Spurious correlation #3,499 · 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 Maggie and the second variable is Air pollution in Terre Haute, Indiana. The chart goes from 1981 to 2022, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Maggie and the second variable is Air pollution in Terre Haute, Indiana. The chart goes from 1981 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the name Maggie gained popularity, so did the use of personalized car air fresheners, leading to a spike in demand for new cars. This influx of new car purchases in Terre Haute revved up the pollution levels, creating a smoggy situation. Looks like the road to popularity was paved with some unintended smog emissions!

^{Show image generation prompt} Model: dalle-3
Prompt: Create an image of the city of Terre Haute, Indiana, where the sky is filled with smog and carbon dioxide emissions from the popular song "Maggie May" by Rod Stewart. The city is shrouded in a thick haze, with buildings and streets barely visible through the polluted air. In the foreground, include a figure representing Maggie, visually inspired by characters from Skyrim, surrounded by the dense smog. As the excess carbon dioxide mixes with the polluted air, it creates an eerie atmosphere, evoking a sense of suffocation and environmental impact. 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 Maggie and Air pollution in Terre Haute, Indiana. 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: Realistic An image that looks like it is a scene from a Pixar movie a funny image you would see on reddit A scene from Skyrim Sci-fi fantacy
ChatGPT: A scene from Skyrim

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 Maggie and Air pollution in Terre Haute, Indiana, in the following situation: As the popularity of the first name Maggie soared in Terre Haute, Indiana, more and more people were singing "Maggie May" by Rod Stewart, causing excessive carbon dioxide emissions. The city became choked with air pollution from all the MAGnificent MAGgie May renditions, leading to a smoggy situation that left everyone gasping.. Keep the description simple.
ChatGPT: In Terre Haute, Indiana, the name Maggie became increasingly popular, and as more and more people sang "Maggie May" by Rod Stewart, the air became thick with smog. The city was filled with carbon dioxide emissions from the MAGnificent MAGgie May renditions, leaving everyone gasping in the midst of air pollution.

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 scene from Skyrim ] and depicting this scene: In Terre Haute, Indiana, the name Maggie became increasingly popular, and as more and more people sang "Maggie May" by Rod Stewart, the air became thick with smog. The city was filled with carbon dioxide emissions from the MAGnificent MAGgie May renditions, leaving everyone gasping in the midst of air pollution. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of the city of Terre Haute, Indiana, where the sky is filled with smog and carbon dioxide emissions from the popular song "Maggie May" by Rod Stewart. The city is shrouded in a thick haze, with buildings and streets barely visible through the polluted air. In the foreground, include a figure representing Maggie, visually inspired by characters from Skyrim, surrounded by the dense smog. As the excess carbon dioxide mixes with the polluted air, it creates an eerie atmosphere, evoking a sense of suffocation and environmental impact.

*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 an increase in Popularity of the first name Maggie caused Air pollution in Terre Haute, Indiana to increase. Include one good pun.

AI academic paper

(Because p < 0.01)

Nitrogen Oxide, Nitrogen You: The Maggie-tude of Popularity in Relation to Air Quality in Terre Haute, Indiana

The Journal of Atmospheric Laughter and Environmental Puns

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 Maggie and Air pollution in Terre Haute, Indiana. 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 a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
"Nitrogen Oxide, Nitrogen You: The Maggie-tude of Popularity in Relation to Air Quality in Terre Haute, Indiana"

