Spurious correlation #2,291 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Number of turnovers by Chris Paul in the Regular NBA season and the second variable is Gasoline pumped in Gambia. The chart goes from 2006 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 Number of turnovers by Chris Paul in the Regular NBA season and the second variable is Gasoline pumped in Gambia. The chart goes from 2006 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

Chris Paul's precision on the court translated to off-the-court efficiency, leading to a ripple effect of smoother operations in the global gasoline industry. As he dropped the turnovers, the petrol pumps in Gambia felt the need for speed and decided to cut down on excess fuel wastage. It's as if his careful dribbling and passing somehow inspired the gasoline in Gambia to go easy on its own 'turnovers.' It just goes to show, when CP3 protects the ball, even the most unexpected places experience a smoother ride.

^{Show image generation prompt} Model: dalle-3
Prompt: Create an image that looks like an enchanting scene from a Pixar movie, showing vibrant colors and lively characters. In the foreground, depict Chris Paul, adorned in his basketball attire, skillfully dribbling the ball down the vividly animated court, his determination shining through. On the side, showcase a bustling gas station with animated characters engaged in pumping gasoline into their vehicles, adding a sense of energy and movement to the scene. Project the statistics of Chris Paul's turnovers in the NBA season onto the stadium screen, and simultaneously, display the amount of gasoline being pumped in Gambia on the digital display at the gas station. Ensure that the characters are expressive and dynamic, capturing the essence of the moment with Pixar's signature charm and storytelling. 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: Number of turnovers by Chris Paul in the Regular NBA season and Gasoline pumped in Gambia, The. 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: Cyberpunk Sci-fi fantacy A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s Concept art An image that looks like it is a scene from a Pixar movie
ChatGPT: An image that looks like it is a scene from a Pixar movie

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 Number of turnovers by Chris Paul in the Regular NBA season and Gasoline pumped in Gambia, The together. Keep the description simple.
ChatGPT: In a basketball arena in Gambia, Chris Paul dribbles the ball down the court. Meanwhile, a gas station nearby is bustling with activity as people pump gasoline into their vehicles. The number of turnovers by Chris Paul in the NBA season is displayed on the stadium screen, while the amount of gasoline pumped in Gambia is shown on the gas station's digital display.

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: [ An image that looks like it is a scene from a Pixar movie ] and depicting this scene: In a basketball arena in Gambia, Chris Paul dribbles the ball down the court. Meanwhile, a gas station nearby is bustling with activity as people pump gasoline into their vehicles. The number of turnovers by Chris Paul in the NBA season is displayed on the stadium screen, while the amount of gasoline pumped in Gambia is shown on the gas station's digital display. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image that looks like an enchanting scene from a Pixar movie, showing vibrant colors and lively characters. In the foreground, depict Chris Paul, adorned in his basketball attire, skillfully dribbling the ball down the vividly animated court, his determination shining through. On the side, showcase a bustling gas station with animated characters engaged in pumping gasoline into their vehicles, adding a sense of energy and movement to the scene. Project the statistics of Chris Paul's turnovers in the NBA season onto the stadium screen, and simultaneously, display the amount of gasoline being pumped in Gambia on the digital display at the gas station. Ensure that the characters are expressive and dynamic, capturing the essence of the moment with Pixar's signature charm and storytelling.

*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 Number of turnovers by Chris Paul in the Regular NBA season caused Gasoline pumped in Gambia to decrease. Make it feel plausible.

AI academic paper

(Because p < 0.01)

The Tally of Turnovers: Tracing the Tenuous Tie between Chris Paul's Carelessness on the Court and Gasoline Gallons in Gambia

The Journal of Sports Psychology and Ecological Economics

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 Number of turnovers by Chris Paul in the Regular NBA season and Gasoline pumped in Gambia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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 few real TV shows that sound like they might be relevant to the topic that you watched as research.

Here is the title and abstract of the paper:
[[TITLE]]
The Tally of Turnovers: Tracing the Tenuous Tie between Chris Paul's Carelessness on the Court and Gasoline Gallons in Gambia

[[ABSTRACT]]
In this study, we delved into the peculiar and perplexing relationship between the number of turnovers committed by the renowned basketball player, Chris Paul, during the regular NBA seasons and the quantity of gasoline pumped in the small West African country of Gambia. The connection between these seemingly incongruent variables has baffled scholars and sports enthusiasts alike, prompting us to embark on this quirky investigation.

Bringing levity to the world of sports analytics, our research uncovered a statistically significant correlation coefficient of 0.6890573, with a p-value less than 0.01, based on data spanning from the years 2006 to 2021. This correlation suggests a notable association between Chris Paul's errant passes and the amount of automotive fuel consumed in Gambia. It seems that, much like a slam dunk, there may be more to turnovers and gasoline consumption than meets the eye.

We also analyzed the economic and environmental implications of this unexpected link, prompting us to ask the timeless question: "If a basketball player fumbles the ball in the playoffs and no one is around to see it, does it still affect gasoline consumption in Gambia?" Perhaps we are witnessing the inception of a new era in sports and energy research, where jump shots and joules collide in unforeseen ways. With these findings, we hope to inspire future researchers to embrace the absurd and uncover the hidden connections that shape our world.

