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Spurious correlation #3,976 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Motor vehicle thefts in Tennessee and the second variable is Gasoline pumped in Belgium.  The chart goes from 1985 to 2022, and the two variables track closely in value over that time. Small Image

AI explanation

As the number of car thefts in Tennessee dwindled, there was a corresponding decrease in the demand for gasoline in the state. This led to a surplus of gasoline, which, in a surprising turn of events, was exported to Belgium. The sudden influx of American gasoline in Belgium caused a shift in the local market, leading to a decrease in the amount of gasoline being pumped. It seems even gas can't escape the far-reaching impact of car theft trends!

Model: dalle-3
Prompt: Generate an image of a surreal, vibrant landscape split in two halves. On one side stands a row of sleek, stolen cars with blazing headlights, racing through a neon-soaked Tennessee city. The cars leave trails of vivid light behind them as they speed away, creating a sense of frenetic movement and excitement. On the other side, set against a backdrop of an idyllic Belgian countryside, an old-fashioned gas station is surrounded by a queue of patient cars. The station is bathed in a soft, hazy glow, exuding a tranquil atmosphere. In the distance, a group of enigmatic, shadowy figures are depicted siphoning gasoline from a hidden tanker, their sly grins adding an air of mischievousness to the scene. The contrast between the chaotic energy of the stolen cars in Tennessee and the serene, unsuspecting scene in Belgium brings out the stark disparities in the cross-country caper, creating a compelling visual narrative. 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: Motor vehicle thefts in Tennessee and Gasoline pumped in Belgium. 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: Scalar art Psychedelic A scene from Skyrim a Polaroid photo Psychedelic
ChatGPT: Psychedelic

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 Motor vehicle thefts in Tennessee and Gasoline pumped in Belgium, in the following situation: Gasoline pumped in Belgium increased because as more motor vehicles were stolen in Tennessee, fuel thieves got bolder and started siphoning gas across the Atlantic. They figured it was the perfect crime because who's gonna look for their stolen gas in a whole other continent? So, Tennessee car thefts led to a global gas getaway, leaving Belgians scratching their heads as their fuel mysteriously disappeared. It's a cross-country caper that's driving everyone nuts!. Keep the description simple.
ChatGPT: In Tennessee, a group of thieves swiftly and skillfully hotwired and stole several cars, their engines roaring as they sped away. Meanwhile, across the Atlantic in Belgium, a line of cars patiently queued at a gas station, their owners pumping fuel into their tanks. In the distance, a group of shadowy figures siphoned gasoline from a hidden tanker, their mischievous grins betraying their sneaky intent. The stolen Tennessee cars and the siphoned gasoline eventually converged, creating a cross-country caper that left people puzzled and frustrated on both sides of the Atlantic.

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: [ Psychedelic ] and depicting this scene: In Tennessee, a group of thieves swiftly and skillfully hotwired and stole several cars, their engines roaring as they sped away. Meanwhile, across the Atlantic in Belgium, a line of cars patiently queued at a gas station, their owners pumping fuel into their tanks. In the distance, a group of shadowy figures siphoned gasoline from a hidden tanker, their mischievous grins betraying their sneaky intent. The stolen Tennessee cars and the siphoned gasoline eventually converged, creating a cross-country caper that left people puzzled and frustrated on both sides of the Atlantic. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a surreal, vibrant landscape split in two halves. On one side stands a row of sleek, stolen cars with blazing headlights, racing through a neon-soaked Tennessee city. The cars leave trails of vivid light behind them as they speed away, creating a sense of frenetic movement and excitement. On the other side, set against a backdrop of an idyllic Belgian countryside, an old-fashioned gas station is surrounded by a queue of patient cars. The station is bathed in a soft, hazy glow, exuding a tranquil atmosphere. In the distance, a group of enigmatic, shadowy figures are depicted siphoning gasoline from a hidden tanker, their sly grins adding an air of mischievousness to the scene. The contrast between the chaotic energy of the stolen cars in Tennessee and the serene, unsuspecting scene in Belgium brings out the stark disparities in the cross-country caper, creating a compelling visual narrative.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how a decrease in Motor vehicle thefts in Tennessee caused Gasoline pumped in Belgium to decrease.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)
Pump It Up: Exploring the Surprising Relationship Between Motor Vehicle Thefts in Tennessee and Gasoline Pumped in Belgium

The Journal of Unexpected Correlations in Societal Phenomena

Jan 2024
Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.




Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Motor vehicle thefts in Tennessee and Gasoline pumped in Belgium. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title a clever pun.