[[ABSTRACT]]
This study investigates the peculiar correlation between the prevalence of the given name "Maggie" and air pollution levels in the charming city of Terre Haute, Indiana. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, our research team delves into the peculiar nexus between the eponymous moniker "Maggie" and the atmospheric quality of Terre Haute. With a correlation coefficient of 0.8390643 and p < 0.01 for the time frame spanning from 1981 to 2022, our findings present a statistically robust link between the two seemingly disparate phenomena. Despite the delightful absurdity of this investigation, the insights gleaned from this research lend themselves to broader discussions about the influence of nomenclature on environmental well-being. The implications of our study extend beyond the confines of academia, prompting reflection on the whimsical interplay between social trends and environmental conditions.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Introduction
The enchanting city of Terre Haute, Indiana, known for its delightful mix of Hoosier hospitality and Midwestern charm, serves as the unlikely stage for our investigation into the curious connection between the prevalence of the given name "Maggie" and the ambient air quality within its environs. This seemingly whimsical endeavor is rooted in the empirical observation of a potential association between the eponymous moniker "Maggie" and the atmospheric conditions that grace the city. It is an inquiry that combines the esoteric allure of onomastics with the pragmatic implications of environmental science, rendering it a study of both levity and gravity - quite like the gaseous constituents we aim to scrutinize.
The impetus for this investigation stems from an inconspicuous observation made by the lead author upon a fortuitous encounter with an affable Terre Haute resident named Maggie. In the midst of an idyllic conversation about the ever-changing weather patterns in the region, a serendipitous thought emerged: could there be a latent relationship between the popularity of the name "Maggie" and the presence of atmospheric pollutants in Terre Haute? Seized by this whimsical notion, the research team embarked on a journey to decipher whether there exists a substantive nexus between nomenclature and nitrogen oxides - a pursuit as curious as a terrier's tail and as complex as the city's industrial fabric.
Despite its offbeat and seemingly capricious premise, this research endeavor harnesses the formidable power of data to unravel the intricate dance between nomenclature and nitrogen compounds. With the aide of robust datasets from the US Social Security Administration and the Environmental Protection Agency, we endeavored to disentangle the threads of causation or correlation that may underlie this peculiar relationship between the name "Maggie" and atmospheric pollutants. It is our aspiration that this study will not only bring a wry smile to the reader's lips but also kindle a deeper contemplation of the oft-overlooked intersections between social phenomena and environmental realities.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Prior research on the association between given names and environmental factors has primarily focused on traditional topics such as socioeconomic status, educational attainment, and occupational choices. However, the remarkably unconventional inquiry into the connection between the popularity of the first name "Maggie" and air pollution levels in Terre Haute, Indiana introduces a refreshingly whimsical twist to the literature.

In "The Significance of Names," Smith delves into the cultural and psychological implications of names, shedding light on the profound impact they have on personal identity and social interactions. Similarly, Doe's "Naming and Society" offers a comprehensive exploration of the social significance of names across different cultures, reframing the conventional understanding of nomenclature as a mere label.

In the realm of environmental studies, Jones' "Atmospheric Chronicles" presents a meticulous analysis of air pollution trends and their societal ramifications. This work offers valuable insights into the multifaceted dynamics of ambient air quality and its intersection with human activities.

A peculiar turn in the literature leads us to consider relevant non-fiction works that tangentially touch upon the subject matter at hand. "The Namesake" by Jhumpa Lahiri, while focusing on the intricacies of immigrant experiences, prompts contemplation on the significance of names and their cultural connotations. Additionally, "The Name of the Wind" by Patrick Rothfuss, though a work of fantasy fiction, lends a poetic nuance to the idea of naming and significance.

Transitioning to a more whimsical realm, the study draws on unexpected sources such as popular fiction novels "Looking for Alaska" by John Green and "Maggie Stiefvater's Raven Cycle Series," which, while not explicitly related to environmental factors, feature characters with the name "Maggie" or themes that tangentially relate to air pollution.

Moreover, the internet meme "Distracted Boyfriend" gains relevance in the context of social trends, serving as a playful nod to the capricious nature of popular names and their potential influence on environmental conditions. Additionally, the meme "This is Fine" humorously underscores the interconnectedness of social trends and environmental well-being, albeit in a tongue-in-cheek manner.

The unorthodox intersection of nomenclature and environmental variables surfaces a convivial and unexpected contribution to the often staid world of academic inquiry, injecting a buoyant levity into the literature that is as refreshing as a breath of clean, unpolluted air.

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 Maggie and Air pollution in Terre Haute, Indiana. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 1981 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]]
"Nitrogen Oxide, Nitrogen You: The Maggie-tude of Popularity in Relation to Air Quality in Terre Haute, Indiana"

[[ABSTRACT]]
This study investigates the peculiar correlation between the prevalence of the given name "Maggie" and air pollution levels in the charming city of Terre Haute, Indiana. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, our research team delves into the peculiar nexus between the eponymous moniker "Maggie" and the atmospheric quality of Terre Haute. With a correlation coefficient of 0.8390643 and p < 0.01 for the time frame spanning from 1981 to 2022, our findings present a statistically robust link between the two seemingly disparate phenomena. Despite the delightful absurdity of this investigation, the insights gleaned from this research lend themselves to broader discussions about the influence of nomenclature on environmental well-being. The implications of our study extend beyond the confines of academia, prompting reflection on the whimsical interplay between social trends and environmental conditions.

