Spurious correlation #3,913 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is GMO use in cotton in California and the second variable is Number of goals scored by Wayne Rooney in the English Premier League. The chart goes from 2003 to 2021, 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 GMO use in cotton in California and the second variable is Number of goals scored by Wayne Rooney in the English Premier League. The chart goes from 2003 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the GMO cotton in California dwindled, so did the enthusiasm of the local insects. With fewer bugs to distract him, Wayne Rooney found it increasingly difficult to concentrate on soccer, leading to a dip in his goal-scoring performance. It seems even the smallest of changes in agriculture can have a big impact on the world of sports!

^{Show image generation prompt} Model: dalle-3
Prompt: Certainly! Here's an improved image generation prompt for DALL·E-3 to create a compelling visual in the requested style: Generate a comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s. Depict a California cotton field under a sunny sky, with genetically modified cotton plants growing tall and strong. Nearby, an English Premier League stadium is visible, and within it, Wayne Rooney is shown struggling to score goals. As he kicks the soccer ball, depict it slowing down and curving off target, seemingly affected by an invisible forcefield surrounding it, generated by the modified cotton fibers. The intertwining of increased GMO cotton production and Rooney's decreased goal tally should be evident, with frustration filling the air. Keep the visual depiction simple, without any words or speech bubbles, and ensure the illustration captures the tension between the two elements. This prompt should provide a clear and visually striking depiction within the specified style, incorporating the contrasting themes of genetically modified cotton and soccer struggle. 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: GMO use in cotton in California and Number of goals scored by Wayne Rooney in the English Premier League. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: An image that looks like it is a scene from A Disney Movie inspired by bauhaus a Polaroid photo A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s An image that looks like it is a scene from A Disney Movie
ChatGPT: A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s

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 GMO use in cotton in California and Number of goals scored by Wayne Rooney in the English Premier League, in the following situation: Because changes in GMO use in cotton in California caused Number of goals scored by Wayne Rooney in the English Premier League. As GMO cotton production increased, the genetically modified cotton fibers generated an invisible forcefield around the soccer balls, making it harder for Rooney to score goals. The increased friction caused by the modified cotton resulted in decreased ball speed, leading to Rooney's decreased goal tally.. Keep the description simple.
ChatGPT: In a California cotton field, genetically modified cotton plants grow tall and strong under the sunny sky. In the nearby English Premier League stadium, Wayne Rooney is seen struggling to score goals. As he kicks the soccer ball, it seems to slow down and curve off target due to an invisible forcefield surrounding it, generated by the modified cotton fibers. The intertwining of increased GMO cotton production and Rooney's decreased goal tally is evident as frustration fills the air.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s ] and depicting this scene: In a California cotton field, genetically modified cotton plants grow tall and strong under the sunny sky. In the nearby English Premier League stadium, Wayne Rooney is seen struggling to score goals. As he kicks the soccer ball, it seems to slow down and curve off target due to an invisible forcefield surrounding it, generated by the modified cotton fibers. The intertwining of increased GMO cotton production and Rooney's decreased goal tally is evident as frustration fills the air. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Certainly! Here's an improved image generation prompt for DALL·E-3 to create a compelling visual in the requested style: Generate a comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s. Depict a California cotton field under a sunny sky, with genetically modified cotton plants growing tall and strong. Nearby, an English Premier League stadium is visible, and within it, Wayne Rooney is shown struggling to score goals. As he kicks the soccer ball, depict it slowing down and curving off target, seemingly affected by an invisible forcefield surrounding it, generated by the modified cotton fibers. The intertwining of increased GMO cotton production and Rooney's decreased goal tally should be evident, with frustration filling the air. Keep the visual depiction simple, without any words or speech bubbles, and ensure the illustration captures the tension between the two elements. This prompt should provide a clear and visually striking depiction within the specified style, incorporating the contrasting themes of genetically modified cotton and soccer struggle.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how a decrease in GMO use in cotton in California caused Number of goals scored by Wayne Rooney in the English Premier League to decrease.

AI academic paper

(Because p < 0.01)

Seeds and Striker: Investigating the Relationship Between GMO Cotton Cultivation in California and Wayne Rooney's Goal Scoring in the English Premier League

The Journal of Quirky Agricultural and Sports Research

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 GMO use in cotton in California and Number of goals scored by Wayne Rooney in the English Premier League. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading the backs of shampoo bottles.

Here is the title and abstract of the paper:
[[TITLE]]
"Seeds and Striker: Investigating the Relationship Between GMO Cotton Cultivation in California and Wayne Rooney's Goal Scoring in the English Premier League"

[[ABSTRACT]]
In this study, we delve into the curious and unexpected relationship between the use of genetically modified organism (GMO) cotton in the agricultural fields of California and the number of goals scored by the renowned footballer, Wayne Rooney, in the English Premier League. While one may initially question the rationality of such an investigation, we were inspired by the notion that seemingly unrelated phenomena may, at times, exhibit intriguing correlations. Utilizing data from the United States Department of Agriculture (USDA) and Wikipedia, we rigorously analyzed a time series from 2003 to 2021. Our findings reveal a striking correlation coefficient of 0.8866812 and a statistically significant p-value of less than 0.01.

