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Spurious correlation #2,561 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Total Number of Gareth Bale's Club Football Matches and the second variable is Automotive recalls issued by Honda.  The chart goes from 2006 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

The more Gareth Bale played, the more spectators' hearts raced, leading to an increased demand for Honda cars, which put pressure on the automotive industry, prompting more recalls to ensure the safety of Bale's enthusiastic fans on the roads. Whether it was his lightning speed or simply the aura of excitement surrounding his games, it seemed that as Bale's club matches went up, so did the need for Honda to call back their cars for a quick fix.

Model: dalle-3
Prompt: Sure, here's an image generation prompt for your request: [Realistic] In a bustling stadium parking lot, Gareth Bale steps onto the field for his 500th club football match. The air is filled with the roar of the crowd and the chorus of Honda car horns honking in celebration. Amidst the excitement, a fleet of Honda cars in the lot start flashing their hazard lights and stalling, while mechanics rush to repair the electrical strain. This causes a surge in recalls issued by Honda, creating a visually chaotic scene in the stadium parking lot. 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: Total Number of Gareth Bale's Club Football Matches and Automotive recalls issued by Honda. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Sci-fi fantacy Symbolism Cybernetic art Realistic An image that looks like it is a scene from a Pixar movie
ChatGPT: Realistic

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 Total Number of Gareth Bale's Club Football Matches and Automotive recalls issued by Honda, in the following situation: Every time Bale plays, the fans honk their Honda car horns in celebration, causing a strain on the electrical system leading to recalls!. Keep the description simple.
ChatGPT: In a busy stadium parking lot, Gareth Bale steps onto the field for his 500th club football match, and the roar of the crowd is met with a chorus of Honda car horns honking in celebration. As the cheers and honking fill the air, a fleet of Honda cars in the lot start flashing their hazard lights and stalling, with mechanics rushing to repair the electrical strain, causing a surge in recalls issued by Honda.

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: [ Realistic ] and depicting this scene: In a busy stadium parking lot, Gareth Bale steps onto the field for his 500th club football match, and the roar of the crowd is met with a chorus of Honda car horns honking in celebration. As the cheers and honking fill the air, a fleet of Honda cars in the lot start flashing their hazard lights and stalling, with mechanics rushing to repair the electrical strain, causing a surge in recalls issued by Honda. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Sure, here's an image generation prompt for your request: [Realistic] In a bustling stadium parking lot, Gareth Bale steps onto the field for his 500th club football match. The air is filled with the roar of the crowd and the chorus of Honda car horns honking in celebration. Amidst the excitement, a fleet of Honda cars in the lot start flashing their hazard lights and stalling, while mechanics rush to repair the electrical strain. This causes a surge in recalls issued by Honda, creating a visually chaotic scene in the stadium parking lot.

*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 Total Number of Gareth Bale's Club Football Matches caused Automotive recalls issued by Honda to increase.

AI academic paper

(Because p < 0.01)
The Bale-Out Effect: An Analysis of the Relationship between Gareth Bale's Total Number of Club Football Matches and Honda Automotive Recalls

The Journal of Unlikely Connections in Research

Jan 2024

Reminder: This paper is AI-generated. Not real!
Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.




Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Total Number of Gareth Bale's Club Football Matches and Automotive recalls issued by Honda. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title seem clever.

Your research team used data from Wikipedia and US DOT to assess this nagging question. You found a correlation coefficient of 0.6787748 and p < 0.01 for 2006 to 2022.

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]]
"The Bale-Out Effect: An Analysis of the Relationship between Gareth Bale's Total Number of Club Football Matches and Honda Automotive Recalls"

[[ABSTRACT]]
This study endeavors to investigate the seemingly unrelated realms of professional football and automotive malfunction through the lens of statistical analysis. By employing data from the infallible source of Wikipedia and the United States Department of Transportation (US DOT), our research team embarked on a journey to unravel the potential connection between the total number of club football matches played by the illustrious Gareth Bale and the issuance of automotive recalls by the notable manufacturer Honda.

Through comprehensive data mining and robust statistical techniques, a correlation coefficient of 0.6787748 and p < 0.01 was derived for the years 2006 to 2022. Despite the initially absurd nature of the inquiry, our findings suggest a noteworthy association between the two seemingly incongruent variables. Our results may incite further investigation into the curious links between athletic prowess and automotive maintenance, underscoring the importance of interdisciplinary research in unraveling the enigmatic web of causality.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Total Number of Gareth Bale's Club Football Matches and Automotive recalls issued by Honda. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
"The Bale-Out Effect: An Analysis of the Relationship between Gareth Bale's Total Number of Club Football Matches and Honda Automotive Recalls"

[[ABSTRACT]]
This study endeavors to investigate the seemingly unrelated realms of professional football and automotive malfunction through the lens of statistical analysis. By employing data from the infallible source of Wikipedia and the United States Department of Transportation (US DOT), our research team embarked on a journey to unravel the potential connection between the total number of club football matches played by the illustrious Gareth Bale and the issuance of automotive recalls by the notable manufacturer Honda.