In conclusion, our study sheds light on the quirky nexus between professional basketball and the energy landscape, reminding us that even the most seemingly unrelated variables can dance in step, much like a dad joke at a family reunion – oddly fitting yet undeniably delightful.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The interplay between sports performance and global energy trends has long been a subject of curiosity and bemusement. In this vein, our investigation sought to untangle the enigmatic relationship between the turnovers made by Chris Paul in the regular NBA season and the volume of gasoline pumped in the West African nation of Gambia. It is a connection both improbable and intriguing, much like a dad joke at a formal dinner party – unexpected, yet impossible to ignore.
As we delve into the unusual alliance of basketball mishaps and gasoline consumption, we aim to inject a dose of lightheartedness into the often serious world of statistical analysis. Our research endeavors to uncover the underlying threads that weave through seemingly disparate realms, much like the puns that inexplicably appear in the middle of academic research papers – a welcome surprise, or, for some, an eyeroll-inducing interruption.
The initial spark for this study came from an offhand comment during a post-game interview, where Chris Paul mused about the curious ebb and flow of his turnovers and the price of fuel in Gambia. This spurred our curiosity, leading us to explore what may be considered the "fast break" of statistical inquiry – a sudden sprint from the well-trodden paths of research into the uncharted territories of correlation.
Grounded in the principles of empirical inquiry, our study ventures into uncharted territory, akin to a basketball player navigating through an opponent's defense to take a three-point shot. We employed rigorous statistical methods to illuminate the unexpected kinship between Chris Paul's on-court blunders and the fueling habits of motorists on the roads of Gambia, much like a skilled magician revealing the secrets behind a seemingly inexplicable magic trick – a revelation that prompts both fascination and bemusement, not unlike a dad joke that elicits a reluctant chuckle from its audience.
We employed an array of data sources, ranging from NBA game logs to gasoline sales records, to construct a comprehensive dataset that underpins our analysis. Our examination covered a time span from 2006 to 2021, capturing over a decade of turnovers and gas tank fill-ups. This meticulous approach allowed us to detect patterns and trends that might otherwise have remained obscured, much like a hidden object waiting to be revealed in a game of "Where's Waldo" – a discovery that brings a sense of accomplishment and glee, not unlike the satisfaction of clever wordplay in a pun.
In the next section, we will delve into the specific methodologies applied in our research, peeling back the layers of our analytical process like an onion, albeit with fewer tears and more statistical formulas. So, buckle up, hold onto your seats, and get ready to accompany us on a journey that promises unexpected correlations and the occasional dad joke.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In their seminal work, Smith and Doe (2015) conducted a comprehensive analysis of turnover statistics in the NBA, focusing on the impact of turnovers on team performance and game outcomes. Their findings underscored the significant influence of turnovers on the ebb and flow of basketball games, shaping the narrative of victory and defeat. However, what Smith and Doe did not anticipate was the potential ripple effect of turnovers on the global gasoline market. It seems that Chris Paul's turnovers may pack more of a punch than a knockout punchline at a comedy club – unexpected and leaving the audience in fits of laughter.

Jones et al. (2018) delved into the nuances of energy consumption patterns in West African countries, offering valuable insights into the driving forces behind gasoline demand in the region. Their meticulous analysis uncovered a web of economic, social, and infrastructural factors that intersect to shape fuel consumption trends. Little did they know that an NBA player's turnovers could add another layer to this complex tapestry, weaving a narrative as surprising as a plot twist in a mystery novel – unexpected, yet strangely fitting.

Drawing from the realm of non-fiction, "The Prize: The Epic Quest for Oil, Money, and Power" by Daniel Yergin and "Energy and Civilization: A History" by Vaclav Smil shed light on the intricate dynamics of energy production and consumption on a global scale. While these works provide invaluable knowledge on energy markets and societal development, they may have missed the mark on the playful connection between a basketball player's blunders and the gasoline habits of a small West African nation. It seems that sometimes the most unexpected connections can be as captivating as the plot twists in a thriller novel – keeping us on the edge of our seats and eager for the next revelation.

In the realm of fiction, the works of Jules Verne, particularly "Around the World in Eighty Days," transport readers to distant lands and adventures that defy expectation. While Verne's tales may not explicitly address the intersection of sports statistics and gasoline consumption, they nonetheless invite us to embrace the wonders of the unexpected. After all, who would have thought that a basketball player's turnovers could hold any sway over the petrol pumps in Gambia? It's as surprising as stumbling upon a comedic moment in a Shakespearean tragedy – a delightful deviation from the norm.

Television series such as "How It's Made" and "SportsCenter" offer glimpses into the inner workings of diverse phenomena, from manufacturing processes to sports highlights. This eclectic exposure serves as a reminder that the most unusual pairings can yield remarkable insights. Just as a lighthearted sitcom can deliver unexpected wisdom in the midst of laughter, so too can the correlation between turnovers by Chris Paul and gasoline consumption in Gambia reveal unexpected truths.

But enough of the literary diversions – let's turn our attention to the empirical studies that have grappled with the intertwined realms of basketball turnovers and global energy consumption.

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 Number of turnovers by Chris Paul in the Regular NBA season and Gasoline pumped in Gambia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 NBA and Energy Information Administration . You used data from 2006 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]]
The Tally of Turnovers: Tracing the Tenuous Tie between Chris Paul's Carelessness on the Court and Gasoline Gallons in Gambia

[[ABSTRACT]]
In this study, we delved into the peculiar and perplexing relationship between the number of turnovers committed by the renowned basketball player, Chris Paul, during the regular NBA seasons and the quantity of gasoline pumped in the small West African country of Gambia. The connection between these seemingly incongruent variables has baffled scholars and sports enthusiasts alike, prompting us to embark on this quirky investigation.

Bringing levity to the world of sports analytics, our research uncovered a statistically significant correlation coefficient of 0.6890573, with a p-value less than 0.01, based on data spanning from the years 2006 to 2021. This correlation suggests a notable association between Chris Paul's errant passes and the amount of automotive fuel consumed in Gambia. It seems that, much like a slam dunk, there may be more to turnovers and gasoline consumption than meets the eye.

We also analyzed the economic and environmental implications of this unexpected link, prompting us to ask the timeless question: "If a basketball player fumbles the ball in the playoffs and no one is around to see it, does it still affect gasoline consumption in Gambia?" Perhaps we are witnessing the inception of a new era in sports and energy research, where jump shots and joules collide in unforeseen ways. With these findings, we hope to inspire future researchers to embrace the absurd and uncover the hidden connections that shape our world.

In conclusion, our study sheds light on the quirky nexus between professional basketball and the energy landscape, reminding us that even the most seemingly unrelated variables can dance in step, much like a dad joke at a family reunion – oddly fitting yet undeniably delightful.

[[INTRODUCTION]]
The interplay between sports performance and global energy trends has long been a subject of curiosity and bemusement. In this vein, our investigation sought to untangle the enigmatic relationship between the turnovers made by Chris Paul in the regular NBA season and the volume of gasoline pumped in the West African nation of Gambia. It is a connection both improbable and intriguing, much like a dad joke at a formal dinner party – unexpected, yet impossible to ignore.
As we delve into the unusual alliance of basketball mishaps and gasoline consumption, we aim to inject a dose of lightheartedness into the often serious world of statistical analysis. Our research endeavors to uncover the underlying threads that weave through seemingly disparate realms, much like the puns that inexplicably appear in the middle of academic research papers – a welcome surprise, or, for some, an eyeroll-inducing interruption.
The initial spark for this study came from an offhand comment during a post-game interview, where Chris Paul mused about the curious ebb and flow of his turnovers and the price of fuel in Gambia. This spurred our curiosity, leading us to explore what may be considered the "fast break" of statistical inquiry – a sudden sprint from the well-trodden paths of research into the uncharted territories of correlation.
Grounded in the principles of empirical inquiry, our study ventures into uncharted territory, akin to a basketball player navigating through an opponent's defense to take a three-point shot. We employed rigorous statistical methods to illuminate the unexpected kinship between Chris Paul's on-court blunders and the fueling habits of motorists on the roads of Gambia, much like a skilled magician revealing the secrets behind a seemingly inexplicable magic trick – a revelation that prompts both fascination and bemusement, not unlike a dad joke that elicits a reluctant chuckle from its audience.
We employed an array of data sources, ranging from NBA game logs to gasoline sales records, to construct a comprehensive dataset that underpins our analysis. Our examination covered a time span from 2006 to 2021, capturing over a decade of turnovers and gas tank fill-ups. This meticulous approach allowed us to detect patterns and trends that might otherwise have remained obscured, much like a hidden object waiting to be revealed in a game of "Where's Waldo" – a discovery that brings a sense of accomplishment and glee, not unlike the satisfaction of clever wordplay in a pun.
In the next section, we will delve into the specific methodologies applied in our research, peeling back the layers of our analytical process like an onion, albeit with fewer tears and more statistical formulas. So, buckle up, hold onto your seats, and get ready to accompany us on a journey that promises unexpected correlations and the occasional dad joke.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To unravel the tangled web of turnovers by Chris Paul and gasoline consumption in Gambia, our research employed a multi-faceted approach, akin to a team executing a well-coordinated play on the basketball court, except with more spreadsheets and less sweating. We combined quantitative analysis, statistical modeling, and a hint of whimsy to probe the improbable connection between these variables, with the hope of shedding light on the unexpected intersections of sports and global energy dynamics.

First, we scoured NBA game logs, statistical databases, and sports analytics platforms to meticulously compile the turnover data for Chris Paul spanning the years 2006 to 2021. This rigorous data gathering process involved sifting through countless game summaries and player statistics, much like searching for a needle in a haystack, except the needle in this case was Chris Paul's turnovers, and the haystack was the vast expanse of NBA records. It was a painstaking task, but one that ultimately yielded a wealth of turnover-related insights, akin to breaking open a pinata and being showered with candy – a rewarding, albeit less sugary, experience.

Simultaneously, we turned our investigative lens towards Gambia's energy landscape, tapping into databases from the Energy Information Administration and international energy agencies to capture the ebb and flow of gasoline consumption in the country over the same time period. This involved navigating complex datasets and grappling with energy consumption trends, much like solving a perplexing puzzle, except instead of matching shapes and colors, we were piecing together gallons and gigajoules. It was a mental workout that paid dividends, offering a deeper understanding of how energy dynamics dovetail with the world of professional sports, much like the satisfying snap of finding the corner piece in a jigsaw puzzle – a small victory amidst the complexity.

With our treasure trove of data in hand – or rather, in spreadsheets and statistical software – we applied robust statistical techniques to analyze the relationship between Chris Paul's turnovers and gasoline consumption in Gambia. Leveraging correlation analyses, regression models, and time series evaluations, we sought to unveil the underlying patterns that underpin this unexpected alliance, much like decoding the cryptic symbols on an ancient artifact, except in this case, the artifact was a scatter plot and the symbols were data points. It was a journey into the heart of statistical inquiry, where each regression coefficient and p-value became a clue in the grand puzzle of sports analytics and energy economics, revealing connections that lay hidden beneath the surface, much like a punchline that sneaks up on you in a serious conversation – surprising, yet undeniably impactful.

Furthermore, to ensure the robustness of our findings, we conducted sensitivity analyses and validation procedures, scrutinizing the stability of the observed correlations and the resilience of our statistical models to various adjustments. This meticulous approach aimed to fortify the reliability of our results, much like double-checking the locks on all the doors in a comedy film, except in this case, instead of preventing a heist, we were guarding against statistical fallacies. It was a critical step in affirming the solidity of our conclusions and reinforcing the credibility of our offbeat discoveries, like the reassuring punchline that ties together a series of comedic sketches – a testament to the prowess of methodological rigor and statistical acumen.

In the following section, we will unravel the findings of our analyses, unveiling the intriguing correlations and unexpected revelations that emerged from our investigation. Stay tuned for the twists and turns, both statistical and comedic, that lie ahead.

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 Number of turnovers by Chris Paul in the Regular NBA season and Gasoline pumped in Gambia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 NBA and Energy Information Administration .

For the time period 2006 to 2021, you found a correlation 0.6890573, r-squared of 0.4748000, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
The Tally of Turnovers: Tracing the Tenuous Tie between Chris Paul's Carelessness on the Court and Gasoline Gallons in Gambia

[[ABSTRACT]]
In this study, we delved into the peculiar and perplexing relationship between the number of turnovers committed by the renowned basketball player, Chris Paul, during the regular NBA seasons and the quantity of gasoline pumped in the small West African country of Gambia. The connection between these seemingly incongruent variables has baffled scholars and sports enthusiasts alike, prompting us to embark on this quirky investigation.

Bringing levity to the world of sports analytics, our research uncovered a statistically significant correlation coefficient of 0.6890573, with a p-value less than 0.01, based on data spanning from the years 2006 to 2021. This correlation suggests a notable association between Chris Paul's errant passes and the amount of automotive fuel consumed in Gambia. It seems that, much like a slam dunk, there may be more to turnovers and gasoline consumption than meets the eye.

We also analyzed the economic and environmental implications of this unexpected link, prompting us to ask the timeless question: "If a basketball player fumbles the ball in the playoffs and no one is around to see it, does it still affect gasoline consumption in Gambia?" Perhaps we are witnessing the inception of a new era in sports and energy research, where jump shots and joules collide in unforeseen ways. With these findings, we hope to inspire future researchers to embrace the absurd and uncover the hidden connections that shape our world.

In conclusion, our study sheds light on the quirky nexus between professional basketball and the energy landscape, reminding us that even the most seemingly unrelated variables can dance in step, much like a dad joke at a family reunion – oddly fitting yet undeniably delightful.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The interplay between sports performance and global energy trends has long been a subject of curiosity and bemusement. In this vein, our investigation sought to untangle the enigmatic relationship between the turnovers made by Chris Paul in the regular NBA season and the volume of gasoline pumped in the West African nation of Gambia. It is a connection both improbable and intriguing, much like a dad joke at a formal dinner party – unexpected, yet impossible to ignore.
As we delve into the unusual alliance of basketball mishaps and gasoline consumption, we aim to inject a dose of lightheartedness into the often serious world of statistical analysis. Our research endeavors to uncover the underlying threads that weave through seemingly disparate realms, much like the puns that inexplicably appear in the middle of academic research papers – a welcome surprise, or, for some, an eyeroll-inducing interruption.
The initial spark for this study came from an offhand comment during a post-game interview, where Chris Paul mused about the curious ebb and flow of his turnovers and the price of fuel in Gambia. This spurred our curiosity, leading us to explore what may be considered the "fast break" of statistical inquiry – a sudden sprint from the well-trodden paths of research into the uncharted territories of correlation.
Grounded in the principles of empirical inquiry, our study ventures into uncharted territory, akin to a basketball player navigating through an opponent's defense to take a three-point shot. We employed rigorous statistical methods to illuminate the unexpected kinship between Chris Paul's on-court blunders and the fueling habits of motorists on the roads of Gambia, much like a skilled magician revealing the secrets behind a seemingly inexplicable magic trick – a revelation that prompts both fascination and bemusement, not unlike a dad joke that elicits a reluctant chuckle from its audience.
We employed an array of data sources, ranging from NBA game logs to gasoline sales records, to construct a comprehensive dataset that underpins our analysis. Our examination covered a time span from 2006 to 2021, capturing over a decade of turnovers and gas tank fill-ups. This meticulous approach allowed us to detect patterns and trends that might otherwise have remained obscured, much like a hidden object waiting to be revealed in a game of "Where's Waldo" – a discovery that brings a sense of accomplishment and glee, not unlike the satisfaction of clever wordplay in a pun.
In the next section, we will delve into the specific methodologies applied in our research, peeling back the layers of our analytical process like an onion, albeit with fewer tears and more statistical formulas. So, buckle up, hold onto your seats, and get ready to accompany us on a journey that promises unexpected correlations and the occasional dad joke.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The statistical analysis revealed a remarkable correlation coefficient of 0.6890573 between the number of turnovers by Chris Paul in the regular NBA season and the volume of gasoline pumped in Gambia, with an r-squared value of 0.4748000 and a p-value less than 0.01. This finding suggests a moderately strong and statistically significant relationship between these seemingly unrelated variables, mirroring the unexpected laughter that follows a well-timed dad joke – surprising, yet undeniably enjoyable.

Upon constructing a scatterplot (Fig. 1), the depicted data points exhibited a clear and discernible trend, resembling the precise arc of a well-executed basketball pass. The plot humorously illustrated the positive correlation between Chris Paul's mishaps on the court and the gallons of gasoline consumed in Gambia, inviting observers to ponder the curious interplay of these disparate elements, much like an intellectual riddle embedded in the heart of a punchline.

The observed correlation unveils an intriguing narrative, reminiscent of a classic dad joke unfolding over the dinner table, where each punchline leads to gleeful anticipation and improbable connections. These findings underscore the unexpected proximity of athletic performance and energy consumption, elevating the importance of exploring unorthodox relationships in statistical analysis – a reminder that, much like a good pun, the essence of discovery lies in unearthing the uncanny.

With these results, our research not only reveals the tantalizing association between turnovers by Chris Paul and gasoline pumped in Gambia but also highlights the whimsical and often overlooked intersections between sports and global energy dynamics, akin to the delightful surprise that accompanies a clever wordplay in the midst of a scholarly discussion. This study paves the way for future investigations to embrace the unanticipated and celebrate the comical yet captivating bond between the seemingly unrelated facets of our 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 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 Number of turnovers by Chris Paul in the Regular NBA season and Gasoline pumped in Gambia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
The Tally of Turnovers: Tracing the Tenuous Tie between Chris Paul's Carelessness on the Court and Gasoline Gallons in Gambia

[[ABSTRACT]]
In this study, we delved into the peculiar and perplexing relationship between the number of turnovers committed by the renowned basketball player, Chris Paul, during the regular NBA seasons and the quantity of gasoline pumped in the small West African country of Gambia. The connection between these seemingly incongruent variables has baffled scholars and sports enthusiasts alike, prompting us to embark on this quirky investigation.

Bringing levity to the world of sports analytics, our research uncovered a statistically significant correlation coefficient of 0.6890573, with a p-value less than 0.01, based on data spanning from the years 2006 to 2021. This correlation suggests a notable association between Chris Paul's errant passes and the amount of automotive fuel consumed in Gambia. It seems that, much like a slam dunk, there may be more to turnovers and gasoline consumption than meets the eye.

We also analyzed the economic and environmental implications of this unexpected link, prompting us to ask the timeless question: "If a basketball player fumbles the ball in the playoffs and no one is around to see it, does it still affect gasoline consumption in Gambia?" Perhaps we are witnessing the inception of a new era in sports and energy research, where jump shots and joules collide in unforeseen ways. With these findings, we hope to inspire future researchers to embrace the absurd and uncover the hidden connections that shape our world.

In conclusion, our study sheds light on the quirky nexus between professional basketball and the energy landscape, reminding us that even the most seemingly unrelated variables can dance in step, much like a dad joke at a family reunion – oddly fitting yet undeniably delightful.

[[LITERATURE REVIEW]]
In their seminal work, Smith and Doe (2015) conducted a comprehensive analysis of turnover statistics in the NBA, focusing on the impact of turnovers on team performance and game outcomes. Their findings underscored the significant influence of turnovers on the ebb and flow of basketball games, shaping the narrative of victory and defeat. However, what Smith and Doe did not anticipate was the potential ripple effect of turnovers on the global gasoline market. It seems that Chris Paul's turnovers may pack more of a punch than a knockout punchline at a comedy club – unexpected and leaving the audience in fits of laughter.
Jones et al. (2018) delved into the nuances of energy consumption patterns in West African countries, offering valuable insights into the driving forces behind gasoline demand in the region. Their meticulous analysis uncovered a web of economic, social, and infrastructural factors that intersect to shape fuel consumption trends. Little did they know that an NBA player's turnovers could add another layer to this complex tapestry, weaving a narrative as surprising as a plot twist in a mystery novel – unexpected, yet strangely fitting.
Drawing from the realm of non-fiction, "The Prize: The Epic Quest for Oil, Money, and Power" by Daniel Yergin and "Energy and Civilization: A History" by Vaclav Smil shed light on the intricate dynamics of energy production and consumption on a global scale. While these works provide invaluable knowledge on energy markets and societal development, they may have missed the mark on the playful connection between a basketball player's blunders and the gasoline habits of a small West African nation. It seems that sometimes the most unexpected connections can be as captivating as the plot twists in a thriller novel – keeping us on the edge of our seats and eager for the next revelation.
In the realm of fiction, the works of Jules Verne, particularly "Around the World in Eighty Days," transport readers to distant lands and adventures that defy expectation. While Verne's tales may not explicitly address the intersection of sports statistics and gasoline consumption, they nonetheless invite us to embrace the wonders of the unexpected. After all, who would have thought that a basketball player's turnovers could hold any sway over the petrol pumps in Gambia? It's as surprising as stumbling upon a comedic moment in a Shakespearean tragedy – a delightful deviation from the norm.
Television series such as "How It's Made" and "SportsCenter" offer glimpses into the inner workings of diverse phenomena, from manufacturing processes to sports highlights. This eclectic exposure serves as a reminder that the most unusual pairings can yield remarkable insights. Just as a lighthearted sitcom can deliver unexpected wisdom in the midst of laughter, so too can the correlation between turnovers by Chris Paul and gasoline consumption in Gambia reveal unexpected truths.
But enough of the literary diversions – let's turn our attention to the empirical studies that have grappled with the intertwined realms of basketball turnovers and global energy consumption.

[[RESULTS]]
The statistical analysis revealed a remarkable correlation coefficient of 0.6890573 between the number of turnovers by Chris Paul in the regular NBA season and the volume of gasoline pumped in Gambia, with an r-squared value of 0.4748000 and a p-value less than 0.01. This finding suggests a moderately strong and statistically significant relationship between these seemingly unrelated variables, mirroring the unexpected laughter that follows a well-timed dad joke – surprising, yet undeniably enjoyable.
Upon constructing a scatterplot (Fig. 1), the depicted data points exhibited a clear and discernible trend, resembling the precise arc of a well-executed basketball pass. The plot humorously illustrated the positive correlation between Chris Paul's mishaps on the court and the gallons of gasoline consumed in Gambia, inviting observers to ponder the curious interplay of these disparate elements, much like an intellectual riddle embedded in the heart of a punchline.
The observed correlation unveils an intriguing narrative, reminiscent of a classic dad joke unfolding over the dinner table, where each punchline leads to gleeful anticipation and improbable connections. These findings underscore the unexpected proximity of athletic performance and energy consumption, elevating the importance of exploring unorthodox relationships in statistical analysis – a reminder that, much like a good pun, the essence of discovery lies in unearthing the uncanny.
With these results, our research not only reveals the tantalizing association between turnovers by Chris Paul and gasoline pumped in Gambia but also highlights the whimsical and often overlooked intersections between sports and global energy dynamics, akin to the delightful surprise that accompanies a clever wordplay in the midst of a scholarly discussion. This study paves the way for future investigations to embrace the unanticipated and celebrate the comical yet captivating bond between the seemingly unrelated facets of our world.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our findings have illuminated a previously unexplored link between the turnovers committed by Chris Paul in the NBA regular season and the volume of gasoline consumed in Gambia, shedding light on a peculiar correlation that challenges conventional wisdom and tickles the intellectual palate much like a well-crafted dad joke. The statistically significant correlation coefficient of 0.6890573, with a p-value less than 0.01, elucidates a surprisingly robust relationship between these variables, akin to the unexpected delight of stumbling upon a witty quip in the midst of a serious conversation.

The results of our study not only align with prior research that has delved into seemingly unrelated realms, such as the impact of turnovers on team performance in basketball and the intricate underpinnings of energy consumption in West African countries, echoing the unpredictable twists and turns of a thoroughly engaging plot. It appears that Chris Paul's on-court actions may indeed hold sway over the gasoline consumption habits of a nation in ways as unforeseen as a clever punchline in a script – an unexpected but undeniably fitting revelation.

The correlation coefficient observed in our study reinforces the importance of embracing unconventional connections in statistical analysis, championing the pursuit of unexpected relationships that challenge conventional boundaries and deliver an intellectual punch akin to a well-timed dad joke. This unorthodox correlation serves as a quirky reminder that the pursuit of knowledge often leads us down unexpected paths, resonating with the delightful surprise that accompanies an unexpected jest in the midst of an erudite conversation.

Our research has not only enriched the annals of sports analytics and energy economics but has also ushered in an era of scholarly inquiry that revels in the whimsical and unforeseen connections that shape our world, much like the charm of a carefully constructed dad joke – oddly fitting yet undeniably delightful. These findings beckon future researchers to continue this journey of uncovering the delightful and often whimsical threads that weave together the seemingly disparate corners of our complex reality, much like the peals of laughter that follow a well-delivered pun.

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 Number of turnovers by Chris Paul in the Regular NBA season and Gasoline pumped in Gambia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
The Tally of Turnovers: Tracing the Tenuous Tie between Chris Paul's Carelessness on the Court and Gasoline Gallons in Gambia

[[ABSTRACT]]
In this study, we delved into the peculiar and perplexing relationship between the number of turnovers committed by the renowned basketball player, Chris Paul, during the regular NBA seasons and the quantity of gasoline pumped in the small West African country of Gambia. The connection between these seemingly incongruent variables has baffled scholars and sports enthusiasts alike, prompting us to embark on this quirky investigation.

Bringing levity to the world of sports analytics, our research uncovered a statistically significant correlation coefficient of 0.6890573, with a p-value less than 0.01, based on data spanning from the years 2006 to 2021. This correlation suggests a notable association between Chris Paul's errant passes and the amount of automotive fuel consumed in Gambia. It seems that, much like a slam dunk, there may be more to turnovers and gasoline consumption than meets the eye.

We also analyzed the economic and environmental implications of this unexpected link, prompting us to ask the timeless question: "If a basketball player fumbles the ball in the playoffs and no one is around to see it, does it still affect gasoline consumption in Gambia?" Perhaps we are witnessing the inception of a new era in sports and energy research, where jump shots and joules collide in unforeseen ways. With these findings, we hope to inspire future researchers to embrace the absurd and uncover the hidden connections that shape our world.

In conclusion, our study sheds light on the quirky nexus between professional basketball and the energy landscape, reminding us that even the most seemingly unrelated variables can dance in step, much like a dad joke at a family reunion – oddly fitting yet undeniably delightful.

[[INTRDUCTION]]
The interplay between sports performance and global energy trends has long been a subject of curiosity and bemusement. In this vein, our investigation sought to untangle the enigmatic relationship between the turnovers made by Chris Paul in the regular NBA season and the volume of gasoline pumped in the West African nation of Gambia. It is a connection both improbable and intriguing, much like a dad joke at a formal dinner party – unexpected, yet impossible to ignore.
As we delve into the unusual alliance of basketball mishaps and gasoline consumption, we aim to inject a dose of lightheartedness into the often serious world of statistical analysis. Our research endeavors to uncover the underlying threads that weave through seemingly disparate realms, much like the puns that inexplicably appear in the middle of academic research papers – a welcome surprise, or, for some, an eyeroll-inducing interruption.
The initial spark for this study came from an offhand comment during a post-game interview, where Chris Paul mused about the curious ebb and flow of his turnovers and the price of fuel in Gambia. This spurred our curiosity, leading us to explore what may be considered the "fast break" of statistical inquiry – a sudden sprint from the well-trodden paths of research into the uncharted territories of correlation.
Grounded in the principles of empirical inquiry, our study ventures into uncharted territory, akin to a basketball player navigating through an opponent's defense to take a three-point shot. We employed rigorous statistical methods to illuminate the unexpected kinship between Chris Paul's on-court blunders and the fueling habits of motorists on the roads of Gambia, much like a skilled magician revealing the secrets behind a seemingly inexplicable magic trick – a revelation that prompts both fascination and bemusement, not unlike a dad joke that elicits a reluctant chuckle from its audience.
We employed an array of data sources, ranging from NBA game logs to gasoline sales records, to construct a comprehensive dataset that underpins our analysis. Our examination covered a time span from 2006 to 2021, capturing over a decade of turnovers and gas tank fill-ups. This meticulous approach allowed us to detect patterns and trends that might otherwise have remained obscured, much like a hidden object waiting to be revealed in a game of "Where's Waldo" – a discovery that brings a sense of accomplishment and glee, not unlike the satisfaction of clever wordplay in a pun.
In the next section, we will delve into the specific methodologies applied in our research, peeling back the layers of our analytical process like an onion, albeit with fewer tears and more statistical formulas. So, buckle up, hold onto your seats, and get ready to accompany us on a journey that promises unexpected correlations and the occasional dad joke.

[[RESULTS]]
The statistical analysis revealed a remarkable correlation coefficient of 0.6890573 between the number of turnovers by Chris Paul in the regular NBA season and the volume of gasoline pumped in Gambia, with an r-squared value of 0.4748000 and a p-value less than 0.01. This finding suggests a moderately strong and statistically significant relationship between these seemingly unrelated variables, mirroring the unexpected laughter that follows a well-timed dad joke – surprising, yet undeniably enjoyable.
Upon constructing a scatterplot (Fig. 1), the depicted data points exhibited a clear and discernible trend, resembling the precise arc of a well-executed basketball pass. The plot humorously illustrated the positive correlation between Chris Paul's mishaps on the court and the gallons of gasoline consumed in Gambia, inviting observers to ponder the curious interplay of these disparate elements, much like an intellectual riddle embedded in the heart of a punchline.
The observed correlation unveils an intriguing narrative, reminiscent of a classic dad joke unfolding over the dinner table, where each punchline leads to gleeful anticipation and improbable connections. These findings underscore the unexpected proximity of athletic performance and energy consumption, elevating the importance of exploring unorthodox relationships in statistical analysis – a reminder that, much like a good pun, the essence of discovery lies in unearthing the uncanny.
With these results, our research not only reveals the tantalizing association between turnovers by Chris Paul and gasoline pumped in Gambia but also highlights the whimsical and often overlooked intersections between sports and global energy dynamics, akin to the delightful surprise that accompanies a clever wordplay in the midst of a scholarly discussion. This study paves the way for future investigations to embrace the unanticipated and celebrate the comical yet captivating bond between the seemingly unrelated facets of our world.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has unearthed a statistically significant correlation between the number of turnovers by Chris Paul during the regular NBA season and the amount of gasoline pumped in Gambia, pointing to an intriguing link that defies conventional expectations. It seems that, much like a missed free throw, this connection cannot be overlooked, prompting further examination and exploration.

This unexpected correlation, akin to a rare gem unearthed from a seemingly ordinary field, opens the door to a realm of unexplored possibilities in sports analytics and energy dynamics. It reminds us that, much like a dad joke, the world of statistical analysis can be full of delightful surprises and connections that defy initial logic.

With these findings, we hope to inspire future researchers to embrace the whimsical and the unexpected, uncovering the hidden relationships that shape our world. As we venture forth into the unknown territory of unconventional correlations, let us not forget to occasionally inject a dose of lightheartedness, much like a well-timed dad joke in the midst of academic discourse.

It is evident that this correlation, though unexpected, demands further attention and contemplation. As we wrap up this study, we assert that no more research is needed in this area. The connection between Chris Paul's turnovers and gasoline consumption in Gambia has been unveiled, leaving us with a newfound appreciation for the unpredictable connections that underpin our world – much like a groan-inducing dad joke, you never quite know when it will pop up, but when it does, it's oddly satisfying.

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited The Tally of Turnovers: Tracing the Tenuous Tie between Chris Paul's Carelessness on the Court and Gasoline Gallons in Gambia. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Sports Psychology and Ecological Economics

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited The Tally of Turnovers: Tracing the Tenuous Tie between Chris Paul's Carelessness on the Court and Gasoline Gallons in Gambia. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Comedic Synchronization Studies

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled The Tally of Turnovers: Tracing the Tenuous Tie between Chris Paul's Carelessness on the Court and Gasoline Gallons in Gambia with an abstract of In this study, we delved into the peculiar and perplexing relationship between the number of turnovers committed by the renowned basketball player, Chris Paul, during the regular NBA seasons and the quantity of gasoline pumped in the small West African country of Gambia. The connection between these seemingly incongruent variables has baffled scholars and sports enthusiasts alike, prompting us to embark on this quirky investigation.
Bringing levity to the world of sports analytics, our research uncovered a statistically significant correlation coefficient of 0.6890573, with a p-value less than 0.01, based on data spanning from the years 2006 to 2021. This correlation suggests a notable association between Chris Paul's errant passes and the amount of automotive fuel consumed in Gambia. It seems that, much like a slam dunk, there may be more to turnovers and gasoline consumption than meets the eye.
We also analyzed the economic and environmental implications of this unexpected link, prompting us to ask the timeless question: "If a basketball player fumbles the ball in the playoffs and no one is around to see it, does it still affect gasoline consumption in Gambia?" Perhaps we are witnessing the inception of a new era in sports and energy research, where jump shots and joules collide in unforeseen ways. With these findings, we hope to inspire future researchers to embrace the absurd and uncover the hidden connections that shape our world.
In conclusion, our study sheds light on the quirky nexus between professional basketball and the energy landscape, reminding us that even the most seemingly unrelated variables can dance in step, much like a dad joke at a family reunion – oddly fitting yet undeniably delightful.

ChatGPT:

Chris Paul, turnovers, gasoline consumption, Gambia, basketball player, NBA, correlation, statistical analysis, sports analytics, environmental implications, economic impact, energy research, hidden connections, professional basketball, energy landscape, statistical significance

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

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Data details

Number of turnovers by Chris Paul in the Regular NBA season
Source: NBA
See what else correlates with Number of turnovers by Chris Paul in the Regular NBA season

Gasoline pumped in Gambia
Detailed data title: Volume of gasoline pumped consumed in Gambia, The in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Gasoline pumped in Gambia

Correlation r = 0.6890573 (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 = 0.4748000 (Coefficient of determination)
This means 47.5% of the change in the one variable (i.e., Gasoline pumped in Gambia) is predictable based on the change in the other (i.e., Number of turnovers by Chris Paul in the Regular NBA season) over the 16 years from 2006 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.0032.^Show 0.0031529889082716144000000000
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 0.69 in 0.32% of random cases. Said differently, if you correlated 317 random variables^Note Which I absolutely did.
with the same 15 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 15 because we have two variables measured over a period of 16 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.29, 0.88 ] 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.

	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Number of turnovers by Chris Paul in the Regular NBA season (Turnovers)	183	161	201	231	112	177	124	159	145	190	194	147	128	152	161	156
Gasoline pumped in Gambia (Million Barrels/Day)	0.888055	1.14512	1.1653	1.56578	0.474408	0.521148	0.494087	0.518811	0.574899	0.577235	0.58265	0.593594	0.584247	0.607616	0.580163	0.61217

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([183,161,201,231,112,177,124,159,145,190,194,147,128,152,161,156,])
array_2 = np.array([0.888055,1.14512,1.1653,1.56578,0.474408,0.521148,0.494087,0.518811,0.574899,0.577235,0.58265,0.593594,0.584247,0.607616,0.580163,0.61217,])
array_1_name = "Number of turnovers by Chris Paul in the Regular NBA season"
array_2_name = "Gasoline pumped in Gambia"

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

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

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Number of turnovers by Chris Paul in the Regular NBA season
Line chart for only Gasoline pumped in Gambia
AI-generated correlation image
The spurious research paper: The Tally of Turnovers: Tracing the Tenuous Tie between Chris Paul's Carelessness on the Court and Gasoline Gallons in Gambia

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Correlation ID: 2291 · Black Variable ID: 317 · Red Variable ID: 24440


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