The high correlation observed between GMO cotton cultivation in California and Wayne Rooney's goal scoring prompts a reevaluation of the potential connections that may exist across unrelated domains. This intriguing association piques our curiosity and beckons the imagination to delve deeper into understanding the whimsical interplay of seemingly disparate elements in our world. Furthermore, the results underscore the importance of exploring unconventional avenues of inquiry, illuminating the sheer unpredictability that can arise in the quest for knowledge.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The interconnectedness of seemingly unrelated phenomena has long fascinated researchers across various disciplines. While conventional wisdom may dictate that genetically modified organism (GMO) cotton cultivation in California has no bearing on the athletic prowess of English Premier League footballer Wayne Rooney, our investigation into this improbable association has yielded surprising findings. As we venture into this uncharted territory of whimsical correlations, we are met with skepticism, amusement, and a dash of bewildered curiosity.
The use of GMO cotton, with its traits of pest resistance and increased yield, has proliferated across the agricultural landscape of California. Simultaneously, Wayne Rooney, an iconic figure in the realm of football, has etched his name in the annals of Premier League history through his prolific goal-scoring abilities. While the temptation to dismiss any potential connection between these disparate domains is strong, we are emboldened by the age-old adage that "correlation does not imply causation," and yet, it invites us to explore the unlikeliest of correlations.
In this pursuit, we meticulously gathered data from the United States Department of Agriculture (USDA) to capture the nuances of GMO cotton cultivation trends in California. Equally integral to our investigation was the compilation of Wayne Rooney's goal-scoring records in the English Premier League, a task facilitated by the wealth of information available through the venerable repository of knowledge that is Wikipedia. With our dataset in hand, we embarked on a rigorous examination of the time series spanning from 2003 to 2021.
The initial skepticism surrounding our chosen research endeavor becomes tempered as we unravel the unexpected synchronicity between the two seemingly incongruous variables. Our analysis unveils a remarkable correlation coefficient of 0.8866812, accompanied by a resoundingly significant p-value of less than 0.01. The sheer magnitude of this correlation beckons us to delve into realms beyond the conventional, reminding us that even in the most improbable pairings, statistical relationships may emerge.
While it would be remiss of us to assert a causal relationship between these two distinct entities based on correlation alone, the strength of this statistical association propels us to further explore the underlying mechanisms at play. We invite the reader to join us on this whimsical scientific sojourn as we seek to unravel the enigmatic dance between genetically modified cotton fields and the net-rippling exploits of a celebrated football striker.
In the words of philosopher Albert Camus, "In the depth of winter, I finally learned that within me there lay an invincible summer." Similarly, within the realm of empirical inquiry, we are driven to embrace the unexpected and curious, for it is within these unassuming corridors that the most extravagant revelations may find refuge.
Stay tuned as we embark on this intellectual odyssey, where the fields of agriculture and the arena of sports converge in an unforeseen tango of correlation.
Let the whimsical journey begin.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The symbiotic relationship between GMO cotton cultivation in California and Wayne Rooney's goal-scoring escapades in the English Premier League has inspired a motley array of inquiries, not the least of which is our own offbeat investigation. As we dive into this whimsical endeavor, we find ourselves peering into a repertoire of scholarly works that offer insights into seemingly bizarre correlations and unexpected connections.

Smith and Doe, in their seminal work "Seeds of Success: GMO Cotton in the Californian Agricultural Landscape," provide a comprehensive overview of the adoption and impact of genetically modified cotton varieties in California. Their meticulous analysis delves into the economic, environmental, and agronomic ramifications of GMO cotton, painting a vivid portrait of its widespread cultivation and the multifaceted implications for the agricultural industry. While the authors' focus lies primarily within the realms of agriculture, their work inadvertently sets the stage for our exploration of serendipitous connections that transcend traditional disciplinary boundaries.

Building upon this foundation, Jones et al., in "Goal Dynamics: A Statistical Analysis of Premier League Strikers," present an extensive examination of the performance dynamics of renowned footballers in the English Premier League. Their rigorous statistical analyses scrutinize a myriad of factors influencing goal-scoring prowess, from biomechanical attributes to tactical strategy, providing an illuminating panorama of the intricacies inherent in the art of goal-scoring. Unbeknownst to Jones and colleagues, their work now inadvertently intertwines with our own quest to unearth the curious interplay between agricultural genetic manipulation and athletic exploits on the football field.

Arriving at the juncture where the scholarly meets the esoteric, we encounter real non-fiction books such as "The Omnivore's Dilemma" by Michael Pollan, and "The Botany of Desire: A Plant's-Eye View of the World" by the same author. These literary inquiries into the complexities of the food ecosystem and the intricate dance between humans and plants may seem worlds apart from our investigation, but the underlying themes of interconnectedness and the unsuspected consequences of human intervention resonate with the essence of our pursuit.

Transitioning from the realm of non-fiction to the world of fiction, we encounter esteemed works such as Margaret Atwood's "Oryx and Crake" and Paolo Bacigalupi's "The Windup Girl." These speculative dystopian narratives exploring the implications of biotechnological and environmental interventions serve as a curious backdrop to our investigation, offering an allegorical portrayal of the potential repercussions of manipulating the natural world, albeit in a more cataclysmic and apocalyptic vein than what we intend to address.

Venturing further down the rabbit hole of literary exploration, we assumed the role of intrepid seekers, trawling the esoteric corners of unconventional knowledge repositories. Our exhaustive pursuit led us to discover that the ingredients list on the back of shampoo bottles, in its cryptic assemblage of unpronounceable chemical compounds, hides an unsuspected trove of wisdom. While it may not boast the veneer of academic erudition, the miniaturized concoctions of surfactants and emollients whimsically allude to the intricate symphony of biochemical interactions, perhaps speaking to the hidden harmony that permeates our seemingly dissonant study.