Your research team used data from FBI Criminal Justice Information Services and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.9406226 and p < 0.01 for 1985 to 2022.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
Pump It Up: Exploring the Surprising Relationship Between Motor Vehicle Thefts in Tennessee and Gasoline Pumped in Belgium

[[ABSTRACT]]
Recent research has uncovered an unexpected connection between motor vehicle thefts in the state of Tennessee and the amount of gasoline pumped in Belgium. Drawing upon data from the FBI Criminal Justice Information Services and the Energy Information Administration, our study analyzes the correlation between these seemingly disparate phenomena. After crunching the numbers, we discovered a remarkably high correlation coefficient of 0.9406226 and a p-value less than 0.01, encompassing the time span from 1985 to 2022. This intriguing finding challenges conventional wisdom and has potential ramifications for both the field of criminal justice and energy economics. While the mechanisms underlying this relationship remain elusive, our study provides a quirky yet thought-provoking entryway into the quirky world of statistical analysis.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the introduction section of an academic research paper presenting the findings of the connection between Motor vehicle thefts in Tennessee and Gasoline pumped in Belgium. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
Pump It Up: Exploring the Surprising Relationship Between Motor Vehicle Thefts in Tennessee and Gasoline Pumped in Belgium

[[ABSTRACT]]
Recent research has uncovered an unexpected connection between motor vehicle thefts in the state of Tennessee and the amount of gasoline pumped in Belgium. Drawing upon data from the FBI Criminal Justice Information Services and the Energy Information Administration, our study analyzes the correlation between these seemingly disparate phenomena. After crunching the numbers, we discovered a remarkably high correlation coefficient of 0.9406226 and a p-value less than 0.01, encompassing the time span from 1985 to 2022. This intriguing finding challenges conventional wisdom and has potential ramifications for both the field of criminal justice and energy economics. While the mechanisms underlying this relationship remain elusive, our study provides a quirky yet thought-provoking entryway into the quirky world of statistical analysis.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

In the realm of academic research, it is not uncommon to stumble upon unexpected and seemingly illogical associations between disparate variables. Such peculiar connections can often challenge conventional wisdom and lead to exhilarating eureka moments that spark intellectual curiosity. One such unlikely but undeniably intriguing relationship has emerged from our investigation into the correlation between motor vehicle thefts in Tennessee and the amount of gasoline pumped in Belgium. This unlikely duo has captivated our attention and propelled us into the whimsical world of statistical analysis, where the quirky and the thought-provoking often intermingle.

At first glance, the connection between motor vehicle thefts in Tennessee and the volume of gasoline pumped in Belgium appears nothing short of absurd. However, as any seasoned researcher knows, the world of statistics is rife with surprises and anomalies, much like a box of chocolates: you never know what you're going to get.

Our investigation was inspired by the growing recognition that statistical analysis can often yield unexpected and fascinating insights, much like finding a hidden treasure trove in a cluttered attic. The unfurling of this research journey began with the collection of data from the FBI Criminal Justice Information Services and the Energy Information Administration, which provided the necessary raw material to unearth the intriguing connection between these seemingly unrelated phenomena.

And so, armed with an insatiable quest for knowledge and armed with statistical tools that rival the precision of a Swiss watch, we embarked on a curious voyage to unravel the enigmatic correlation between motor vehicle thefts in Tennessee and the amount of gasoline pumped in Belgium. Little did we know that this journey would lead us into the underbelly of statistical analysis, where every data point holds the potential to surprise and excite, much like a mystery novel that promises unexpected twists at every turn.

In the following sections of this paper, we shall unveil the captivating findings of our analysis, which not only challenge conventional wisdom but also open a portal to a world where statistical curiosities abound like mushrooms after a spring rain. So, fasten your seatbelts and prepare to journey with us into the peculiar yet captivating landscape of statistical analysis, where the unexpected is often waiting to be discovered.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Motor vehicle thefts in Tennessee and Gasoline pumped in Belgium. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
Pump It Up: Exploring the Surprising Relationship Between Motor Vehicle Thefts in Tennessee and Gasoline Pumped in Belgium

[[ABSTRACT]]
Recent research has uncovered an unexpected connection between motor vehicle thefts in the state of Tennessee and the amount of gasoline pumped in Belgium. Drawing upon data from the FBI Criminal Justice Information Services and the Energy Information Administration, our study analyzes the correlation between these seemingly disparate phenomena. After crunching the numbers, we discovered a remarkably high correlation coefficient of 0.9406226 and a p-value less than 0.01, encompassing the time span from 1985 to 2022. This intriguing finding challenges conventional wisdom and has potential ramifications for both the field of criminal justice and energy economics. While the mechanisms underlying this relationship remain elusive, our study provides a quirky yet thought-provoking entryway into the quirky world of statistical analysis.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the realm of academic research, it is not uncommon to stumble upon unexpected and seemingly illogical associations between disparate variables. Such peculiar connections can often challenge conventional wisdom and lead to exhilarating eureka moments that spark intellectual curiosity. One such unlikely but undeniably intriguing relationship has emerged from our investigation into the correlation between motor vehicle thefts in Tennessee and the amount of gasoline pumped in Belgium. This unlikely duo has captivated our attention and propelled us into the whimsical world of statistical analysis, where the quirky and the thought-provoking often intermingle.
At first glance, the connection between motor vehicle thefts in Tennessee and the volume of gasoline pumped in Belgium appears nothing short of absurd. However, as any seasoned researcher knows, the world of statistics is rife with surprises and anomalies, much like a box of chocolates: you never know what you're going to get.
Our investigation was inspired by the growing recognition that statistical analysis can often yield unexpected and fascinating insights, much like finding a hidden treasure trove in a cluttered attic. The unfurling of this research journey began with the collection of data from the FBI Criminal Justice Information Services and the Energy Information Administration, which provided the necessary raw material to unearth the intriguing connection between these seemingly unrelated phenomena.
And so, armed with an insatiable quest for knowledge and armed with statistical tools that rival the precision of a Swiss watch, we embarked on a curious voyage to unravel the enigmatic correlation between motor vehicle thefts in Tennessee and the amount of gasoline pumped in Belgium. Little did we know that this journey would lead us into the underbelly of statistical analysis, where every data point holds the potential to surprise and excite, much like a mystery novel that promises unexpected twists at every turn.
In the following sections of this paper, we shall unveil the captivating findings of our analysis, which not only challenge conventional wisdom but also open a portal to a world where statistical curiosities abound like mushrooms after a spring rain. So, fasten your seatbelts and prepare to journey with us into the peculiar yet captivating landscape of statistical analysis, where the unexpected is often waiting to be discovered.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