Through comprehensive data mining and robust statistical techniques, a correlation coefficient of 0.6787748 and p < 0.01 was derived for the years 2006 to 2022. Despite the initially absurd nature of the inquiry, our findings suggest a noteworthy association between the two seemingly incongruent variables. Our results may incite further investigation into the curious links between athletic prowess and automotive maintenance, underscoring the importance of interdisciplinary research in unraveling the enigmatic web of causality.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The intersection of professional sports and automotive industry has long been an underexplored area in the annals of research. As elusive as the Higgs boson, the connection between these two domains has largely eluded scrutiny and analysis. However, the present study boldly ventures into this uncharted territory to probe the potential relationship between the enigmatic Gareth Bale’s total number of club football matches and the issuance of automotive recalls by the venerable manufacturer Honda.

Sporting prowess, particularly in the context of the "beautiful game" of football, has often taken center stage in the public eye, much like a theatrical production with an elaborate set of statistical dynamics. Meanwhile, the automotive industry, with its own quirks and regulations, is no stranger to the spotlight but has seldom shared it with the world of sports, much like an introverted quark amidst the bustling particles of a collider.

The aim, however, is not merely to draw parallels, but to scrutinize the potential causal relationship, if any, between these two seemingly disparate variables. With the precision of a well-calibrated chronometer, our study sets out to unravel the mystery that lies beneath the surface - much like a quantum particle waiting to reveal its properties upon observation.

By assembling a comprehensive dataset from the venerable source of Wikipedia and the authoritative United States Department of Transportation, our research team embarked on the arduous task of data curation and manipulation, akin to navigating through a scientific labyrinth without a working compass.

In doing so, we have heeded the call for interdisciplinary exploration and statistical inquiry – akin to searching for correlations in a galaxy of data, albeit with a touch of good-natured humor and a penchant for puns that would make Schrödinger's cat purr in delight.

The ensuing pages will unravel the saga of our quest, from data collection to analysis, with all the twists and turns of a statistical rollercoaster. We hope to shed light on this unforeseen connection and potentially pave the way for further investigations, all while maintaining the spirit of scientific inquiry and perhaps even injecting a bit of joviality into the otherwise serious discourse of academia.



Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Total Number of Gareth Bale's Club Football Matches and Automotive recalls issued by Honda. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
"The Bale-Out Effect: An Analysis of the Relationship between Gareth Bale's Total Number of Club Football Matches and Honda Automotive Recalls"

[[ABSTRACT]]
This study endeavors to investigate the seemingly unrelated realms of professional football and automotive malfunction through the lens of statistical analysis. By employing data from the infallible source of Wikipedia and the United States Department of Transportation (US DOT), our research team embarked on a journey to unravel the potential connection between the total number of club football matches played by the illustrious Gareth Bale and the issuance of automotive recalls by the notable manufacturer Honda.

Through comprehensive data mining and robust statistical techniques, a correlation coefficient of 0.6787748 and p < 0.01 was derived for the years 2006 to 2022. Despite the initially absurd nature of the inquiry, our findings suggest a noteworthy association between the two seemingly incongruent variables. Our results may incite further investigation into the curious links between athletic prowess and automotive maintenance, underscoring the importance of interdisciplinary research in unraveling the enigmatic web of causality.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intersection of professional sports and automotive industry has long been an underexplored area in the annals of research. As elusive as the Higgs boson, the connection between these two domains has largely eluded scrutiny and analysis. However, the present study boldly ventures into this uncharted territory to probe the potential relationship between the enigmatic Gareth Bale’s total number of club football matches and the issuance of automotive recalls by the venerable manufacturer Honda.
Sporting prowess, particularly in the context of the "beautiful game" of football, has often taken center stage in the public eye, much like a theatrical production with an elaborate set of statistical dynamics. Meanwhile, the automotive industry, with its own quirks and regulations, is no stranger to the spotlight but has seldom shared it with the world of sports, much like an introverted quark amidst the bustling particles of a collider.
The aim, however, is not merely to draw parallels, but to scrutinize the potential causal relationship, if any, between these two seemingly disparate variables. With the precision of a well-calibrated chronometer, our study sets out to unravel the mystery that lies beneath the surface - much like a quantum particle waiting to reveal its properties upon observation.
By assembling a comprehensive dataset from the venerable source of Wikipedia and the authoritative United States Department of Transportation, our research team embarked on the arduous task of data curation and manipulation, akin to navigating through a scientific labyrinth without a working compass.
In doing so, we have heeded the call for interdisciplinary exploration and statistical inquiry – akin to searching for correlations in a galaxy of data, albeit with a touch of good-natured humor and a penchant for puns that would make Schrödinger's cat purr in delight.
The ensuing pages will unravel the saga of our quest, from data collection to analysis, with all the twists and turns of a statistical rollercoaster. We hope to shed light on this unforeseen connection and potentially pave the way for further investigations, all while maintaining the spirit of scientific inquiry and perhaps even injecting a bit of joviality into the otherwise serious discourse of academia.


