Spurious correlation #2,339 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Josef and the second variable is Air pollution in Oklahoma City. The chart goes from 1980 to 2022, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Josef and the second variable is Air pollution in Oklahoma City. The chart goes from 1980 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

Less people wanting to "Joe-sef" around means less carpooling and more "Oklahom-alone." With fewer Joes in the car, there's a "re-duction" in vehicle emissions. It's a "fresh air" perspective on the impact of names on air quality!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image that visually depicts an Oklahoma City street scene where individual cars are seen outnumbering carpooling vehicles. The decrease in popularity of the first name Josef has led to this shift in transportation habits. Show the city street with individual cars bustling about, emitting more traffic. However, amidst this, capture a noticeable reduction in vehicle emissions, symbolized by fresher, cleaner air permeating the atmosphere. The contrast between the increased traffic and the clearer air should be the central focus of the image. 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: Popularity of the first name Josef and Air pollution in Oklahoma City. 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: inspired by bauhaus Hyper-realistic Minimalism An image that looks like it is a scene from a Pixar movie A Discovery magazine cover image
ChatGPT: A Discovery magazine cover image

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 Popularity of the first name Josef and Air pollution in Oklahoma City, in the following situation: Less people wanting to "Joe-sef" around means less carpooling and more "Oklahom-alone." With fewer Joes in the car, there's a "re-duction" in vehicle emissions. It's a "fresh air" perspective on the impact of names on air quality!. Keep the description simple.
ChatGPT: In a bustling Oklahoma City street, fewer people are carpooling due to the decreasing popularity of the first name Josef. As a result, there are more individual cars on the road, contributing to air pollution. However, amidst the commute, there is a noticeable reduction in vehicle emissions, leading to fresher air in the city.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A Discovery magazine cover image ] and depicting this scene: In a bustling Oklahoma City street, fewer people are carpooling due to the decreasing popularity of the first name Josef. As a result, there are more individual cars on the road, contributing to air pollution. However, amidst the commute, there is a noticeable reduction in vehicle emissions, leading to fresher air in the city. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that visually depicts an Oklahoma City street scene where individual cars are seen outnumbering carpooling vehicles. The decrease in popularity of the first name Josef has led to this shift in transportation habits. Show the city street with individual cars bustling about, emitting more traffic. However, amidst this, capture a noticeable reduction in vehicle emissions, symbolized by fresher, cleaner air permeating the atmosphere. The contrast between the increased traffic and the clearer air should be the central focus of the image.

*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 humerus 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 Popularity of the first name Josef caused Air pollution in Oklahoma City to decrease. Include a lot of puns.

AI academic paper

(Because p < 0.01)

Blowin' in the Josef: The Curious Case of Air Pollution and Name Popularity in Oklahoma City

The Journal of Ecological Quirks and Curiosities

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 Popularity of the first name Josef and Air pollution in Oklahoma City. Make lots of jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name 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]]
Blowin' in the Josef: The Curious Case of Air Pollution and Name Popularity in Oklahoma City

[[ABSTRACT]]
In recent years, research has highlighted the surprising and often bizarre relationships between seemingly unrelated phenomena. In this study, we delve into the whimsical world of name popularity and air pollution, focusing specifically on the intriguing case of the first name Josef and air quality in Oklahoma City. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, we conducted a rigorous analysis spanning over four decades from 1980 to 2022.

Our findings revealed a remarkably robust correlation between the popularity of the first name Josef and air pollution in the bustling metropolis of Oklahoma City. With a correlation coefficient of 0.6331067 and a p-value of less than 0.01, the evidence for this seemingly inexplicable relationship is not one to be easily dismissed. Although any definitive causal mechanism eluded our grasp, our research opens the door to a realm of speculation and amusement, as we ponder the whims of fate and the enigmatic forces shaping the world around us.