In "Smith and Doe (2015)," the authors find a robust correlation between motor vehicle thefts in Tennessee and the amount of gasoline pumped in Belgium, sparking intrigue and bewilderment in the academic community. The unexpected nature of this relationship has prompted a reassessment of traditional assumptions and a flurry of research endeavors aimed at unraveling the underlying mechanisms. Building upon this foundation, "Jones (2018)" delves into the nuanced interplay between regional energy consumption patterns and criminal behavior, offering a comprehensive framework for understanding the peculiar association between these seemingly incongruous variables.

Drawing from the realm of non-fiction, "The Power of Habit" by Charles Duhigg and "Freakonomics" by Steven D. Levitt and Stephen J. Dubner offer valuable insights into the intricate dynamics of human behavior and the interconnectedness of seemingly disparate phenomena, laying the groundwork for contemplating the unexpected relationship between motor vehicle thefts in Tennessee and gasoline pumped in Belgium. Additionally, fictional works such as "The Da Vinci Code" by Dan Brown and "The Curious Incident of the Dog in the Night-Time" by Mark Haddon provide an unconventional lens through which to ponder the enigmatic correlation at hand.

Venturing beyond the conventional confines of academic literature, the authors conducted an extensive review of diverse sources, including ancient scrolls, enchanted parchment, and even the prophecies of a soothsayer residing in a remote mountain village. Amidst this eclectic array of resources, an unexpected breakthrough emerged in the form of deciphering cryptic messages embedded within ancient hieroglyphics and gleaning wisdom from the whimsical entries of a centuries-old manuscript passed down through generations.

As the authors delved deeper into the rabbit hole of research, an unassuming CVS receipt unearthed from a forgotten coat pocket emerged as an unexpected informant, whispering cryptic clues regarding the esoteric relationship between motor vehicle thefts in Tennessee and gasoline pumped in Belgium. Mysterious transactions and enigmatic discounts served as faint breadcrumbs, leading the authors on a whimsical journey through the labyrinthine corridors of statistical analysis.

In summary, the literature review has unveiled a tapestry of diverse sources that not only shed light on the surprising correlation between motor vehicle thefts in Tennessee and gasoline pumped in Belgium but also encapsulate the quirky and enthralling nature of academic inquiry. Through a blend of serious scholarship, fictional escapades, and whimsical detours, the authors aim to invigorate the scholarly discourse surrounding this unorthodox yet captivating research trajectory.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Motor vehicle thefts in Tennessee and Gasoline pumped in Belgium. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from FBI Criminal Justice Information Services and Energy Information Administration . You used data from 1985 to 2022

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Pump It Up: Exploring the Surprising Relationship Between Motor Vehicle Thefts in Tennessee and Gasoline Pumped in Belgium

[[ABSTRACT]]
Recent research has uncovered an unexpected connection between motor vehicle thefts in the state of Tennessee and the amount of gasoline pumped in Belgium. Drawing upon data from the FBI Criminal Justice Information Services and the Energy Information Administration, our study analyzes the correlation between these seemingly disparate phenomena. After crunching the numbers, we discovered a remarkably high correlation coefficient of 0.9406226 and a p-value less than 0.01, encompassing the time span from 1985 to 2022. This intriguing finding challenges conventional wisdom and has potential ramifications for both the field of criminal justice and energy economics. While the mechanisms underlying this relationship remain elusive, our study provides a quirky yet thought-provoking entryway into the quirky world of statistical analysis.

[[INTRODUCTION]]
In the realm of academic research, it is not uncommon to stumble upon unexpected and seemingly illogical associations between disparate variables. Such peculiar connections can often challenge conventional wisdom and lead to exhilarating eureka moments that spark intellectual curiosity. One such unlikely but undeniably intriguing relationship has emerged from our investigation into the correlation between motor vehicle thefts in Tennessee and the amount of gasoline pumped in Belgium. This unlikely duo has captivated our attention and propelled us into the whimsical world of statistical analysis, where the quirky and the thought-provoking often intermingle.
At first glance, the connection between motor vehicle thefts in Tennessee and the volume of gasoline pumped in Belgium appears nothing short of absurd. However, as any seasoned researcher knows, the world of statistics is rife with surprises and anomalies, much like a box of chocolates: you never know what you're going to get.
Our investigation was inspired by the growing recognition that statistical analysis can often yield unexpected and fascinating insights, much like finding a hidden treasure trove in a cluttered attic. The unfurling of this research journey began with the collection of data from the FBI Criminal Justice Information Services and the Energy Information Administration, which provided the necessary raw material to unearth the intriguing connection between these seemingly unrelated phenomena.
And so, armed with an insatiable quest for knowledge and armed with statistical tools that rival the precision of a Swiss watch, we embarked on a curious voyage to unravel the enigmatic correlation between motor vehicle thefts in Tennessee and the amount of gasoline pumped in Belgium. Little did we know that this journey would lead us into the underbelly of statistical analysis, where every data point holds the potential to surprise and excite, much like a mystery novel that promises unexpected twists at every turn.
In the following sections of this paper, we shall unveil the captivating findings of our analysis, which not only challenge conventional wisdom but also open a portal to a world where statistical curiosities abound like mushrooms after a spring rain. So, fasten your seatbelts and prepare to journey with us into the peculiar yet captivating landscape of statistical analysis, where the unexpected is often waiting to be discovered.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To uncover the tantalizing connection between motor vehicle thefts in Tennessee and the gasoline pumped in Belgium, our research team embarked on a statistically daring expedition that would rival the audacity of exploring uncharted territories. The methodology adopted for this inquiry combined elements of meticulous data collection, cunning statistical analysis, and a pinch of whimsical intuition that allowed for the unearthing of this quirky correlation.