-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

In the literature pertaining to the connection between sporting achievements and automotive industry phenomena, a myriad of studies have sought to explore the uncharted waters of this seemingly incongruous relationship. Smith et al. (2015) delved into the realm of unexpected correlations, uncovering a surprising association between the number of penalty kicks conceded in football matches and the sales figures of organic kale in urban markets. Moreover, Doe and Jones (2018) observed a peculiar overlap between international cricket tournament outcomes and the purchasing patterns of weather-resistant umbrellas in regions prone to sudden downpours.

Turning our attention to a more specific domain, the oeuvre of non-fictional works offers some intriguing insights. In "The Statistical Symphony of Sports and Machines" (Garcia, 2017), the author infuses dry statistical analyses with a touch of whimsy, akin to a dash of nutmeg in a frothy cappuccino. Furthermore, "Data Dances: A Statistical Rumba with Reliability" (Johnson, 2020) provides a comprehensive overview of statistical techniques in the context of unusual correlations, akin to an intricately choreographed tango between mathematical concepts.

Venturing into the realm of fiction, the classic works such as "The Wheels of Fate" by Dickens (1859) and "The Kick And The Curious: A Tale of Sporting Shenanigans" by Austen (1818) elicit a sense of intrigue and whimsy, much like stumbling upon an unexpected plot twist in a statistical model. While these narratives may appear to be far removed from our academic inquiry, they serve to remind us of the significance of unexpected connections and the joy of unraveling enigmatic puzzles, akin to stumbling upon a comedy amidst a stack of scholarly tomes.

Moreover, anecdotal evidence from social media platforms has also provided casual observations that seem to parallel our current investigation. A user on a popular microblogging site posited that "the number of Cristiano Ronaldo's goals and the price of avocados seem to move in tandem," prompting a flurry of speculative discussions akin to a virtual symposium on unexpected correlations. Similarly, a thread on a forum dedicated to automotive enthusiasts humorously suggested a connection between the frequency of Formula 1 races and the efficiency of dishwashing detergents, highlighting the pervasive nature of seemingly whimsical correlations in everyday discourse.

While the initial foray into these seemingly tangential literary and observational sources may appear whimsical, the amalgamation of various perspectives and sources presents a panorama of unconventional correlations awaiting exploration, akin to stumbling upon a treasure map in a haystack of mundane data. The subsequent sections will build upon this foundation and aim to reconcile the seemingly divergent worlds of sporting accomplishments and automotive reticulation through robust statistical analyses and a hint of scholarly mirth.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Total Number of Gareth Bale's Club Football Matches and Automotive recalls issued by Honda. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Wikipedia and US DOT . You used data from 2006 to 2022

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"The Bale-Out Effect: An Analysis of the Relationship between Gareth Bale's Total Number of Club Football Matches and Honda Automotive Recalls"

[[ABSTRACT]]
This study endeavors to investigate the seemingly unrelated realms of professional football and automotive malfunction through the lens of statistical analysis. By employing data from the infallible source of Wikipedia and the United States Department of Transportation (US DOT), our research team embarked on a journey to unravel the potential connection between the total number of club football matches played by the illustrious Gareth Bale and the issuance of automotive recalls by the notable manufacturer Honda.

Through comprehensive data mining and robust statistical techniques, a correlation coefficient of 0.6787748 and p < 0.01 was derived for the years 2006 to 2022. Despite the initially absurd nature of the inquiry, our findings suggest a noteworthy association between the two seemingly incongruent variables. Our results may incite further investigation into the curious links between athletic prowess and automotive maintenance, underscoring the importance of interdisciplinary research in unraveling the enigmatic web of causality.

[[INTRODUCTION]]
The intersection of professional sports and automotive industry has long been an underexplored area in the annals of research. As elusive as the Higgs boson, the connection between these two domains has largely eluded scrutiny and analysis. However, the present study boldly ventures into this uncharted territory to probe the potential relationship between the enigmatic Gareth Bale’s total number of club football matches and the issuance of automotive recalls by the venerable manufacturer Honda.
Sporting prowess, particularly in the context of the "beautiful game" of football, has often taken center stage in the public eye, much like a theatrical production with an elaborate set of statistical dynamics. Meanwhile, the automotive industry, with its own quirks and regulations, is no stranger to the spotlight but has seldom shared it with the world of sports, much like an introverted quark amidst the bustling particles of a collider.
The aim, however, is not merely to draw parallels, but to scrutinize the potential causal relationship, if any, between these two seemingly disparate variables. With the precision of a well-calibrated chronometer, our study sets out to unravel the mystery that lies beneath the surface - much like a quantum particle waiting to reveal its properties upon observation.
By assembling a comprehensive dataset from the venerable source of Wikipedia and the authoritative United States Department of Transportation, our research team embarked on the arduous task of data curation and manipulation, akin to navigating through a scientific labyrinth without a working compass.
In doing so, we have heeded the call for interdisciplinary exploration and statistical inquiry – akin to searching for correlations in a galaxy of data, albeit with a touch of good-natured humor and a penchant for puns that would make Schrödinger's cat purr in delight.
The ensuing pages will unravel the saga of our quest, from data collection to analysis, with all the twists and turns of a statistical rollercoaster. We hope to shed light on this unforeseen connection and potentially pave the way for further investigations, all while maintaining the spirit of scientific inquiry and perhaps even injecting a bit of joviality into the otherwise serious discourse of academia.


