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Spurious correlation #1,572 · 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 Elyse and the second variable is Air pollution in Bremerton, Washington.  The chart goes from 1987 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As the popularity of the name Elyse waned, so did the Elyse-mobiles on the roads. You see, these Elyse-mobiles were not just vehicles, they were smog machines in disguise, Elyse-ly contributing to the pollution problem. With fewer Elyses revving their engines, the air in Bremerton finally had a breath of fresh air, all thanks to a de-cline in Elyse.

Model: dalle-3
Prompt: Prompt: Generate an image showing a TIME magazine cover featuring a bustling city park in Bremerton, Washington. Families are seen enjoying a sunny day, while a group of kids playfully kicks around a soccer ball. The name "Elyse" is called out by friends. In the distance, the sky appears hazy with smog, indicating less than ideal air quality. The image should capture the vibrancy of the park and the presence of smog in the sky. 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 Elyse and Less than ideal air quality in Bremerton, Washington. 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: High-tech A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s Art nouveau A TIME magazine cover image Cutsy art illustration
ChatGPT: A TIME 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 Elyse and Less than ideal air quality in Bremerton, Washington together. Keep the description simple.
ChatGPT: In Bremerton, Washington, a bustling city park is filled with families enjoying a sunny day. Among them, a group of kids playfully kicks around a soccer ball, and the name "Elyse" can be heard being called out by friends. However, in the distance, the sky appears hazy with smog, indicating less than ideal air quality.

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 TIME magazine cover image ] and depicting this scene: In Bremerton, Washington, a bustling city park is filled with families enjoying a sunny day. Among them, a group of kids playfully kicks around a soccer ball, and the name "Elyse" can be heard being called out by friends. However, in the distance, the sky appears hazy with smog, indicating less than ideal air quality. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image showing a TIME magazine cover featuring a bustling city park in Bremerton, Washington. Families are seen enjoying a sunny day, while a group of kids playfully kicks around a soccer ball. The name "Elyse" is called out by friends. In the distance, the sky appears hazy with smog, indicating less than ideal air quality. The image should capture the vibrancy of the park and the presence of smog in the sky.

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

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

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how a decrease in Popularity of the first name Elyse caused Air pollution in Bremerton, Washington to decrease. Include one good pun.

AI academic paper

(Because p < 0.01)
The Elyse Effect: A Whimsical Exploration of the Correlation Between the Popularity of the Name Elyse and Air Quality in Bremerton, Washington

The Journal of Quirky Connections

Jan 2024

Reminder: This paper is AI-generated. Not real!
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 write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Popularity of the first name Elyse and Air pollution in Bremerton, Washington. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title seem clever.

Your research team used data from US Social Security Administration and Environmental Protection Agency to assess this nagging question. You found a correlation coefficient of 0.6950273 and p < 0.01 for 1987 to 2022.

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

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
"The Elyse Effect: A Whimsical Exploration of the Correlation Between the Popularity of the Name Elyse and Air Quality in Bremerton, Washington"

[[ABSTRACT]]
This paper delves into the intriguing relationship between the prevalence of the first name Elyse and atmospheric pollution levels in the picturesque town of Bremerton, Washington. Utilizing extensive data from the US Social Security Administration and the Environmental Protection Agency, our research team embarked on a whimsical quest to unravel this peculiar conundrum. Through meticulous analysis, we uncovered a striking correlation coefficient of 0.6950273 with a significance level of p < 0.01, spanning the years 1987 to 2022. Our findings not only shed light on the enigmatic connection between nomenclature and environmental quality, but also illuminate the whimsical nature of statistical exploration.


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 introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the introduction section of an academic research paper presenting the findings of the connection between Popularity of the first name Elyse and Air pollution in Bremerton, Washington. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Here is the title and abstract of the paper:
[[TITLE]]
"The Elyse Effect: A Whimsical Exploration of the Correlation Between the Popularity of the Name Elyse and Air Quality in Bremerton, Washington"

[[ABSTRACT]]
This paper delves into the intriguing relationship between the prevalence of the first name Elyse and atmospheric pollution levels in the picturesque town of Bremerton, Washington. Utilizing extensive data from the US Social Security Administration and the Environmental Protection Agency, our research team embarked on a whimsical quest to unravel this peculiar conundrum. Through meticulous analysis, we uncovered a striking correlation coefficient of 0.6950273 with a significance level of p < 0.01, spanning the years 1987 to 2022. Our findings not only shed light on the enigmatic connection between nomenclature and environmental quality, but also illuminate the whimsical nature of statistical exploration.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
Introduction

The relationship between human nomenclature and environmental factors has long been a topic of curiosity, invoking the whimsical musings of researchers and the general public alike. One such peculiar association that has piqued our interest is the correlation between the prevalence of the first name Elyse and the air quality in Bremerton, Washington. We embark on this endeavor with a blend of scientific rigor and childlike wonder, seeking to unravel the mysterious "Elyse Effect" that seems to hover over the atmospheric landscape of this charming town.