Data Collection:
Like dedicated prospectors hunting for rare gems, our team scoured the vast expanse of the internet, diligently gathering information from reliable sources such as the FBI Criminal Justice Information Services and the Energy Information Administration. We cast our digital nets far and wide, encapsulating data spanning the years 1985 to 2022, in pursuit of the elusive relationship between motor vehicle thefts in Tennessee and the amount of gasoline pumped in Belgium. As our data set coalesced, it became apparent that this investigation would be no ordinary intellectual escapade but a thrilling quest for statistical treasure.

Statistical Analysis:
Upon assembling a robust data set, we called upon the prowess of correlational analysis to scrutinize the potential linkage between motor vehicle thefts in Tennessee and gasoline consumption in Belgium. With the seriousness of a detective piecing together clues at a crime scene, we calculated the correlation coefficient and its accompanying p-value, wielding our statistical tools like the artisans of yore, meticulously crafting a fine tapestry of quantitative evidence. Like performers at a vaudeville show, our statistical techniques danced across the data, revealing a remarkably high correlation coefficient of 0.9406226 and a p-value less than 0.01, much to the delight and astonishment of our research team.

Subtle Offhand Remarks, Jokes, and Clever Observations:
Throughout the voyage of our research, we encountered numerous quirky nuances and surprising insights that almost seemed to pop out of the data like unexpected confetti. Our statistical foray into the correlation between motor vehicle thefts in Tennessee and gasoline consumption in Belgium invited moments of whimsy and levity, reminding us that even in the realms of science and research, a touch of humor can enliven the most esoteric of inquiries. After all, data-driven discoveries can sometimes rival the delightful unpredictability of a stand-up comedy routine, where the punchline is often lurking in the unlikeliest of places.

In the forthcoming sections of this paper, we will unveil the mesmerizing findings emerging from this investigation, shedding light on the captivating statistical oddities that have made this research journey akin to a delightful game of sudoku: each revelation brings a sense of satisfaction but also hints at the presence of further tantalizing patterns yet to be deciphered.

Stay tuned as we delve further into the enthralling realm of statistical quirkiness, where the unexpected awaits at every turn, like a hidden punchline in a labyrinth of data.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the results section of an academic research paper presenting the findings of the connection between Motor vehicle thefts in Tennessee and Gasoline pumped in Belgium. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from FBI Criminal Justice Information Services and Energy Information Administration .

For the time period 1985 to 2022, you found a correlation 0.9406226, r-squared of 0.8847708, 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]]
Pump It Up: Exploring the Surprising Relationship Between Motor Vehicle Thefts in Tennessee and Gasoline Pumped in Belgium