-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

Data Collection:
The data for Gareth Bale's total number of club football matches was sourced from the venerable and seemingly omniscient fountain of information, Wikipedia. We utilized an elaborate process of cross-referencing and fact-checking, much like a detective solving a mind-bending case, to ensure the accuracy and reliability of the data. Every edit on the Wikipedia page was scrutinized with the precision of a hawk-eyed statistician, excluding any instances of erroneous or speculative entries – for we endeavor to maintain statistical integrity, even in the wild and often unpredictable world of online content.

On the other hand, the automotive recall data for Honda was obtained from the United States Department of Transportation (US DOT). Delving into the labyrinthine corridors of automotive safety reports, our team navigated through the digital archives, like intrepid explorers unearthing historical relics, unearthing vital information on automotive recalls issued by Honda from 2006 to 2022. Much like an automotive safety-minded Sherlock Holmes, we meticulously sifted through the data, discarding any anomalies or outliers that threatened to distort the reliability of our findings.

Method of Analysis:
Having acquired the datasets through our intrepid digital scavenger hunt, we subjected the information to a rigorous application of statistical methodologies. Through the application of robust correlation analysis, aided by the precision of mathematical algorithms, we explored the potential relationship between the total number of Gareth Bale's club football matches and the automotive recalls issued by Honda.

The correlation coefficient was calculated with the meticulous care of a watchmaker assembling a pristine timepiece, and the significance level was determined with the unwavering scrutiny of a discerning judge examining evidence in a court of law. The statistical software employed exhibited the resilience of a seasoned warrior, processing the data with the fortitude of a battle-hardened veteran.

Additionally, we conducted time-series analysis to discern any temporal patterns or trends that might elucidate the nature of the relationship between the variables. The data was scrutinized over time intervals with the scrutiny of an aging bottle of wine, seeking to uncover hidden complexities and nuances as one would unravel an intricately woven tapestry.

Limitations:
As with any scientific endeavor, this study is not without its limitations. The data obtained from Wikipedia and US DOT, while extensive and comprehensive, may contain inherent biases or potential inaccuracies, much like the proverbial grain of salt that must be taken when perusing online information. Additionally, the observational nature of the study precludes drawing definitive causal inferences, as the association between Gareth Bale's club football matches and Honda automotive recalls may be confounded by a multitude of unaccounted variables, akin to the elusive and enigmatic dark matter in astrophysical studies.

Nevertheless, armed with a blend of statistical prowess and a sprinkle of scientific curiosity, we set forth on this empirical journey with the hope of shedding light on a peculiar and unexpected relationship, while infusing the rigorous pursuit of knowledge with a dash of lighthearted humor and the occasional statistical pun.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Total Number of Gareth Bale's Club Football Matches and Automotive recalls issued by Honda. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Wikipedia and US DOT .

For the time period 2006 to 2022, you found a correlation 0.6787748, r-squared of 0.4607352, 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]]
"The Bale-Out Effect: An Analysis of the Relationship between Gareth Bale's Total Number of Club Football Matches and Honda Automotive Recalls"

[[ABSTRACT]]
This study endeavors to investigate the seemingly unrelated realms of professional football and automotive malfunction through the lens of statistical analysis. By employing data from the infallible source of Wikipedia and the United States Department of Transportation (US DOT), our research team embarked on a journey to unravel the potential connection between the total number of club football matches played by the illustrious Gareth Bale and the issuance of automotive recalls by the notable manufacturer Honda.

Through comprehensive data mining and robust statistical techniques, a correlation coefficient of 0.6787748 and p < 0.01 was derived for the years 2006 to 2022. Despite the initially absurd nature of the inquiry, our findings suggest a noteworthy association between the two seemingly incongruent variables. Our results may incite further investigation into the curious links between athletic prowess and automotive maintenance, underscoring the importance of interdisciplinary research in unraveling the enigmatic web of causality.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The intersection of professional sports and automotive industry has long been an underexplored area in the annals of research. As elusive as the Higgs boson, the connection between these two domains has largely eluded scrutiny and analysis. However, the present study boldly ventures into this uncharted territory to probe the potential relationship between the enigmatic Gareth Bale’s total number of club football matches and the issuance of automotive recalls by the venerable manufacturer Honda.
Sporting prowess, particularly in the context of the "beautiful game" of football, has often taken center stage in the public eye, much like a theatrical production with an elaborate set of statistical dynamics. Meanwhile, the automotive industry, with its own quirks and regulations, is no stranger to the spotlight but has seldom shared it with the world of sports, much like an introverted quark amidst the bustling particles of a collider.
The aim, however, is not merely to draw parallels, but to scrutinize the potential causal relationship, if any, between these two seemingly disparate variables. With the precision of a well-calibrated chronometer, our study sets out to unravel the mystery that lies beneath the surface - much like a quantum particle waiting to reveal its properties upon observation.
By assembling a comprehensive dataset from the venerable source of Wikipedia and the authoritative United States Department of Transportation, our research team embarked on the arduous task of data curation and manipulation, akin to navigating through a scientific labyrinth without a working compass.
In doing so, we have heeded the call for interdisciplinary exploration and statistical inquiry – akin to searching for correlations in a galaxy of data, albeit with a touch of good-natured humor and a penchant for puns that would make Schrödinger's cat purr in delight.
The ensuing pages will unravel the saga of our quest, from data collection to analysis, with all the twists and turns of a statistical rollercoaster. We hope to shed light on this unforeseen connection and potentially pave the way for further investigations, all while maintaining the spirit of scientific inquiry and perhaps even injecting a bit of joviality into the otherwise serious discourse of academia.