As we bridge the annals of scholarly discourse with the whimsy of the literary realm and the idiosyncrasy of unconventional information sources, we are reminded that within the most unlikely amalgamation of elements, a peculiar coherence may yet emerge. Our pursuit, therefore, marches onward, propelled by an unyielding commitment to unravel the enigmatic dance between genetically modified cotton fields and the net-rippling exploits of a celebrated football striker.

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 GMO use in cotton in California and Number of goals scored by Wayne Rooney in the English Premier League. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from USDA and Wikipedia . You used data from 2003 to 2021

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]]
"Seeds and Striker: Investigating the Relationship Between GMO Cotton Cultivation in California and Wayne Rooney's Goal Scoring in the English Premier League"

[[ABSTRACT]]
In this study, we delve into the curious and unexpected relationship between the use of genetically modified organism (GMO) cotton in the agricultural fields of California and the number of goals scored by the renowned footballer, Wayne Rooney, in the English Premier League. While one may initially question the rationality of such an investigation, we were inspired by the notion that seemingly unrelated phenomena may, at times, exhibit intriguing correlations. Utilizing data from the United States Department of Agriculture (USDA) and Wikipedia, we rigorously analyzed a time series from 2003 to 2021. Our findings reveal a striking correlation coefficient of 0.8866812 and a statistically significant p-value of less than 0.01.

The high correlation observed between GMO cotton cultivation in California and Wayne Rooney's goal scoring prompts a reevaluation of the potential connections that may exist across unrelated domains. This intriguing association piques our curiosity and beckons the imagination to delve deeper into understanding the whimsical interplay of seemingly disparate elements in our world. Furthermore, the results underscore the importance of exploring unconventional avenues of inquiry, illuminating the sheer unpredictability that can arise in the quest for knowledge.

[[INTRODUCTION]]
The interconnectedness of seemingly unrelated phenomena has long fascinated researchers across various disciplines. While conventional wisdom may dictate that genetically modified organism (GMO) cotton cultivation in California has no bearing on the athletic prowess of English Premier League footballer Wayne Rooney, our investigation into this improbable association has yielded surprising findings. As we venture into this uncharted territory of whimsical correlations, we are met with skepticism, amusement, and a dash of bewildered curiosity.
The use of GMO cotton, with its traits of pest resistance and increased yield, has proliferated across the agricultural landscape of California. Simultaneously, Wayne Rooney, an iconic figure in the realm of football, has etched his name in the annals of Premier League history through his prolific goal-scoring abilities. While the temptation to dismiss any potential connection between these disparate domains is strong, we are emboldened by the age-old adage that "correlation does not imply causation," and yet, it invites us to explore the unlikeliest of correlations.
In this pursuit, we meticulously gathered data from the United States Department of Agriculture (USDA) to capture the nuances of GMO cotton cultivation trends in California. Equally integral to our investigation was the compilation of Wayne Rooney's goal-scoring records in the English Premier League, a task facilitated by the wealth of information available through the venerable repository of knowledge that is Wikipedia. With our dataset in hand, we embarked on a rigorous examination of the time series spanning from 2003 to 2021.
The initial skepticism surrounding our chosen research endeavor becomes tempered as we unravel the unexpected synchronicity between the two seemingly incongruous variables. Our analysis unveils a remarkable correlation coefficient of 0.8866812, accompanied by a resoundingly significant p-value of less than 0.01. The sheer magnitude of this correlation beckons us to delve into realms beyond the conventional, reminding us that even in the most improbable pairings, statistical relationships may emerge.
While it would be remiss of us to assert a causal relationship between these two distinct entities based on correlation alone, the strength of this statistical association propels us to further explore the underlying mechanisms at play. We invite the reader to join us on this whimsical scientific sojourn as we seek to unravel the enigmatic dance between genetically modified cotton fields and the net-rippling exploits of a celebrated football striker.
In the words of philosopher Albert Camus, "In the depth of winter, I finally learned that within me there lay an invincible summer." Similarly, within the realm of empirical inquiry, we are driven to embrace the unexpected and curious, for it is within these unassuming corridors that the most extravagant revelations may find refuge.
Stay tuned as we embark on this intellectual odyssey, where the fields of agriculture and the arena of sports converge in an unforeseen tango of correlation.
Let the whimsical journey begin.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To elucidate the perplexing web of interconnectedness between the cultivation of genetically modified organism (GMO) cotton in California and the goal-scoring prowess of Wayne Rooney in the English Premier League, our research team navigated through a labyrinth of analytical methods that would make Theseus and his ball of yarn envious. The first puzzle piece in this grand intellectual jigsaw involved the collection and aggregation of data from disparate sources, akin to assembling a cosmic jigsaw puzzle where the pieces are scattered across the multi-verse.

Our journey began with a pilgrimage to the sacred repository of agricultural data, the United States Department of Agriculture (USDA). Here, we acquired comprehensive information on the cultivation trends of GMO cotton in the Golden State, meticulously documenting the ebb and flow of these agrarian marvels through the years. As the sun set on the fields of California, our quest continued into the digital realm, where the hallowed halls of Wikipedia bestowed upon us the statistical chronicles of Wayne Rooney's prodigious goal-scoring exploits. Like intrepid explorers charting uncharted territories, we traversed through the annals of these data archives, foraging for nuggets of knowledge amidst the digital underbrush.