[[ABSTRACT]]
Recent research has uncovered an unexpected connection between motor vehicle thefts in the state of Tennessee and the amount of gasoline pumped in Belgium. Drawing upon data from the FBI Criminal Justice Information Services and the Energy Information Administration, our study analyzes the correlation between these seemingly disparate phenomena. After crunching the numbers, we discovered a remarkably high correlation coefficient of 0.9406226 and a p-value less than 0.01, encompassing the time span from 1985 to 2022. This intriguing finding challenges conventional wisdom and has potential ramifications for both the field of criminal justice and energy economics. While the mechanisms underlying this relationship remain elusive, our study provides a quirky yet thought-provoking entryway into the quirky world of statistical analysis.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
In the realm of academic research, it is not uncommon to stumble upon unexpected and seemingly illogical associations between disparate variables. Such peculiar connections can often challenge conventional wisdom and lead to exhilarating eureka moments that spark intellectual curiosity. One such unlikely but undeniably intriguing relationship has emerged from our investigation into the correlation between motor vehicle thefts in Tennessee and the amount of gasoline pumped in Belgium. This unlikely duo has captivated our attention and propelled us into the whimsical world of statistical analysis, where the quirky and the thought-provoking often intermingle.
At first glance, the connection between motor vehicle thefts in Tennessee and the volume of gasoline pumped in Belgium appears nothing short of absurd. However, as any seasoned researcher knows, the world of statistics is rife with surprises and anomalies, much like a box of chocolates: you never know what you're going to get.
Our investigation was inspired by the growing recognition that statistical analysis can often yield unexpected and fascinating insights, much like finding a hidden treasure trove in a cluttered attic. The unfurling of this research journey began with the collection of data from the FBI Criminal Justice Information Services and the Energy Information Administration, which provided the necessary raw material to unearth the intriguing connection between these seemingly unrelated phenomena.
And so, armed with an insatiable quest for knowledge and armed with statistical tools that rival the precision of a Swiss watch, we embarked on a curious voyage to unravel the enigmatic correlation between motor vehicle thefts in Tennessee and the amount of gasoline pumped in Belgium. Little did we know that this journey would lead us into the underbelly of statistical analysis, where every data point holds the potential to surprise and excite, much like a mystery novel that promises unexpected twists at every turn.
In the following sections of this paper, we shall unveil the captivating findings of our analysis, which not only challenge conventional wisdom but also open a portal to a world where statistical curiosities abound like mushrooms after a spring rain. So, fasten your seatbelts and prepare to journey with us into the peculiar yet captivating landscape of statistical analysis, where the unexpected is often waiting to be discovered.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The results of our offbeat investigation revealed a remarkably strong correlation between motor vehicle thefts in Tennessee and the quantity of gasoline pumped in Belgium. Over the time period from 1985 to 2022, our statistical analysis unearthed a correlation coefficient of 0.9406226, a coefficient of determination (r-squared) of 0.8847708, and a p-value less than 0.01. This unexpected correlation is depicted in Figure 1, a scatterplot illustrating the striking relationship between these seemingly unrelated variables.

The robust correlation coefficient of 0.9406226 suggests a highly positive linear association between the number of motor vehicle thefts in Tennessee and the volume of gasoline pumped in Belgium. The coefficient of determination (r-squared) of 0.8847708 indicates that a substantial 88.47% of the variability in motor vehicle thefts in Tennessee can be explained by the quantity of gasoline pumped in Belgium, leaving a mere 11.53% to be attributed to other factors, much like a compelling mystery plot where most of the clues lead to a clear conclusion with just a few loose ends hanging about.

Moreover, the p-value falling below the threshold of 0.01 indicates that the observed correlation is statistically significant, thereby dismissing the possibility that this intriguing connection is merely a fluke. It's as if this improbable statistical relationship knocked on the door of conventional wisdom and confidently proclaimed, "I'm not just any random correlation; I'm statistically significant!"

In essence, our findings demonstrate a curious and unexpected linkage between the rate of motor vehicle thefts in Tennessee and the amount of gasoline pumped in Belgium, igniting a sense of wonder akin to stumbling upon a hidden treasure buried beneath layers of perplexing data. This whimsical correlation challenges traditional assumptions and beckons for further exploration, resembling a puzzle that demands to be solved for the sheer joy of unraveling its enigmatic twists and turns.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Motor vehicle thefts in Tennessee and Gasoline pumped in Belgium. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Pump It Up: Exploring the Surprising Relationship Between Motor Vehicle Thefts in Tennessee and Gasoline Pumped in Belgium

[[ABSTRACT]]
Recent research has uncovered an unexpected connection between motor vehicle thefts in the state of Tennessee and the amount of gasoline pumped in Belgium. Drawing upon data from the FBI Criminal Justice Information Services and the Energy Information Administration, our study analyzes the correlation between these seemingly disparate phenomena. After crunching the numbers, we discovered a remarkably high correlation coefficient of 0.9406226 and a p-value less than 0.01, encompassing the time span from 1985 to 2022. This intriguing finding challenges conventional wisdom and has potential ramifications for both the field of criminal justice and energy economics. While the mechanisms underlying this relationship remain elusive, our study provides a quirky yet thought-provoking entryway into the quirky world of statistical analysis.

[[LITERATURE REVIEW]]
In "Smith and Doe (2015)," the authors find a robust correlation between motor vehicle thefts in Tennessee and the amount of gasoline pumped in Belgium, sparking intrigue and bewilderment in the academic community. The unexpected nature of this relationship has prompted a reassessment of traditional assumptions and a flurry of research endeavors aimed at unraveling the underlying mechanisms. Building upon this foundation, "Jones (2018)" delves into the nuanced interplay between regional energy consumption patterns and criminal behavior, offering a comprehensive framework for understanding the peculiar association between these seemingly incongruous variables.
Drawing from the realm of non-fiction, "The Power of Habit" by Charles Duhigg and "Freakonomics" by Steven D. Levitt and Stephen J. Dubner offer valuable insights into the intricate dynamics of human behavior and the interconnectedness of seemingly disparate phenomena, laying the groundwork for contemplating the unexpected relationship between motor vehicle thefts in Tennessee and gasoline pumped in Belgium. Additionally, fictional works such as "The Da Vinci Code" by Dan Brown and "The Curious Incident of the Dog in the Night-Time" by Mark Haddon provide an unconventional lens through which to ponder the enigmatic correlation at hand.
Venturing beyond the conventional confines of academic literature, the authors conducted an extensive review of diverse sources, including ancient scrolls, enchanted parchment, and even the prophecies of a soothsayer residing in a remote mountain village. Amidst this eclectic array of resources, an unexpected breakthrough emerged in the form of deciphering cryptic messages embedded within ancient hieroglyphics and gleaning wisdom from the whimsical entries of a centuries-old manuscript passed down through generations.
As the authors delved deeper into the rabbit hole of research, an unassuming CVS receipt unearthed from a forgotten coat pocket emerged as an unexpected informant, whispering cryptic clues regarding the esoteric relationship between motor vehicle thefts in Tennessee and gasoline pumped in Belgium. Mysterious transactions and enigmatic discounts served as faint breadcrumbs, leading the authors on a whimsical journey through the labyrinthine corridors of statistical analysis.
In summary, the literature review has unveiled a tapestry of diverse sources that not only shed light on the surprising correlation between motor vehicle thefts in Tennessee and gasoline pumped in Belgium but also encapsulate the quirky and enthralling nature of academic inquiry. Through a blend of serious scholarship, fictional escapades, and whimsical detours, the authors aim to invigorate the scholarly discourse surrounding this unorthodox yet captivating research trajectory.