-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The analysis of the relationship between Gareth Bale's total number of club football matches and Honda automotive recalls yielded intriguing findings. The correlation coefficient, a measure of the strength and direction of the linear relationship, was found to be 0.6787748, indicating a moderately strong positive association between these two ostensibly unrelated variables. This statistical nugget of information suggests that as the number of Gareth Bale's club football matches increases, the issuance of automotive recalls by Honda also tends to rise, creating a correlation as compelling as the plot twist in a mystery novel.

Furthermore, the coefficient of determination (r-squared) of 0.4607352 indicated that approximately 46.07% of the variation in automotive recalls issued by Honda can be explained by the total number of Gareth Bale's club football matches. This statistic underscores the capacity of Gareth Bale's on-field exploits to explain a considerable portion of the fluctuations in automotive recalls, juxtaposing the agility and finesse required in statistical modeling with the nimble footwork exhibited on the football pitch.

The p-value of less than 0.01 provides compelling evidence to reject the null hypothesis and assert the presence of a significant relationship between the variables. This result is as robust as a reinforced steel beam, bolstering the credibility of our findings and reinforcing the strength of the association discovered.

Fig. 1 showcases the plot of the total number of Gareth Bale's club football matches against the count of automotive recalls issued by Honda, depicting a visibly discernible trend that aligns with our quantitative analysis. This graph is truly a visualization worth a thousand data points, illustrating the connection between these divergent phenomena with clarity and precision.

While the surreal nature of our inquiry may elicit raised eyebrows and quizzical looks, the statistical evidence suggests a tangible link, sparking contemplation akin to unraveling a complex mathematical theorem amidst the buzz of a football stadium.

The unanticipated revelation of this association emphasizes the unforeseen connections that can emerge from data analysis and serves as a humble reminder of the whimsical surprises that await within the realm of statistical research—a reminder that even in the world of academia, a dash of humor and unexpected correlations can keep the ever-curious intellectual spirit kicking like a well-struck football.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Total Number of Gareth Bale's Club Football Matches and Automotive recalls issued by Honda. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"The Bale-Out Effect: An Analysis of the Relationship between Gareth Bale's Total Number of Club Football Matches and Honda Automotive Recalls"

[[ABSTRACT]]
This study endeavors to investigate the seemingly unrelated realms of professional football and automotive malfunction through the lens of statistical analysis. By employing data from the infallible source of Wikipedia and the United States Department of Transportation (US DOT), our research team embarked on a journey to unravel the potential connection between the total number of club football matches played by the illustrious Gareth Bale and the issuance of automotive recalls by the notable manufacturer Honda.

Through comprehensive data mining and robust statistical techniques, a correlation coefficient of 0.6787748 and p < 0.01 was derived for the years 2006 to 2022. Despite the initially absurd nature of the inquiry, our findings suggest a noteworthy association between the two seemingly incongruent variables. Our results may incite further investigation into the curious links between athletic prowess and automotive maintenance, underscoring the importance of interdisciplinary research in unraveling the enigmatic web of causality.

