Spurious correlation #2,896 · View random

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This page remains only to prevent link rot.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Roger Federer's annual earnings and the second variable is Sales of LP/Vinyl Albums. The chart goes from 1998 to 2022, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Roger Federer's annual earnings and the second variable is Sales of LP/Vinyl Albums. The chart goes from 1998 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As Roger Federer's earnings rose, more people wanted to experience a "richer" sound, leading to a resurgence in the popularity of classic vinyl albums.

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a cozy living room with bright, vibrant colors and bold patterns, resembling a pop art style. Show Roger Federer surrounded by shelves filled with an expansive collection of vintage vinyl records. He is flipping through the records with a content expression on his face, and in the background, his fans are seen flocking to local record stores, creating a bustling retro music scene. The turntable is spinning, emitting warm, colorful waves to convey the impact of the music on the room and the surrounding environment. 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: Roger Federer's annual earnings and Sales of LP/Vinyl Albums. 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: Surrealism a meme Sci-fi fantacy Pop art An image that looks like it is a scene from 'Star Wars'
ChatGPT: Pop art

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 Roger Federer's annual earnings and Sales of LP/Vinyl Albums, in the following situation: Sales of LP/Vinyl Albums increased because with more money, Roger Federer could afford to buy a larger record collection, leading to increased interest in vinyl among his fans. As people saw him "serving" up some groovy tunes, they wanted to "rally" around the vintage sound, creating a "retro racket" in the music industry.. Keep the description simple.
ChatGPT: In a cozy living room adorned with shelves filled with vintage vinyl records, Roger Federer flips through his expansive collection, his annual earnings allowing him to indulge in his passion for music. As the turntable spins and fills the room with warm melodies, his fans, inspired by his musical tastes, flock to local record stores, causing the sales of LP/vinyl albums to surge, creating a retro music boom.

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: [ Pop art ] and depicting this scene: In a cozy living room adorned with shelves filled with vintage vinyl records, Roger Federer flips through his expansive collection, his annual earnings allowing him to indulge in his passion for music. As the turntable spins and fills the room with warm melodies, his fans, inspired by his musical tastes, flock to local record stores, causing the sales of LP/vinyl albums to surge, creating a retro music boom. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a cozy living room with bright, vibrant colors and bold patterns, resembling a pop art style. Show Roger Federer surrounded by shelves filled with an expansive collection of vintage vinyl records. He is flipping through the records with a content expression on his face, and in the background, his fans are seen flocking to local record stores, creating a bustling retro music scene. The turntable is spinning, emitting warm, colorful waves to convey the impact of the music on the room and the surrounding environment.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Roger Federer's annual earnings caused Sales of LP/Vinyl Albums to increase.

AI academic paper

(Because p < 0.01)

Love-Love: Exploring the Groovy Relationship Between Roger Federer's Earnings and LP/Vinyl Album Sales

The Journal of Sports Economics and Musical Trends

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 Roger Federer's annual earnings and Sales of LP/Vinyl Albums. Make lots of jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name some cartoons and childrens' shows that you watched that are related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
Love-Love: Exploring the Groovy Relationship Between Roger Federer's Earnings and LP/Vinyl Album Sales

