Spurious correlation #1,482 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of cutters and trimmers, hand in Utah and the second variable is Adrian Wilson's tackle count. The chart goes from 2003 to 2012, 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 The number of cutters and trimmers, hand in Utah and the second variable is Adrian Wilson's tackle count. The chart goes from 2003 to 2012, and the two variables track closely in value over that time.

Download png, svg

AI explanation

Fewer cutters and trimmers led to an abundance of unruly bushes and shrubbery across Utah. This created a wild and untamed landscape, which in turn distracted Adrian Wilson during his football games, ultimately leading to a decrease in his tackle count.

^{Show image generation prompt} Model: dalle-3
Prompt: Prompt: Generate an image of a futuristic manufacturing facility in a vast open space, where high-tech industrial cutting and trimming machines are being operated by busy workers. Adjacent to the facility, there is a football field where Adrian Wilson, a skilled player, is making swift tackles, inhibiting the opposition's progress. The scene should exude a high-tech ambiance and showcase the seamless coexistence of advanced machinery and human athletic prowess. 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: The number of cutters and trimmers, hand in Utah and Adrian Wilson's tackle count. 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: Minimalism Cubism High-tech Macabre inspired by bauhaus
ChatGPT: High-tech

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 The number of cutters and trimmers, hand in Utah and Adrian Wilson's tackle count together. Keep the description simple.
ChatGPT: In a spacious facility in Utah, there are several workers busily operating industrial cutting and trimming machines, ensuring that the production line runs smoothly. Meanwhile, on a sprawling football field, Adrian Wilson is making swift tackles, reducing the opposition's yards gained.

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: [ High-tech ] and depicting this scene: In a spacious facility in Utah, there are several workers busily operating industrial cutting and trimming machines, ensuring that the production line runs smoothly. Meanwhile, on a sprawling football field, Adrian Wilson is making swift tackles, reducing the opposition's yards gained. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image of a futuristic manufacturing facility in a vast open space, where high-tech industrial cutting and trimming machines are being operated by busy workers. Adjacent to the facility, there is a football field where Adrian Wilson, a skilled player, is making swift tackles, inhibiting the opposition's progress. The scene should exude a high-tech ambiance and showcase the seamless coexistence of advanced machinery and human athletic prowess.

*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 The number of cutters and trimmers, hand in Utah caused Adrian Wilson's tackle count to decrease.

AI academic paper

(Because p < 0.01)

Trimming the Fat: The Tackling Connection Between Utah Handymen and Adrian Wilson

The Journal of Quirky Trades and Unlikely Connections

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 The number of cutters and trimmers, hand in Utah and Adrian Wilson's tackle count. 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 name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
"Trimming the Fat: The Tackling Connection Between Utah Handymen and Adrian Wilson"

[[ABSTRACT]]
In this paper, we delve into the unexplored territory of the relationship between the number of cutters and trimmers, hand in Utah, and the tackle count of former professional football player Adrian Wilson. Utilizing data from the Bureau of Labor Statistics and Pro-football-reference, we sought to shed light on this puzzling correlation. Our findings revealed a remarkably high correlation coefficient of 0.9057088 and a statistically significant p-value of less than 0.01 for the years 2003 to 2012. While the connection between handymen and NFL athletes may seem far-fetched, our research uncovers an inexplicable link that may leave readers scratching their heads, much like a particularly perplexing DIY home improvement project. As we trim through the data, we urge fellow researchers to tackle the implications of these findings with caution – after all, the correlation is quite the "catch"!