[[LITERATURE REVIEW]]
In the literature pertaining to the connection between sporting achievements and automotive industry phenomena, a myriad of studies have sought to explore the uncharted waters of this seemingly incongruous relationship. Smith et al. (2015) delved into the realm of unexpected correlations, uncovering a surprising association between the number of penalty kicks conceded in football matches and the sales figures of organic kale in urban markets. Moreover, Doe and Jones (2018) observed a peculiar overlap between international cricket tournament outcomes and the purchasing patterns of weather-resistant umbrellas in regions prone to sudden downpours.
Turning our attention to a more specific domain, the oeuvre of non-fictional works offers some intriguing insights. In "The Statistical Symphony of Sports and Machines" (Garcia, 2017), the author infuses dry statistical analyses with a touch of whimsy, akin to a dash of nutmeg in a frothy cappuccino. Furthermore, "Data Dances: A Statistical Rumba with Reliability" (Johnson, 2020) provides a comprehensive overview of statistical techniques in the context of unusual correlations, akin to an intricately choreographed tango between mathematical concepts.
Venturing into the realm of fiction, the classic works such as "The Wheels of Fate" by Dickens (1859) and "The Kick And The Curious: A Tale of Sporting Shenanigans" by Austen (1818) elicit a sense of intrigue and whimsy, much like stumbling upon an unexpected plot twist in a statistical model. While these narratives may appear to be far removed from our academic inquiry, they serve to remind us of the significance of unexpected connections and the joy of unraveling enigmatic puzzles, akin to stumbling upon a comedy amidst a stack of scholarly tomes.
Moreover, anecdotal evidence from social media platforms has also provided casual observations that seem to parallel our current investigation. A user on a popular microblogging site posited that "the number of Cristiano Ronaldo's goals and the price of avocados seem to move in tandem," prompting a flurry of speculative discussions akin to a virtual symposium on unexpected correlations. Similarly, a thread on a forum dedicated to automotive enthusiasts humorously suggested a connection between the frequency of Formula 1 races and the efficiency of dishwashing detergents, highlighting the pervasive nature of seemingly whimsical correlations in everyday discourse.
While the initial foray into these seemingly tangential literary and observational sources may appear whimsical, the amalgamation of various perspectives and sources presents a panorama of unconventional correlations awaiting exploration, akin to stumbling upon a treasure map in a haystack of mundane data. The subsequent sections will build upon this foundation and aim to reconcile the seemingly divergent worlds of sporting accomplishments and automotive reticulation through robust statistical analyses and a hint of scholarly mirth.

[[RESULTS]]
The analysis of the relationship between Gareth Bale's total number of club football matches and Honda automotive recalls yielded intriguing findings. The correlation coefficient, a measure of the strength and direction of the linear relationship, was found to be 0.6787748, indicating a moderately strong positive association between these two ostensibly unrelated variables. This statistical nugget of information suggests that as the number of Gareth Bale's club football matches increases, the issuance of automotive recalls by Honda also tends to rise, creating a correlation as compelling as the plot twist in a mystery novel.
Furthermore, the coefficient of determination (r-squared) of 0.4607352 indicated that approximately 46.07% of the variation in automotive recalls issued by Honda can be explained by the total number of Gareth Bale's club football matches. This statistic underscores the capacity of Gareth Bale's on-field exploits to explain a considerable portion of the fluctuations in automotive recalls, juxtaposing the agility and finesse required in statistical modeling with the nimble footwork exhibited on the football pitch.
The p-value of less than 0.01 provides compelling evidence to reject the null hypothesis and assert the presence of a significant relationship between the variables. This result is as robust as a reinforced steel beam, bolstering the credibility of our findings and reinforcing the strength of the association discovered.
Fig. 1 showcases the plot of the total number of Gareth Bale's club football matches against the count of automotive recalls issued by Honda, depicting a visibly discernible trend that aligns with our quantitative analysis. This graph is truly a visualization worth a thousand data points, illustrating the connection between these divergent phenomena with clarity and precision.
While the surreal nature of our inquiry may elicit raised eyebrows and quizzical looks, the statistical evidence suggests a tangible link, sparking contemplation akin to unraveling a complex mathematical theorem amidst the buzz of a football stadium.
The unanticipated revelation of this association emphasizes the unforeseen connections that can emerge from data analysis and serves as a humble reminder of the whimsical surprises that await within the realm of statistical research—a reminder that even in the world of academia, a dash of humor and unexpected correlations can keep the ever-curious intellectual spirit kicking like a well-struck football.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The findings of this study have produced truly spectacular results, akin to stumbling upon a pot of statistical gold at the end of a particularly whimsical rainbow. Our results support and extend the existing literature on unexpected correlations, reaffirming the peculiar but undeniably real link between the total number of Gareth Bale's club football matches and the issuance of automotive recalls by Honda.

Our discovery of a correlation coefficient of 0.6787748, with a p-value of less than 0.01, has turned the spotlight onto the unexpected intertwined dance of individual athletic prowess and automotive engineering finesse. This unforeseen association has indeed bolstered the findings of prior research that delved into seemingly whimsical correlations. The works of Smith et al. (2015) and Doe and Jones (2018) paved the way for embracing unexpected links, much like boldly stepping onto the dance floor of unconventional statistical relationships.

We have observed a moderately strong positive association between Gareth Bale's on-field exploits and the issuance of automotive recalls by the esteemed manufacturer, Honda. The r-squared value of 0.4607352 encapsulates the narrative of how approximately 46.07% of the variation in automotive recalls issued by Honda can be elucidated by the astoundingly consistent performances of Gareth Bale on the field. This statistic is as revealing as a freshly uncovered plot twist in a statistical thriller, underscoring the power of individual sporting accomplishments to foretell automotive disruptions.

Our results depict a tale of statistical significance and robustness, much like navigating through a labyrinth of data with the precision of an ace footballer. The correlation uncovered transcends the boundaries of the expected, infusing statistics with an unexpected sense of mirth and revelry, akin to stumbling upon a well-placed punchline in a voluminous tome of scholarly literature.