Bremerton, located in the scenic backdrop of the Puget Sound, is not only renowned for its naval history and picturesque surroundings but also for the enigmatic variations in air quality that have left researchers scratching their heads. Meanwhile, the name Elyse, with its melodic cadence and subtle charm, has steadily woven its way into the fabric of American nomenclature. It is against this backdrop of natural beauty and linguistic intrigue that our research takes root, poised to uncover the intricacies of this unlikely pairing.

While the notion of a correlation between a name and air pollution may initially prompt a whimsical chuckle, the empirical foundation of our investigation remains steadfast. Leveraging data from the US Social Security Administration, we meticulously traced the trajectory of the name Elyse across temporal bounds, encompassing the years 1987 to 2022. Simultaneously, the Environmental Protection Agency served as our stalwart ally, supplying comprehensive measures of air quality in the Bremerton region.

As we methodically delved into the abyss of data analysis, our initial amusement gradually gave way to a profound sense of curiosity and intrigue. The statistical tapestry that unfurled before us revealed a correlation coefficient of 0.6950273, accompanied by a significance level of p < 0.01, encapsulating the dance between Elyses and airborne particulate matter. This revelation not only lends credence to the notion of the "Elyse Effect" but also beckons us to ponder the whimsical nature of statistical exploration.

In this whimsical odyssey of research, we aspire to unearth the underlying mechanisms that underpin this improbable entwining of nomenclature and atmospheric composition. The implications of our findings extend beyond mere statistical jargon, transcending into the realm of wonder and curiosity that so often fuels scientific inquiry. Our scholarly pursuit is driven by the relentless quest to unravel the inexplicable, all while embracing the whimsy that threads through the fabric of our academic endeavors.

So, with a dash of statistical wizardry and a pinch of linguistic whimsy, we invite the reader to embark on this delightful expedition into the "Elyse Effect," where the esoteric dance of data and nomenclature awaits its fervent unraveling.


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 Elyse and Air pollution in Bremerton, Washington. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name some cartoons and childrens' shows that you watched that are related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
"The Elyse Effect: A Whimsical Exploration of the Correlation Between the Popularity of the Name Elyse and Air Quality in Bremerton, Washington"

[[ABSTRACT]]
This paper delves into the intriguing relationship between the prevalence of the first name Elyse and atmospheric pollution levels in the picturesque town of Bremerton, Washington. Utilizing extensive data from the US Social Security Administration and the Environmental Protection Agency, our research team embarked on a whimsical quest to unravel this peculiar conundrum. Through meticulous analysis, we uncovered a striking correlation coefficient of 0.6950273 with a significance level of p < 0.01, spanning the years 1987 to 2022. Our findings not only shed light on the enigmatic connection between nomenclature and environmental quality, but also illuminate the whimsical nature of statistical exploration.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Introduction
The relationship between human nomenclature and environmental factors has long been a topic of curiosity, invoking the whimsical musings of researchers and the general public alike. One such peculiar association that has piqued our interest is the correlation between the prevalence of the first name Elyse and the air quality in Bremerton, Washington. We embark on this endeavor with a blend of scientific rigor and childlike wonder, seeking to unravel the mysterious "Elyse Effect" that seems to hover over the atmospheric landscape of this charming town.
Bremerton, located in the scenic backdrop of the Puget Sound, is not only renowned for its naval history and picturesque surroundings but also for the enigmatic variations in air quality that have left researchers scratching their heads. Meanwhile, the name Elyse, with its melodic cadence and subtle charm, has steadily woven its way into the fabric of American nomenclature. It is against this backdrop of natural beauty and linguistic intrigue that our research takes root, poised to uncover the intricacies of this unlikely pairing.
While the notion of a correlation between a name and air pollution may initially prompt a whimsical chuckle, the empirical foundation of our investigation remains steadfast. Leveraging data from the US Social Security Administration, we meticulously traced the trajectory of the name Elyse across temporal bounds, encompassing the years 1987 to 2022. Simultaneously, the Environmental Protection Agency served as our stalwart ally, supplying comprehensive measures of air quality in the Bremerton region.
As we methodically delved into the abyss of data analysis, our initial amusement gradually gave way to a profound sense of curiosity and intrigue. The statistical tapestry that unfurled before us revealed a correlation coefficient of 0.6950273, accompanied by a significance level of p < 0.01, encapsulating the dance between Elyses and airborne particulate matter. This revelation not only lends credence to the notion of the "Elyse Effect" but also beckons us to ponder the whimsical nature of statistical exploration.
In this whimsical odyssey of research, we aspire to unearth the underlying mechanisms that underpin this improbable entwining of nomenclature and atmospheric composition. The implications of our findings extend beyond mere statistical jargon, transcending into the realm of wonder and curiosity that so often fuels scientific inquiry. Our scholarly pursuit is driven by the relentless quest to unravel the inexplicable, all while embracing the whimsy that threads through the fabric of our academic endeavors.
So, with a dash of statistical wizardry and a pinch of linguistic whimsy, we invite the reader to embark on this delightful expedition into the "Elyse Effect," where the esoteric dance of data and nomenclature awaits its fervent unraveling.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The existing body of literature concerning the correlation between personal nomenclature and environmental parameters forms a heterogeneous landscape, spanning from rigorous statistical analyses to fanciful conjectures. Smith et al. (2010) provide a comprehensive exploration of the impact of individual names on societal perceptions, laying the groundwork for our own whimsical investigation of the Elyse phenomenon. Drawing from a multidisciplinary approach, Doe and Jones (2015) offer a thorough examination of atmospheric pollutants and their effects on local communities, inadvertently setting the stage for the intersection of our peculiar foci.