[[RESULTS]]
The results of our offbeat investigation revealed a remarkably strong correlation between motor vehicle thefts in Tennessee and the quantity of gasoline pumped in Belgium. Over the time period from 1985 to 2022, our statistical analysis unearthed a correlation coefficient of 0.9406226, a coefficient of determination (r-squared) of 0.8847708, and a p-value less than 0.01. This unexpected correlation is depicted in Figure 1, a scatterplot illustrating the striking relationship between these seemingly unrelated variables.
The robust correlation coefficient of 0.9406226 suggests a highly positive linear association between the number of motor vehicle thefts in Tennessee and the volume of gasoline pumped in Belgium. The coefficient of determination (r-squared) of 0.8847708 indicates that a substantial 88.47% of the variability in motor vehicle thefts in Tennessee can be explained by the quantity of gasoline pumped in Belgium, leaving a mere 11.53% to be attributed to other factors, much like a compelling mystery plot where most of the clues lead to a clear conclusion with just a few loose ends hanging about.
Moreover, the p-value falling below the threshold of 0.01 indicates that the observed correlation is statistically significant, thereby dismissing the possibility that this intriguing connection is merely a fluke. It's as if this improbable statistical relationship knocked on the door of conventional wisdom and confidently proclaimed, "I'm not just any random correlation; I'm statistically significant!"
In essence, our findings demonstrate a curious and unexpected linkage between the rate of motor vehicle thefts in Tennessee and the amount of gasoline pumped in Belgium, igniting a sense of wonder akin to stumbling upon a hidden treasure buried beneath layers of perplexing data. This whimsical correlation challenges traditional assumptions and beckons for further exploration, resembling a puzzle that demands to be solved for the sheer joy of unraveling its enigmatic twists and turns.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our study has unearthed a riveting and magnetizing correlation between motor vehicle thefts in Tennessee and the quantity of gasoline pumped in Belgium, echoing the unexpected findings of predecessors in this peculiar field of research. Delving into the spirited realm of statistical analysis, our results bolster the earlier work by "Smith and Doe (2015)," who first unveiled this enthralling connection. This unanticipated relationship has intrigued and bemused the academic community, much like a magician performing a sleight of hand that leaves the audience both confounded and captivated.

Building upon the quirky findings of "Jones (2018)," our study corroborates the robustness of the association between regional energy consumption patterns and criminal behavior, providing empirical evidence to support the offbeat yet compelling hypothesis proposed in the literature. The hitherto obscure relationship between motor vehicle thefts in Tennessee and gasoline pumped in Belgium has come into sharper focus, much like a sudden burst of clarity amidst a convoluted plotline.

As alluded to in the literature review, one cannot help but draw parallels between this enigmatic correlation and the unconventional insights offered by works of fiction, such as "The Da Vinci Code" and "The Curious Incident of the Dog in the Night-Time." Like a cryptic message deciphered from ancient scrolls, our statistical analysis has shed light on the mysterious bond between two ostensibly unrelated variables, infusing the scholarly discourse with a sense of intrigue and a touch of whimsy.

The substantial correlation coefficient of 0.9406226 observed in our study lends support to the notion of a highly positive linear association between motor vehicle thefts in Tennessee and the volume of gasoline pumped in Belgium, akin to the harmonious synchrony of a well-conducted orchestra. The coefficient of determination (r-squared) of 0.8847708 further reinforces the robustness of this connection, leaving a modest 11.53% of variability to the realm of the unknown, much like the lingering suspense in a mystery novel that tantalizingly invites further exploration.

In light of the statistically significant p-value below the threshold of 0.01, our findings dismiss the possibility of this intriguing correlation being a mere product of chance. Rather, this serendipitous discovery beckons for deeper investigation, cascading a sense of scholarly wonder akin to stumbling upon an unexpected revelation. With a nod to the whimsical detours and curious expeditions recounted in the literature review, our study underscores the captivating and unorthodox nature of research, where every peculiar correlation holds the potential to unravel an engrossing tale.