The visual representation of our findings, as depicted in Fig. 1, resonates with the clarity and precision of a beautifully executed statistical model. The narrative it weaves is as compelling as a Shakespearean tragedy, portraying the ebb and flow of automotive recalls in tandem with Gareth Bale's on-field exploits.

In conclusion, our study has illuminated a pathway for further investigation into the intertwined tapestry of sports and industry, reminding the academic community of the exhilarating surprises that await within the realm of statistical research. Our findings serve as a whimsical reminder that even in the disciplined realm of academia, unexpected correlations and a touch of scholarly mirth can enrich the tapestry of knowledge, much like an unexpected punchline nestled within the earnest pages of a research paper.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 Total Number of Gareth Bale's Club Football Matches and Automotive recalls issued by Honda. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"The Bale-Out Effect: An Analysis of the Relationship between Gareth Bale's Total Number of Club Football Matches and Honda Automotive Recalls"

[[ABSTRACT]]
This study endeavors to investigate the seemingly unrelated realms of professional football and automotive malfunction through the lens of statistical analysis. By employing data from the infallible source of Wikipedia and the United States Department of Transportation (US DOT), our research team embarked on a journey to unravel the potential connection between the total number of club football matches played by the illustrious Gareth Bale and the issuance of automotive recalls by the notable manufacturer Honda.

Through comprehensive data mining and robust statistical techniques, a correlation coefficient of 0.6787748 and p < 0.01 was derived for the years 2006 to 2022. Despite the initially absurd nature of the inquiry, our findings suggest a noteworthy association between the two seemingly incongruent variables. Our results may incite further investigation into the curious links between athletic prowess and automotive maintenance, underscoring the importance of interdisciplinary research in unraveling the enigmatic web of causality.

[[INTRDUCTION]]
The intersection of professional sports and automotive industry has long been an underexplored area in the annals of research. As elusive as the Higgs boson, the connection between these two domains has largely eluded scrutiny and analysis. However, the present study boldly ventures into this uncharted territory to probe the potential relationship between the enigmatic Gareth Bale’s total number of club football matches and the issuance of automotive recalls by the venerable manufacturer Honda.
Sporting prowess, particularly in the context of the "beautiful game" of football, has often taken center stage in the public eye, much like a theatrical production with an elaborate set of statistical dynamics. Meanwhile, the automotive industry, with its own quirks and regulations, is no stranger to the spotlight but has seldom shared it with the world of sports, much like an introverted quark amidst the bustling particles of a collider.
The aim, however, is not merely to draw parallels, but to scrutinize the potential causal relationship, if any, between these two seemingly disparate variables. With the precision of a well-calibrated chronometer, our study sets out to unravel the mystery that lies beneath the surface - much like a quantum particle waiting to reveal its properties upon observation.
By assembling a comprehensive dataset from the venerable source of Wikipedia and the authoritative United States Department of Transportation, our research team embarked on the arduous task of data curation and manipulation, akin to navigating through a scientific labyrinth without a working compass.
In doing so, we have heeded the call for interdisciplinary exploration and statistical inquiry – akin to searching for correlations in a galaxy of data, albeit with a touch of good-natured humor and a penchant for puns that would make Schrödinger's cat purr in delight.
The ensuing pages will unravel the saga of our quest, from data collection to analysis, with all the twists and turns of a statistical rollercoaster. We hope to shed light on this unforeseen connection and potentially pave the way for further investigations, all while maintaining the spirit of scientific inquiry and perhaps even injecting a bit of joviality into the otherwise serious discourse of academia.


[[RESULTS]]
The analysis of the relationship between Gareth Bale's total number of club football matches and Honda automotive recalls yielded intriguing findings. The correlation coefficient, a measure of the strength and direction of the linear relationship, was found to be 0.6787748, indicating a moderately strong positive association between these two ostensibly unrelated variables. This statistical nugget of information suggests that as the number of Gareth Bale's club football matches increases, the issuance of automotive recalls by Honda also tends to rise, creating a correlation as compelling as the plot twist in a mystery novel.
Furthermore, the coefficient of determination (r-squared) of 0.4607352 indicated that approximately 46.07% of the variation in automotive recalls issued by Honda can be explained by the total number of Gareth Bale's club football matches. This statistic underscores the capacity of Gareth Bale's on-field exploits to explain a considerable portion of the fluctuations in automotive recalls, juxtaposing the agility and finesse required in statistical modeling with the nimble footwork exhibited on the football pitch.
The p-value of less than 0.01 provides compelling evidence to reject the null hypothesis and assert the presence of a significant relationship between the variables. This result is as robust as a reinforced steel beam, bolstering the credibility of our findings and reinforcing the strength of the association discovered.
Fig. 1 showcases the plot of the total number of Gareth Bale's club football matches against the count of automotive recalls issued by Honda, depicting a visibly discernible trend that aligns with our quantitative analysis. This graph is truly a visualization worth a thousand data points, illustrating the connection between these divergent phenomena with clarity and precision.
While the surreal nature of our inquiry may elicit raised eyebrows and quizzical looks, the statistical evidence suggests a tangible link, sparking contemplation akin to unraveling a complex mathematical theorem amidst the buzz of a football stadium.
The unanticipated revelation of this association emphasizes the unforeseen connections that can emerge from data analysis and serves as a humble reminder of the whimsical surprises that await within the realm of statistical research—a reminder that even in the world of academia, a dash of humor and unexpected correlations can keep the ever-curious intellectual spirit kicking like a well-struck football.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation into the "Bale-Out Effect" has unveiled a noteworthy association between Gareth Bale's total number of club football matches and the issuance of automotive recalls by Honda. The correlation coefficient of 0.6787748 and the p-value of less than 0.01 indicate a compelling statistical relationship, as solid as a goalkeeper's defense. This unanticipated correlation serves as a testament to the serendipitous discoveries that await within the realm of interdisciplinary research, akin to finding a hidden gem in a sea of statistical data.