[[INTRODUCTION]]
Introduction
The enchanting city of Terre Haute, Indiana, known for its delightful mix of Hoosier hospitality and Midwestern charm, serves as the unlikely stage for our investigation into the curious connection between the prevalence of the given name "Maggie" and the ambient air quality within its environs. This seemingly whimsical endeavor is rooted in the empirical observation of a potential association between the eponymous moniker "Maggie" and the atmospheric conditions that grace the city. It is an inquiry that combines the esoteric allure of onomastics with the pragmatic implications of environmental science, rendering it a study of both levity and gravity - quite like the gaseous constituents we aim to scrutinize.
The impetus for this investigation stems from an inconspicuous observation made by the lead author upon a fortuitous encounter with an affable Terre Haute resident named Maggie. In the midst of an idyllic conversation about the ever-changing weather patterns in the region, a serendipitous thought emerged: could there be a latent relationship between the popularity of the name "Maggie" and the presence of atmospheric pollutants in Terre Haute? Seized by this whimsical notion, the research team embarked on a journey to decipher whether there exists a substantive nexus between nomenclature and nitrogen oxides - a pursuit as curious as a terrier's tail and as complex as the city's industrial fabric.
Despite its offbeat and seemingly capricious premise, this research endeavor harnesses the formidable power of data to unravel the intricate dance between nomenclature and nitrogen compounds. With the aide of robust datasets from the US Social Security Administration and the Environmental Protection Agency, we endeavored to disentangle the threads of causation or correlation that may underlie this peculiar relationship between the name "Maggie" and atmospheric pollutants. It is our aspiration that this study will not only bring a wry smile to the reader's lips but also kindle a deeper contemplation of the oft-overlooked intersections between social phenomena and environmental realities.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

The methodology employed in this study represents a harmonious fusion of quantitative analysis and whimsical inquiry, akin to the interplay of statistical modeling and levity in a vaudevillian performance. Leveraging datasets from the US Social Security Administration and the Environmental Protection Agency, the researchers embarked on a journey through the corridors of data analysis, simultaneously channeling the spirit of Sherlock Holmes and that of a stand-up comedian.

Firstly, the team obtained data on the frequency of the first name "Maggie" from the US Social Security Administration, navigating through the digital catacombs of historical records to unearth the temporal ebbs and flows of this endearing appellation. The timeframe spanned from 1981 to 2022, capturing the undulating tides of nomenclatural popularity with precision.

Concomitantly, air quality data for Terre Haute, Indiana, was sourced from the Environmental Protection Agency, mirroring the diligence of a truffle-hunting sow in sniffing out the aromatic nuances of atmospheric composition. Metrics such as nitrogen dioxide (NO2) and particulate matter (PM10) were scrutinized to discern the whims of atmospheric whimsy alongside the chronological fluctuations of Maggie's eminence.

The research team then applied a series of statistical analyses to disentangle the enigmatic relationship between the frequency of the name "Maggie" and the ambient air pollutant levels. Utilizing correlation coefficients and regression models, the researchers well and truly harnessed the formidable power of numbers, wielding them not only as tools of elucidation but also as whimsical companions in this lyrical dance of investigation.

It is important to note that in conducting this research, the team exercised due diligence in accounting for confounding variables and potential spurious correlations, akin to a detective sifting through red herrings to unveil the true culprit. Moreover, the researchers treated the data with the utmost respect, as one might tenderly handle a fragile Fabergé egg, ensuring that the integrity of the analysis remained unblemished.

In summation, the methodology employed in this study demonstrates a careful blend of analytical rigor and playful exploration, charting a course through the seas of data with both the precision of a cartographer and the unbridled curiosity of a child with a new toy. This harmonious marriage of statistical inquiry and lighthearted fascination underpins the validity and vitality of the findings presented in this research endeavor.

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 Maggie and Air pollution in Terre Haute, Indiana. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
"Nitrogen Oxide, Nitrogen You: The Maggie-tude of Popularity in Relation to Air Quality in Terre Haute, Indiana"

[[ABSTRACT]]
This study investigates the peculiar correlation between the prevalence of the given name "Maggie" and air pollution levels in the charming city of Terre Haute, Indiana. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, our research team delves into the peculiar nexus between the eponymous moniker "Maggie" and the atmospheric quality of Terre Haute. With a correlation coefficient of 0.8390643 and p < 0.01 for the time frame spanning from 1981 to 2022, our findings present a statistically robust link between the two seemingly disparate phenomena. Despite the delightful absurdity of this investigation, the insights gleaned from this research lend themselves to broader discussions about the influence of nomenclature on environmental well-being. The implications of our study extend beyond the confines of academia, prompting reflection on the whimsical interplay between social trends and environmental conditions.

[[LITERATURE REVIEW]]
Prior research on the association between given names and environmental factors has primarily focused on traditional topics such as socioeconomic status, educational attainment, and occupational choices. However, the remarkably unconventional inquiry into the connection between the popularity of the first name "Maggie" and air pollution levels in Terre Haute, Indiana introduces a refreshingly whimsical twist to the literature.
In "The Significance of Names," Smith delves into the cultural and psychological implications of names, shedding light on the profound impact they have on personal identity and social interactions. Similarly, Doe's "Naming and Society" offers a comprehensive exploration of the social significance of names across different cultures, reframing the conventional understanding of nomenclature as a mere label.
In the realm of environmental studies, Jones' "Atmospheric Chronicles" presents a meticulous analysis of air pollution trends and their societal ramifications. This work offers valuable insights into the multifaceted dynamics of ambient air quality and its intersection with human activities.
A peculiar turn in the literature leads us to consider relevant non-fiction works that tangentially touch upon the subject matter at hand. "The Namesake" by Jhumpa Lahiri, while focusing on the intricacies of immigrant experiences, prompts contemplation on the significance of names and their cultural connotations. Additionally, "The Name of the Wind" by Patrick Rothfuss, though a work of fantasy fiction, lends a poetic nuance to the idea of naming and significance.
Transitioning to a more whimsical realm, the study draws on unexpected sources such as popular fiction novels "Looking for Alaska" by John Green and "Maggie Stiefvater's Raven Cycle Series," which, while not explicitly related to environmental factors, feature characters with the name "Maggie" or themes that tangentially relate to air pollution.
Moreover, the internet meme "Distracted Boyfriend" gains relevance in the context of social trends, serving as a playful nod to the capricious nature of popular names and their potential influence on environmental conditions. Additionally, the meme "This is Fine" humorously underscores the interconnectedness of social trends and environmental well-being, albeit in a tongue-in-cheek manner.
The unorthodox intersection of nomenclature and environmental variables surfaces a convivial and unexpected contribution to the often staid world of academic inquiry, injecting a buoyant levity into the literature that is as refreshing as a breath of clean, unpolluted air.

[[RESULTS]]
The analysis of the data collected for the time period of 1981 to 2022 revealed a striking correlation (r = 0.8390643) between the popularity of the first name "Maggie" and air pollution levels in Terre Haute, Indiana. This relationship was further supported by an r-squared value of 0.7040290, indicating that approximately 70.4% of the variability in air pollution levels can be explained by the variability in the popularity of the name "Maggie." The associated p-value was found to be less than 0.01, underscoring the statistical significance of this connection.
Upon further examination, the scatterplot (Fig. 1) paints a vivid picture of the strong positive correlation between the prevalence of the name "Maggie" and air pollution levels in Terre Haute. The data points align themselves in a near-linear fashion, resembling the arc of a balloon's trajectory when released into the atmosphere - a whimsical analogy befitting the theme of this unusual investigation.
In light of these findings, we are compelled to acknowledge the uncanny synergy between the popularity of the name "Maggie" and the atmospheric composition of Terre Haute. At first glance, the shared trajectory of these two seemingly unrelated variables may appear as capricious as a gentle gust of wind, but our results underscore a robust statistical association that cannot be easily dismissed.
These discoveries provoke profound contemplation about the quirky and unexpected interplay of social trends and environmental dynamics, leading us to ponder the question: Is there an ethereal, otherworldly influence of this endearing name that manifests itself in the very air we breathe? While the answer may elude us, the correlation we uncovered is certainly nothing to sneeze at.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of our investigation present an intriguing alignment with the existing body of research on the influence of nomenclature on environmental phenomena. Although the correlation between the popularity of the first name "Maggie" and air pollution levels in Terre Haute, Indiana may at first seem as fanciful as a whimsical daydream, the robust statistical significance of our results lends credence to the notion that there might be more to a name than meets the eye.

Building on the unconventional twist in the literature review, our study adds a touch of lightheartedness to the usually serious discourse of environmental science. The unexpected sources referenced, from Jhumpa Lahiri's "The Namesake" to the internet meme "Distracted Boyfriend," although seemingly outlandish, inadvertently highlight the potential influence of social trends, cultural connotations, and even internet humor on environmental dynamics. It is as though the fickle winds of societal trends, represented by the eponymous name "Maggie," playfully dance with the atmospheric currents, nudging us to consider the playful intricacies of our surroundings.

The r-squared value of 0.7040290 indicates that approximately 70.4% of the variability in air pollution levels can be explained by the variability in the popularity of the name "Maggie." This substantial association, reminiscent of a mischievous imp blowing bubbles in the air, harks back to the whimsical allusions in the literature review. The scatterplot, with its near-linear depiction of the relationship between the prevalence of the name "Maggie" and air pollution levels, exudes an almost mischievous playfulness, akin to a misbehaving weather vane pointing to the lighthearted jousting between societal whims and environmental conditions.

While our results do not elucidate the metaphysical underpinnings of this correlation, the statistical robustness of the connection cannot be disregarded. The seemingly imperturbable influence of the name "Maggie" on the atmospheric composition prompts contemplation on the capricious interplay of ethereal factors and mundane environmental realities. Is it possible that the echoes of shared laughter and joyful exuberance, borne by those who bear the name "Maggie," reverberate through the atmosphere, shaping the very air we breathe? Although this fanciful notion may strike some as a flight of fancy, our results underscore the empirical evidence behind this jocular pondering.

In conclusion, our study injects a welcome dose of levity into the often austere domain of environmental research, urging us to consider the unexpected interplay between nomenclature and atmospheric conditions. The whimsical nature of our findings, akin to a playful gust of wind, beckons further inquiry into the merry dance between human influence and environmental manifestations. As we ponder this peculiar correlation, we are reminded that amidst the rigors of scientific inquiry, there is always room for a bit of playful imagination and a dash of lighthearted merriment. The startling link between the name "Maggie" and air pollution levels in Terre Haute, Indiana serves as a lighthearted reminder that the whims of the world may hold more surprises than we ever dared to dream.

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 Maggie and Air pollution in Terre Haute, Indiana. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
"Nitrogen Oxide, Nitrogen You: The Maggie-tude of Popularity in Relation to Air Quality in Terre Haute, Indiana"

[[ABSTRACT]]
This study investigates the peculiar correlation between the prevalence of the given name "Maggie" and air pollution levels in the charming city of Terre Haute, Indiana. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, our research team delves into the peculiar nexus between the eponymous moniker "Maggie" and the atmospheric quality of Terre Haute. With a correlation coefficient of 0.8390643 and p < 0.01 for the time frame spanning from 1981 to 2022, our findings present a statistically robust link between the two seemingly disparate phenomena. Despite the delightful absurdity of this investigation, the insights gleaned from this research lend themselves to broader discussions about the influence of nomenclature on environmental well-being. The implications of our study extend beyond the confines of academia, prompting reflection on the whimsical interplay between social trends and environmental conditions.

[[INTRDUCTION]]
Introduction
The enchanting city of Terre Haute, Indiana, known for its delightful mix of Hoosier hospitality and Midwestern charm, serves as the unlikely stage for our investigation into the curious connection between the prevalence of the given name "Maggie" and the ambient air quality within its environs. This seemingly whimsical endeavor is rooted in the empirical observation of a potential association between the eponymous moniker "Maggie" and the atmospheric conditions that grace the city. It is an inquiry that combines the esoteric allure of onomastics with the pragmatic implications of environmental science, rendering it a study of both levity and gravity - quite like the gaseous constituents we aim to scrutinize.
The impetus for this investigation stems from an inconspicuous observation made by the lead author upon a fortuitous encounter with an affable Terre Haute resident named Maggie. In the midst of an idyllic conversation about the ever-changing weather patterns in the region, a serendipitous thought emerged: could there be a latent relationship between the popularity of the name "Maggie" and the presence of atmospheric pollutants in Terre Haute? Seized by this whimsical notion, the research team embarked on a journey to decipher whether there exists a substantive nexus between nomenclature and nitrogen oxides - a pursuit as curious as a terrier's tail and as complex as the city's industrial fabric.
Despite its offbeat and seemingly capricious premise, this research endeavor harnesses the formidable power of data to unravel the intricate dance between nomenclature and nitrogen compounds. With the aide of robust datasets from the US Social Security Administration and the Environmental Protection Agency, we endeavored to disentangle the threads of causation or correlation that may underlie this peculiar relationship between the name "Maggie" and atmospheric pollutants. It is our aspiration that this study will not only bring a wry smile to the reader's lips but also kindle a deeper contemplation of the oft-overlooked intersections between social phenomena and environmental realities.

[[RESULTS]]
The analysis of the data collected for the time period of 1981 to 2022 revealed a striking correlation (r = 0.8390643) between the popularity of the first name "Maggie" and air pollution levels in Terre Haute, Indiana. This relationship was further supported by an r-squared value of 0.7040290, indicating that approximately 70.4% of the variability in air pollution levels can be explained by the variability in the popularity of the name "Maggie." The associated p-value was found to be less than 0.01, underscoring the statistical significance of this connection.
Upon further examination, the scatterplot (Fig. 1) paints a vivid picture of the strong positive correlation between the prevalence of the name "Maggie" and air pollution levels in Terre Haute. The data points align themselves in a near-linear fashion, resembling the arc of a balloon's trajectory when released into the atmosphere - a whimsical analogy befitting the theme of this unusual investigation.
In light of these findings, we are compelled to acknowledge the uncanny synergy between the popularity of the name "Maggie" and the atmospheric composition of Terre Haute. At first glance, the shared trajectory of these two seemingly unrelated variables may appear as capricious as a gentle gust of wind, but our results underscore a robust statistical association that cannot be easily dismissed.
These discoveries provoke profound contemplation about the quirky and unexpected interplay of social trends and environmental dynamics, leading us to ponder the question: Is there an ethereal, otherworldly influence of this endearing name that manifests itself in the very air we breathe? While the answer may elude us, the correlation we uncovered is certainly nothing to sneeze at.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has shed light on the tantalizing correlation between the prevalence of the moniker "Maggie" and the atmospheric composition of Terre Haute, Indiana. The robust statistical link between the popularity of this name and air pollution levels, as demonstrated by the impressive correlation coefficient and p-value, leaves us pondering the whimsical interplay between nomenclature and nitrogen oxides. It's as if the very essence of "Maggie" permeates the air, leaving an indelible mark on the atmospheric quality of the city.

The scatterplot, resembling the graceful trajectory of a balloon, captures the enchanting dance between the name "Maggie" and air pollution levels, like a quirky waltz set to the tune of atmospheric whimsy. One cannot help but wonder if there is a charming serendipity in the air, carried aloft by the playful breezes of statistical significance.

Our findings beckon us to contemplate the quirky and unexpected ways in which social trends and environmental dynamics intersect, urging us to consider the possibility that there may be an enigmatic, ethereal influence of the name "Maggie" that transcends the boundaries of conventional understanding. Perhaps it's not just "nitrogen oxide," but "nitrogen you" that we should be considering in this fascinating relationship.

With these revelations in mind, we proclaim that this newfound correlation between the popularity of the first name "Maggie" and air pollution levels in Terre Haute, Indiana is a discovery as delightful as a serendipitous encounter with a friendly local bearing the eponymous name.

Therefore, we assert with confidence that further research in this area is unwarranted. The whimsical enigma of "Maggie" and air pollution in Terre Haute has been lovingly embraced by our investigation, leaving us to contemplate the curious, coquettish ways of statistical fate.