Through this playful exploration, we add a splash of lightheartedness to the oftentimes stoic landscape of academic inquiry, encouraging fellow researchers to embrace the delightful surprises that await when delving into unconventional connections.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Ladies and gentlemen, esteemed colleagues, and those who stumbled upon this paper thinking it was about the great works of Franz Kafka, welcome to a quirky journey through the unexpected realms of name popularity and air pollution. In the halls of academia, where discussions usually revolve around weighty matters, we dare to take a light-hearted detour into the realm of the peculiar and whimsical.
While the idea of examining the link between the popularity of the name Josef and air pollution in Oklahoma City may seem as outlandish as a cat in a spacesuit, our intrepid research team embarked on this delightful adventure with the hope of uncovering unanticipated connections and injecting a dose of laughter into the sober world of scholarly inquiry.
Now, you might be wondering why Josef, of all names, and why in the heartland of America. But fear not, dear readers, for as we delve into this arcane quest, you will soon realize that the world of academia is not all charts and equations; sometimes, it's about finding a little mirth in the most unexpected places.
So, sit back, and let us guide you through our journey into the peculiar pairing of name popularity and air quality, where the winds of chance blow through the data like a playful zephyr, leaving us grinning at the mysterious synchronicities that unfold before our eyes.
As we present our findings, sprinkle in some wit, and maybe throw in a pun or two, we invite you to join us on this light-hearted trek through the whimsy and wonder of academic exploration. After all, who knew that a name and the air we breathe could tango in such an intriguing fashion?

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The startling connection between the popularity of the first name Josef and air pollution in Oklahoma City has fueled a surge of interest in the scholarly community, prompting a peculiar blend of fascination and bewilderment. This research endeavor, audacious in its whimsicality, has evoked a range of responses, from intrigued eyebrow raises to outright guffaws. By examining the existing literature on both name popularity trends and air pollution dynamics, we aim to shed light on the unexpected convergence of these seemingly disparate realms.

Smith et al. (2015) provide a comprehensive analysis of name popularity trends over the past century, offering insights into the societal shift in naming preferences and the cultural factors influencing the rise and fall of particular names. Doe and Jones (2018) delve into the psychological underpinnings of name perception, exploring the nuanced associations and biases that individuals may hold toward certain names.

However, as we saunter further down the winding path of academia, let us diverge from the well-trodden trail and venture into the whimsical world of non-fiction and fiction books that may or may not be tangentially related to our curious inquiry.

In "The Namesake" by Jhumpa Lahiri, we are beckoned into a narrative brimming with names, identities, and the intricate interplay of culture and individuality. While the focus may not be on the popularity of Josef specifically, the exploration of names and their significance may provide a touch of inspiration amid our quest for quirky connections.

Turning to fiction, the classic tale of "Great Expectations" by Charles Dickens invites us to contemplate the weight of names and the destiny they carry. Although Pip and Miss Havisham may not grace the streets of Oklahoma City, their fictional footsteps may nudge our musings toward the whimsical nature of nomenclature and its elusive ties to atmospheric phenomena.

In our ardent pursuit of relevant stimuli, we must not overlook the potential guidance offered by television shows. "The Good Place" presents an intriguing melange of philosophical conundrums and unexpected plot twists. While the show's plot may appear light years away from the ponderings of name popularity and air pollution, its penchant for quirky connections and delightful absurdity serves as a peculiar beacon in our sea of academic inquiry.

On the less fantastical side, "Breaking Bad" propels us into the realm of chemistry and human ambition, offering a tangential reminder of the curious cocktail of elements intertwining in our study. As Walter White's schemes unfurl amidst the New Mexican desert, we find a parallel to the entangled web of factors dictating name popularity and air quality trends.

With this whimsical foray into the literary and televised realms, we invite our fellow academics to join us in embracing the levity and unexpected connections that infuse the corridors of scholarly exploration. After all, who can resist the magnetic pull of a good pun or an unexpectedly relevant fiction reference?

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 Popularity of the first name Josef and Air pollution in Oklahoma City. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and Environmental Protection Agency . You used data from 1980 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]]
Blowin' in the Josef: The Curious Case of Air Pollution and Name Popularity in Oklahoma City

[[ABSTRACT]]
In recent years, research has highlighted the surprising and often bizarre relationships between seemingly unrelated phenomena. In this study, we delve into the whimsical world of name popularity and air pollution, focusing specifically on the intriguing case of the first name Josef and air quality in Oklahoma City. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, we conducted a rigorous analysis spanning over four decades from 1980 to 2022.

Our findings revealed a remarkably robust correlation between the popularity of the first name Josef and air pollution in the bustling metropolis of Oklahoma City. With a correlation coefficient of 0.6331067 and a p-value of less than 0.01, the evidence for this seemingly inexplicable relationship is not one to be easily dismissed. Although any definitive causal mechanism eluded our grasp, our research opens the door to a realm of speculation and amusement, as we ponder the whims of fate and the enigmatic forces shaping the world around us.

Through this playful exploration, we add a splash of lightheartedness to the oftentimes stoic landscape of academic inquiry, encouraging fellow researchers to embrace the delightful surprises that await when delving into unconventional connections.

[[INTRODUCTION]]
Ladies and gentlemen, esteemed colleagues, and those who stumbled upon this paper thinking it was about the great works of Franz Kafka, welcome to a quirky journey through the unexpected realms of name popularity and air pollution. In the halls of academia, where discussions usually revolve around weighty matters, we dare to take a light-hearted detour into the realm of the peculiar and whimsical.
While the idea of examining the link between the popularity of the name Josef and air pollution in Oklahoma City may seem as outlandish as a cat in a spacesuit, our intrepid research team embarked on this delightful adventure with the hope of uncovering unanticipated connections and injecting a dose of laughter into the sober world of scholarly inquiry.
Now, you might be wondering why Josef, of all names, and why in the heartland of America. But fear not, dear readers, for as we delve into this arcane quest, you will soon realize that the world of academia is not all charts and equations; sometimes, it's about finding a little mirth in the most unexpected places.
So, sit back, and let us guide you through our journey into the peculiar pairing of name popularity and air quality, where the winds of chance blow through the data like a playful zephyr, leaving us grinning at the mysterious synchronicities that unfold before our eyes.
As we present our findings, sprinkle in some wit, and maybe throw in a pun or two, we invite you to join us on this light-hearted trek through the whimsy and wonder of academic exploration. After all, who knew that a name and the air we breathe could tango in such an intriguing fashion?

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

Preparation for this offbeat odyssey into the entwined realms of nomenclature and pollution began with the arduous task of data collection. We scoured the vast expanses of the internet, navigating through the virtual jungles of the US Social Security Administration and the Environmental Protection Agency. Armed with determination and copious amounts of coffee, our team set out to gather information spanning the years 1980 to 2022, like intrepid explorers charting uncharted territory.

The first phase involved extracting records of the popularity of the first name Josef from the Social Security Administration database. After sifting through an abundance of names, we diligently compiled the frequency of occurrences for each year with Josef's illustrious presence. We were on a quest for Josef, and Josef alone, amidst a sea of monikers, akin to searching for a single sock in a dryer filled with socks of all shapes and colors.

Simultaneously, our intrepid researchers sought out data on air pollution levels in the captivating city of Oklahoma. We tapped into the rich reservoir of environmental data provided by the EPA, decoding the intricate web of air quality indices and pollutant concentrations. It was a digital ballet of sorts, gracefully navigating through datasets and spreadsheets like a dancer pirouetting through the shimmering pixels of information.

With our trusty treasure trove of data in hand, we summoned the statistical titans of analysis to unfurl their might. Armed with the venerable companions of correlation coefficients, p-values, and regression analyses, we sought to uncover the enigmatic relationship between Josef's popularity and the nebulous tendrils of air pollution in Oklahoma City.

The correlation analysis, akin to a celestial dance between two celestial bodies, unveiled the striking relationship between the ebb and flow of Josef's fame and the atmospheric intricacies of air pollution in Oklahoma City. The statistical machinery whirred and clanked like a whimsical contraption, yielding a correlation coefficient of 0.6331067 and a p-value that elicited bewilderment with its diminutive stature, standing at less than 0.01.

Furthermore, our team embraced the enchanting allure of time series analyses, tracing the undulating waves of Josef's renown alongside the undulating tides of air pollution. As the data points waltzed across the timeline, we marveled at the synchronous cadences and curious coalescences, akin to witnessing a choreographed performance in the twinkling expanse of data visualizations.

In our quest for awakening mirth and wonder in the domain of scholarly pursuit, we employed a hint of playful speculation, daring to ponder the whims of fate and the delightful caprices governing this unlikely liaison. Delving into the inexplicable depths of this correlation, we teased out threads of lighthearted inquiry, reminding the academic community that even in the solemn halls of research, there exists ample room for amusement and curiosity.

Thus, with gaiety and rigor entwined, we embarked on this charming investigation, unearthing a mystifying alignment between a name and the very air that envelops us. In the tradition of academic discourse, we beckon our fellow scholars to join us in celebrating the serendipitous surprises that await those who dare to venture beyond the beaten paths of conventional inquiry.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Popularity of the first name Josef and Air pollution in Oklahoma City. Make lots of jokes, goofy observations, and puns.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Blowin' in the Josef: The Curious Case of Air Pollution and Name Popularity in Oklahoma City

[[ABSTRACT]]
In recent years, research has highlighted the surprising and often bizarre relationships between seemingly unrelated phenomena. In this study, we delve into the whimsical world of name popularity and air pollution, focusing specifically on the intriguing case of the first name Josef and air quality in Oklahoma City. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, we conducted a rigorous analysis spanning over four decades from 1980 to 2022.

Our findings revealed a remarkably robust correlation between the popularity of the first name Josef and air pollution in the bustling metropolis of Oklahoma City. With a correlation coefficient of 0.6331067 and a p-value of less than 0.01, the evidence for this seemingly inexplicable relationship is not one to be easily dismissed. Although any definitive causal mechanism eluded our grasp, our research opens the door to a realm of speculation and amusement, as we ponder the whims of fate and the enigmatic forces shaping the world around us.

Through this playful exploration, we add a splash of lightheartedness to the oftentimes stoic landscape of academic inquiry, encouraging fellow researchers to embrace the delightful surprises that await when delving into unconventional connections.

[[LITERATURE REVIEW]]
The startling connection between the popularity of the first name Josef and air pollution in Oklahoma City has fueled a surge of interest in the scholarly community, prompting a peculiar blend of fascination and bewilderment. This research endeavor, audacious in its whimsicality, has evoked a range of responses, from intrigued eyebrow raises to outright guffaws. By examining the existing literature on both name popularity trends and air pollution dynamics, we aim to shed light on the unexpected convergence of these seemingly disparate realms.
Smith et al. (2015) provide a comprehensive analysis of name popularity trends over the past century, offering insights into the societal shift in naming preferences and the cultural factors influencing the rise and fall of particular names. Doe and Jones (2018) delve into the psychological underpinnings of name perception, exploring the nuanced associations and biases that individuals may hold toward certain names.
However, as we saunter further down the winding path of academia, let us diverge from the well-trodden trail and venture into the whimsical world of non-fiction and fiction books that may or may not be tangentially related to our curious inquiry.
In "The Namesake" by Jhumpa Lahiri, we are beckoned into a narrative brimming with names, identities, and the intricate interplay of culture and individuality. While the focus may not be on the popularity of Josef specifically, the exploration of names and their significance may provide a touch of inspiration amid our quest for quirky connections.
Turning to fiction, the classic tale of "Great Expectations" by Charles Dickens invites us to contemplate the weight of names and the destiny they carry. Although Pip and Miss Havisham may not grace the streets of Oklahoma City, their fictional footsteps may nudge our musings toward the whimsical nature of nomenclature and its elusive ties to atmospheric phenomena.
In our ardent pursuit of relevant stimuli, we must not overlook the potential guidance offered by television shows. "The Good Place" presents an intriguing melange of philosophical conundrums and unexpected plot twists. While the show's plot may appear light years away from the ponderings of name popularity and air pollution, its penchant for quirky connections and delightful absurdity serves as a peculiar beacon in our sea of academic inquiry.
On the less fantastical side, "Breaking Bad" propels us into the realm of chemistry and human ambition, offering a tangential reminder of the curious cocktail of elements intertwining in our study. As Walter White's schemes unfurl amidst the New Mexican desert, we find a parallel to the entangled web of factors dictating name popularity and air quality trends.
With this whimsical foray into the literary and televised realms, we invite our fellow academics to join us in embracing the levity and unexpected connections that infuse the corridors of scholarly exploration. After all, who can resist the magnetic pull of a good pun or an unexpectedly relevant fiction reference?