While our findings may appear as unexpected as an own-goal, they emphasize the importance of considering unconventional variables in statistical analyses and the potential for unexpected connections to emerge—a valuable lesson that reverberates through the hallowed halls of academia like a well-struck penalty kick.

This inquiry sheds light on the potential impact of sporting events on consumer products, unraveling a web of causality as intricate as a striker's footwork in the box. It also underscores the quirky and playful nature of statistical exploration, akin to a delightful dance between variables and coefficients—an ode to the whimsical surprises that await within the domain of research.

With that said, we contend that no further research is needed in this area. The door to this peculiar pairing of football matches and automotive recalls has been delightfully kicked open, revealing a statistically significant connection that warrants acknowledgment and, perhaps, a good-natured chuckle. In the immortal words of the legendary football coach, Vince Lombardi, "If winning isn't everything, why do they keep score?" Our statistical analysis has revealed a winning connection, leaving no need for further investigation into this comical yet intriguing relationship.


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 The Bale-Out Effect: An Analysis of the Relationship between Gareth Bale's Total Number of Club Football Matches and Honda Automotive Recalls. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Unlikely Connections in Research


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 The Bale-Out Effect: An Analysis of the Relationship between Gareth Bale's Total Number of Club Football Matches and Honda Automotive Recalls. Respond only with the name of a fictional organization.

ChatGPT:

The International Institute for Quirky Research Studies


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 The Bale-Out Effect: An Analysis of the Relationship between Gareth Bale's Total Number of Club Football Matches and Honda Automotive Recalls with an abstract of This study endeavors to investigate the seemingly unrelated realms of professional football and automotive malfunction through the lens of statistical analysis. By employing data from the infallible source of Wikipedia and the United States Department of Transportation (US DOT), our research team embarked on a journey to unravel the potential connection between the total number of club football matches played by the illustrious Gareth Bale and the issuance of automotive recalls by the notable manufacturer Honda.
Through comprehensive data mining and robust statistical techniques, a correlation coefficient of 0.6787748 and p < 0.01 was derived for the years 2006 to 2022. Despite the initially absurd nature of the inquiry, our findings suggest a noteworthy association between the two seemingly incongruent variables. Our results may incite further investigation into the curious links between athletic prowess and automotive maintenance, underscoring the importance of interdisciplinary research in unraveling the enigmatic web of causality.

ChatGPT:

"Gareth Bale club football matches," "Honda automotive recalls," "statistical analysis football matches and automotive recalls," "association between football matches and automotive recalls," "correlation coefficient football matches and automotive recalls," "interdisciplinary research athletic prowess and automotive maintenance," "Gareth Bale Wikipedia data," "Honda US DOT recalls," "causality football matches and automotive recalls"

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



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Data details

Total Number of Gareth Bale's Club Football Matches
Source: Wikipedia
See what else correlates with Total Number of Gareth Bale's Club Football Matches

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

Correlation r = 0.6787748 (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 = 0.4607352 (Coefficient of determination)
This means 46.1% of the change in the one variable (i.e., Automotive recalls issued by Honda) is predictable based on the change in the other (i.e., Total Number of Gareth Bale's Club Football Matches) over the 17 years from 2006 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.0027. 0.0027361857560294894000000000
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 0.68 in 0.27% of random cases. Said differently, if you correlated 365 random variables Which I absolutely did.
with the same 16 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 16 because we have two variables measured over a period of 17 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.29, 0.87 ] 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.
20062007200820092010201120122013201420152016201720182019202020212022
Total Number of Gareth Bale's Club Football Matches (Matches)243123034414244444831273942203413
Automotive recalls issued by Honda (Recalls)313741416161515211817232218137




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.




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([2,43,12,30,34,41,42,44,44,48,31,27,39,42,20,34,13,])
array_2 = np.array([3,13,7,4,14,16,16,15,15,21,18,17,23,22,18,13,7,])
array_1_name = "Total Number of Gareth Bale's Club Football Matches"
array_2_name = "Automotive recalls issued by Honda"

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

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



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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. 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.

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Correlation ID: 2561 · Black Variable ID: 357 · Red Variable ID: 1123
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