[[ABSTRACT]]
In this paper, we serve up some ace insights into the surprisingly harmonious correlation between the annual earnings of tennis legend Roger Federer and the sales of LP/vinyl albums. As we volley into the nitty-gritty, we uncover a striking correlation coefficient of 0.9114131, with a p-value of less than 0.01 based on data from 1998 to 2022. Our findings suggest that as Federer's earnings soared like a well-placed lob, so did the sales of LP/vinyl albums, forming a grand slam connection between the two seemingly unrelated variables. Through this research, we aim to lob some light-hearted fun into the world of academia while also uncovering meaningful connections that otherwise might have been lost in the noise.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Ladies and gentlemen, esteemed colleagues, and fellow aficionados of the sublime art of statistical analysis, prepare to be served a delectable volley of findings that will leave you spinning like a well-angled topspin forehand! In this paper, we endeavor to unravel the mesmerizing connection between the annual earnings of the distinguished tennis virtuoso Roger Federer and the groovy sales of LP/vinyl albums.
As we embark on this scientific odyssey, it is essential to appreciate the whimsical nature of this investigation. Uniting the world of professional sports and the nostalgic allure of vinyl records may seem as incongruous as a kangaroo attempting to master the art of ballet. However, as with any captivating research endeavor, one must be prepared to embrace the unexpected and view the world through the lens of curiosity and bold exploration.
Before diving headfirst into the exhilarating depths of our findings, it is paramount to acknowledge the intriguing genesis of this research inquiry. Picture, if you will, a spirited debate between a group of intrepid researchers as they pondered the potential interplay of variables that seemingly inhabited disparate realms. Some might have posited that the correlation between Roger Federer's earnings and LP/vinyl album sales was as likely as stumbling upon a unicorn prancing through a statistical meadow. Yet, dear reader, sometimes the most whimsical pairings yield the most awe-inspiring revelations.
With our scientific rackets at the ready and our data sets meticulously curated, we set out to scrutinize the relationship between the earnings of the illustrious tennis maestro and the buoyant sales of those charming, circular sound vessels known as LP/vinyl albums. One might ask, "Why these two variables in particular?" To that, we respond with a mischievous twinkle in our eyes, "Why not?"
As we delve into the heart of this investigation, we invite you to accompany us on this intellectual frolic, where statistical analyses are adorned with a dash of whimsy and scholarly pursuits are infused with the infectious rhythm of discovery. Buckle up, fellow travelers of the academic cosmos, for we are about to embark on a scientific adventure that will leave you marveling at the improbable and embracing the uncanny – all in the pursuit of shedding light on the inexplicable bond between Roger Federer's earnings and the enchanting world of LP/vinyl album sales.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Smith et al. 2010," the researchers investigate the correlation between celebrity earnings and cultural influences. While their focus seems worlds apart from our own, their work lays the groundwork for understanding the interplay of celebrity success and societal trends. Building on this, "Doe and Jones 2015" delve into the captivating world of entertainment economics, exploring the unanticipated connections between famous personalities and consumer behavior. Their meticulous analysis of consumer spending habits provides a compelling backdrop for our own exploration.

But now, let's take a wild detour into the world of non-fiction books that could somewhat relate to our topic. In "The Vinyl Frontier" by Jonathan Scott, the author delves into the resurgence of vinyl records in the digital age, shedding light on the whims of modern music enthusiasts who yearn for the tactile experience of needle meeting groove. "Cash: The Autobiography" by Johnny Cash offers a personal account of the music industry during the heyday of vinyl, providing insights into the cultural and economic dynamics that shaped the era.

Now, as we navigate through the fictional realm, we encounter "High Fidelity" by Nick Hornby, a novel that waltzes through the love affairs and music obsessions of a compulsive list-maker. This literary gem immerses readers in the quirky subculture of vinyl enthusiasts and encapsulates the intoxicating allure of music in physical form. In a parallel universe, "The Curious Incident of the Dog in the Night-Time" by Mark Haddon offers a unique perspective on patterns and connections, albeit not directly related to our topic. Who knew that a tale of a detective-wannabe could unlock the mysteries of statistical relationships?

And now, let's tap into the nostalgia-inducing, cartoon landscape. "Scooby-Doo" takes us on a whimsical adventure where mystery-solving and groovy soundtracks reign supreme. While our paper is less about unmasking villains and more about unraveling statistical mysteries, the spirit of exploration and unexpected revelations aligns with our scholarly pursuit. Lastly, "Phineas and Ferb" invites us to embrace sheer creativity and audacious experimentation, much like our endeavor to uncover the peculiar connection between Roger Federer's earnings and the sale of LP/vinyl albums. After all, who wouldn't want to whistle a merry tune while analyzing statistical data?

With these in mind, we now turn to the serious scholarship and lighthearted musings that underpin our quest to illuminate the eccentric, yet gripping, relationship between the financial triumphs of Roger Federer and the melodious allure of LP/vinyl albums.

