of correlations and puns that characterizes this peculiar intersection of sports and labor economics.

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 Hoist and Winch: Unraveling the Tether Between Super Bowl Champion's Winning Score and the Sheer Force of Texas Labor. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Sports Engineering and Industrial Labor Relations

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 Hoist and Winch: Unraveling the Tether Between Super Bowl Champion's Winning Score and the Sheer Force of Texas Labor. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Cerebral Sports 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 Hoist and Winch: Unraveling the Tether Between Super Bowl Champion's Winning Score and the Sheer Force of Texas Labor with an abstract of The relationship between sporting events and labor dynamics has long been a subject of curiosity, and the intriguing nexus between the Super Bowl and the bustling hoist and winch operations in the great state of Texas has captivated both scholars and enthusiasts alike. In this paper, we embark on an empirical journey to demystify the enigmatic link between the winning score of the Super Bowl champions and the number of hoist and winch operators in Texas.
Drawing from a rich tapestry of data sources, including Wikipedia for football scores and the Bureau of Labor Statistics for employment figures, we meticulously captured the essence of this connection. Employing rigorous statistical analysis, we unveiled a correlation coefficient of 0.6481248 and a stunning p-value less than 0.01 for the period spanning 2003 to 2019. Our findings not only substantiate the presence of a robust association but also underscore the potential influence of pigskin prowess on the labor landscape.
While the unassailable link between Super Bowl success and the demand for hoist and winch operators in Texas may seem bemusing at first glance, our research aims to provoke deeper contemplation, adding a touch of whimsy to the realm of labor economics. The implications of these irrefutable findings extend beyond mere statistical curiosity, as they beckon us to ponder the quirky interplay of sports triumphs and the labor market, inviting a delightful blend of pigskin fervor and industrial insight into the scholarly discourse.

ChatGPT:

Super Bowl, champion, winning score, Texas labor, hoist operators, winch operators, labor dynamics, sporting events, correlation coefficient, statistical analysis, Bureau of Labor Statistics, football scores, employment figures, labor market, labor economics, Super Bowl success, Texas employment, pigskin prowess.

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

Random correlation

Discover a new correlation

View all correlations

View all research papers

Report an error

Data details

Super Bowl Champion's Winning Score
Source: Wikipedia
See what else correlates with Super Bowl Champion's Winning Score

The number of hoist and winch operators in Texas
Detailed data title: BLS estimate of hoist and winch operators in Texas
Source: Bureau of Larbor Statistics
See what else correlates with The number of hoist and winch operators in Texas

Correlation r = 0.6481248 (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 = 0.4200658 (Coefficient of determination)
This means 42% of the change in the one variable (i.e., The number of hoist and winch operators in Texas) is predictable based on the change in the other (i.e., Super Bowl Champion's Winning Score) over the 17 years from 2003 through 2019.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.0049.^Show 0.0048968070882816600000000000
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 0.65 in 0.49% of random cases. Said differently, if you correlated 204 random variables^Note Which I absolutely did.
with the same 16 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 16 because we have two variables measured over a period of 17 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.24, 0.86 ] 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.

	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019
Super Bowl Champion's Winning Score (Goals scored)	48	32	24	21	29	17	27	31	31	21	34	43	28	24	34	41	13
The number of hoist and winch operators in Texas (Laborers)	640	360	140	100	60	40	30	60	100	220	250	230	120	100	160	150	70

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([48,32,24,21,29,17,27,31,31,21,34,43,28,24,34,41,13,])
array_2 = np.array([640,360,140,100,60,40,30,60,100,220,250,230,120,100,160,150,70,])
array_1_name = "Super Bowl Champion's Winning Score"
array_2_name = "The number of hoist and winch operators in Texas"

# 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 Super Bowl Champion's Winning Score
Line chart for only The number of hoist and winch operators in Texas
AI-generated correlation image
The spurious research paper: Hoist and Winch: Unraveling the Tether Between Super Bowl Champion's Winning Score and the Sheer Force of Texas Labor

View another random correlation

How fun was this correlation?

Your rating is stellar!

Correlation ID: 3876 · Black Variable ID: 92 · Red Variable ID: 14958


Problem variable:
Issue:
Additional details: Optional
Confirm you are a human: