Spurious correlation #2,705 · 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 Alfonso and the second variable is Air pollution in Central City, Kentucky. The chart goes from 1980 to 2001, 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 Alfonso and the second variable is Air pollution in Central City, Kentucky. The chart goes from 1980 to 2001, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the number of Alfonso's grew, so did the demand for fresh air, leading to a campaign for cleaner skies. It seems like they were all about being Al-fresh and Al-clean, sparking a breath of fresh heir!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a busy street in Central City, Kentucky, crowded with people wearing shiny leather jackets. Show the distinct fashion trend and a hazy skyline in the background due to increased air pollution, which symbolizes the rise in popularity of the name Alfonso. Capture the essence of the era with a vintage aesthetic, displaying the bustling activity and the impact of the trend on the environment. 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 Alfonso and Air pollution in Central City, Kentucky. 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: Cutsy graphics Cyberpunk a meme a funny image you would see on reddit a funny image you would see on reddit
ChatGPT: a meme

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 Alfonso and Air pollution in Central City, Kentucky, in the following situation: Because as the name Alfonso gained popularity, more and more people started saying "Ayyy, Fonzie!" which in turn caused an increase in the number of leather jackets being worn. The excessive use of leather polish to keep those jackets looking slick led to a spike in air pollution in Central City, Kentucky. So next time you think about naming your baby Alfonso, just remember you might be contributing to some smoggy skies!. Keep the description simple.
ChatGPT: In Central City, Kentucky, the streets were bustling with people sporting leather jackets, with many calling out "Ayyy, Fonzie!" as the name Alfonso gained popularity. As the shiny jackets became a common sight, the air filled with the scent of leather polish, contributing to a spike in air pollution. The skies over the city grew hazy with smog, a consequence of the newfound popularity of the name Alfonso.

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 meme ] and depicting this scene: In Central City, Kentucky, the streets were bustling with people sporting leather jackets, with many calling out "Ayyy, Fonzie!" as the name Alfonso gained popularity. As the shiny jackets became a common sight, the air filled with the scent of leather polish, contributing to a spike in air pollution. The skies over the city grew hazy with smog, a consequence of the newfound popularity of the name Alfonso. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a busy street in Central City, Kentucky, crowded with people wearing shiny leather jackets. Show the distinct fashion trend and a hazy skyline in the background due to increased air pollution, which symbolizes the rise in popularity of the name Alfonso. Capture the essence of the era with a vintage aesthetic, displaying the bustling activity and the impact of the trend on the environment.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how increases in Popularity of the first name Alfonso negatively influenced Air pollution in Central City, Kentucky. Include one good pun.

AI academic paper

(Because p < 0.01)

The Peculiar Paradigm: The Perplexing Link Between the Popularity of the First Name Alfonso and Air Pollution in Central City, Kentucky

Journal of Quirky Social and Environmental Studies

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 Alfonso and Air pollution in Central City, Kentucky. 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 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]]
The Peculiar Paradigm: The Perplexing Link Between the Popularity of the First Name Alfonso and Air Pollution in Central City, Kentucky

[[ABSTRACT]]
This study examines the seemingly unlikely connection between the popularity of the first name Alfonso and air pollution levels in Central City, Kentucky. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, we set out to unravel this peculiar puzzle. Our findings revealed a striking correlation coefficient of -0.7999638 and a statistically significant p-value of < 0.01 for the years 1980 to 2001. We delved into the whimsical world of nomenclature and atmospheric composition to uncover this curious relationship, leaving us pondering whether the name Alfonso wields a mystical influence over air quality. It appears that the name Alfonso may not only carry historical significance but also atmospheric implications, provoking laughter and astonishment in equal measure among researchers. Our exploration prompts further investigation into the unexpected interconnectedness of seemingly unrelated factors, reminding us that the research world is full of surprises, much like discovering aerosol particles in a balloon factory.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The world of scientific inquiry is a wondrous and mysterious place, where researchers often find themselves delving into the most unexpected and entertaining of phenomena. In the realm of peculiar correlations, few discoveries rival the perplexing link between the popularity of the first name Alfonso and air pollution levels in Central City, Kentucky. While some may dismiss this peculiar pairing as mere happenstance, our study sought to disentangle the enigmatic relationship between nomenclature and atmospheric composition, much to the amusement and bemusement of the research community.
As we embarked on this whimsical research endeavor, we couldn't help but marvel at the sheer absurdity of our hypothesis. The very notion that the name Alfonso could exert any influence on air quality seemed like a punchline to a scientific joke. Nevertheless, armed with data from the US Social Security Administration and the Environmental Protection Agency, we set out on an expedition into the quirky terrain of name popularity and airborne particulate matter.
The very mention of the name Alfonso conjures up images of medieval nobility or perhaps a suave and debonair gentleman sauntering through the cobblestone streets of a European city. Little did we anticipate that this regal moniker might hold sway over the atmospheric whims of Central City, Kentucky. It's as though the winds of fate were carrying us into uncharted territory, akin to stumbling upon a mysterious alchemy lab while searching for the nearest coffee shop.
Our initial findings left us scratching our heads in astonishment. The correlation coefficient of -0.7999638 between the popularity of the name Alfonso and air pollution levels seemed to mock the very foundations of rational explanation. It was as if the statistical gods were playing an elaborate prank on our research endeavors, whispering in hushed tones, "Can you believe this?"
The statistical significance of the p-value, clocking in at less than < 0.01, only added to the grand theatrical production of our scholarly escapade. If there ever was a time for a drumroll and a hearty round of applause for unexpected findings, this was it.
In the hallowed halls of scientific inquiry, our discovery prompted a lively debate on whether the name Alfonso holds some sort of clandestine arcane power over the atmospheric makeup of Central City, Kentucky. It's as though we stumbled into a realm where the laws of causality frolic and play, leaving us mere mortals gasping in bewildered amusement.
As we peer into the peculiar paradigm that connects the first name Alfonso and air pollution, we invite fellow researchers to join us on this merry dance through the serendipitous realms of scholarly investigation. After all, in the grand theater of scientific exploration, even the most unlikely of correlations might just be waiting to steal the show.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
**[[LITERATURE REVIEW]]**

The enigmatic relationship between the popularity of the first name Alfonso and air pollution levels in Central City, Kentucky has sparked a gathering of scholarly exploration, not unlike a peculiar masquerade ball where the guests of honor are whimsy and wonderment. Our quest to unravel this enthralling mystery led us to peruse an eclectic array of sources, ranging from the conventional to the delightfully absurd.

In their seminal work, "The Correlation Chronicles: Unearthing Unlikely Associations," Smith and Doe expound upon the art of uncovering unexpected connections in the realm of sociological and environmental phenomena. Their insightful dissection of peculiar correlations serves as the scholarly compass guiding researchers through the uncharted territories of unconventional relationships, much like a treasure map leading to a chest filled with improbable findings.

Furthermore, Jones and Smith, in their magnum opus "Quantifying Quirks: Statistical Surprises and Singular Circumstances," delve into the whimsical world of statistical anomalies, where the improbable takes center stage and the ordinary scatters into laughter and disbelief. Their meticulous examination of statistical surprises lays the groundwork for embracing the peculiar puzzle of the Alfonso-air pollution paradox with both curiosity and levity.

Transitioning from the esoteric domains of scholarly literature, we can draw inspiration from non-fiction books that delve into the intriguing interplay of human culture and environmental influences. "The Air We Breathe: A Sociological Study of Inhaled Auras" by Dr. A. Q. A. Rice invites readers to contemplate the unseen influence of societal nomenclature on atmospheric composition, weaving a captivating narrative that tantalizes the mind and tickles the funny bone.

On the fictional front, "The Name Effect: A Tale of Mysterious Monikers" by E. Nigma combines the elements of intrigue, humor, and speculative intrigue, offering a whimsical exploration of the fantastical notion that names hold the power to shape the very air we breathe. Meanwhile, in the quirk-infused pages of "The Peculiar Portents of Pollutants," penned by the aptly named author I. M. A. Gination, readers are transported to a world where the improbable is a commonplace occurrence, blending whimsy with scholarly intrigue in a delightful amalgamation.

Now, dear reader, as we tiptoe further into the fantastical forest of literature, we must, for the sake of scholarly integrity, acknowledge that our pursuit of wisdom also traversed the most unexpected of terrains. In our quest to leave no stone unturned, we stumbled upon invaluable insights in the most unlikely of places, from the cryptic clues hidden within ancient hieroglyphics to the enigmatic wisdom encoded within the humble CVS receipts. Indeed, the pursuit of knowledge often dances with the absurd, as if scholarly truth hides behind the mundane facade of everyday life, waiting to be discovered amidst the checkout line banter.

In the ever-astonishing world of academic exploration, we find ourselves navigating through a landscape where the unlikely and the humorous converge, creating a whirlwind of mirth and enlightenment. As we sift through the kaleidoscope of literature, let us not forget that the pursuit of knowledge is often a delightful romp through unanticipated realms, where even the most whimsical of ideas might hold the key to unlocking the mysteries of the world around us.

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 Alfonso and Air pollution in Central City, Kentucky. 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 2001

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
The Peculiar Paradigm: The Perplexing Link Between the Popularity of the First Name Alfonso and Air Pollution in Central City, Kentucky

[[ABSTRACT]]
This study examines the seemingly unlikely connection between the popularity of the first name Alfonso and air pollution levels in Central City, Kentucky. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, we set out to unravel this peculiar puzzle. Our findings revealed a striking correlation coefficient of -0.7999638 and a statistically significant p-value of < 0.01 for the years 1980 to 2001. We delved into the whimsical world of nomenclature and atmospheric composition to uncover this curious relationship, leaving us pondering whether the name Alfonso wields a mystical influence over air quality. It appears that the name Alfonso may not only carry historical significance but also atmospheric implications, provoking laughter and astonishment in equal measure among researchers. Our exploration prompts further investigation into the unexpected interconnectedness of seemingly unrelated factors, reminding us that the research world is full of surprises, much like discovering aerosol particles in a balloon factory.

[[INTRODUCTION]]
The world of scientific inquiry is a wondrous and mysterious place, where researchers often find themselves delving into the most unexpected and entertaining of phenomena. In the realm of peculiar correlations, few discoveries rival the perplexing link between the popularity of the first name Alfonso and air pollution levels in Central City, Kentucky. While some may dismiss this peculiar pairing as mere happenstance, our study sought to disentangle the enigmatic relationship between nomenclature and atmospheric composition, much to the amusement and bemusement of the research community.
As we embarked on this whimsical research endeavor, we couldn't help but marvel at the sheer absurdity of our hypothesis. The very notion that the name Alfonso could exert any influence on air quality seemed like a punchline to a scientific joke. Nevertheless, armed with data from the US Social Security Administration and the Environmental Protection Agency, we set out on an expedition into the quirky terrain of name popularity and airborne particulate matter.
The very mention of the name Alfonso conjures up images of medieval nobility or perhaps a suave and debonair gentleman sauntering through the cobblestone streets of a European city. Little did we anticipate that this regal moniker might hold sway over the atmospheric whims of Central City, Kentucky. It's as though the winds of fate were carrying us into uncharted territory, akin to stumbling upon a mysterious alchemy lab while searching for the nearest coffee shop.
Our initial findings left us scratching our heads in astonishment. The correlation coefficient of -0.7999638 between the popularity of the name Alfonso and air pollution levels seemed to mock the very foundations of rational explanation. It was as if the statistical gods were playing an elaborate prank on our research endeavors, whispering in hushed tones, "Can you believe this?"
The statistical significance of the p-value, clocking in at less than < 0.01, only added to the grand theatrical production of our scholarly escapade. If there ever was a time for a drumroll and a hearty round of applause for unexpected findings, this was it.
In the hallowed halls of scientific inquiry, our discovery prompted a lively debate on whether the name Alfonso holds some sort of clandestine arcane power over the atmospheric makeup of Central City, Kentucky. It's as though we stumbled into a realm where the laws of causality frolic and play, leaving us mere mortals gasping in bewildered amusement.
As we peer into the peculiar paradigm that connects the first name Alfonso and air pollution, we invite fellow researchers to join us on this merry dance through the serendipitous realms of scholarly investigation. After all, in the grand theater of scientific exploration, even the most unlikely of correlations might just be waiting to steal the show.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To untangle the whimsical web of the link between the popularity of the first name Alfonso and air pollution levels in Central City, Kentucky, we employed a methodological approach that was as unconventional as the subject matter itself. Our research team embarked on a data-driven odyssey, utilizing sources such as the US Social Security Administration and the Environmental Protection Agency to capture the essence of this perplexing paradigm.

First, we delved into the annals of the US Social Security Administration's treasure trove of birth name data. We extracted historical records spanning the years 1980 to 2001 with meticulous care, ensuring that no Alfonso would be left behind in our analysis. With a fervent zeal typically reserved for unraveling mysteries of the cosmos, we combed through the data, leaving no Baby Alfonso unaccounted for in our quest for empirical insight.

In parallel, we turned our gaze towards the Environmental Protection Agency's arsenal of air quality measurements in Central City, Kentucky. We collected data on various pollutants, including particulate matter, nitrous oxides, and ozone, painting a vivid tapestry of the atmospheric intricacies that enveloped this charming locale. Our team operated under the assumption that the very air itself might hold clues to the mysterious dance between Alfonso and air pollution, akin to deciphering an ancient hieroglyphic message from a mischievous deity.

Armed with two disparate strands of data, we proceeded to conduct a ballet of statistical acrobatics. We calculated the popularity of the name Alfonso in each year and contrasted it with the levels of air pollutants, employing regression analyses, correlation coefficients, and enough mathematical juggling to rival the most daring circus act. Our analysis aimed to tease out any semblance of a meaningful relationship between Alfonso's allure and the atmospheric composition, lending an air of intrigue to our empirical escapade.

It should be noted that our approach, while rigorous and systematic, was not without its whimsical charm. As we waded through the datasets, we couldn't help but feel a kinship with intrepid explorers setting sail on uncharted waters, armed with nothing but a compass and a healthy dose of curiosity. The research process, much like a daring escapade into unexplored territories, was rife with surprises and the occasional bout of laughter at the unexpected twists and turns encountered along the way.

In conclusion, our methodology embraced the peculiarity of our subject matter, marrying the rigors of empirical analysis with the playful spirit of scholarly exploration. We invite fellow researchers to join us in this delightful dalliance through data, where the most improbable of connections might just unveil themselves, much like finding a hidden treasure map in a dusty old tome.

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

Please make up the results section of an academic research paper presenting the findings of the connection between Popularity of the first name Alfonso and Air pollution in Central City, Kentucky. 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 .

For the time period 1980 to 2001, you found a correlation -0.7999638, r-squared of 0.6399422, and p < 0.01.

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

Here is the title and abstract of the paper:
[[TITLE]]
The Peculiar Paradigm: The Perplexing Link Between the Popularity of the First Name Alfonso and Air Pollution in Central City, Kentucky

[[ABSTRACT]]
This study examines the seemingly unlikely connection between the popularity of the first name Alfonso and air pollution levels in Central City, Kentucky. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, we set out to unravel this peculiar puzzle. Our findings revealed a striking correlation coefficient of -0.7999638 and a statistically significant p-value of < 0.01 for the years 1980 to 2001. We delved into the whimsical world of nomenclature and atmospheric composition to uncover this curious relationship, leaving us pondering whether the name Alfonso wields a mystical influence over air quality. It appears that the name Alfonso may not only carry historical significance but also atmospheric implications, provoking laughter and astonishment in equal measure among researchers. Our exploration prompts further investigation into the unexpected interconnectedness of seemingly unrelated factors, reminding us that the research world is full of surprises, much like discovering aerosol particles in a balloon factory.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The world of scientific inquiry is a wondrous and mysterious place, where researchers often find themselves delving into the most unexpected and entertaining of phenomena. In the realm of peculiar correlations, few discoveries rival the perplexing link between the popularity of the first name Alfonso and air pollution levels in Central City, Kentucky. While some may dismiss this peculiar pairing as mere happenstance, our study sought to disentangle the enigmatic relationship between nomenclature and atmospheric composition, much to the amusement and bemusement of the research community.
As we embarked on this whimsical research endeavor, we couldn't help but marvel at the sheer absurdity of our hypothesis. The very notion that the name Alfonso could exert any influence on air quality seemed like a punchline to a scientific joke. Nevertheless, armed with data from the US Social Security Administration and the Environmental Protection Agency, we set out on an expedition into the quirky terrain of name popularity and airborne particulate matter.
The very mention of the name Alfonso conjures up images of medieval nobility or perhaps a suave and debonair gentleman sauntering through the cobblestone streets of a European city. Little did we anticipate that this regal moniker might hold sway over the atmospheric whims of Central City, Kentucky. It's as though the winds of fate were carrying us into uncharted territory, akin to stumbling upon a mysterious alchemy lab while searching for the nearest coffee shop.
Our initial findings left us scratching our heads in astonishment. The correlation coefficient of -0.7999638 between the popularity of the name Alfonso and air pollution levels seemed to mock the very foundations of rational explanation. It was as if the statistical gods were playing an elaborate prank on our research endeavors, whispering in hushed tones, "Can you believe this?"
The statistical significance of the p-value, clocking in at less than < 0.01, only added to the grand theatrical production of our scholarly escapade. If there ever was a time for a drumroll and a hearty round of applause for unexpected findings, this was it.
In the hallowed halls of scientific inquiry, our discovery prompted a lively debate on whether the name Alfonso holds some sort of clandestine arcane power over the atmospheric makeup of Central City, Kentucky. It's as though we stumbled into a realm where the laws of causality frolic and play, leaving us mere mortals gasping in bewildered amusement.
As we peer into the peculiar paradigm that connects the first name Alfonso and air pollution, we invite fellow researchers to join us on this merry dance through the serendipitous realms of scholarly investigation. After all, in the grand theater of scientific exploration, even the most unlikely of correlations might just be waiting to steal the show.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

Our foray into the delightful realm of correlations and curious coincidences has yielded some truly remarkable results. The correlation coefficient of -0.7999638 between the popularity of the name Alfonso and air pollution levels in Central City, Kentucky from 1980 to 2001 left us both flabbergasted and amused in equal measure. This substantial negative correlation signifies that as the popularity of the name Alfonso increased, air pollution levels tended to decrease, painting a whimsical picture of nomenclature influencing atmospheric composition.

The r-squared value of 0.6399422 further strengthens the case for this truly peculiar relationship. This indicates that a substantial proportion of the variability in air pollution levels in Central City, Kentucky can be explained by the popularity of the name Alfonso. It's almost as if the name Alfonso whispered to the particles in the air, compelling them to dance in a more orderly and less polluting manner.

The statistical significance of the p-value (< 0.01) graced our findings with an air of grandeur, as if the research gods themselves had bestowed their blessing upon this whimsical connection. This signaled to the scientific community that the correlation we uncovered is not merely a fluke, but a peculiar and significant revelation worthy of further investigation.

Figure 1, our dear scatterplot, eloquently captures the essence of this astonishing correlation. It splendidly showcases the inverse relationship between the popularity of the name Alfonso and air pollution levels, as if the very data points were playfully waltzing across the plot, whispering sweet scientific nothings into the ears of astounded onlookers.

In conclusion, our study unfurled a tapestry of unexpectedly interconnected factors, with the name Alfonso emerging as an unlikely protagonist in the whimsical saga of air pollution levels in Central City, Kentucky. We cannot help but marvel at the capricious ways of research, where the most unexpected and delightful discoveries await those brave enough to embark on scholarly escapades. As we bid adieu to this peculiar paradigm, we invite fellow researchers to revel in the lighthearted dance of scholarly investigation, where even the most seemingly unrelated variables may yet share a whimsical and mystical bond.

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 Alfonso and Air pollution in Central City, Kentucky. 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]]
The Peculiar Paradigm: The Perplexing Link Between the Popularity of the First Name Alfonso and Air Pollution in Central City, Kentucky

[[ABSTRACT]]
This study examines the seemingly unlikely connection between the popularity of the first name Alfonso and air pollution levels in Central City, Kentucky. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, we set out to unravel this peculiar puzzle. Our findings revealed a striking correlation coefficient of -0.7999638 and a statistically significant p-value of < 0.01 for the years 1980 to 2001. We delved into the whimsical world of nomenclature and atmospheric composition to uncover this curious relationship, leaving us pondering whether the name Alfonso wields a mystical influence over air quality. It appears that the name Alfonso may not only carry historical significance but also atmospheric implications, provoking laughter and astonishment in equal measure among researchers. Our exploration prompts further investigation into the unexpected interconnectedness of seemingly unrelated factors, reminding us that the research world is full of surprises, much like discovering aerosol particles in a balloon factory.

[[LITERATURE REVIEW]]
The enigmatic relationship between the popularity of the first name Alfonso and air pollution levels in Central City, Kentucky has sparked a gathering of scholarly exploration, not unlike a peculiar masquerade ball where the guests of honor are whimsy and wonderment. Our quest to unravel this enthralling mystery led us to peruse an eclectic array of sources, ranging from the conventional to the delightfully absurd.
In their seminal work, "The Correlation Chronicles: Unearthing Unlikely Associations," Smith and Doe expound upon the art of uncovering unexpected connections in the realm of sociological and environmental phenomena. Their insightful dissection of peculiar correlations serves as the scholarly compass guiding researchers through the uncharted territories of unconventional relationships, much like a treasure map leading to a chest filled with improbable findings.
Furthermore, Jones and Smith, in their magnum opus "Quantifying Quirks: Statistical Surprises and Singular Circumstances," delve into the whimsical world of statistical anomalies, where the improbable takes center stage and the ordinary scatters into laughter and disbelief. Their meticulous examination of statistical surprises lays the groundwork for embracing the peculiar puzzle of the Alfonso-air pollution paradox with both curiosity and levity.
Transitioning from the esoteric domains of scholarly literature, we can draw inspiration from non-fiction books that delve into the intriguing interplay of human culture and environmental influences. "The Air We Breathe: A Sociological Study of Inhaled Auras" by Dr. A. Q. A. Rice invites readers to contemplate the unseen influence of societal nomenclature on atmospheric composition, weaving a captivating narrative that tantalizes the mind and tickles the funny bone.
On the fictional front, "The Name Effect: A Tale of Mysterious Monikers" by E. Nigma combines the elements of intrigue, humor, and speculative intrigue, offering a whimsical exploration of the fantastical notion that names hold the power to shape the very air we breathe. Meanwhile, in the quirk-infused pages of "The Peculiar Portents of Pollutants," penned by the aptly named author I. M. A. Gination, readers are transported to a world where the improbable is a commonplace occurrence, blending whimsy with scholarly intrigue in a delightful amalgamation.
Now, dear reader, as we tiptoe further into the fantastical forest of literature, we must, for the sake of scholarly integrity, acknowledge that our pursuit of wisdom also traversed the most unexpected of terrains. In our quest to leave no stone unturned, we stumbled upon invaluable insights in the most unlikely of places, from the cryptic clues hidden within ancient hieroglyphics to the enigmatic wisdom encoded within the humble CVS receipts. Indeed, the pursuit of knowledge often dances with the absurd, as if scholarly truth hides behind the mundane facade of everyday life, waiting to be discovered amidst the checkout line banter.
In the ever-astonishing world of academic exploration, we find ourselves navigating through a landscape where the unlikely and the humorous converge, creating a whirlwind of mirth and enlightenment. As we sift through the kaleidoscope of literature, let us not forget that the pursuit of knowledge is often a delightful romp through unanticipated realms, where even the most whimsical of ideas might hold the key to unlocking the mysteries of the world around us.

[[RESULTS]]
Our foray into the delightful realm of correlations and curious coincidences has yielded some truly remarkable results. The correlation coefficient of -0.7999638 between the popularity of the name Alfonso and air pollution levels in Central City, Kentucky from 1980 to 2001 left us both flabbergasted and amused in equal measure. This substantial negative correlation signifies that as the popularity of the name Alfonso increased, air pollution levels tended to decrease, painting a whimsical picture of nomenclature influencing atmospheric composition.
The r-squared value of 0.6399422 further strengthens the case for this truly peculiar relationship. This indicates that a substantial proportion of the variability in air pollution levels in Central City, Kentucky can be explained by the popularity of the name Alfonso. It's almost as if the name Alfonso whispered to the particles in the air, compelling them to dance in a more orderly and less polluting manner.
The statistical significance of the p-value (< 0.01) graced our findings with an air of grandeur, as if the research gods themselves had bestowed their blessing upon this whimsical connection. This signaled to the scientific community that the correlation we uncovered is not merely a fluke, but a peculiar and significant revelation worthy of further investigation.
Figure 1, our dear scatterplot, eloquently captures the essence of this astonishing correlation. It splendidly showcases the inverse relationship between the popularity of the name Alfonso and air pollution levels, as if the very data points were playfully waltzing across the plot, whispering sweet scientific nothings into the ears of astounded onlookers.
In conclusion, our study unfurled a tapestry of unexpectedly interconnected factors, with the name Alfonso emerging as an unlikely protagonist in the whimsical saga of air pollution levels in Central City, Kentucky. We cannot help but marvel at the capricious ways of research, where the most unexpected and delightful discoveries await those brave enough to embark on scholarly escapades. As we bid adieu to this peculiar paradigm, we invite fellow researchers to revel in the lighthearted dance of scholarly investigation, where even the most seemingly unrelated variables may yet share a whimsical and mystical bond.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The connection between the popularity of the first name Alfonso and air pollution levels in Central City, Kentucky has emerged as a most delightful and unexpected phenomenon, akin to stumbling upon a circus of statistical acrobatics and whimsical wonder. Our findings, much like a grand spectacle of scholarly marvel, not only corroborate but also elevate the beguiling quirkiness unearthed in prior research endeavors.

In the Correlation Chronicles penned by the erudite Smith and Doe, our study resonates with the spirit of uncovering unlikely associations, akin to discovering an impromptu dance party between statistical wizardry and whimsical wordplay. Our results bolster their poignant musings, painting a picture where the enigmatic charm of the name Alfonso seemingly waltzes hand in hand with atmospheric serendipity, much like an endearing pas de deux performed by variables of unexpected resonance.

Moreover, the effervescent work of Jones and Smith in Quantifying Quirks stands testament to the beguiling nature of statistical anomalies, a realm where the unimaginable takes center stage and the ordinary whimsically waltzes into laughter and disbelief. Our study mirrors their ethos, casting the spotlight on the unlikely spectacle of the Alfonso-air pollution paradox, leaving researchers and readers alike teetering on the edge of scholarly amusement and astute contemplation, not unlike a juggling act where statistical significance and whimsical revelations perform a delightful balancing act.

Our findings, embodied by the ineffable correlation coefficient of -0.7999638 and the statistically significant p-value of < 0.01, stand not as outliers of scholarly mirth but as paragons of statistical gravitas infused with an irresistible whimsy. It is as if the cosmic tides of scholarly truth themselves conspired to unveil this curious connection in all its capricious glory, akin to stumbling upon a cache of laughter amidst the hallowed halls of scientific solemnity.

As we bid adieu to this bewildering ballet of scholarly wit and statistical serendipity, we invite fellow researchers to partake in the spirited revelry of exploration, where even the most unsuspecting variables may yet tango in a lighthearted symphony of unforeseen significance. Let us embrace the scholarly tango, where the enchanting allure of research continuously beckons us beyond the staid confines of convention, into a world profuse with sprightly connections and delightful anomalies, much like a whimsical masquerade ball of statistical surprises and scholarly enlightenment.

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 Alfonso and Air pollution in Central City, Kentucky. 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]]
The Peculiar Paradigm: The Perplexing Link Between the Popularity of the First Name Alfonso and Air Pollution in Central City, Kentucky

[[ABSTRACT]]
This study examines the seemingly unlikely connection between the popularity of the first name Alfonso and air pollution levels in Central City, Kentucky. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, we set out to unravel this peculiar puzzle. Our findings revealed a striking correlation coefficient of -0.7999638 and a statistically significant p-value of < 0.01 for the years 1980 to 2001. We delved into the whimsical world of nomenclature and atmospheric composition to uncover this curious relationship, leaving us pondering whether the name Alfonso wields a mystical influence over air quality. It appears that the name Alfonso may not only carry historical significance but also atmospheric implications, provoking laughter and astonishment in equal measure among researchers. Our exploration prompts further investigation into the unexpected interconnectedness of seemingly unrelated factors, reminding us that the research world is full of surprises, much like discovering aerosol particles in a balloon factory.

[[INTRDUCTION]]
The world of scientific inquiry is a wondrous and mysterious place, where researchers often find themselves delving into the most unexpected and entertaining of phenomena. In the realm of peculiar correlations, few discoveries rival the perplexing link between the popularity of the first name Alfonso and air pollution levels in Central City, Kentucky. While some may dismiss this peculiar pairing as mere happenstance, our study sought to disentangle the enigmatic relationship between nomenclature and atmospheric composition, much to the amusement and bemusement of the research community.
As we embarked on this whimsical research endeavor, we couldn't help but marvel at the sheer absurdity of our hypothesis. The very notion that the name Alfonso could exert any influence on air quality seemed like a punchline to a scientific joke. Nevertheless, armed with data from the US Social Security Administration and the Environmental Protection Agency, we set out on an expedition into the quirky terrain of name popularity and airborne particulate matter.
The very mention of the name Alfonso conjures up images of medieval nobility or perhaps a suave and debonair gentleman sauntering through the cobblestone streets of a European city. Little did we anticipate that this regal moniker might hold sway over the atmospheric whims of Central City, Kentucky. It's as though the winds of fate were carrying us into uncharted territory, akin to stumbling upon a mysterious alchemy lab while searching for the nearest coffee shop.
Our initial findings left us scratching our heads in astonishment. The correlation coefficient of -0.7999638 between the popularity of the name Alfonso and air pollution levels seemed to mock the very foundations of rational explanation. It was as if the statistical gods were playing an elaborate prank on our research endeavors, whispering in hushed tones, "Can you believe this?"
The statistical significance of the p-value, clocking in at less than < 0.01, only added to the grand theatrical production of our scholarly escapade. If there ever was a time for a drumroll and a hearty round of applause for unexpected findings, this was it.
In the hallowed halls of scientific inquiry, our discovery prompted a lively debate on whether the name Alfonso holds some sort of clandestine arcane power over the atmospheric makeup of Central City, Kentucky. It's as though we stumbled into a realm where the laws of causality frolic and play, leaving us mere mortals gasping in bewildered amusement.
As we peer into the peculiar paradigm that connects the first name Alfonso and air pollution, we invite fellow researchers to join us on this merry dance through the serendipitous realms of scholarly investigation. After all, in the grand theater of scientific exploration, even the most unlikely of correlations might just be waiting to steal the show.

[[RESULTS]]
Our foray into the delightful realm of correlations and curious coincidences has yielded some truly remarkable results. The correlation coefficient of -0.7999638 between the popularity of the name Alfonso and air pollution levels in Central City, Kentucky from 1980 to 2001 left us both flabbergasted and amused in equal measure. This substantial negative correlation signifies that as the popularity of the name Alfonso increased, air pollution levels tended to decrease, painting a whimsical picture of nomenclature influencing atmospheric composition.
The r-squared value of 0.6399422 further strengthens the case for this truly peculiar relationship. This indicates that a substantial proportion of the variability in air pollution levels in Central City, Kentucky can be explained by the popularity of the name Alfonso. It's almost as if the name Alfonso whispered to the particles in the air, compelling them to dance in a more orderly and less polluting manner.
The statistical significance of the p-value (< 0.01) graced our findings with an air of grandeur, as if the research gods themselves had bestowed their blessing upon this whimsical connection. This signaled to the scientific community that the correlation we uncovered is not merely a fluke, but a peculiar and significant revelation worthy of further investigation.
Figure 1, our dear scatterplot, eloquently captures the essence of this astonishing correlation. It splendidly showcases the inverse relationship between the popularity of the name Alfonso and air pollution levels, as if the very data points were playfully waltzing across the plot, whispering sweet scientific nothings into the ears of astounded onlookers.
In conclusion, our study unfurled a tapestry of unexpectedly interconnected factors, with the name Alfonso emerging as an unlikely protagonist in the whimsical saga of air pollution levels in Central City, Kentucky. We cannot help but marvel at the capricious ways of research, where the most unexpected and delightful discoveries await those brave enough to embark on scholarly escapades. As we bid adieu to this peculiar paradigm, we invite fellow researchers to revel in the lighthearted dance of scholarly investigation, where even the most seemingly unrelated variables may yet share a whimsical and mystical bond.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In the illustrious annals of scholarly inquiry, our expedition into the improbable intersection of Alfonso and air pollution in Central City, Kentucky has left us in a state of both befuddled amusement and scholarly awe. Our research not only revealed a substantial negative correlation coefficient, but it also unearthed a peculiarly significant p-value that would make even the most stoic researcher crack a wry smile. The idea that the name Alfonso could wield such an unexpected influence over air quality is as confounding as finding a hidden treasure map in a bowl of alphabet soup.

As we reflect on our findings, it becomes increasingly evident that the whimsical world of research is a place where the absurd and the extraordinary converge with surprising regularity. Just as we thought we had seen it all, the name Alfonso prances into the scientific spotlight, donning a cloak of mystery and whimsy that could rival the most enigmatic of Shakespearean characters.

Figure 1, our beloved scatterplot, stands as a testament to the surreal nature of our discoveries, immortalizing the dance of data points in a manner reminiscent of a whimsical carnival parade. It's as if the particles in the air whispered ancient secrets to each other, orchestrating a ballet of atmospheric intrigue that would confound even the most seasoned meteorologist.

While we bid farewell to this peculiar paradigm with a chuckle and a bemused shake of the head, we cannot help but marvel at the uncharted territories of research that continue to beckon us with their unexpected and delightful surprises. As we close the chapter on this whimsical saga, we dare say that no further research is needed in this area. After all, who could possibly fathom the need for further investigation when the name Alfonso has already woven such a delightfully kooky tale of atmospheric antics and statistical capers?

In the grand theater of scientific exploration, sometimes the most peculiar correlations simply demand a standing ovation and a resounding chorus of "Bravo!"

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited The Peculiar Paradigm: The Perplexing Link Between the Popularity of the First Name Alfonso and Air Pollution in Central City, Kentucky. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Quirky Social and Environmental Studies

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited The Peculiar Paradigm: The Perplexing Link Between the Popularity of the First Name Alfonso and Air Pollution in Central City, Kentucky. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Curious Connections in Social Sciences

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled The Peculiar Paradigm: The Perplexing Link Between the Popularity of the First Name Alfonso and Air Pollution in Central City, Kentucky with an abstract of This study examines the seemingly unlikely connection between the popularity of the first name Alfonso and air pollution levels in Central City, Kentucky. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, we set out to unravel this peculiar puzzle. Our findings revealed a striking correlation coefficient of -0.7999638 and a statistically significant p-value of < 0.01 for the years 1980 to 2001. We delved into the whimsical world of nomenclature and atmospheric composition to uncover this curious relationship, leaving us pondering whether the name Alfonso wields a mystical influence over air quality. It appears that the name Alfonso may not only carry historical significance but also atmospheric implications, provoking laughter and astonishment in equal measure among researchers. Our exploration prompts further investigation into the unexpected interconnectedness of seemingly unrelated factors, reminding us that the research world is full of surprises, much like discovering aerosol particles in a balloon factory.

ChatGPT:

Alfonso first name popularity, air pollution Central City Kentucky, US Social Security Administration data, Environmental Protection Agency air pollution data, correlation coefficient, statistical significance, nomenclature influence on atmospheric composition

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

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Data details

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

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

Correlation r = -0.7999638 (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 = 0.6399422 (Coefficient of determination)
This means 64% of the change in the one variable (i.e., Air pollution in Central City, Kentucky) is predictable based on the change in the other (i.e., Popularity of the first name Alfonso) over the 22 years from 1980 through 2001.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 7.9E-6.^Show 0.0000078727118819851900000000
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 -0.8 in 0.00079% of random cases. Said differently, if you correlated 127,021 random variables^Note You don't actually need 127 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 21 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 21 because we have two variables measured over a period of 22 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.

[ -0.91, -0.57 ] 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
Popularity of the first name Alfonso (Babies born)	453	460	434	420	399	458	494	444	501	496	537	579	532	544	529	494	508	506	485	490	476	428
Air pollution in Central City, Kentucky (Bad air quality days)	6.53409	6.80473	5.64263	15.0289	13.9037	1.0582	0	14	0	0	0	0	0	0	0	0	0	0	0	0	0	12.2449

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.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.
Inverted Y-axis: I inverted the Y-axis on the chart above so that the lines would move together. This is visually pleasing, but not at all intuitive. Below is a line graph that does not invert the Y-axis.

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([453,460,434,420,399,458,494,444,501,496,537,579,532,544,529,494,508,506,485,490,476,428,])
array_2 = np.array([6.53409,6.80473,5.64263,15.0289,13.9037,1.0582,0,14,0,0,0,0,0,0,0,0,0,0,0,0,0,12.2449,])
array_1_name = "Popularity of the first name Alfonso"
array_2_name = "Air pollution in Central City, Kentucky"

# 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 Alfonso
Line chart for only Air pollution in Central City, Kentucky
AI-generated correlation image
The spurious research paper: The Peculiar Paradigm: The Perplexing Link Between the Popularity of the First Name Alfonso and Air Pollution in Central City, Kentucky

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Correlation ID: 2705 · Black Variable ID: 2882 · Red Variable ID: 20426


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