The ball is in our court, and we're ready for an ace of a time!

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 Roger Federer's annual earnings and Sales of LP/Vinyl Albums. Make lots of 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 Statista . You used data from 1998 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]]
Love-Love: Exploring the Groovy Relationship Between Roger Federer's Earnings and LP/Vinyl Album Sales

[[ABSTRACT]]
In this paper, we serve up some ace insights into the surprisingly harmonious correlation between the annual earnings of tennis legend Roger Federer and the sales of LP/vinyl albums. As we volley into the nitty-gritty, we uncover a striking correlation coefficient of 0.9114131, with a p-value of less than 0.01 based on data from 1998 to 2022. Our findings suggest that as Federer's earnings soared like a well-placed lob, so did the sales of LP/vinyl albums, forming a grand slam connection between the two seemingly unrelated variables. Through this research, we aim to lob some light-hearted fun into the world of academia while also uncovering meaningful connections that otherwise might have been lost in the noise.

[[INTRODUCTION]]
Ladies and gentlemen, esteemed colleagues, and fellow aficionados of the sublime art of statistical analysis, prepare to be served a delectable volley of findings that will leave you spinning like a well-angled topspin forehand! In this paper, we endeavor to unravel the mesmerizing connection between the annual earnings of the distinguished tennis virtuoso Roger Federer and the groovy sales of LP/vinyl albums.
As we embark on this scientific odyssey, it is essential to appreciate the whimsical nature of this investigation. Uniting the world of professional sports and the nostalgic allure of vinyl records may seem as incongruous as a kangaroo attempting to master the art of ballet. However, as with any captivating research endeavor, one must be prepared to embrace the unexpected and view the world through the lens of curiosity and bold exploration.
Before diving headfirst into the exhilarating depths of our findings, it is paramount to acknowledge the intriguing genesis of this research inquiry. Picture, if you will, a spirited debate between a group of intrepid researchers as they pondered the potential interplay of variables that seemingly inhabited disparate realms. Some might have posited that the correlation between Roger Federer's earnings and LP/vinyl album sales was as likely as stumbling upon a unicorn prancing through a statistical meadow. Yet, dear reader, sometimes the most whimsical pairings yield the most awe-inspiring revelations.
With our scientific rackets at the ready and our data sets meticulously curated, we set out to scrutinize the relationship between the earnings of the illustrious tennis maestro and the buoyant sales of those charming, circular sound vessels known as LP/vinyl albums. One might ask, "Why these two variables in particular?" To that, we respond with a mischievous twinkle in our eyes, "Why not?"
As we delve into the heart of this investigation, we invite you to accompany us on this intellectual frolic, where statistical analyses are adorned with a dash of whimsy and scholarly pursuits are infused with the infectious rhythm of discovery. Buckle up, fellow travelers of the academic cosmos, for we are about to embark on a scientific adventure that will leave you marveling at the improbable and embracing the uncanny – all in the pursuit of shedding light on the inexplicable bond between Roger Federer's earnings and the enchanting world of LP/vinyl album sales.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To unravel the enigmatic connection between the financial triumphs of Roger Federer and the resonant allure of LP/vinyl albums, our intrepid research team immersed themselves in a concoction of statistical wizardry and digital excavation that would make even the most ambitious data miner blush with admiration.

Data Collection:
The first step in our convoluted dance of data collection involved scouring the vast plains of the internet, armed with little more than a fervent desire for truth and access to Wikipedia. We meticulously combed through decades of financial disclosures, tournament winnings, endorsement deals, and other sundry sources to assemble an exhaustive chronicle of Roger Federer's annual earnings. Meanwhile, in the vibrant realm of music commerce, we tapped into the musical archives and ancient tomes of Statista to procure the global sales figures of LP/vinyl albums from 1998 to 2022. It should be noted that attempts to procure the data through more orthodox channels were met with flinching stares and raised eyebrows, prompting our reliance on the virtual bastions of knowledge.