In the realm of non-fiction works, "The Air We Breathe: Understanding Atmospheric Composition" by Clean Air Coalition delves into the intricate balance of gaseous constituents that swirl within our Earth's atmosphere, shedding light on the delightful quirks of air quality considerations. Additionally, "Names and Identities: A Linguistic Analysis" by Lexis Linguistics presents an erudite compilation of name-related studies, providing a scholarly backdrop for our whimsical juxtaposition of Elyses and airborne particles.

Turning to the world of fiction, the works of authors such as Gabriel Garcia Marquez, particularly "One Hundred Years of Solitude," beckon us to dance on the delicate tightrope between reality and whimsy, mirroring the intricate interplay between the ethereal nature of nomenclature and the tangible embrace of environmental factors. Similarly, the poignant satire of Douglas Adams in "The Hitchhiker's Guide to the Galaxy" encourages a sublimely whimsical lens through which to view our statistical foray into the enigmatic Elyse Effect.

In the domain of animated manifestations, the whimsical charm and environmental themes of "Captain Planet and the Planeteers" serendipitously resonate with our own research pursuits, encapsulating the meritorious balance between statistical analysis and anthropomorphic allegories. Moreover, the imaginative allure of "The Magic School Bus" provides a playful yet insightful backdrop to our scholarly journey, echoing the whimsical depths of scientific exploration as we unravel the cryptic ties between Elyses and air pollution.

As we wade through this delightful mélange of literature, it becomes evident that the intersection of nomenclature and environmental quality is not merely a statistical dalliance but also a whimsical expedition into the wondrous tapestry of human experience. With these diverse influences shaping our perspective, we embark on our own whimsical venture, prepared to mesh empirical rigor with a sprinkle of fantastical whimsy as we untangle the ethereal "Elyse Effect" in the atmospheric realm of Bremerton, Washington.


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 Elyse and Air pollution in Bremerton, Washington. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and Environmental Protection Agency . You used data from 1987 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]]
"The Elyse Effect: A Whimsical Exploration of the Correlation Between the Popularity of the Name Elyse and Air Quality in Bremerton, Washington"

[[ABSTRACT]]
This paper delves into the intriguing relationship between the prevalence of the first name Elyse and atmospheric pollution levels in the picturesque town of Bremerton, Washington. Utilizing extensive data from the US Social Security Administration and the Environmental Protection Agency, our research team embarked on a whimsical quest to unravel this peculiar conundrum. Through meticulous analysis, we uncovered a striking correlation coefficient of 0.6950273 with a significance level of p < 0.01, spanning the years 1987 to 2022. Our findings not only shed light on the enigmatic connection between nomenclature and environmental quality, but also illuminate the whimsical nature of statistical exploration.

[[INTRODUCTION]]
Introduction
The relationship between human nomenclature and environmental factors has long been a topic of curiosity, invoking the whimsical musings of researchers and the general public alike. One such peculiar association that has piqued our interest is the correlation between the prevalence of the first name Elyse and the air quality in Bremerton, Washington. We embark on this endeavor with a blend of scientific rigor and childlike wonder, seeking to unravel the mysterious "Elyse Effect" that seems to hover over the atmospheric landscape of this charming town.
Bremerton, located in the scenic backdrop of the Puget Sound, is not only renowned for its naval history and picturesque surroundings but also for the enigmatic variations in air quality that have left researchers scratching their heads. Meanwhile, the name Elyse, with its melodic cadence and subtle charm, has steadily woven its way into the fabric of American nomenclature. It is against this backdrop of natural beauty and linguistic intrigue that our research takes root, poised to uncover the intricacies of this unlikely pairing.
While the notion of a correlation between a name and air pollution may initially prompt a whimsical chuckle, the empirical foundation of our investigation remains steadfast. Leveraging data from the US Social Security Administration, we meticulously traced the trajectory of the name Elyse across temporal bounds, encompassing the years 1987 to 2022. Simultaneously, the Environmental Protection Agency served as our stalwart ally, supplying comprehensive measures of air quality in the Bremerton region.
As we methodically delved into the abyss of data analysis, our initial amusement gradually gave way to a profound sense of curiosity and intrigue. The statistical tapestry that unfurled before us revealed a correlation coefficient of 0.6950273, accompanied by a significance level of p < 0.01, encapsulating the dance between Elyses and airborne particulate matter. This revelation not only lends credence to the notion of the "Elyse Effect" but also beckons us to ponder the whimsical nature of statistical exploration.
In this whimsical odyssey of research, we aspire to unearth the underlying mechanisms that underpin this improbable entwining of nomenclature and atmospheric composition. The implications of our findings extend beyond mere statistical jargon, transcending into the realm of wonder and curiosity that so often fuels scientific inquiry. Our scholarly pursuit is driven by the relentless quest to unravel the inexplicable, all while embracing the whimsy that threads through the fabric of our academic endeavors.
So, with a dash of statistical wizardry and a pinch of linguistic whimsy, we invite the reader to embark on this delightful expedition into the "Elyse Effect," where the esoteric dance of data and nomenclature awaits its fervent unraveling.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

The methodology employed in this study was a blend of meticulous data collection, rigorous statistical analysis, and a sprinkling of whimsical curiosity. Our research endeavored to bridge the realms of nomenclature and atmospheric composition through a series of convoluted yet oddly delightful steps.

Data Collection:
Our research team embarked on a grand adventure through the digital expanse, scouring the annals of the US Social Security Administration's database to trace the ebbs and flows of the name Elyse from 1987 to 2022. We meticulously recorded the frequency of this melodious moniker, transcending time and space with the tenacity of data-driven explorers.

Meanwhile, our endeavor into the atmospheric landscape of Bremerton, Washington would not have been complete without the stalwart guidance of the Environmental Protection Agency. With an air of scientific reverence, we plumbed the depths of the EPA's treasure trove of air quality data, encompassing the same temporal scope as our nomenclatural odyssey.

Data Analysis:
Armed with an arsenal of statistical tools and a touch of whimsical mystique, we set forth to unravel the quirks of the "Elyse Effect." The correlation between the prevalence of the name Elyse and the ambient air quality was unveiled through the meticulous calculation of correlation coefficients and significance levels. Our statistical foray bore witness to the emergence of a striking correlation coefficient of 0.6950273, tinged with the enigmatic allure of p < 0.01.

Interdisciplinary Concoction:
The enigmatic interplay between nomenclature and environmental quality necessitated a medley of disciplines to fully grasp its whimsical essence. Drawing from the wellspring of linguistics, sociology, and environmental science, our analytical gaze transcended the traditional confines of academic inquiry, imbuing our methodology with a delightful hodgepodge of interdisciplinary fervor.

A Touch of Whimsy:
Unbeknownst to the stoic facade of empirical research, a dash of whimsy lingered in the folds of our methodology. As we traversed the labyrinth of data analysis, our hearts swelled with the childlike wonder of uncovering the "Elyse Effect" that had long awaited its moment in the whimsical limelight.

In this enrapturing odyssey of statistical rigour and scholarly whimsy, we embarked on a quest that transcended conventional research paradigms, delving into the playful interweaving of nomenclature and atmospheric ambiance. Our methodology, like a jester's dance, sought not only to elucidate the correlation at hand but to celebrate the wonder that lies at the intersection of empirical inquiry and enchanting curiosity.


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 Elyse and Air pollution in Bremerton, Washington. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and Environmental Protection Agency .

For the time period 1987 to 2022, you found a correlation 0.6950273, r-squared of 0.4830630, 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 Elyse Effect: A Whimsical Exploration of the Correlation Between the Popularity of the Name Elyse and Air Quality in Bremerton, Washington"

[[ABSTRACT]]
This paper delves into the intriguing relationship between the prevalence of the first name Elyse and atmospheric pollution levels in the picturesque town of Bremerton, Washington. Utilizing extensive data from the US Social Security Administration and the Environmental Protection Agency, our research team embarked on a whimsical quest to unravel this peculiar conundrum. Through meticulous analysis, we uncovered a striking correlation coefficient of 0.6950273 with a significance level of p < 0.01, spanning the years 1987 to 2022. Our findings not only shed light on the enigmatic connection between nomenclature and environmental quality, but also illuminate the whimsical nature of statistical exploration.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Introduction
The relationship between human nomenclature and environmental factors has long been a topic of curiosity, invoking the whimsical musings of researchers and the general public alike. One such peculiar association that has piqued our interest is the correlation between the prevalence of the first name Elyse and the air quality in Bremerton, Washington. We embark on this endeavor with a blend of scientific rigor and childlike wonder, seeking to unravel the mysterious "Elyse Effect" that seems to hover over the atmospheric landscape of this charming town.
Bremerton, located in the scenic backdrop of the Puget Sound, is not only renowned for its naval history and picturesque surroundings but also for the enigmatic variations in air quality that have left researchers scratching their heads. Meanwhile, the name Elyse, with its melodic cadence and subtle charm, has steadily woven its way into the fabric of American nomenclature. It is against this backdrop of natural beauty and linguistic intrigue that our research takes root, poised to uncover the intricacies of this unlikely pairing.
While the notion of a correlation between a name and air pollution may initially prompt a whimsical chuckle, the empirical foundation of our investigation remains steadfast. Leveraging data from the US Social Security Administration, we meticulously traced the trajectory of the name Elyse across temporal bounds, encompassing the years 1987 to 2022. Simultaneously, the Environmental Protection Agency served as our stalwart ally, supplying comprehensive measures of air quality in the Bremerton region.
As we methodically delved into the abyss of data analysis, our initial amusement gradually gave way to a profound sense of curiosity and intrigue. The statistical tapestry that unfurled before us revealed a correlation coefficient of 0.6950273, accompanied by a significance level of p < 0.01, encapsulating the dance between Elyses and airborne particulate matter. This revelation not only lends credence to the notion of the "Elyse Effect" but also beckons us to ponder the whimsical nature of statistical exploration.
In this whimsical odyssey of research, we aspire to unearth the underlying mechanisms that underpin this improbable entwining of nomenclature and atmospheric composition. The implications of our findings extend beyond mere statistical jargon, transcending into the realm of wonder and curiosity that so often fuels scientific inquiry. Our scholarly pursuit is driven by the relentless quest to unravel the inexplicable, all while embracing the whimsy that threads through the fabric of our academic endeavors.
So, with a dash of statistical wizardry and a pinch of linguistic whimsy, we invite the reader to embark on this delightful expedition into the "Elyse Effect," where the esoteric dance of data and nomenclature awaits its fervent unraveling.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The statistical analysis of the relationship between the prevalence of the first name Elyse and air pollution levels in Bremerton, Washington unveiled an intriguing correlation. Over the time period from 1987 to 2022, a correlation coefficient of 0.6950273 was observed, with an r-squared value of 0.4830630 and a robust p-value of less than 0.01. These results signified a significant association between the frequency of the name Elyse and the atmospheric quality of the picturesque town of Bremerton.

For the visual learners among us, a scatterplot (Fig. 1) graphically illustrates this remarkable correlation, showcasing the whimsical dance between Elyses and airborne pollutants. It's like a high-brow art piece, with each data point adding its own unique flair to the canvas of statistical exploration. Who knew that a seemingly innocent name could have such an atmospheric impact? It's almost as if the letters themselves waltz through the air, leaving their mark on the very fabric of environmental quality.

These results not only affirm the existence of the "Elyse Effect," but also elevate the discourse on the interconnectedness of nomenclature and environmental phenomena. The statistical significance of this correlation encourages us to ponder the enigmatic ways in which human identity, in the form of a simple name, intertwines with the natural world. It's a whimsical, thought-provoking tango between the ethereal realm of linguistics and the tangible embrace of environmental science.

Moreover, our findings point to the whimsical nature of statistical exploration, where the seemingly absurd can often harbor profound insights. It's as though statistical analysis is a magician, pulling unexpected wonders out of the hat of data. The "Elyse Effect" serves as a delightful reminder that scientific inquiry, even in its most rigorous form, can be colored by the playful curiosity that underpins our academic pursuits.


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 Elyse and Air pollution in Bremerton, Washington. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"The Elyse Effect: A Whimsical Exploration of the Correlation Between the Popularity of the Name Elyse and Air Quality in Bremerton, Washington"

[[ABSTRACT]]
This paper delves into the intriguing relationship between the prevalence of the first name Elyse and atmospheric pollution levels in the picturesque town of Bremerton, Washington. Utilizing extensive data from the US Social Security Administration and the Environmental Protection Agency, our research team embarked on a whimsical quest to unravel this peculiar conundrum. Through meticulous analysis, we uncovered a striking correlation coefficient of 0.6950273 with a significance level of p < 0.01, spanning the years 1987 to 2022. Our findings not only shed light on the enigmatic connection between nomenclature and environmental quality, but also illuminate the whimsical nature of statistical exploration.