With our data trove secured, we embarked on the arduous task of wrangling spreadsheets and databases, like literary heroes composing an epic saga from scattered parchment. The 2003 to 2021 time series provided the canvas upon which we aimed to paint the portrait of this unexpected correlation. Our statistical arsenal boasted an array of analytical tools, including but not limited to, correlation coefficients, regression analyses, and hypothetical musings about the use of goal-scoring talents to fend off agricultural pests – a concept we jokingly referred to as "scary striker tactics." As we ventured deep into the chambers of statistical inference, we remained mindful of the cardinal rule of empirical inquiry: correlation does not imply causation, but it does beguile the inquisitive mind with its enigmatic dance.

The amalgamation of datasets and the application of statistical sorcery culminated in our unveiling of a striking correlation coefficient of 0.8866812, accompanied by a statistically significant p-value, reminiscent of discovering a rare treasure trove amidst the statistical Sahara. While we stop short of professing a causal relationship between GMO cotton cultivation and Wayne Rooney's goal-scoring exploits, the strength of this correlation nudges us to peep behind the veil of statistical significance into the underlying forces at play.

In the words of the inimitable William Shakespeare, “there are more things in heaven and earth, Horatio, than are dreamt of in your philosophy.” And indeed, as we navigate this intellectual labyrinth, we approach our findings with a sense of wonder and curiosity, recognizing that each statistical thread we pull may unravel a hidden tapestry of interconnections. As we prepare to unveil and interpret our findings, we invite the reader to don their analytical spectacles and journey with us into the whimsical, yet alluring realm of GMO cotton and goal-scoring synchronicity.

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 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 GMO use in cotton in California and Number of goals scored by Wayne Rooney in the English Premier League. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

For the time period 2003 to 2021, you found a correlation 0.8866812, r-squared of 0.7862035, 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]]
"Seeds and Striker: Investigating the Relationship Between GMO Cotton Cultivation in California and Wayne Rooney's Goal Scoring in the English Premier League"

[[ABSTRACT]]
In this study, we delve into the curious and unexpected relationship between the use of genetically modified organism (GMO) cotton in the agricultural fields of California and the number of goals scored by the renowned footballer, Wayne Rooney, in the English Premier League. While one may initially question the rationality of such an investigation, we were inspired by the notion that seemingly unrelated phenomena may, at times, exhibit intriguing correlations. Utilizing data from the United States Department of Agriculture (USDA) and Wikipedia, we rigorously analyzed a time series from 2003 to 2021. Our findings reveal a striking correlation coefficient of 0.8866812 and a statistically significant p-value of less than 0.01.

The high correlation observed between GMO cotton cultivation in California and Wayne Rooney's goal scoring prompts a reevaluation of the potential connections that may exist across unrelated domains. This intriguing association piques our curiosity and beckons the imagination to delve deeper into understanding the whimsical interplay of seemingly disparate elements in our world. Furthermore, the results underscore the importance of exploring unconventional avenues of inquiry, illuminating the sheer unpredictability that can arise in the quest for knowledge.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The interconnectedness of seemingly unrelated phenomena has long fascinated researchers across various disciplines. While conventional wisdom may dictate that genetically modified organism (GMO) cotton cultivation in California has no bearing on the athletic prowess of English Premier League footballer Wayne Rooney, our investigation into this improbable association has yielded surprising findings. As we venture into this uncharted territory of whimsical correlations, we are met with skepticism, amusement, and a dash of bewildered curiosity.
The use of GMO cotton, with its traits of pest resistance and increased yield, has proliferated across the agricultural landscape of California. Simultaneously, Wayne Rooney, an iconic figure in the realm of football, has etched his name in the annals of Premier League history through his prolific goal-scoring abilities. While the temptation to dismiss any potential connection between these disparate domains is strong, we are emboldened by the age-old adage that "correlation does not imply causation," and yet, it invites us to explore the unlikeliest of correlations.
In this pursuit, we meticulously gathered data from the United States Department of Agriculture (USDA) to capture the nuances of GMO cotton cultivation trends in California. Equally integral to our investigation was the compilation of Wayne Rooney's goal-scoring records in the English Premier League, a task facilitated by the wealth of information available through the venerable repository of knowledge that is Wikipedia. With our dataset in hand, we embarked on a rigorous examination of the time series spanning from 2003 to 2021.
The initial skepticism surrounding our chosen research endeavor becomes tempered as we unravel the unexpected synchronicity between the two seemingly incongruous variables. Our analysis unveils a remarkable correlation coefficient of 0.8866812, accompanied by a resoundingly significant p-value of less than 0.01. The sheer magnitude of this correlation beckons us to delve into realms beyond the conventional, reminding us that even in the most improbable pairings, statistical relationships may emerge.
While it would be remiss of us to assert a causal relationship between these two distinct entities based on correlation alone, the strength of this statistical association propels us to further explore the underlying mechanisms at play. We invite the reader to join us on this whimsical scientific sojourn as we seek to unravel the enigmatic dance between genetically modified cotton fields and the net-rippling exploits of a celebrated football striker.
In the words of philosopher Albert Camus, "In the depth of winter, I finally learned that within me there lay an invincible summer." Similarly, within the realm of empirical inquiry, we are driven to embrace the unexpected and curious, for it is within these unassuming corridors that the most extravagant revelations may find refuge.
Stay tuned as we embark on this intellectual odyssey, where the fields of agriculture and the arena of sports converge in an unforeseen tango of correlation.
Let the whimsical journey begin.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The statistical analysis of the relationship between GMO cotton cultivation in California and Wayne Rooney's goal scoring in the English Premier League yielded noteworthy findings. Over the time period from 2003 to 2021, a remarkably high correlation coefficient of 0.8866812 was established, signifying a strong linear relationship between the two seemingly disparate variables. The coefficient of determination (R-squared) of 0.7862035 indicates that approximately 78.6% of the variability in Wayne Rooney's goal scoring can be explained by the fluctuations in GMO cotton cultivation in California. In addition, the p-value of less than 0.01 underscores the statistical significance of this correlation, providing compelling evidence against the null hypothesis of no association.

As depicted in Fig. 1, the scatterplot illustrates the striking linear trend between the annual quantity of GMO cotton cultivation in California and the number of goals scored by Wayne Rooney in the English Premier League. The data points coalesce into a discernible pattern, affirming the robustness of the correlation observed.

These results signify a departure from conventional wisdom and challenge our preconceived notions regarding the potential interplay between agricultural practices and sporting achievements. The unexpected convergence of GMO cotton cultivation and a renowned footballer's goal-scoring prowess invites further exploration into the whimsical and enigmatic intersections of unrelated domains.

In light of these compelling findings, our investigation sparks intrigue into the intricacies of serendipitous correlations and serves as a reminder of the unforeseen connections that may lurk beneath the surface of ostensibly unrelated phenomena. It beckons us to embrace the unpredictability of empirical inquiry and to consider the improbable with an open mind, for amidst the mosaic of data and variables, unexpected tales of correlation may unfold.

The profound correlation uncovered in this study between GMO cotton cultivation in California and Wayne Rooney's goal scoring prompts the scientific community to reevaluate the arbitrary boundaries that circumscribe the perceived domains of influence. As we embrace the implausible and delve into the labyrinth of statistical relationships, we are reminded that within the empirical tapestry, the most extraordinary connections may emerge from the unlikeliest of pairings.

In the spirit of intellectual curiosity, this study encourages further interdisciplinary explorations, aiming to unearth the latent connections that thread through the intricate tapestry of human endeavors. It is in these unforeseen correlations that the richness and unpredictability of empirical inquiry find their most compelling expression.

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 GMO use in cotton in California and Number of goals scored by Wayne Rooney in the English Premier League. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
"Seeds and Striker: Investigating the Relationship Between GMO Cotton Cultivation in California and Wayne Rooney's Goal Scoring in the English Premier League"

[[ABSTRACT]]
In this study, we delve into the curious and unexpected relationship between the use of genetically modified organism (GMO) cotton in the agricultural fields of California and the number of goals scored by the renowned footballer, Wayne Rooney, in the English Premier League. While one may initially question the rationality of such an investigation, we were inspired by the notion that seemingly unrelated phenomena may, at times, exhibit intriguing correlations. Utilizing data from the United States Department of Agriculture (USDA) and Wikipedia, we rigorously analyzed a time series from 2003 to 2021. Our findings reveal a striking correlation coefficient of 0.8866812 and a statistically significant p-value of less than 0.01.

The high correlation observed between GMO cotton cultivation in California and Wayne Rooney's goal scoring prompts a reevaluation of the potential connections that may exist across unrelated domains. This intriguing association piques our curiosity and beckons the imagination to delve deeper into understanding the whimsical interplay of seemingly disparate elements in our world. Furthermore, the results underscore the importance of exploring unconventional avenues of inquiry, illuminating the sheer unpredictability that can arise in the quest for knowledge.

[[LITERATURE REVIEW]]
The symbiotic relationship between GMO cotton cultivation in California and Wayne Rooney's goal-scoring escapades in the English Premier League has inspired a motley array of inquiries, not the least of which is our own offbeat investigation. As we dive into this whimsical endeavor, we find ourselves peering into a repertoire of scholarly works that offer insights into seemingly bizarre correlations and unexpected connections.
Smith and Doe, in their seminal work "Seeds of Success: GMO Cotton in the Californian Agricultural Landscape," provide a comprehensive overview of the adoption and impact of genetically modified cotton varieties in California. Their meticulous analysis delves into the economic, environmental, and agronomic ramifications of GMO cotton, painting a vivid portrait of its widespread cultivation and the multifaceted implications for the agricultural industry. While the authors' focus lies primarily within the realms of agriculture, their work inadvertently sets the stage for our exploration of serendipitous connections that transcend traditional disciplinary boundaries.
Building upon this foundation, Jones et al., in "Goal Dynamics: A Statistical Analysis of Premier League Strikers," present an extensive examination of the performance dynamics of renowned footballers in the English Premier League. Their rigorous statistical analyses scrutinize a myriad of factors influencing goal-scoring prowess, from biomechanical attributes to tactical strategy, providing an illuminating panorama of the intricacies inherent in the art of goal-scoring. Unbeknownst to Jones and colleagues, their work now inadvertently intertwines with our own quest to unearth the curious interplay between agricultural genetic manipulation and athletic exploits on the football field.
Arriving at the juncture where the scholarly meets the esoteric, we encounter real non-fiction books such as "The Omnivore's Dilemma" by Michael Pollan, and "The Botany of Desire: A Plant's-Eye View of the World" by the same author. These literary inquiries into the complexities of the food ecosystem and the intricate dance between humans and plants may seem worlds apart from our investigation, but the underlying themes of interconnectedness and the unsuspected consequences of human intervention resonate with the essence of our pursuit.
Transitioning from the realm of non-fiction to the world of fiction, we encounter esteemed works such as Margaret Atwood's "Oryx and Crake" and Paolo Bacigalupi's "The Windup Girl." These speculative dystopian narratives exploring the implications of biotechnological and environmental interventions serve as a curious backdrop to our investigation, offering an allegorical portrayal of the potential repercussions of manipulating the natural world, albeit in a more cataclysmic and apocalyptic vein than what we intend to address.
Venturing further down the rabbit hole of literary exploration, we assumed the role of intrepid seekers, trawling the esoteric corners of unconventional knowledge repositories. Our exhaustive pursuit led us to discover that the ingredients list on the back of shampoo bottles, in its cryptic assemblage of unpronounceable chemical compounds, hides an unsuspected trove of wisdom. While it may not boast the veneer of academic erudition, the miniaturized concoctions of surfactants and emollients whimsically allude to the intricate symphony of biochemical interactions, perhaps speaking to the hidden harmony that permeates our seemingly dissonant study.
As we bridge the annals of scholarly discourse with the whimsy of the literary realm and the idiosyncrasy of unconventional information sources, we are reminded that within the most unlikely amalgamation of elements, a peculiar coherence may yet emerge. Our pursuit, therefore, marches onward, propelled by an unyielding commitment to unravel the enigmatic dance between genetically modified cotton fields and the net-rippling exploits of a celebrated football striker.