Data Processing:
With our cacophony of raw data in hand, we engaged in a spirited tango with spreadsheets and statistical software to wrangle the information into submission. Utilizing an arsenal of mathematical incantations, we calculated annual earnings trends for Roger Federer and charted the undulating waves of LP/vinyl album sales with a finesse that would make Pythagoras blush with mathematical envy.

Statistical Analysis:
In the grand tradition of statistical scrutiny, we harnessed the formidable power of correlation analysis to explore the synchronicity between the maestro's earnings and the melodic transactions of LP/vinyl albums. The Pearson correlation coefficient emerged as our trusty companion, illuminating the degree of association between these seemingly disparate variables. Riddled with excitement, we calculated p-values, confidence intervals, and conducted hypothesis tests with the gusto of a caffeine-infused mathematician on the brink of enlightenment.

Control Variables:
In our earnest endeavor to tease out a robust relationship, we also employed a ballet of control variables to thwart the mischievous whispers of lurking confounders. Factors such as global economic indicators, technological advancements in music distribution, and the inevitable shifts in cultural preferences for vintage auditory experiences were corralled and scrutinized to ensure that our findings danced to the tune of empirical rigor.

Sensitivity Analysis:
To fortify the bulwarks of our findings, we cordially invited the specter of sensitivity analysis to our scholarly soiree. By delicately altering the parameters and assumptions of our statistical models, we gauged the resilience of our results, ensuring that the whims of statistical fortune did not lead us astray.

Ethical Considerations:
Amidst the fervor of our analytical pursuit, we remain vigilant custodians of academic integrity. All data sources were acknowledged with the reverence due to digital patriots of knowledge, and no vinyl record or tennis racket was harmed in the pursuit of our research. Our commitment to scientific ethics remained unyielding, even in the face of tempting shenanigans involving Wimbledon tickets and rare LPs.

In summary, our methodology represents a harmonious blend of rigorous scrutiny, whimsical exploration, and statistical hijinks, allowing us to peel back the layers of this compelling relationship between the illustrious Roger Federer's earnings and the charming siren song of LP/vinyl album sales. Queued with anticipation, our findings are poised to astound and delight, much like a perfectly executed drop shot on the wondrous tapestries of academic 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 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 Roger Federer's annual earnings and Sales of LP/Vinyl Albums. Make lots of 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]]
Love-Love: Exploring the Groovy Relationship Between Roger Federer's Earnings and LP/Vinyl Album Sales

[[ABSTRACT]]
In this paper, we serve up some ace insights into the surprisingly harmonious correlation between the annual earnings of tennis legend Roger Federer and the sales of LP/vinyl albums. As we volley into the nitty-gritty, we uncover a striking correlation coefficient of 0.9114131, with a p-value of less than 0.01 based on data from 1998 to 2022. Our findings suggest that as Federer's earnings soared like a well-placed lob, so did the sales of LP/vinyl albums, forming a grand slam connection between the two seemingly unrelated variables. Through this research, we aim to lob some light-hearted fun into the world of academia while also uncovering meaningful connections that otherwise might have been lost in the noise.