[[RESULTS]]
The crux of our analysis lies in the examination of the relationship between the popularity of the first name Josef and air pollution levels in the vibrant city of Oklahoma. Upon scrutinizing the data spanning from 1980 to 2022, we unearthed a correlation coefficient of 0.6331067, illuminating a surprisingly robust statistical association between these seemingly unrelated variables.
With an r-squared value of 0.4008241, we could explain 40% of the variation in air pollution levels in Oklahoma City by the popularity of the name Josef. Now, that's a substantially higher percentage than we expected when we started down this peculiar path. It seems Josef has been stirring up more than just your average baby name debates!
Moreover, our findings come with a p-value < 0.01, indicating that the likelihood of observing such a strong relationship between the two variables by chance is about as rare as discovering a four-leaf clover while strolling through a polluted field.
Fig. 1, which we have artfully designated as the "Blowin' in the Josef" scatterplot, clearly illustrates the impressive correlation between the popularity of the name Josef and air pollution in Oklahoma City. While we wish we could claim artistic credit for the figure, alas, our talents are limited to data analysis and enthusiastic wordplay.
These results astonish and tickle the academic fancy, prompting us to consider whether the winds of fate carry more than just whispers and gusts - they might also carry the echoes of a name!
In conclusion, our research paints a compelling picture of the mysterious interplay between the popularity of a name and the quality of the air we breathe. With this unorthodox discovery, we urge our academic compatriots to entertain the unexpected and revel in the quirks that make our scholarly pursuits a delightfully waggish endeavor.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our study has uncovered a correlation between the popularity of the first name Josef and air pollution in Oklahoma City, leaving us both astounded and amused. The robust statistical association between these seemingly unrelated variables suggests that Josef's influence extends beyond mere nomenclature, venturing into the realm of atmospheric mischief.

Our findings align with the existing literature, where Smith et al. (2015) and Doe and Jones (2018) laid the groundwork for understanding societal naming trends and the psychological nuances associated with names. Though our study may have commenced as an exercise in whimsy, the evidence for a tangible connection between Josef and air pollution imparts a sense of gravity to our lighthearted odyssey.

As we gaze upon the "Blowin' in the Josef" scatterplot, we ponder the enigmatic forces at play. While we set out on this peculiar path in pursuit of levity, the strength of this correlation cannot be overlooked. It seems that Josef's name has been more than just a casual moniker; it has been an unwitting protagonist in the narrative of Oklahoma City's atmospheric composition.

The r-squared value of 0.4008241 imparts a sense of legitimacy to our findings, indicating that 40% of the variation in air pollution levels in Oklahoma City can be explained by Josef's popularity. This substantial explanatory power underscores the significance of our discovery, prompting us to reflect on the unassuming influence of a name.

The elusive causal mechanism behind this correlation eludes us, much like a mischievous breeze slipping through our fingers. However, our results warrant consideration and spark a whimsical curiosity regarding the unseen threads connecting human naming whims and environmental phenomena.

In the grand tapestry of academic inquiry, our study stands as a playful reminder of the surprising connections that await amidst the rigors of research. Our objective, should we dare say, transcends the mere search for causal relationships; it ventures into the delightfully unexpected realm of "Josef"-ying conventions and breathing life into unconventional associations.

Our exploration into the realm of name popularity and air pollution may evoke a chuckle or two, but it also invites fellow academics to embrace the peculiar assemblage of scholarship and amusement. After all, who can resist the magnetic pull of a good pun or an unexpectedly relevant fiction reference – much like Josef's inexplicable allure in the atmospheric expanse of Oklahoma City?

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 Popularity of the first name Josef and Air pollution in Oklahoma City. Make lots of jokes, goofy observations, and puns.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Blowin' in the Josef: The Curious Case of Air Pollution and Name Popularity in Oklahoma City

[[ABSTRACT]]
In recent years, research has highlighted the surprising and often bizarre relationships between seemingly unrelated phenomena. In this study, we delve into the whimsical world of name popularity and air pollution, focusing specifically on the intriguing case of the first name Josef and air quality in Oklahoma City. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, we conducted a rigorous analysis spanning over four decades from 1980 to 2022.

Our findings revealed a remarkably robust correlation between the popularity of the first name Josef and air pollution in the bustling metropolis of Oklahoma City. With a correlation coefficient of 0.6331067 and a p-value of less than 0.01, the evidence for this seemingly inexplicable relationship is not one to be easily dismissed. Although any definitive causal mechanism eluded our grasp, our research opens the door to a realm of speculation and amusement, as we ponder the whims of fate and the enigmatic forces shaping the world around us.

Through this playful exploration, we add a splash of lightheartedness to the oftentimes stoic landscape of academic inquiry, encouraging fellow researchers to embrace the delightful surprises that await when delving into unconventional connections.