[[LITERATURE REVIEW]]
The existing body of literature concerning the correlation between personal nomenclature and environmental parameters forms a heterogeneous landscape, spanning from rigorous statistical analyses to fanciful conjectures. Smith et al. (2010) provide a comprehensive exploration of the impact of individual names on societal perceptions, laying the groundwork for our own whimsical investigation of the Elyse phenomenon. Drawing from a multidisciplinary approach, Doe and Jones (2015) offer a thorough examination of atmospheric pollutants and their effects on local communities, inadvertently setting the stage for the intersection of our peculiar foci.
In the realm of non-fiction works, "The Air We Breathe: Understanding Atmospheric Composition" by Clean Air Coalition delves into the intricate balance of gaseous constituents that swirl within our Earth's atmosphere, shedding light on the delightful quirks of air quality considerations. Additionally, "Names and Identities: A Linguistic Analysis" by Lexis Linguistics presents an erudite compilation of name-related studies, providing a scholarly backdrop for our whimsical juxtaposition of Elyses and airborne particles.
Turning to the world of fiction, the works of authors such as Gabriel Garcia Marquez, particularly "One Hundred Years of Solitude," beckon us to dance on the delicate tightrope between reality and whimsy, mirroring the intricate interplay between the ethereal nature of nomenclature and the tangible embrace of environmental factors. Similarly, the poignant satire of Douglas Adams in "The Hitchhiker's Guide to the Galaxy" encourages a sublimely whimsical lens through which to view our statistical foray into the enigmatic Elyse Effect.
In the domain of animated manifestations, the whimsical charm and environmental themes of "Captain Planet and the Planeteers" serendipitously resonate with our own research pursuits, encapsulating the meritorious balance between statistical analysis and anthropomorphic allegories. Moreover, the imaginative allure of "The Magic School Bus" provides a playful yet insightful backdrop to our scholarly journey, echoing the whimsical depths of scientific exploration as we unravel the cryptic ties between Elyses and air pollution.
As we wade through this delightful mélange of literature, it becomes evident that the intersection of nomenclature and environmental quality is not merely a statistical dalliance but also a whimsical expedition into the wondrous tapestry of human experience. With these diverse influences shaping our perspective, we embark on our own whimsical venture, prepared to mesh empirical rigor with a sprinkle of fantastical whimsy as we untangle the ethereal "Elyse Effect" in the atmospheric realm of Bremerton, Washington.

[[RESULTS]]
The statistical analysis of the relationship between the prevalence of the first name Elyse and air pollution levels in Bremerton, Washington unveiled an intriguing correlation. Over the time period from 1987 to 2022, a correlation coefficient of 0.6950273 was observed, with an r-squared value of 0.4830630 and a robust p-value of less than 0.01. These results signified a significant association between the frequency of the name Elyse and the atmospheric quality of the picturesque town of Bremerton.
For the visual learners among us, a scatterplot (Fig. 1) graphically illustrates this remarkable correlation, showcasing the whimsical dance between Elyses and airborne pollutants. It's like a high-brow art piece, with each data point adding its own unique flair to the canvas of statistical exploration. Who knew that a seemingly innocent name could have such an atmospheric impact? It's almost as if the letters themselves waltz through the air, leaving their mark on the very fabric of environmental quality.
These results not only affirm the existence of the "Elyse Effect," but also elevate the discourse on the interconnectedness of nomenclature and environmental phenomena. The statistical significance of this correlation encourages us to ponder the enigmatic ways in which human identity, in the form of a simple name, intertwines with the natural world. It's a whimsical, thought-provoking tango between the ethereal realm of linguistics and the tangible embrace of environmental science.
Moreover, our findings point to the whimsical nature of statistical exploration, where the seemingly absurd can often harbor profound insights. It's as though statistical analysis is a magician, pulling unexpected wonders out of the hat of data. The "Elyse Effect" serves as a delightful reminder that scientific inquiry, even in its most rigorous form, can be colored by the playful curiosity that underpins our academic pursuits.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The striking correlation between the prevalence of the first name Elyse and atmospheric pollution levels in Bremerton, Washington has captivated our whimsical curiosity and prompted a revelrous discussion that dances between statistical sophistication and a sprinkle of irrepressible mirth. Our findings resonate with the prior research, intertwining the delightful quirkiness of nomenclature with the tangible embrace of environmental parameters. Indeed, our statistical tango showcases a whimsical waltz between Elyses and airborne pollutants, akin to an elegant piece of art created by Mother Earth's very own hand.

Harking back to the fanciful influences in the literature review, our results echo the enchanting sentiments encapsulated in the works of Gabriel Garcia Marquez and Douglas Adams. Just as Marquez beckoned us to dance on the delicate tightrope between reality and whimsy, our statistical foray into the "Elyse Effect" teases out the playful coalescence of human identity and atmospheric nuances. Similarly, the sublimely whimsical lens through which Douglas Adams viewed the world amplifies the unexpected wonders present in our own analysis – it's as though statistical analysis is a magician, conjuring profound insights from the seemingly absurd.

The statistical significance of our correlation not only underscores the empirical rigor underpinning our outcomes but also underscores the potent intertwining of human identity and the natural world. It's a whimsical reminder that scientific inquiry, even in its most rigorous form, can be colored by the playful curiosity that underpins our academic pursuits. As we unravel the ethereal "Elyse Effect," we find ourselves gleefully balancing the weighty mantle of statistical analysis with a pinch of whimsy, embodying the meritorious balance between empirical scrutiny and whimsical exploration.

In closing, the enchanting dance between Elyses and air pollution in the picturesque town of Bremerton, Washington not only amplifies the whimsical depths of scientific exploration but also beckons us to ponder the catalytic interplay between personal nomenclature and atmospheric conditions. As we continue to unravel the enigmatic ties between nomenclature and environmental quality, our scholarly journey retains its endearing whimsy, promising to mesmerize and illuminate, much like a captivating piece of fiction that embraces the heart of empirical discovery.


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 Elyse and Air pollution in Bremerton, Washington. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"The Elyse Effect: A Whimsical Exploration of the Correlation Between the Popularity of the Name Elyse and Air Quality in Bremerton, Washington"

[[ABSTRACT]]
This paper delves into the intriguing relationship between the prevalence of the first name Elyse and atmospheric pollution levels in the picturesque town of Bremerton, Washington. Utilizing extensive data from the US Social Security Administration and the Environmental Protection Agency, our research team embarked on a whimsical quest to unravel this peculiar conundrum. Through meticulous analysis, we uncovered a striking correlation coefficient of 0.6950273 with a significance level of p < 0.01, spanning the years 1987 to 2022. Our findings not only shed light on the enigmatic connection between nomenclature and environmental quality, but also illuminate the whimsical nature of statistical exploration.

[[INTRDUCTION]]
Introduction
The relationship between human nomenclature and environmental factors has long been a topic of curiosity, invoking the whimsical musings of researchers and the general public alike. One such peculiar association that has piqued our interest is the correlation between the prevalence of the first name Elyse and the air quality in Bremerton, Washington. We embark on this endeavor with a blend of scientific rigor and childlike wonder, seeking to unravel the mysterious "Elyse Effect" that seems to hover over the atmospheric landscape of this charming town.
Bremerton, located in the scenic backdrop of the Puget Sound, is not only renowned for its naval history and picturesque surroundings but also for the enigmatic variations in air quality that have left researchers scratching their heads. Meanwhile, the name Elyse, with its melodic cadence and subtle charm, has steadily woven its way into the fabric of American nomenclature. It is against this backdrop of natural beauty and linguistic intrigue that our research takes root, poised to uncover the intricacies of this unlikely pairing.
While the notion of a correlation between a name and air pollution may initially prompt a whimsical chuckle, the empirical foundation of our investigation remains steadfast. Leveraging data from the US Social Security Administration, we meticulously traced the trajectory of the name Elyse across temporal bounds, encompassing the years 1987 to 2022. Simultaneously, the Environmental Protection Agency served as our stalwart ally, supplying comprehensive measures of air quality in the Bremerton region.
As we methodically delved into the abyss of data analysis, our initial amusement gradually gave way to a profound sense of curiosity and intrigue. The statistical tapestry that unfurled before us revealed a correlation coefficient of 0.6950273, accompanied by a significance level of p < 0.01, encapsulating the dance between Elyses and airborne particulate matter. This revelation not only lends credence to the notion of the "Elyse Effect" but also beckons us to ponder the whimsical nature of statistical exploration.
In this whimsical odyssey of research, we aspire to unearth the underlying mechanisms that underpin this improbable entwining of nomenclature and atmospheric composition. The implications of our findings extend beyond mere statistical jargon, transcending into the realm of wonder and curiosity that so often fuels scientific inquiry. Our scholarly pursuit is driven by the relentless quest to unravel the inexplicable, all while embracing the whimsy that threads through the fabric of our academic endeavors.
So, with a dash of statistical wizardry and a pinch of linguistic whimsy, we invite the reader to embark on this delightful expedition into the "Elyse Effect," where the esoteric dance of data and nomenclature awaits its fervent unraveling.

[[RESULTS]]
The statistical analysis of the relationship between the prevalence of the first name Elyse and air pollution levels in Bremerton, Washington unveiled an intriguing correlation. Over the time period from 1987 to 2022, a correlation coefficient of 0.6950273 was observed, with an r-squared value of 0.4830630 and a robust p-value of less than 0.01. These results signified a significant association between the frequency of the name Elyse and the atmospheric quality of the picturesque town of Bremerton.
For the visual learners among us, a scatterplot (Fig. 1) graphically illustrates this remarkable correlation, showcasing the whimsical dance between Elyses and airborne pollutants. It's like a high-brow art piece, with each data point adding its own unique flair to the canvas of statistical exploration. Who knew that a seemingly innocent name could have such an atmospheric impact? It's almost as if the letters themselves waltz through the air, leaving their mark on the very fabric of environmental quality.
These results not only affirm the existence of the "Elyse Effect," but also elevate the discourse on the interconnectedness of nomenclature and environmental phenomena. The statistical significance of this correlation encourages us to ponder the enigmatic ways in which human identity, in the form of a simple name, intertwines with the natural world. It's a whimsical, thought-provoking tango between the ethereal realm of linguistics and the tangible embrace of environmental science.
Moreover, our findings point to the whimsical nature of statistical exploration, where the seemingly absurd can often harbor profound insights. It's as though statistical analysis is a magician, pulling unexpected wonders out of the hat of data. The "Elyse Effect" serves as a delightful reminder that scientific inquiry, even in its most rigorous form, can be colored by the playful curiosity that underpins our academic pursuits.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our whimsical expedition into the peculiar nexus of the "Elyse Effect" has illuminated a captivating correlation between the abundance of the name Elyse and the ambient air quality in Bremerton, Washington. The correlation coefficient of 0.6950273, coupled with a strikingly robust p-value of less than 0.01, unveils a compelling association that beckons us to ponder the enigmatic interplay of nomenclature and atmospheric composition. As we contemplated the statistical tapestry, we couldn't help but marvel at the whimsicality of this unexpected correlation. It's like stumbling upon a secret joke hidden within the confines of empirical data – a delightful surprise, indeed.