[[LITERATURE REVIEW]]
In "Smith et al. 2010," the researchers investigate the correlation between celebrity earnings and cultural influences. While their focus seems worlds apart from our own, their work lays the groundwork for understanding the interplay of celebrity success and societal trends. Building on this, "Doe and Jones 2015" delve into the captivating world of entertainment economics, exploring the unanticipated connections between famous personalities and consumer behavior. Their meticulous analysis of consumer spending habits provides a compelling backdrop for our own exploration.
But now, let's take a wild detour into the world of non-fiction books that could somewhat relate to our topic. In "The Vinyl Frontier" by Jonathan Scott, the author delves into the resurgence of vinyl records in the digital age, shedding light on the whims of modern music enthusiasts who yearn for the tactile experience of needle meeting groove. "Cash: The Autobiography" by Johnny Cash offers a personal account of the music industry during the heyday of vinyl, providing insights into the cultural and economic dynamics that shaped the era.
Now, as we navigate through the fictional realm, we encounter "High Fidelity" by Nick Hornby, a novel that waltzes through the love affairs and music obsessions of a compulsive list-maker. This literary gem immerses readers in the quirky subculture of vinyl enthusiasts and encapsulates the intoxicating allure of music in physical form. In a parallel universe, "The Curious Incident of the Dog in the Night-Time" by Mark Haddon offers a unique perspective on patterns and connections, albeit not directly related to our topic. Who knew that a tale of a detective-wannabe could unlock the mysteries of statistical relationships?
And now, let's tap into the nostalgia-inducing, cartoon landscape. "Scooby-Doo" takes us on a whimsical adventure where mystery-solving and groovy soundtracks reign supreme. While our paper is less about unmasking villains and more about unraveling statistical mysteries, the spirit of exploration and unexpected revelations aligns with our scholarly pursuit. Lastly, "Phineas and Ferb" invites us to embrace sheer creativity and audacious experimentation, much like our endeavor to uncover the peculiar connection between Roger Federer's earnings and the sale of LP/vinyl albums. After all, who wouldn't want to whistle a merry tune while analyzing statistical data?
With these in mind, we now turn to the serious scholarship and lighthearted musings that underpin our quest to illuminate the eccentric, yet gripping, relationship between the financial triumphs of Roger Federer and the melodious allure of LP/vinyl albums.
The ball is in our court, and we're ready for an ace of a time!

[[RESULTS]]
The results of our analysis serve up an ace of a revelation that is bound to make even the most stoic of statisticians crack a smile. We discovered a striking correlation coefficient of 0.9114131 between the annual earnings of the illustrious Roger Federer and the sales of LP/vinyl albums, spanning the years 1998 to 2022. To put it in tennis terms, this correlation is as strong as a serve from the great Federer himself!
In the world of statistics, a correlation coefficient close to 1 indicates a strong positive relationship between two variables. In this case, it's as if Federer's earnings and LP/vinyl album sales were engaged in a synchronized dance, moving in perfect harmony like a well-coordinated doubles team at Wimbledon. The r-squared value of 0.8306738 further reinforces this connection, suggesting that a staggering 83% of the variation in LP/vinyl album sales can be explained by the fluctuations in Roger Federer's annual earnings. Who knew that beneath the sleek surface of statistical analysis lay a groovy rhythm waiting to be uncovered?
Now, let's talk about the p-value. With a p-value of less than 0.01, our findings are about as statistically significant as a rare moment of on-court levity from the usually serious-faced Federer. This means that the likelihood of observing such a strong relationship between the variables due to random chance is, well, quite unlikely – almost as unlikely as witnessing a serve clocked at 163 mph while juggling LP/vinyl albums.
And now, for the pièce de résistance, we present the visual showcase of this unexpected union – the scatterplot (Fig. 1). Brace yourselves, fellow scholars, as you feast your eyes upon a graph that captures the remarkable interplay between the annual earnings of the tennis virtuoso and the sales of those musical relics known as LP/vinyl albums. It's a sight to behold, akin to witnessing a perfectly executed drop shot or a flawless one-handed backhand – an elegant and awe-inspiring display of statistical artistry.
In conclusion, our findings reveal a connection between Roger Federer's earnings and the sales of LP/vinyl albums that is as harmonious as a well-struck chord on a vintage vinyl record. Through this research, we have not only uncovered an unexpected correlation but have also served up a lighthearted reminder that in the world of statistics, as in life, there's always room for a bit of whimsy and wonder.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

In the game of research, our findings have aced their way into the hallowed halls of statistical revelations, revealing a correlation between Roger Federer's annual earnings and the sales of LP/vinyl albums that is as surprisingly seamless as a perfectly executed drop shot. Our results not only serve as a testament to the unanticipated connections that can be uncovered through rigorous analysis but also add a delightful dash of whimsy to the often-serious realm of scholarly inquiry.

Building on the whimsical detours taken in our literature review, we tastefully emulated the thoroughness and rigor of Smith et al. (2010) and Doe and Jones (2015) in exploring the interplay of celebrity success and cultural trends. While the world of non-fiction literature and cartoon adventures may have seemed like playful diversions, these seemingly unrelated references aligned with our findings, emphasizing the unexpected patterns and correlations that can emerge when exploring seemingly disparate spheres.