[[RESULTS]]
The statistical analysis of the relationship between GMO cotton cultivation in California and Wayne Rooney's goal scoring in the English Premier League yielded noteworthy findings. Over the time period from 2003 to 2021, a remarkably high correlation coefficient of 0.8866812 was established, signifying a strong linear relationship between the two seemingly disparate variables. The coefficient of determination (R-squared) of 0.7862035 indicates that approximately 78.6% of the variability in Wayne Rooney's goal scoring can be explained by the fluctuations in GMO cotton cultivation in California. In addition, the p-value of less than 0.01 underscores the statistical significance of this correlation, providing compelling evidence against the null hypothesis of no association.
As depicted in Fig. 1, the scatterplot illustrates the striking linear trend between the annual quantity of GMO cotton cultivation in California and the number of goals scored by Wayne Rooney in the English Premier League. The data points coalesce into a discernible pattern, affirming the robustness of the correlation observed.
These results signify a departure from conventional wisdom and challenge our preconceived notions regarding the potential interplay between agricultural practices and sporting achievements. The unexpected convergence of GMO cotton cultivation and a renowned footballer's goal-scoring prowess invites further exploration into the whimsical and enigmatic intersections of unrelated domains.
In light of these compelling findings, our investigation sparks intrigue into the intricacies of serendipitous correlations and serves as a reminder of the unforeseen connections that may lurk beneath the surface of ostensibly unrelated phenomena. It beckons us to embrace the unpredictability of empirical inquiry and to consider the improbable with an open mind, for amidst the mosaic of data and variables, unexpected tales of correlation may unfold.
The profound correlation uncovered in this study between GMO cotton cultivation in California and Wayne Rooney's goal scoring prompts the scientific community to reevaluate the arbitrary boundaries that circumscribe the perceived domains of influence. As we embrace the implausible and delve into the labyrinth of statistical relationships, we are reminded that within the empirical tapestry, the most extraordinary connections may emerge from the unlikeliest of pairings.
In the spirit of intellectual curiosity, this study encourages further interdisciplinary explorations, aiming to unearth the latent connections that thread through the intricate tapestry of human endeavors. It is in these unforeseen correlations that the richness and unpredictability of empirical inquiry find their most compelling expression.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The intriguing association between GMO cotton cultivation in California and Wayne Rooney's goal scoring in the English Premier League that emerged from our study raises a plethora of thought-provoking considerations. The unequivocal support for our original hypothesis paves the way for a deeper examination of the underlying mechanisms driving this seemingly whimsical correlation. Our present findings align with prior research that suggested unexpected interconnections between disparate domains, reminiscent of the idiosyncratic connections explored in Margaret Atwood's speculative fiction and the enigmatic coherence of surfactants and emollients on shampoo bottles.

Building upon the pioneering work of Smith and Doe, who comprehensively expounded on the ramifications of GMO cotton cultivation in California, we now add a new dimension to the discourse by highlighting the unforeseen convergence with the athletic prowess of Wayne Rooney. As we bridge the chasm between agriculture and professional football, the unexpected intersection of these ostensibly unrelated domains impels us to reconsider the intricate web of potential influences that may permeate our world.

Moreover, our results resonate with Jones et al.'s statistical analysis of Premier League strikers, showcasing that factors beyond traditional biomechanical attributes and tactical strategies may exert an unforeseen impact on goal-scoring prowess. The statistical significance we have established bolsters the notion that the inexplicable link between agricultural genetic manipulation and athletic achievements may harbor deeper implications worthy of exploration.

The unanticipated marriage between agriculture and sport underscores the capricious nature of empirical inquiry and compels us to transcend conventional disciplinary boundaries, echoing the sentiments espoused in real non-fiction works such as "The Omnivore's Dilemma" and "The Botany of Desire." Our study underscores the paradoxical interplay of seemingly incongruous elements, beckoning us to assimilate the whimsy of unpredictable correlations and the unforeseen consequences of human interventions within our natural ecosystem.

Continuing in the spirit of interdisciplinary exploration, our research advocates for a nuanced reconsideration of the limitations that are often imposed by disciplinary confines. Embracing the unpredictability of empirical inquiry, the unmasking of this unexpected correlation serves as a beacon for further ventures into the uncharted territory of serendipitous connections and the enigmatic relationships that underpin our multifaceted world.

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 GMO use in cotton in California and Number of goals scored by Wayne Rooney in the English Premier League. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
"Seeds and Striker: Investigating the Relationship Between GMO Cotton Cultivation in California and Wayne Rooney's Goal Scoring in the English Premier League"

[[ABSTRACT]]
In this study, we delve into the curious and unexpected relationship between the use of genetically modified organism (GMO) cotton in the agricultural fields of California and the number of goals scored by the renowned footballer, Wayne Rooney, in the English Premier League. While one may initially question the rationality of such an investigation, we were inspired by the notion that seemingly unrelated phenomena may, at times, exhibit intriguing correlations. Utilizing data from the United States Department of Agriculture (USDA) and Wikipedia, we rigorously analyzed a time series from 2003 to 2021. Our findings reveal a striking correlation coefficient of 0.8866812 and a statistically significant p-value of less than 0.01.

The high correlation observed between GMO cotton cultivation in California and Wayne Rooney's goal scoring prompts a reevaluation of the potential connections that may exist across unrelated domains. This intriguing association piques our curiosity and beckons the imagination to delve deeper into understanding the whimsical interplay of seemingly disparate elements in our world. Furthermore, the results underscore the importance of exploring unconventional avenues of inquiry, illuminating the sheer unpredictability that can arise in the quest for knowledge.

[[INTRDUCTION]]
The interconnectedness of seemingly unrelated phenomena has long fascinated researchers across various disciplines. While conventional wisdom may dictate that genetically modified organism (GMO) cotton cultivation in California has no bearing on the athletic prowess of English Premier League footballer Wayne Rooney, our investigation into this improbable association has yielded surprising findings. As we venture into this uncharted territory of whimsical correlations, we are met with skepticism, amusement, and a dash of bewildered curiosity.
The use of GMO cotton, with its traits of pest resistance and increased yield, has proliferated across the agricultural landscape of California. Simultaneously, Wayne Rooney, an iconic figure in the realm of football, has etched his name in the annals of Premier League history through his prolific goal-scoring abilities. While the temptation to dismiss any potential connection between these disparate domains is strong, we are emboldened by the age-old adage that "correlation does not imply causation," and yet, it invites us to explore the unlikeliest of correlations.
In this pursuit, we meticulously gathered data from the United States Department of Agriculture (USDA) to capture the nuances of GMO cotton cultivation trends in California. Equally integral to our investigation was the compilation of Wayne Rooney's goal-scoring records in the English Premier League, a task facilitated by the wealth of information available through the venerable repository of knowledge that is Wikipedia. With our dataset in hand, we embarked on a rigorous examination of the time series spanning from 2003 to 2021.
The initial skepticism surrounding our chosen research endeavor becomes tempered as we unravel the unexpected synchronicity between the two seemingly incongruous variables. Our analysis unveils a remarkable correlation coefficient of 0.8866812, accompanied by a resoundingly significant p-value of less than 0.01. The sheer magnitude of this correlation beckons us to delve into realms beyond the conventional, reminding us that even in the most improbable pairings, statistical relationships may emerge.
While it would be remiss of us to assert a causal relationship between these two distinct entities based on correlation alone, the strength of this statistical association propels us to further explore the underlying mechanisms at play. We invite the reader to join us on this whimsical scientific sojourn as we seek to unravel the enigmatic dance between genetically modified cotton fields and the net-rippling exploits of a celebrated football striker.
In the words of philosopher Albert Camus, "In the depth of winter, I finally learned that within me there lay an invincible summer." Similarly, within the realm of empirical inquiry, we are driven to embrace the unexpected and curious, for it is within these unassuming corridors that the most extravagant revelations may find refuge.
Stay tuned as we embark on this intellectual odyssey, where the fields of agriculture and the arena of sports converge in an unforeseen tango of correlation.
Let the whimsical journey begin.

[[RESULTS]]
The statistical analysis of the relationship between GMO cotton cultivation in California and Wayne Rooney's goal scoring in the English Premier League yielded noteworthy findings. Over the time period from 2003 to 2021, a remarkably high correlation coefficient of 0.8866812 was established, signifying a strong linear relationship between the two seemingly disparate variables. The coefficient of determination (R-squared) of 0.7862035 indicates that approximately 78.6% of the variability in Wayne Rooney's goal scoring can be explained by the fluctuations in GMO cotton cultivation in California. In addition, the p-value of less than 0.01 underscores the statistical significance of this correlation, providing compelling evidence against the null hypothesis of no association.
As depicted in Fig. 1, the scatterplot illustrates the striking linear trend between the annual quantity of GMO cotton cultivation in California and the number of goals scored by Wayne Rooney in the English Premier League. The data points coalesce into a discernible pattern, affirming the robustness of the correlation observed.
These results signify a departure from conventional wisdom and challenge our preconceived notions regarding the potential interplay between agricultural practices and sporting achievements. The unexpected convergence of GMO cotton cultivation and a renowned footballer's goal-scoring prowess invites further exploration into the whimsical and enigmatic intersections of unrelated domains.
In light of these compelling findings, our investigation sparks intrigue into the intricacies of serendipitous correlations and serves as a reminder of the unforeseen connections that may lurk beneath the surface of ostensibly unrelated phenomena. It beckons us to embrace the unpredictability of empirical inquiry and to consider the improbable with an open mind, for amidst the mosaic of data and variables, unexpected tales of correlation may unfold.
The profound correlation uncovered in this study between GMO cotton cultivation in California and Wayne Rooney's goal scoring prompts the scientific community to reevaluate the arbitrary boundaries that circumscribe the perceived domains of influence. As we embrace the implausible and delve into the labyrinth of statistical relationships, we are reminded that within the empirical tapestry, the most extraordinary connections may emerge from the unlikeliest of pairings.
In the spirit of intellectual curiosity, this study encourages further interdisciplinary explorations, aiming to unearth the latent connections that thread through the intricate tapestry of human endeavors. It is in these unforeseen correlations that the richness and unpredictability of empirical inquiry find their most compelling expression.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, the striking correlation between GMO cotton cultivation in California and Wayne Rooney's goal scoring in the English Premier League raises eyebrows and urges us to ponder the unforeseen interplay between agricultural practices and athletic achievements. The perplexing synchronicity, with a correlation coefficient of 0.8866812 and a statistically significant p-value, challenges our conventional understanding of unrelated phenomena. While we resist the temptation to ascribe causation based on correlation alone, this study serves as a whimsical reminder that within the labyrinth of statistical inquiry, unpredictability may reign supreme.

As we wrap up this peculiar exploration, the unexpected tango of GMO cotton fields and net-rippling feats on the football pitch beckons us to reconsider the arbitrary boundaries that confine our perception of causal influence. In the immortal words of Shakespeare, "There are more things in heaven and earth, Horatio, than are dreamt of in your philosophy" – and perhaps, the correlation between GMO cotton and goal-scoring prowess is one such enigmatic phenomenon.

While the findings of this investigation may elicit a chuckle or two from the scientific community, they also underscore the need for open-mindedness in research pursuits. Let us rest content in the knowledge that, for now, the mystery of GMO cotton and Wayne Rooney's goals remains an enigma worthy of a raised eyebrow and a mischievous grin.

In the grand scheme of scholarly exploration, it is with a light-hearted nod and a sprightly skip in our step that we assert: No further research on this curious correlation is necessary. For now, let the seeds of wonder and the thrill of statistical serendipity linger in the annals of empirical inquiry.

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 Seeds and Striker: Investigating the Relationship Between GMO Cotton Cultivation in California and Wayne Rooney's Goal Scoring in the English Premier League. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Quirky Agricultural and Sports 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 Seeds and Striker: Investigating the Relationship Between GMO Cotton Cultivation in California and Wayne Rooney's Goal Scoring in the English Premier League. Respond only with the name of a fictional organization.

ChatGPT:

The Association for Agricultural Advancement and Athletic Achievement

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 Seeds and Striker: Investigating the Relationship Between GMO Cotton Cultivation in California and Wayne Rooney's Goal Scoring in the English Premier League with an abstract of In this study, we delve into the curious and unexpected relationship between the use of genetically modified organism (GMO) cotton in the agricultural fields of California and the number of goals scored by the renowned footballer, Wayne Rooney, in the English Premier League. While one may initially question the rationality of such an investigation, we were inspired by the notion that seemingly unrelated phenomena may, at times, exhibit intriguing correlations. Utilizing data from the United States Department of Agriculture (USDA) and Wikipedia, we rigorously analyzed a time series from 2003 to 2021. Our findings reveal a striking correlation coefficient of 0.8866812 and a statistically significant p-value of less than 0.01.
The high correlation observed between GMO cotton cultivation in California and Wayne Rooney's goal scoring prompts a reevaluation of the potential connections that may exist across unrelated domains. This intriguing association piques our curiosity and beckons the imagination to delve deeper into understanding the whimsical interplay of seemingly disparate elements in our world. Furthermore, the results underscore the importance of exploring unconventional avenues of inquiry, illuminating the sheer unpredictability that can arise in the quest for knowledge.

ChatGPT:

GMO cotton cultivation California, Wayne Rooney, English Premier League, correlation, genetically modified organism, agriculture, data analysis, time series analysis, United States Department of Agriculture, USDA, California agriculture, football statistics, unusual correlations

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

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Data details

GMO use in cotton in California
Detailed data title: Percent of cotton planted in California that is genetically modified to be insect-resistant (Bt), but not herbicide-tolerant (HT)
Source: USDA
See what else correlates with GMO use in cotton in California

Number of goals scored by Wayne Rooney in the English Premier League
Source: Wikipedia
See what else correlates with Number of goals scored by Wayne Rooney in the English Premier League

Correlation r = 0.8866812 (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 = 0.7862035 (Coefficient of determination)
This means 78.6% of the change in the one variable (i.e., Number of goals scored by Wayne Rooney in the English Premier League) is predictable based on the change in the other (i.e., GMO use in cotton in California) over the 19 years from 2003 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 4.3E-7.^Show 0.0000004280955006269003700000
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 0.89 in 4.3E-5% of random cases. Said differently, if you correlated 2,335,927 random variables^Note You don't actually need 2 million 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 18 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 18 because we have two variables measured over a period of 19 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.

[ 0.72, 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.

	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
GMO use in cotton in California (GMO cotton %)	9	6	8	9	4	7	8	19	9	21	9	15	10	3	2	6	10	3	3
Number of goals scored by Wayne Rooney in the English Premier League (Goals scored)	6	9	11	16	14	12	12	26	11	27	12	17	12	8	5	10	11	5	1

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([9,6,8,9,4,7,8,19,9,21,9,15,10,3,2,6,10,3,3,])
array_2 = np.array([6,9,11,16,14,12,12,26,11,27,12,17,12,8,5,10,11,5,1,])
array_1_name = "GMO use in cotton in California"
array_2_name = "Number of goals scored by Wayne Rooney in the English Premier League"

# 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
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Line chart for only GMO use in cotton in California
Line chart for only Number of goals scored by Wayne Rooney in the English Premier League
AI-generated correlation image
The spurious research paper: Seeds and Striker: Investigating the Relationship Between GMO Cotton Cultivation in California and Wayne Rooney's Goal Scoring in the English Premier League

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Correlation ID: 3913 · Black Variable ID: 769 · Red Variable ID: 80


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