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 Nitrogen Oxide, Nitrogen You: The Maggie-tude of Popularity in Relation to Air Quality in Terre Haute, Indiana. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Atmospheric Laughter and Environmental Puns

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 Nitrogen Oxide, Nitrogen You: The Maggie-tude of Popularity in Relation to Air Quality in Terre Haute, Indiana. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Atmospheric Popularity 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 Nitrogen Oxide, Nitrogen You: The Maggie-tude of Popularity in Relation to Air Quality in Terre Haute, Indiana with an abstract of This study investigates the peculiar correlation between the prevalence of the given name "Maggie" and air pollution levels in the charming city of Terre Haute, Indiana. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, our research team delves into the peculiar nexus between the eponymous moniker "Maggie" and the atmospheric quality of Terre Haute. With a correlation coefficient of 0.8390643 and p < 0.01 for the time frame spanning from 1981 to 2022, our findings present a statistically robust link between the two seemingly disparate phenomena. Despite the delightful absurdity of this investigation, the insights gleaned from this research lend themselves to broader discussions about the influence of nomenclature on environmental well-being. The implications of our study extend beyond the confines of academia, prompting reflection on the whimsical interplay between social trends and environmental conditions.

ChatGPT:

Nitrogen oxide, air quality, Terre Haute Indiana, Maggie, Social Security Administration, Environmental Protection Agency, correlation coefficient, atmospheric quality, nomenclature, environmental well-being, social trends, whimsical interplay

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

Air pollution in Terre Haute, Indiana
Detailed data title: Percentage of days with moderate or worse air quality in Terre Haute, IN
Source: Environmental Protection Agency
See what else correlates with Air pollution in Terre Haute, Indiana

Correlation r = 0.8390643 (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 = 0.7040290 (Coefficient of determination)
This means 70.4% of the change in the one variable (i.e., Air pollution in Terre Haute, Indiana) is predictable based on the change in the other (i.e., Popularity of the first name Maggie) over the 42 years from 1981 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 3.9E-12.^Show 0.0000000000039367384517973020
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 0.84 in 3.9E-10% of random cases. Said differently, if you correlated 254,017,383,233 random variables^Note You don't actually need 254 billion 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 41 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 41 because we have two variables measured over a period of 42 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.

[ 0.72, 0.91 ] 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.

	1981	1982	1983	1984	1985	1986	1987	1988	1989	1990	1991	1992	1993	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Popularity of the first name Maggie (Babies born)	487	602	738	843	946	828	883	888	840	958	937	1040	991	1225	1137	1103	1054	1238	1423	1614	1819	1697	1718	1643	1663	1858	1873	1607	1426	1408	1389	1307	1385	1355	1338	1324	1285	1127	1135	1087	1119	1068
Air pollution in Terre Haute, Indiana (Bad air quality days)	0.824176	1.09589	17.6796	24.3169	26.5753	20.5479	33.9483	25.614	27.9221	28.2209	26.7296	11.254	15.4676	33.4375	25.6983	25.1366	19.5055	43.9252	44.9782	43.9834	55.3279	56.3786	42.562	37.7049	47.9508	39.3443	59.7101	40.9471	30.916	52.4862	53.6111	45.9155	41.1602	45.1977	37.0166	30.5785	37.2603	33.6986	35.0685	19.6721	30.137	27.3973

Why this works

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

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([487,602,738,843,946,828,883,888,840,958,937,1040,991,1225,1137,1103,1054,1238,1423,1614,1819,1697,1718,1643,1663,1858,1873,1607,1426,1408,1389,1307,1385,1355,1338,1324,1285,1127,1135,1087,1119,1068,])
array_2 = np.array([0.824176,1.09589,17.6796,24.3169,26.5753,20.5479,33.9483,25.614,27.9221,28.2209,26.7296,11.254,15.4676,33.4375,25.6983,25.1366,19.5055,43.9252,44.9782,43.9834,55.3279,56.3786,42.562,37.7049,47.9508,39.3443,59.7101,40.9471,30.916,52.4862,53.6111,45.9155,41.1602,45.1977,37.0166,30.5785,37.2603,33.6986,35.0685,19.6721,30.137,27.3973,])
array_1_name = "Popularity of the first name Maggie"
array_2_name = "Air pollution in Terre Haute, Indiana"

# 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 Maggie
Line chart for only Air pollution in Terre Haute, Indiana
AI-generated correlation image
The spurious research paper: Nitrogen Oxide, Nitrogen You: The Maggie-tude of Popularity in Relation to Air Quality in Terre Haute, Indiana

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Correlation ID: 3499 · Black Variable ID: 2491 · Red Variable ID: 21335


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