Our results not only support the prior research that laid the groundwork for understanding the interplay of celebrity success and societal trends but also enhance it with a groovy twist. The correlation coefficient of 0.9114131, akin to a match point in statistical significance, echoes the interconnectedness of celebrity earnings and consumer behavior illuminated by Smith et al. (2010) and Doe and Jones (2015). Furthermore, our staggering r-squared value of 0.8306738 reinforces the compelling notion that a significant portion of the variation in LP/vinyl album sales can be attributed to the fluctuations in Roger Federer's annual earnings, thereby enriching the existing scholarship in understanding the far-reaching impacts of celebrity influence.

As we volley into uncharted statistical territories, our findings unmask the enigmatic relationship between the financial triumphs of a global tennis icon and the melodic allure of retro music formats. The p-value of less than 0.01 serves as a testament to the statistical significance of this unexpected connection, akin to witnessing a rare moment of on-court levity from the usually composed Federer. This underlines the unlikelihood of observing such a strong relationship due to random chance, reminiscent of the improbable sight of a serve clocked at 163 mph while juggling LP/vinyl albums – both captivating and statistically improbable feats.

Our visual showcase, the scatterplot (Fig. 1), serves as a captivating testament to the enthralling dance of financial success and musical appreciation. Just as a perfectly executed drop shot embodies the pinnacle of tennis finesse, our scatterplot encapsulates the elegance and artistry of statistical analysis. It epitomizes the ability of data visualization to communicate complex relationships in a visually captivating manner, much like a perfectly executed one-handed backhand – an elegant display of finesse and precision that transcends the confines of the tennis court.

In unraveling the peculiar relationship between Roger Federer's earnings and the sales of LP/vinyl albums, our research not only underscores the surprising interconnectedness of ostensibly unrelated variables but also injects a spirit of lighthearted curiosity into the scholarly pursuit. Through this unconventional exploration, we have unveiled a harmony between economic triumphs and analogue nostalgia that is as captivating as a well-struck chord on a vintage vinyl record, reminding researchers and readers alike that even in the realm of statistics, there's always room for a bit of whimsy and wonder.

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 Roger Federer's annual earnings and Sales of LP/Vinyl Albums. Make lots of 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]]
Love-Love: Exploring the Groovy Relationship Between Roger Federer's Earnings and LP/Vinyl Album Sales

[[ABSTRACT]]
In this paper, we serve up some ace insights into the surprisingly harmonious correlation between the annual earnings of tennis legend Roger Federer and the sales of LP/vinyl albums. As we volley into the nitty-gritty, we uncover a striking correlation coefficient of 0.9114131, with a p-value of less than 0.01 based on data from 1998 to 2022. Our findings suggest that as Federer's earnings soared like a well-placed lob, so did the sales of LP/vinyl albums, forming a grand slam connection between the two seemingly unrelated variables. Through this research, we aim to lob some light-hearted fun into the world of academia while also uncovering meaningful connections that otherwise might have been lost in the noise.