In essence, our research lends empirical credence to the offbeat yet fascinating connection between motor vehicle thefts in Tennessee and gasoline pumped in Belgium, evoking a spirit of scholarly curiosity and a nod to the enigmatic unpredictability of statistical relationships. Thus, our findings beckon forth an insatiable sense of intellectual adventure, akin to embarking on an enthralling journey of discovery through the enchanted realms of scientific inquiry.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Motor vehicle thefts in Tennessee and Gasoline pumped in Belgium. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Pump It Up: Exploring the Surprising Relationship Between Motor Vehicle Thefts in Tennessee and Gasoline Pumped in Belgium

[[ABSTRACT]]
Recent research has uncovered an unexpected connection between motor vehicle thefts in the state of Tennessee and the amount of gasoline pumped in Belgium. Drawing upon data from the FBI Criminal Justice Information Services and the Energy Information Administration, our study analyzes the correlation between these seemingly disparate phenomena. After crunching the numbers, we discovered a remarkably high correlation coefficient of 0.9406226 and a p-value less than 0.01, encompassing the time span from 1985 to 2022. This intriguing finding challenges conventional wisdom and has potential ramifications for both the field of criminal justice and energy economics. While the mechanisms underlying this relationship remain elusive, our study provides a quirky yet thought-provoking entryway into the quirky world of statistical analysis.

[[INTRDUCTION]]
In the realm of academic research, it is not uncommon to stumble upon unexpected and seemingly illogical associations between disparate variables. Such peculiar connections can often challenge conventional wisdom and lead to exhilarating eureka moments that spark intellectual curiosity. One such unlikely but undeniably intriguing relationship has emerged from our investigation into the correlation between motor vehicle thefts in Tennessee and the amount of gasoline pumped in Belgium. This unlikely duo has captivated our attention and propelled us into the whimsical world of statistical analysis, where the quirky and the thought-provoking often intermingle.
At first glance, the connection between motor vehicle thefts in Tennessee and the volume of gasoline pumped in Belgium appears nothing short of absurd. However, as any seasoned researcher knows, the world of statistics is rife with surprises and anomalies, much like a box of chocolates: you never know what you're going to get.
Our investigation was inspired by the growing recognition that statistical analysis can often yield unexpected and fascinating insights, much like finding a hidden treasure trove in a cluttered attic. The unfurling of this research journey began with the collection of data from the FBI Criminal Justice Information Services and the Energy Information Administration, which provided the necessary raw material to unearth the intriguing connection between these seemingly unrelated phenomena.
And so, armed with an insatiable quest for knowledge and armed with statistical tools that rival the precision of a Swiss watch, we embarked on a curious voyage to unravel the enigmatic correlation between motor vehicle thefts in Tennessee and the amount of gasoline pumped in Belgium. Little did we know that this journey would lead us into the underbelly of statistical analysis, where every data point holds the potential to surprise and excite, much like a mystery novel that promises unexpected twists at every turn.
In the following sections of this paper, we shall unveil the captivating findings of our analysis, which not only challenge conventional wisdom but also open a portal to a world where statistical curiosities abound like mushrooms after a spring rain. So, fasten your seatbelts and prepare to journey with us into the peculiar yet captivating landscape of statistical analysis, where the unexpected is often waiting to be discovered.

[[RESULTS]]
The results of our offbeat investigation revealed a remarkably strong correlation between motor vehicle thefts in Tennessee and the quantity of gasoline pumped in Belgium. Over the time period from 1985 to 2022, our statistical analysis unearthed a correlation coefficient of 0.9406226, a coefficient of determination (r-squared) of 0.8847708, and a p-value less than 0.01. This unexpected correlation is depicted in Figure 1, a scatterplot illustrating the striking relationship between these seemingly unrelated variables.
The robust correlation coefficient of 0.9406226 suggests a highly positive linear association between the number of motor vehicle thefts in Tennessee and the volume of gasoline pumped in Belgium. The coefficient of determination (r-squared) of 0.8847708 indicates that a substantial 88.47% of the variability in motor vehicle thefts in Tennessee can be explained by the quantity of gasoline pumped in Belgium, leaving a mere 11.53% to be attributed to other factors, much like a compelling mystery plot where most of the clues lead to a clear conclusion with just a few loose ends hanging about.
Moreover, the p-value falling below the threshold of 0.01 indicates that the observed correlation is statistically significant, thereby dismissing the possibility that this intriguing connection is merely a fluke. It's as if this improbable statistical relationship knocked on the door of conventional wisdom and confidently proclaimed, "I'm not just any random correlation; I'm statistically significant!"
In essence, our findings demonstrate a curious and unexpected linkage between the rate of motor vehicle thefts in Tennessee and the amount of gasoline pumped in Belgium, igniting a sense of wonder akin to stumbling upon a hidden treasure buried beneath layers of perplexing data. This whimsical correlation challenges traditional assumptions and beckons for further exploration, resembling a puzzle that demands to be solved for the sheer joy of unraveling its enigmatic twists and turns.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our study has unearthed a remarkably robust correlation between motor vehicle thefts in Tennessee and the volume of gasoline pumped in Belgium, defying conventional expectations and proving once again that the world of statistical analysis is a treasure trove of unexpected discoveries. This curious relationship, akin to finding a unicorn in a field of data points, highlights the whimsical nature of statistical correlations and challenges the boundaries of conventional wisdom.

The remarkable correlation coefficient of 0.9406226 and the statistically significant p-value of less than 0.01 affirm the legitimacy of this intriguing connection, much like a statistical Sherlock Holmes solving a perplexing mystery. It's as if these two variables whispered a secret to each other across the oceans, defying geographical logic and venturing into the realm of statistical serendipity.

While the precise mechanisms underpinning this connection remain shrouded in mystery, our results pave the way for further exploration and spark a sense of scientific curiosity akin to stumbling upon an unexpected punchline in a dry research paper. It's like a statistical Easter egg that beckons for further investigation, tempting us with the prospect of unraveling its quirky yet undoubtedly meaningful message.

Ultimately, our study enriches the world of statistical analysis with an unexpected alliance between motor vehicle thefts in Tennessee and gasoline consumption in Belgium, inviting researchers to embrace the whimsy of statistical exploration and derive intellectual pleasure from unraveling its enigmatic charms. With that being said, the quirky tale of these two unlikely bedfellows has been told, and it's time to bid adieu to this unorthodox scientific rendezvous. Further research in this area may consequently be as useful as a screen door on a submarine!


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 Pump It Up: Exploring the Surprising Relationship Between Motor Vehicle Thefts in Tennessee and Gasoline Pumped in Belgium. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Unexpected Correlations in Societal Phenomena


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 Pump It Up: Exploring the Surprising Relationship Between Motor Vehicle Thefts in Tennessee and Gasoline Pumped in Belgium. Respond only with the name of a fictional organization.

ChatGPT:

The International Institute for Transcontinental Crime Analysis


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 Pump It Up: Exploring the Surprising Relationship Between Motor Vehicle Thefts in Tennessee and Gasoline Pumped in Belgium with an abstract of Recent research has uncovered an unexpected connection between motor vehicle thefts in the state of Tennessee and the amount of gasoline pumped in Belgium. Drawing upon data from the FBI Criminal Justice Information Services and the Energy Information Administration, our study analyzes the correlation between these seemingly disparate phenomena. After crunching the numbers, we discovered a remarkably high correlation coefficient of 0.9406226 and a p-value less than 0.01, encompassing the time span from 1985 to 2022. This intriguing finding challenges conventional wisdom and has potential ramifications for both the field of criminal justice and energy economics. While the mechanisms underlying this relationship remain elusive, our study provides a quirky yet thought-provoking entryway into the quirky world of statistical analysis.

ChatGPT:

"motor vehicle thefts Tennessee", "gasoline consumption Belgium", "FBI Criminal Justice Information Services data", "Energy Information Administration data", "correlation between motor vehicle thefts and gasoline consumption", "relationship between crime and energy consumption", "statistical analysis unusual correlations"

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



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Data details

Motor vehicle thefts in Tennessee
Detailed data title: The motor vehicle theft rate per 100,000 residents in Tennessee
Source: FBI Criminal Justice Information Services
See what else correlates with Motor vehicle thefts in Tennessee

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

Correlation r = 0.9406226 (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 = 0.8847708 (Coefficient of determination)
This means 88.5% of the change in the one variable (i.e., Gasoline pumped in Belgium) is predictable based on the change in the other (i.e., Motor vehicle thefts in Tennessee) over the 38 years from 1985 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.8E-18. 0.0000000000000000017947658833
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.94 in 1.8E-16% of random cases. Said differently, if you correlated 557,175,734,899,373,056 random variables You don't actually need 557 quadrillion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 37 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 37 because we have two variables measured over a period of 38 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.

[ 0.89, 0.97 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!


All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
19851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007200820092010201120122013201420152016201720182019202020212022
Motor vehicle thefts in Tennessee (Motor Vehicle Theft rate)485.2543.6566.9542.8532.9571.5613.6575.9591560.3648.5647.1628.6517.4460.6483.9491.7458.4452.9420.4423.6375.1352.8309238.5233.3221200.8183.2193.2197.6229.2276.8304.9282.4306.4297.5362.3
Gasoline pumped in Belgium (Million Barrels/Day)57.928862.969965.682267.740466.602763.131563.383667.027365.720665.728865.586363.237758.690458.156255.427451.830650.608248.317848.734244.606641.479538.58936.490433.385232.443830.290429.221928.412628.435629.860331.660334.024635.904140.167144.994537.683145.961651.874




Why this works

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




Try it yourself

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

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

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

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

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

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

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

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

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


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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([485.2,543.6,566.9,542.8,532.9,571.5,613.6,575.9,591,560.3,648.5,647.1,628.6,517.4,460.6,483.9,491.7,458.4,452.9,420.4,423.6,375.1,352.8,309,238.5,233.3,221,200.8,183.2,193.2,197.6,229.2,276.8,304.9,282.4,306.4,297.5,362.3,])
array_2 = np.array([57.9288,62.9699,65.6822,67.7404,66.6027,63.1315,63.3836,67.0273,65.7206,65.7288,65.5863,63.2377,58.6904,58.1562,55.4274,51.8306,50.6082,48.3178,48.7342,44.6066,41.4795,38.589,36.4904,33.3852,32.4438,30.2904,29.2219,28.4126,28.4356,29.8603,31.6603,34.0246,35.9041,40.1671,44.9945,37.6831,45.9616,51.874,])
array_1_name = "Motor vehicle thefts in Tennessee"
array_2_name = "Gasoline pumped in Belgium"

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

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



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

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

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

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Correlation ID: 3976 · Black Variable ID: 20163 · Red Variable ID: 24190
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