Our findings not only lend support to the existence of the "Elyse Effect" but also underscore the profound interconnectedness between human identity, reflected in a simple name, and the ambient environment. This whimsical dance of data and nomenclature offers a whimsical reminder that scientific inquiry, amidst its rigors, is never devoid of lighthearted curiosity.

In the grand tapestry of statistical exploration, the "Elyse Effect" stands as a charming anecdote, urging us to embrace the quirky and unexpected, all while unraveling the mysterious ways in which the ethereal world of linguistics intersects with the tangible embrace of environmental science. Truly, the enchanting waltz of Elyses and airborne particulate matter serves as a testament to the delightful surprises that await us in the realm of statistical exploration.

With these delightful findings in hand, we assert that further inquiries into the "Elyse Effect" would likely yield diminishing returns, akin to searching for a needle in a statistically significant haystack. Therefore, we declare that no more research is needed in this area. After all, in the whimsical land of statistical exploration, sometimes it's best to leave a touch of mystery in the 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 The Elyse Effect: A Whimsical Exploration of the Correlation Between the Popularity of the Name Elyse and Air Quality in Bremerton, Washington. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Quirky Connections


Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited The Elyse Effect: A Whimsical Exploration of the Correlation Between the Popularity of the Name Elyse and Air Quality in Bremerton, Washington. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Quirky Urban Studies and Research


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 Elyse Effect: A Whimsical Exploration of the Correlation Between the Popularity of the Name Elyse and Air Quality in Bremerton, Washington with an abstract of This paper delves into the intriguing relationship between the prevalence of the first name Elyse and atmospheric pollution levels in the picturesque town of Bremerton, Washington. Utilizing extensive data from the US Social Security Administration and the Environmental Protection Agency, our research team embarked on a whimsical quest to unravel this peculiar conundrum. Through meticulous analysis, we uncovered a striking correlation coefficient of 0.6950273 with a significance level of p < 0.01, spanning the years 1987 to 2022. Our findings not only shed light on the enigmatic connection between nomenclature and environmental quality, but also illuminate the whimsical nature of statistical exploration.

ChatGPT:

Elyse, air quality, Bremerton, Washington, correlation, name prevalence, atmospheric pollution levels, US Social Security Administration data, Environmental Protection Agency data, correlation coefficient, significance level, statistical exploration, whimsical, nomenclature, environmental quality

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

Air pollution in Bremerton, Washington
Detailed data title: Percentage of days with moderate or worse air quality in Bremerton-Silverdale, WA
Source: Environmental Protection Agency
See what else correlates with Air pollution in Bremerton, Washington

Correlation r = 0.6950273 (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 = 0.4830630 (Coefficient of determination)
This means 48.3% of the change in the one variable (i.e., Air pollution in Bremerton, Washington) is predictable based on the change in the other (i.e., Popularity of the first name Elyse) over the 36 years from 1987 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.6E-6. 0.0000025546692743309472000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.7 in 0.00026% of random cases. Said differently, if you correlated 391,440 random variables You don't actually need 391 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 35 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 35 because we have two variables measured over a period of 36 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.

[ 0.47, 0.83 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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


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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
198719881989199019911992199319941995199619971998199920002001200220032004200520062007200820092010201120122013201420152016201720182019202020212022
Popularity of the first name Elyse (Babies born)803797619454412330264276249216248283270278292314349368386419389432454461479571495477440418428421385388313341
Air pollution in Bremerton, Washington (Bad air quality days)0.2346370.1955920.049450600000.006134970.00824176000000000000.1717450.1168830.1769660.1221590.1108030.05362780.02292260.02209940.02513970.002801120.050.04584530.005882350.05817170.01671310.086351




Why this works

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




Try it yourself

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

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

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

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

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

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

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

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

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


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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([803,797,619,454,412,330,264,276,249,216,248,283,270,278,292,314,349,368,386,419,389,432,454,461,479,571,495,477,440,418,428,421,385,388,313,341,])
array_2 = np.array([0.234637,0.195592,0.0494506,0,0,0,0,0.00613497,0.00824176,0,0,0,0,0,0,0,0,0,0,0,0.171745,0.116883,0.176966,0.122159,0.110803,0.0536278,0.0229226,0.0220994,0.0251397,0.00280112,0.05,0.0458453,0.00588235,0.0581717,0.0167131,0.086351,])
array_1_name = "Popularity of the first name Elyse"
array_2_name = "Air pollution in Bremerton, Washington"

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

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



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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."

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Correlation ID: 1572 · Black Variable ID: 3582 · Red Variable ID: 21905
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