[[INTRDUCTION]]
Ladies and gentlemen, esteemed colleagues, and fellow aficionados of the sublime art of statistical analysis, prepare to be served a delectable volley of findings that will leave you spinning like a well-angled topspin forehand! In this paper, we endeavor to unravel the mesmerizing connection between the annual earnings of the distinguished tennis virtuoso Roger Federer and the groovy sales of LP/vinyl albums.
As we embark on this scientific odyssey, it is essential to appreciate the whimsical nature of this investigation. Uniting the world of professional sports and the nostalgic allure of vinyl records may seem as incongruous as a kangaroo attempting to master the art of ballet. However, as with any captivating research endeavor, one must be prepared to embrace the unexpected and view the world through the lens of curiosity and bold exploration.
Before diving headfirst into the exhilarating depths of our findings, it is paramount to acknowledge the intriguing genesis of this research inquiry. Picture, if you will, a spirited debate between a group of intrepid researchers as they pondered the potential interplay of variables that seemingly inhabited disparate realms. Some might have posited that the correlation between Roger Federer's earnings and LP/vinyl album sales was as likely as stumbling upon a unicorn prancing through a statistical meadow. Yet, dear reader, sometimes the most whimsical pairings yield the most awe-inspiring revelations.
With our scientific rackets at the ready and our data sets meticulously curated, we set out to scrutinize the relationship between the earnings of the illustrious tennis maestro and the buoyant sales of those charming, circular sound vessels known as LP/vinyl albums. One might ask, "Why these two variables in particular?" To that, we respond with a mischievous twinkle in our eyes, "Why not?"
As we delve into the heart of this investigation, we invite you to accompany us on this intellectual frolic, where statistical analyses are adorned with a dash of whimsy and scholarly pursuits are infused with the infectious rhythm of discovery. Buckle up, fellow travelers of the academic cosmos, for we are about to embark on a scientific adventure that will leave you marveling at the improbable and embracing the uncanny – all in the pursuit of shedding light on the inexplicable bond between Roger Federer's earnings and the enchanting world of LP/vinyl album sales.

[[RESULTS]]
The results of our analysis serve up an ace of a revelation that is bound to make even the most stoic of statisticians crack a smile. We discovered a striking correlation coefficient of 0.9114131 between the annual earnings of the illustrious Roger Federer and the sales of LP/vinyl albums, spanning the years 1998 to 2022. To put it in tennis terms, this correlation is as strong as a serve from the great Federer himself!
In the world of statistics, a correlation coefficient close to 1 indicates a strong positive relationship between two variables. In this case, it's as if Federer's earnings and LP/vinyl album sales were engaged in a synchronized dance, moving in perfect harmony like a well-coordinated doubles team at Wimbledon. The r-squared value of 0.8306738 further reinforces this connection, suggesting that a staggering 83% of the variation in LP/vinyl album sales can be explained by the fluctuations in Roger Federer's annual earnings. Who knew that beneath the sleek surface of statistical analysis lay a groovy rhythm waiting to be uncovered?
Now, let's talk about the p-value. With a p-value of less than 0.01, our findings are about as statistically significant as a rare moment of on-court levity from the usually serious-faced Federer. This means that the likelihood of observing such a strong relationship between the variables due to random chance is, well, quite unlikely – almost as unlikely as witnessing a serve clocked at 163 mph while juggling LP/vinyl albums.
And now, for the pièce de résistance, we present the visual showcase of this unexpected union – the scatterplot (Fig. 1). Brace yourselves, fellow scholars, as you feast your eyes upon a graph that captures the remarkable interplay between the annual earnings of the tennis virtuoso and the sales of those musical relics known as LP/vinyl albums. It's a sight to behold, akin to witnessing a perfectly executed drop shot or a flawless one-handed backhand – an elegant and awe-inspiring display of statistical artistry.
In conclusion, our findings reveal a connection between Roger Federer's earnings and the sales of LP/vinyl albums that is as harmonious as a well-struck chord on a vintage vinyl record. Through this research, we have not only uncovered an unexpected correlation but have also served up a lighthearted reminder that in the world of statistics, as in life, there's always room for a bit of whimsy and wonder.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In this whimsically engaging odyssey through the enchanting realms of sports earnings and musical nostalgia, we've volleyed our way to a delightful revelation. The correlation between Roger Federer's earnings and LP/vinyl album sales is as rock-solid as a 1970s classic hit. With a correlation coefficient of 0.9114131, this connection is tighter than the tension in Federer's racket strings!

The statistical significance of our findings is as clear as an unchallenged line call – with a p-value of less than 0.01, the likelihood of this association occurring by mere chance is about as probable as finding a hidden track on a vinyl album without a trusty turntable!

In the world of scholarly pursuits, it's refreshing to unearth unexpected connections that harmonize like a Beatles melody. Our results illustrate that 83% of the variations in LP/vinyl album sales can be pirouetted around through fluctuations in Roger Federer's annual earnings, proving that statistical analyses can indeed dance to the beat of vintage vinyl.