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The world of sports statistics is a fascinating and often perplexing realm, full of unexpected connections and peculiar correlations. In this paper, we embark on an exploration of the curious relationship between the number of cutters and trimmers, hand in Utah, and the tackle count of the esteemed former professional football player, Adrian Wilson. While the initial proposal of such a connection may elicit raised eyebrows and quizzical expressions akin to encountering a particularly confounding IKEA assembly manual, our investigation aims to elucidate the statistical underpinnings of this enigmatic association.
As researchers, we are often called upon to tackle unconventional and idiosyncratic inquiries, and this study is no exception. The intersection of occupational data and athletic performance may seem, at first glance, as incongruous as mismatched socks – but it is precisely in the unlikeliest of pairings that we may uncover unexpected revelations. We are poised to trim through the foliage of anecdotal conjecture and unearth the tangible roots of this curious correlation, shedding light on a connection as intriguing as finding a power tool in the produce section.
The potential implications of our findings reach far beyond the realm of sports and manual labor – they may hold implications for workforce dynamics, physical exertion, or even the metaphysical interplay of destiny and happenstance. While our investigation may navigate through uncharted territories, we trust that our peers will join us in this odyssey, with a spirit of inquisitiveness and a willingness to "tackle" unconventional hypotheses with scholarly rigor. And after all, as we venture deeper into this investigation, we are reminded that sometimes, the most unexpected connections can emerge from the most ordinary of scenarios, not unlike finding a treasure trove of football trivia in a tool shed.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

To contextualize our investigation into the curious connection between the number of cutters and trimmers, hand in Utah, and the tackle count of Adrian Wilson, we turn our attention to a body of literature that ranges from occupational trends to sports performance analysis. We begin by examining scholarly studies by esteemed researchers such as Smith, Doe, and Jones, whose work sets the stage for our exploration of this eclectic correlation.

In "Occupational Exertion Patterns in the American West," Smith et al. delve into the physical demands of various occupations in the Western United States, highlighting the prevalence of manual labor in Utah. Meanwhile, Doe's seminal work, "The Human Hand: An Evolutionary Perspective," presents a comprehensive analysis of the anatomical and functional aspects of the human hand, providing valuable insights into the dexterity and capabilities of handymen in the region. Jones, in "Performance Metrics in Professional Football," offers a meticulous examination of statistical measures used to evaluate the prowess of NFL players, bookmarking the touchdown of facts, and the goalpost of empirical observations.

Expanding our purview beyond scholarly articles, we turn to non-fiction works that offer tangential perspectives on our perplexing correlation. "Cutting Through the Underbrush: A History of Lumberjack Traditions in America" provides a historical backdrop to the manual labor landscape, offering insights into the tools and techniques that have shaped the trade of cutting and trimming. Additionally, "The Gridiron and the Gladiator: An Insight into the Physiological Demands of American Football" captures the intensity and physical demands of professional football, drawing a parallel to the grueling tasks undertaken by handymen wielding saws and shears.

Venturing into the realm of fiction, we encounter works that, while not directly related to our topic, evoke the spirit of unexpected connections and uncharted territories. "The Cutting Edge of Destiny" presents a fantastical tale of serendipitous encounters and unforeseen bonds, reminiscent of the peculiar correlation we seek to unravel. Conversely, "Tackling the Unknown: Adventures in Statistical Serendipity" entertains the notion of fortuitous discoveries and unlikely relationships, mirroring the surprising union of occupational data and athletic performance that has captured our scholarly curiosity.

Adding a contemporary touch to our literary exploration, we cannot overlook the influence of popular internet memes that humorously intersect with our topic. The "Distracted Boyfriend" meme, emblematic of unexpected attractions and diverted attention, offers a lighthearted metaphor for our investigation into the unlikely connection between Utah handymen and a seasoned NFL player. Additionally, the "This Is Fine" dog meme, depicting a canine amidst chaos, humorously reflects the sense of bemusement that may accompany the contemplation of our seemingly incongruous correlation.

As we sift through this diverse array of literature, both serious and whimsical, we set the stage for our own analysis, poised to tackle the formidable task of unraveling the enigmatic relationship between handymen and tackles. Our academic journey through this literature review has been nothing short of an intellectual decathlon, encompassing scholarly rigor, literary fancy, and the occasional meme-induced chuckle. With a wink to the scholarly community, we invite our peers to join us in this scholarly caper, secured with a dash of statistical pizzazz and a hearty dose of pun-laden cheer.

It's safe to say that as researchers, we're ready to tackle - wait for it - anything.

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 The number of cutters and trimmers, hand in Utah and Adrian Wilson's tackle count. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Bureau of Larbor Statistics and Pro-football-reference . You used data from 2003 to 2012

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]]
"Trimming the Fat: The Tackling Connection Between Utah Handymen and Adrian Wilson"

[[ABSTRACT]]
In this paper, we delve into the unexplored territory of the relationship between the number of cutters and trimmers, hand in Utah, and the tackle count of former professional football player Adrian Wilson. Utilizing data from the Bureau of Labor Statistics and Pro-football-reference, we sought to shed light on this puzzling correlation. Our findings revealed a remarkably high correlation coefficient of 0.9057088 and a statistically significant p-value of less than 0.01 for the years 2003 to 2012. While the connection between handymen and NFL athletes may seem far-fetched, our research uncovers an inexplicable link that may leave readers scratching their heads, much like a particularly perplexing DIY home improvement project. As we trim through the data, we urge fellow researchers to tackle the implications of these findings with caution – after all, the correlation is quite the "catch"!

[[INTRODUCTION]]
The world of sports statistics is a fascinating and often perplexing realm, full of unexpected connections and peculiar correlations. In this paper, we embark on an exploration of the curious relationship between the number of cutters and trimmers, hand in Utah, and the tackle count of the esteemed former professional football player, Adrian Wilson. While the initial proposal of such a connection may elicit raised eyebrows and quizzical expressions akin to encountering a particularly confounding IKEA assembly manual, our investigation aims to elucidate the statistical underpinnings of this enigmatic association.
As researchers, we are often called upon to tackle unconventional and idiosyncratic inquiries, and this study is no exception. The intersection of occupational data and athletic performance may seem, at first glance, as incongruous as mismatched socks – but it is precisely in the unlikeliest of pairings that we may uncover unexpected revelations. We are poised to trim through the foliage of anecdotal conjecture and unearth the tangible roots of this curious correlation, shedding light on a connection as intriguing as finding a power tool in the produce section.
The potential implications of our findings reach far beyond the realm of sports and manual labor – they may hold implications for workforce dynamics, physical exertion, or even the metaphysical interplay of destiny and happenstance. While our investigation may navigate through uncharted territories, we trust that our peers will join us in this odyssey, with a spirit of inquisitiveness and a willingness to "tackle" unconventional hypotheses with scholarly rigor. And after all, as we venture deeper into this investigation, we are reminded that sometimes, the most unexpected connections can emerge from the most ordinary of scenarios, not unlike finding a treasure trove of football trivia in a tool shed.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To unravel the perplexing connection between the number of cutters and trimmers, hand in Utah, and the tackling prowess of Adrian Wilson, our research adopted a multi-faceted approach that combined data collection from the Bureau of Labor Statistics with comprehensive statistics from Pro-football-reference. Our methodology, much like a multi-tool in the hands of a handyman, was designed to deftly handle the complexities of this investigation while incorporating a touch of whimsy and lightheartedness.

Firstly, we scoured the archives of the Bureau of Labor Statistics, combing through occupational data related to the number of cutters and trimmers, hand, in the state of Utah from 2003 to 2012. The painstaking process of extracting this data was akin to meticulously pruning a particularly unruly hedge – requiring precision, patience, and perhaps the occasional pair of safety goggles.

Simultaneously, we delved into the troves of Pro-football-reference, where we compiled and scrutinized the detailed tackle counts of Adrian Wilson over the same period. This meticulous analysis involved sifting through a veritable mountain of statistical information, not unlike a treasure hunter meticulously sifting through sand in search of hidden gems – albeit in this case, the gems were in the form of tackle statistics rather than precious stones.

Our research team then employed advanced statistical techniques to analyze and scrutinize the collected data. The correlation between the number of cutters and trimmers, hand in Utah, and Adrian Wilson’s tackle count was examined using sophisticated correlation analysis methods. The enchanting dance of numbers, much like a well-executed touchdown celebration, revealed a strikingly high correlation coefficient of 0.9057088, signifying a remarkably strong relationship between these seemingly disparate variables.

Additionally, the application of inferential statistics allowed us to ascertain the statistical significance of this correlation. Our analysis unveiled a p-value of less than 0.01, emphasizing the robustness and reliability of the observed association. This statistical significance, like a perfectly executed tackle on the football field, emphasized the weighty implications of our findings – a correlation not to be taken lightly.

Furthermore, in order to add a layer of depth to our investigation, we employed qualitative interviews with a select group of handymen and football enthusiasts. These interviews provided valuable contextual insights and anecdotal evidence, offering a human touch to our data-driven analysis. The colorful anecdotes shared by participants added a touch of character to our investigation, much like an unexpected streak of paint on a pristine wall.

Ultimately, our methodology embraced the idiosyncratic nature of our research question, melding together the analytical rigor of statistical analysis with the unpredictable charm of offbeat correlations. As we present our findings, we invite our esteemed colleagues to join us in this delightful journey of blending statistical inquiry with a dash of whimsy, reminiscent of a well-crafted joke delivered amidst a serious discourse.

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 The number of cutters and trimmers, hand in Utah and Adrian Wilson's tackle count. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"Trimming the Fat: The Tackling Connection Between Utah Handymen and Adrian Wilson"

[[ABSTRACT]]
In this paper, we delve into the unexplored territory of the relationship between the number of cutters and trimmers, hand in Utah, and the tackle count of former professional football player Adrian Wilson. Utilizing data from the Bureau of Labor Statistics and Pro-football-reference, we sought to shed light on this puzzling correlation. Our findings revealed a remarkably high correlation coefficient of 0.9057088 and a statistically significant p-value of less than 0.01 for the years 2003 to 2012. While the connection between handymen and NFL athletes may seem far-fetched, our research uncovers an inexplicable link that may leave readers scratching their heads, much like a particularly perplexing DIY home improvement project. As we trim through the data, we urge fellow researchers to tackle the implications of these findings with caution – after all, the correlation is quite the "catch"!

[[LITERATURE REVIEW]]
To contextualize our investigation into the curious connection between the number of cutters and trimmers, hand in Utah, and the tackle count of Adrian Wilson, we turn our attention to a body of literature that ranges from occupational trends to sports performance analysis. We begin by examining scholarly studies by esteemed researchers such as Smith, Doe, and Jones, whose work sets the stage for our exploration of this eclectic correlation.
In "Occupational Exertion Patterns in the American West," Smith et al. delve into the physical demands of various occupations in the Western United States, highlighting the prevalence of manual labor in Utah. Meanwhile, Doe's seminal work, "The Human Hand: An Evolutionary Perspective," presents a comprehensive analysis of the anatomical and functional aspects of the human hand, providing valuable insights into the dexterity and capabilities of handymen in the region. Jones, in "Performance Metrics in Professional Football," offers a meticulous examination of statistical measures used to evaluate the prowess of NFL players, bookmarking the touchdown of facts, and the goalpost of empirical observations.
Expanding our purview beyond scholarly articles, we turn to non-fiction works that offer tangential perspectives on our perplexing correlation. "Cutting Through the Underbrush: A History of Lumberjack Traditions in America" provides a historical backdrop to the manual labor landscape, offering insights into the tools and techniques that have shaped the trade of cutting and trimming. Additionally, "The Gridiron and the Gladiator: An Insight into the Physiological Demands of American Football" captures the intensity and physical demands of professional football, drawing a parallel to the grueling tasks undertaken by handymen wielding saws and shears.
Venturing into the realm of fiction, we encounter works that, while not directly related to our topic, evoke the spirit of unexpected connections and uncharted territories. "The Cutting Edge of Destiny" presents a fantastical tale of serendipitous encounters and unforeseen bonds, reminiscent of the peculiar correlation we seek to unravel. Conversely, "Tackling the Unknown: Adventures in Statistical Serendipity" entertains the notion of fortuitous discoveries and unlikely relationships, mirroring the surprising union of occupational data and athletic performance that has captured our scholarly curiosity.
Adding a contemporary touch to our literary exploration, we cannot overlook the influence of popular internet memes that humorously intersect with our topic. The "Distracted Boyfriend" meme, emblematic of unexpected attractions and diverted attention, offers a lighthearted metaphor for our investigation into the unlikely connection between Utah handymen and a seasoned NFL player. Additionally, the "This Is Fine" dog meme, depicting a canine amidst chaos, humorously reflects the sense of bemusement that may accompany the contemplation of our seemingly incongruous correlation.
As we sift through this diverse array of literature, both serious and whimsical, we set the stage for our own analysis, poised to tackle the formidable task of unraveling the enigmatic relationship between handymen and tackles. Our academic journey through this literature review has been nothing short of an intellectual decathlon, encompassing scholarly rigor, literary fancy, and the occasional meme-induced chuckle. With a wink to the scholarly community, we invite our peers to join us in this scholarly caper, secured with a dash of statistical pizzazz and a hearty dose of pun-laden cheer.
It's safe to say that as researchers, we're ready to tackle - wait for it - anything.

[[RESULTS]]
The analysis of the data gathered from the Bureau of Labor Statistics and Pro-football-reference revealed a strikingly robust correlation between the number of cutters and trimmers, hand in Utah, and the tackle count of Adrian Wilson, former professional football player. For the time period spanning 2003 to 2012, a correlation coefficient of 0.9057088 was observed, signifying a remarkably strong positive relationship between these seemingly disparate variables. The coefficient of determination (r-squared) was calculated to be 0.8203084, further bolstering the evidence for a notable association. The p-value, which determined the significance of the correlation, was found to be less than 0.01, confirming the statistical strength of the observed relationship.
As if predicting tackling prowess from the number of handymen in Utah wasn't surprising enough, the figure (Fig. 1) depicts a scatterplot illustrating the unmistakable correlation, serving as a visual testament to this unexpected connection. The plot showcases the data points converging in a manner reminiscent of a precision cut during a DIY project, highlighting the cohesion between the two variables and solidifying the curious relationship uncovered in our analysis.
These results, while initially confounding, offer a thought-provoking insight into the enigmatic interplay between seemingly unrelated domains. It seems that the impact of handymen in Utah may stretch further than just home improvements, reaching into the realm of professional football and athletic performance. The astoundingly high correlation coefficient, r-squared value, and p-value all point to a connection that is as puzzling as finding a football playbook in a tool shed – an unexpected and captivating discovery that challenges conventional wisdom and beckons further exploration.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our investigation into the surprising correlation between the number of cutters and trimmers, hand in Utah, and the tackle count of Adrian Wilson has yielded intriguing results. As we expand upon our findings, it is crucial to revisit the lighthearted musings from the literature review that uncannily align with the seriousness of our inquiry, much like a team's unexpected triumph in the face of adversity.

The robust correlation coefficient of 0.9057088 is a triumph as resounding as a victorious touchdown dance, endorsing the newfound alliance between the gritty handymen of Utah and the gridiron prowess of Adrian Wilson. This statistical strength validates the impactful presence of handymen in Utah, resonating with the force of a well-executed tackle on the football field.

In line with the literature reviewed, the unexpected connections conjured by memes and whimsical fiction find expression in the improbable link we have uncovered. The "This Is Fine" dog meme, in its comical portrayal of chaos and nonchalance, mirrors the initial disbelief and eventual acceptance of our findings – much like a referee acknowledging a surprising call. In a similar vein, "The Cutting Edge of Destiny" fable, with its tales of chance encounters and unforeseen bonds, mirrors the resilience of our correlation against skepticism, echoing the triumph of an underdog team against all odds.

Furthermore, as the scatterplot aptly illustrates, the convergence of data points embodies the precision and harmony of a master craftsman, underscoring the undeniable connection between these hitherto disconnected variables. This visual representation adds a layer of vivid symbolism to our research, akin to a meticulously choreographed end-zone celebration – a testament to the fortuitous pairing of handymen and tackles.

In summary, our findings substantiate and extend the suppositions put forth by prior literature – an exciting revelation akin to a long-awaited touchdown in the final seconds of a game. The statistical vigor and visual eloquence of our results substantiate the enigmatic relationship between Utah handymen and professional football performance, inviting further inquiry into this uncharted and captivating intersection of occupational data and sports prowess. As researchers, we are brimming with enthusiasm to embark on the next phase of exploration, charting a course toward unraveling the intricacies of this unexpected convergence.

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 The number of cutters and trimmers, hand in Utah and Adrian Wilson's tackle count. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Trimming the Fat: The Tackling Connection Between Utah Handymen and Adrian Wilson"

[[ABSTRACT]]
In this paper, we delve into the unexplored territory of the relationship between the number of cutters and trimmers, hand in Utah, and the tackle count of former professional football player Adrian Wilson. Utilizing data from the Bureau of Labor Statistics and Pro-football-reference, we sought to shed light on this puzzling correlation. Our findings revealed a remarkably high correlation coefficient of 0.9057088 and a statistically significant p-value of less than 0.01 for the years 2003 to 2012. While the connection between handymen and NFL athletes may seem far-fetched, our research uncovers an inexplicable link that may leave readers scratching their heads, much like a particularly perplexing DIY home improvement project. As we trim through the data, we urge fellow researchers to tackle the implications of these findings with caution – after all, the correlation is quite the "catch"!

[[INTRDUCTION]]
The world of sports statistics is a fascinating and often perplexing realm, full of unexpected connections and peculiar correlations. In this paper, we embark on an exploration of the curious relationship between the number of cutters and trimmers, hand in Utah, and the tackle count of the esteemed former professional football player, Adrian Wilson. While the initial proposal of such a connection may elicit raised eyebrows and quizzical expressions akin to encountering a particularly confounding IKEA assembly manual, our investigation aims to elucidate the statistical underpinnings of this enigmatic association.
As researchers, we are often called upon to tackle unconventional and idiosyncratic inquiries, and this study is no exception. The intersection of occupational data and athletic performance may seem, at first glance, as incongruous as mismatched socks – but it is precisely in the unlikeliest of pairings that we may uncover unexpected revelations. We are poised to trim through the foliage of anecdotal conjecture and unearth the tangible roots of this curious correlation, shedding light on a connection as intriguing as finding a power tool in the produce section.
The potential implications of our findings reach far beyond the realm of sports and manual labor – they may hold implications for workforce dynamics, physical exertion, or even the metaphysical interplay of destiny and happenstance. While our investigation may navigate through uncharted territories, we trust that our peers will join us in this odyssey, with a spirit of inquisitiveness and a willingness to "tackle" unconventional hypotheses with scholarly rigor. And after all, as we venture deeper into this investigation, we are reminded that sometimes, the most unexpected connections can emerge from the most ordinary of scenarios, not unlike finding a treasure trove of football trivia in a tool shed.

[[RESULTS]]
The analysis of the data gathered from the Bureau of Labor Statistics and Pro-football-reference revealed a strikingly robust correlation between the number of cutters and trimmers, hand in Utah, and the tackle count of Adrian Wilson, former professional football player. For the time period spanning 2003 to 2012, a correlation coefficient of 0.9057088 was observed, signifying a remarkably strong positive relationship between these seemingly disparate variables. The coefficient of determination (r-squared) was calculated to be 0.8203084, further bolstering the evidence for a notable association. The p-value, which determined the significance of the correlation, was found to be less than 0.01, confirming the statistical strength of the observed relationship.
As if predicting tackling prowess from the number of handymen in Utah wasn't surprising enough, the figure (Fig. 1) depicts a scatterplot illustrating the unmistakable correlation, serving as a visual testament to this unexpected connection. The plot showcases the data points converging in a manner reminiscent of a precision cut during a DIY project, highlighting the cohesion between the two variables and solidifying the curious relationship uncovered in our analysis.
These results, while initially confounding, offer a thought-provoking insight into the enigmatic interplay between seemingly unrelated domains. It seems that the impact of handymen in Utah may stretch further than just home improvements, reaching into the realm of professional football and athletic performance. The astoundingly high correlation coefficient, r-squared value, and p-value all point to a connection that is as puzzling as finding a football playbook in a tool shed – an unexpected and captivating discovery that challenges conventional wisdom and beckons further exploration.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

Our investigation into the relationship between the number of cutters and trimmers, hand in Utah, and the tackle count of Adrian Wilson has yielded intriguing and unforeseen results. The strikingly high correlation coefficient of 0.9057088 has unearthed a connection as surprising as stumbling upon a quarterback in the plumbing aisle. The statistically significant p-value further bolsters the evidence, indicating a relationship as unexpected as discovering a touchdown celebration in a hardware store.

This study challenges traditional paradigms, illustrating how the world of sports and the domain of manual labor can intersect in ways as curious as finding a jigsaw in a toolbox. The observed correlation may leave us bemused, much like puzzling over the intricacies of assembling IKEA furniture – but it also invites us to explore the uncharted terrain where occupational data and athletic performance converge, much like navigating through a DIY project with only vague instructions.

As we wrap up this investigation, it is evident that the potential implications of these findings stretch far beyond the confines of our initial inquiry. The correlation between the number of handymen in Utah and Adrian Wilson's tackle count may hold the key to unlocking a host of unforeseen associations, much like discovering an unexpected hidden compartment in a workbench.

In light of these unforeseen findings, we must acknowledge that no more research is needed in this area. The results are as clear as a perfectly mowed lawn, and any further exploration would be as unnecessary as a snowblower in a desert.

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 Trimming the Fat: The Tackling Connection Between Utah Handymen and Adrian Wilson. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Quirky Trades and Unlikely Connections

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 Trimming the Fat: The Tackling Connection Between Utah Handymen and Adrian Wilson. Respond only with the name of a fictional organization.

ChatGPT:

The Collaborative Institute for Home Improvement Studies

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Trimming the Fat: The Tackling Connection Between Utah Handymen and Adrian Wilson with an abstract of In this paper, we delve into the unexplored territory of the relationship between the number of cutters and trimmers, hand in Utah, and the tackle count of former professional football player Adrian Wilson. Utilizing data from the Bureau of Labor Statistics and Pro-football-reference, we sought to shed light on this puzzling correlation. Our findings revealed a remarkably high correlation coefficient of 0.9057088 and a statistically significant p-value of less than 0.01 for the years 2003 to 2012. While the connection between handymen and NFL athletes may seem far-fetched, our research uncovers an inexplicable link that may leave readers scratching their heads, much like a particularly perplexing DIY home improvement project. As we trim through the data, we urge fellow researchers to tackle the implications of these findings with caution – after all, the correlation is quite the "catch"!

ChatGPT:

Utah handymen, Adrian Wilson, correlation, cutters and trimmers, Bureau of Labor Statistics, Pro-football-reference, relationship, correlation coefficient, statistical significance, NFL athletes, DIY home improvement, data analysis, implications

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

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Data details

The number of cutters and trimmers, hand in Utah
Detailed data title: BLS estimate of cutters and trimmers, hand in Utah
Source: Bureau of Larbor Statistics
See what else correlates with The number of cutters and trimmers, hand in Utah

Adrian Wilson's tackle count
Source: Pro-football-reference
See what else correlates with Adrian Wilson's tackle count

Correlation r = 0.9057088 (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 = 0.8203084 (Coefficient of determination)
This means 82% of the change in the one variable (i.e., Adrian Wilson's tackle count) is predictable based on the change in the other (i.e., The number of cutters and trimmers, hand in Utah) over the 10 years from 2003 through 2012.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.000308.^Show 0.0003082161337154489000000000
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 0.0308% of random cases. Said differently, if you correlated 3,244 random variables^Note Which I absolutely did.
with the same 9 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 9 because we have two variables measured over a period of 10 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.

[ 0.64, 0.98 ] 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
The number of cutters and trimmers, hand in Utah (Laborers)	120	160	150	130	90	130	130	160	110	90
Adrian Wilson's tackle count (Tackles)	68	80	93	74	33	60	61	76	48	39

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([120,160,150,130,90,130,130,160,110,90,])
array_2 = np.array([68,80,93,74,33,60,61,76,48,39,])
array_1_name = "The number of cutters and trimmers, hand in Utah"
array_2_name = "Adrian Wilson's tackle count"

# 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 The number of cutters and trimmers, hand in Utah
Line chart for only Adrian Wilson's tackle count
AI-generated correlation image
The spurious research paper: Trimming the Fat: The Tackling Connection Between Utah Handymen and Adrian Wilson

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Correlation ID: 1482 · Black Variable ID: 15175 · Red Variable ID: 235


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