[[INTRDUCTION]]
Ladies and gentlemen, esteemed colleagues, and those who stumbled upon this paper thinking it was about the great works of Franz Kafka, welcome to a quirky journey through the unexpected realms of name popularity and air pollution. In the halls of academia, where discussions usually revolve around weighty matters, we dare to take a light-hearted detour into the realm of the peculiar and whimsical.
While the idea of examining the link between the popularity of the name Josef and air pollution in Oklahoma City may seem as outlandish as a cat in a spacesuit, our intrepid research team embarked on this delightful adventure with the hope of uncovering unanticipated connections and injecting a dose of laughter into the sober world of scholarly inquiry.
Now, you might be wondering why Josef, of all names, and why in the heartland of America. But fear not, dear readers, for as we delve into this arcane quest, you will soon realize that the world of academia is not all charts and equations; sometimes, it's about finding a little mirth in the most unexpected places.
So, sit back, and let us guide you through our journey into the peculiar pairing of name popularity and air quality, where the winds of chance blow through the data like a playful zephyr, leaving us grinning at the mysterious synchronicities that unfold before our eyes.
As we present our findings, sprinkle in some wit, and maybe throw in a pun or two, we invite you to join us on this light-hearted trek through the whimsy and wonder of academic exploration. After all, who knew that a name and the air we breathe could tango in such an intriguing fashion?

[[RESULTS]]
The crux of our analysis lies in the examination of the relationship between the popularity of the first name Josef and air pollution levels in the vibrant city of Oklahoma. Upon scrutinizing the data spanning from 1980 to 2022, we unearthed a correlation coefficient of 0.6331067, illuminating a surprisingly robust statistical association between these seemingly unrelated variables.
With an r-squared value of 0.4008241, we could explain 40% of the variation in air pollution levels in Oklahoma City by the popularity of the name Josef. Now, that's a substantially higher percentage than we expected when we started down this peculiar path. It seems Josef has been stirring up more than just your average baby name debates!
Moreover, our findings come with a p-value < 0.01, indicating that the likelihood of observing such a strong relationship between the two variables by chance is about as rare as discovering a four-leaf clover while strolling through a polluted field.
Fig. 1, which we have artfully designated as the "Blowin' in the Josef" scatterplot, clearly illustrates the impressive correlation between the popularity of the name Josef and air pollution in Oklahoma City. While we wish we could claim artistic credit for the figure, alas, our talents are limited to data analysis and enthusiastic wordplay.
These results astonish and tickle the academic fancy, prompting us to consider whether the winds of fate carry more than just whispers and gusts - they might also carry the echoes of a name!
In conclusion, our research paints a compelling picture of the mysterious interplay between the popularity of a name and the quality of the air we breathe. With this unorthodox discovery, we urge our academic compatriots to entertain the unexpected and revel in the quirks that make our scholarly pursuits a delightfully waggish endeavor.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In the whimsical world of academic inquiry, our research has blown in with surprising gusts of correlation between the popularity of the name Josef and air pollution in Oklahoma City. We've uncovered a statistical relationship so robust, it practically has us reaching for oxygen tanks to process the unexpected coherence between these seemingly unrelated variables. Perhaps the name Josef brings with it a gust of mischievous air pollution - or maybe it's just a peculiar play of fate that has left us marveling at the whims of statistical splendor.

As we leave this lighthearted footprint in the hallowed halls of academia, we encourage our esteemed colleagues to savor this peculiar dance of data and take a moment to revel in the unexpected quirks that make scholarly pursuits a delightfully waggish affair. For in the endless expanse of academic exploration, we mustn't overlook the jocular interplay of the enigmatic forces shaping our world - be it through a name or the air we breathe.

And with that, our research team firmly asserts that no more research is needed in this zany realm of whimsy and air. We've uncovered enough delightful surprises to last a lifetime, and now it's time to sit back, soak in the playful correlations, and enjoy a breath of fresh, pun-filled air.

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 Blowin' in the Josef: The Curious Case of Air Pollution and Name Popularity in Oklahoma City. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Ecological Quirks and Curiosities

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 Blowin' in the Josef: The Curious Case of Air Pollution and Name Popularity in Oklahoma City. Respond only with the name of a fictional organization.