On a final note, we assert with the certainty of a well-placed match point that no further explorations in this area are required. We've served up a lighthearted reminder of the whimsical wonders that await when statistical analyses don their dancing shoes and waltz into uncharted territories.

No return volley necessary – this game, set, and match is one for the statistical record books!

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 Love-Love: Exploring the Groovy Relationship Between Roger Federer's Earnings and LP/Vinyl Album Sales. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Sports Economics and Musical Trends

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 Love-Love: Exploring the Groovy Relationship Between Roger Federer's Earnings and LP/Vinyl Album Sales. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Experiential Data Analysis and Synthesis (SEDAS)

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 Love-Love: Exploring the Groovy Relationship Between Roger Federer's Earnings and LP/Vinyl Album Sales with an abstract of In this paper, we serve up some ace insights into the surprisingly harmonious correlation between the annual earnings of tennis legend Roger Federer and the sales of LP/vinyl albums. As we volley into the nitty-gritty, we uncover a striking correlation coefficient of 0.9114131, with a p-value of less than 0.01 based on data from 1998 to 2022. Our findings suggest that as Federer's earnings soared like a well-placed lob, so did the sales of LP/vinyl albums, forming a grand slam connection between the two seemingly unrelated variables. Through this research, we aim to lob some light-hearted fun into the world of academia while also uncovering meaningful connections that otherwise might have been lost in the noise.

ChatGPT:

Roger Federer earnings, LP sales, vinyl album sales, correlation, Roger Federer income, annual earnings, sales correlation, LP vinyl album sales, Roger Federer financials

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

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Data details

Roger Federer's annual earnings
Source: Wikipedia
See what else correlates with Roger Federer's annual earnings

Sales of LP/Vinyl Albums
Source: Statista
See what else correlates with Sales of LP/Vinyl Albums

Correlation r = 0.9114131 (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 = 0.8306738 (Coefficient of determination)
This means 83.1% of the change in the one variable (i.e., Sales of LP/Vinyl Albums) is predictable based on the change in the other (i.e., Roger Federer's annual earnings) over the 25 years from 1998 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.4E-10.^Show 0.0000000002418192838137046000
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 0.91 in 2.4E-8% of random cases. Said differently, if you correlated 4,135,319,501 random variables^Note You don't actually need 4 billion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 24 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 24 because we have two variables measured over a period of 25 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.

[ 0.81, 0.96 ] 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.

	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Roger Federer's annual earnings (Thousands of dollars)	27.955	225.139	623.782	865.425	1995.03	4000.68	6357.55	6137.02	8343.88	10130.6	5886.88	8768.11	7698.29	6369.58	8584.84	3203.64	2338.45	7802890	1527270	13054900	8629230	8716980	10600000	90000000	90000000
Sales of LP/Vinyl Albums (Units)	1400000	1400000	1500000	1200000	1300000	1400000	1200000	900000	900000	1000000	1900000	2500000	2800000	3900000	4600000	6100000	9200000	11900000	13100000	14320000	16800000	18840000	21500000	41700000	43460000

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([27.955,225.139,623.782,865.425,1995.03,4000.68,6357.55,6137.02,8343.88,10130.6,5886.88,8768.11,7698.29,6369.58,8584.84,3203.64,2338.45,7802890,1527270,13054900,8629230,8716980,10600000,90000000,90000000,])
array_2 = np.array([1400000,1400000,1500000,1200000,1300000,1400000,1200000,900000,900000,1000000,1900000,2500000,2800000,3900000,4600000,6100000,9200000,11900000,13100000,14320000,16800000,18840000,21500000,41700000,43460000,])
array_1_name = "Roger Federer's annual earnings"
array_2_name = "Sales of LP/Vinyl Albums"

# 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 Roger Federer's annual earnings
Line chart for only Sales of LP/Vinyl Albums
AI-generated correlation image
The spurious research paper: Love-Love: Exploring the Groovy Relationship Between Roger Federer's Earnings and LP/Vinyl Album Sales

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Correlation ID: 2896 · Black Variable ID: 84 · Red Variable ID: 25


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