ChatGPT:

Southwestern Environmental Research Association

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 Blowin' in the Josef: The Curious Case of Air Pollution and Name Popularity in Oklahoma City with an abstract of In recent years, research has highlighted the surprising and often bizarre relationships between seemingly unrelated phenomena. In this study, we delve into the whimsical world of name popularity and air pollution, focusing specifically on the intriguing case of the first name Josef and air quality in Oklahoma City. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, we conducted a rigorous analysis spanning over four decades from 1980 to 2022.
Our findings revealed a remarkably robust correlation between the popularity of the first name Josef and air pollution in the bustling metropolis of Oklahoma City. With a correlation coefficient of 0.6331067 and a p-value of less than 0.01, the evidence for this seemingly inexplicable relationship is not one to be easily dismissed. Although any definitive causal mechanism eluded our grasp, our research opens the door to a realm of speculation and amusement, as we ponder the whims of fate and the enigmatic forces shaping the world around us.
Through this playful exploration, we add a splash of lightheartedness to the oftentimes stoic landscape of academic inquiry, encouraging fellow researchers to embrace the delightful surprises that await when delving into unconventional connections.

ChatGPT:

Josef name popularity, air pollution, Oklahoma City, correlation, US Social Security Administration data, Environmental Protection Agency data, name trends, air quality trends, whimsical relationships, surprising correlations, unusual connections, academic research, speculation, causation, correlation coefficient, p-value, lighthearted academic inquiry

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

Random correlation

Discover a new correlation

View all correlations

View all research papers

Report an error

Data details

Popularity of the first name Josef
Detailed data title: Babies of all sexes born in the US named Josef
Source: US Social Security Administration
See what else correlates with Popularity of the first name Josef

Air pollution in Oklahoma City
Detailed data title: Percentage of days with air quality at 'unhealthy for sensitive groups' or worse in Oklahoma City, OK
Source: Environmental Protection Agency
See what else correlates with Air pollution in Oklahoma City

Correlation r = 0.6331067 (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 = 0.4008241 (Coefficient of determination)
This means 40.1% of the change in the one variable (i.e., Air pollution in Oklahoma City) is predictable based on the change in the other (i.e., Popularity of the first name Josef) over the 43 years from 1980 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 5.2E-6.^Show 0.0000052152037014760730000000
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 0.63 in 0.00052% of random cases. Said differently, if you correlated 191,747 random variables^Note You don't actually need 191 thousand 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 42 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 42 because we have two variables measured over a period of 43 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.

[ 0.41, 0.78 ] 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.

	1980	1981	1982	1983	1984	1985	1986	1987	1988	1989	1990	1991	1992	1993	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Popularity of the first name Josef (Babies born)	151	131	149	130	170	172	159	164	177	156	165	154	163	170	179	168	175	183	211	220	198	211	195	188	185	218	191	164	157	125	129	137	95	108	113	91	92	81	83	80	66	71	57
Air pollution in Oklahoma City (Bad air quality days)	8.74317	8.21918	4.93151	9.31507	18.0328	9.31507	6.84932	12.6027	12.0219	7.94521	5.75342	6.84932	3.82514	3.83562	10.6849	12.3288	6.01093	6.84932	16.4384	9.0411	9.83607	10.6849	9.86301	8.49315	3.55191	9.0411	13.9726	2.73973	2.73224	4.38356	3.0137	12.0548	10.6557	2.19178	1.36986	0.547945	0.819672	1.91781	3.28767	0.547945	1.36612	2.73973	2.46575

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([151,131,149,130,170,172,159,164,177,156,165,154,163,170,179,168,175,183,211,220,198,211,195,188,185,218,191,164,157,125,129,137,95,108,113,91,92,81,83,80,66,71,57,])
array_2 = np.array([8.74317,8.21918,4.93151,9.31507,18.0328,9.31507,6.84932,12.6027,12.0219,7.94521,5.75342,6.84932,3.82514,3.83562,10.6849,12.3288,6.01093,6.84932,16.4384,9.0411,9.83607,10.6849,9.86301,8.49315,3.55191,9.0411,13.9726,2.73973,2.73224,4.38356,3.0137,12.0548,10.6557,2.19178,1.36986,0.547945,0.819672,1.91781,3.28767,0.547945,1.36612,2.73973,2.46575,])
array_1_name = "Popularity of the first name Josef"
array_2_name = "Air pollution in Oklahoma City"

# 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 Popularity of the first name Josef
Line chart for only Air pollution in Oklahoma City
AI-generated correlation image
The spurious research paper: Blowin' in the Josef: The Curious Case of Air Pollution and Name Popularity in Oklahoma City

View another random correlation

How fun was this correlation?

Thanks for shining a light on this correlation!

Correlation ID: 2339 · Black Variable ID: 3830 · Red Variable ID: 21001


Problem variable:
Issue:
Additional details: Optional
Confirm you are a human: