Spurious correlation #3,168 · 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 Dusty and the second variable is Air pollution in Toledo. The chart goes from 1980 to 2022, and the two variables track closely in value over that time.

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

Download png, svg

AI explanation

As fewer babies were named Dusty, there were fewer fans of dusty, old cars, leading to a decrease in their usage and ultimately reducing air pollution in Toledo. It seems the Dusty name just couldn't help but leave the air a little cleaner in the end!

^{Show image generation prompt} Model: dalle-3
Prompt: An image that looks like it is a scene from a Pixar movie, depicting a serene landscape in Toledo. Fewer whimsically named characters with Dusty as the focal point, meandering through a field of fluffy dandelions. The clean air envelops the scene, illustrating industrious ants diligently at work, filtering pollution particles from the atmosphere. The setting is simple, with warm, inviting colors, and an emphasis on the tranquil connection between nature and the characters. 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 Dusty and Air pollution in Toledo. 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: a meme Cutsy graphics Data cyber art A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s An image that looks like it is a scene from a Pixar movie
ChatGPT: An image that looks like it is a scene from a Pixar movie

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 Dusty and Air pollution in Toledo, in the following situation: Because the decrease in popularity of the name Dusty led to fewer people in Toledo sneezing simultaneously, which reduced air turbulence and kept pollution particles closer to the ground where they could be filtered out by dandelions and industrious ants.. Keep the description simple.
ChatGPT: In Toledo, fewer people named Dusty strolling amidst the dandelions mirrored cleaner air that nestled closely to the ground, where industrious ants diligently toiled to filter out pollution particles.

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: [ An image that looks like it is a scene from a Pixar movie ] and depicting this scene: In Toledo, fewer people named Dusty strolling amidst the dandelions mirrored cleaner air that nestled closely to the ground, where industrious ants diligently toiled to filter out pollution particles. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: An image that looks like it is a scene from a Pixar movie, depicting a serene landscape in Toledo. Fewer whimsically named characters with Dusty as the focal point, meandering through a field of fluffy dandelions. The clean air envelops the scene, illustrating industrious ants diligently at work, filtering pollution particles from the atmosphere. The setting is simple, with warm, inviting colors, and an emphasis on the tranquil connection between nature and the characters.

*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 a decrease in Popularity of the first name Dusty caused Air pollution in Toledo to decrease. Include one good pun.

AI academic paper

(Because p < 0.01)

Dusty Connections: Exploring the Link Between the Popularity of the Name Dusty and Air Pollution in Toledo

The Journal of Unlikely Correlations

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Popularity of the first name Dusty and Air pollution in Toledo. Make lots of jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
"Dusty Connections: Exploring the Link Between the Popularity of the Name Dusty and Air Pollution in Toledo"

[[ABSTRACT]]
This study delves into the whimsical world of first names and air quality by examining the correlation between the prevalence of the moniker “Dusty” and levels of airborne particles in Toledo. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, a correlation coefficient of 0.7560970 and p < 0.01 were uncovered for the period spanning 1980 to 2022. The findings reveal a surprisingly robust association between the popularity of the name "Dusty" and the presence of environmental dustiness, sparking curiosity about the underlying mechanisms behind this peculiar relationship. While the causal pathway remains a dusty mystery, this research offers a lighthearted yet intriguing insight into the potential influence of nomenclature on atmospheric conditions.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The connection between a person's name and their destiny has long fascinated scholars and laypeople alike. From the fortune-telling implications of "Crystal" to the musical inclination of "Melody," there seems to be a certain serendipitous alignment between nomenclature and life's trajectory. In this context, the name "Dusty" evokes visions of open plains, cowboy boots, and perhaps a touch of nostalgia for some. However, could there be more to this name than meets the eye, or should we say, the dust particle?
In the bustling city of Toledo, Ohio, where industrial prowess meets the tranquility of Lake Erie, a peculiar correlation has been unearthed. It appears that the more individuals are christened "Dusty," the more particles of dust and other airborne pollutants seem to permeate the skies. While this discovery may initially seem as whimsical as cotton candy in a tornado, the empirical evidence paints a startling picture.
Drawing on data from the US Social Security Administration and the Environmental Protection Agency, this study investigates the intriguing relationship between the popularity of the first name "Dusty" and air pollution levels in Toledo. The correlation coefficient of 0.7560970 and statistically significant p-value (p < 0.01) indicate a robust association between these seemingly disparate phenomena. This finding prompts us to peer through the dusty veil of happenstance and ponder the underlying mechanisms at play.
While some may dismiss this correlation as a mere coincidence, the larger-than-expected effect size beckons us to consider potential explanations. Could it be that the frequency of "Dusty" adorning birth certificates exerts an inadvertent influence on local environmental conditions? Might there be subtle forces at work, involving the name "Dusty" as a harbinger of atmospheric dustiness?
As we embark on this scholarly expedition into the uncharted territory of nomenclatural whimsy, let us approach the ensuing analysis with both humor and inquiry. For hidden within the dust clouds of Toledo, there may lie an unprecedented revelation about the unforeseen consequence of a name.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Numerous scholarly inquiries have probed the enthralling nexus between nomenclature and its purported influence on diverse aspects of human experience. Smith and Doe (2010) endeavored to unravel the enigmatic bond between personal monikers and life trajectories, postulating the existence of subtle yet persistent effects. Jones et al. (2015) delved into the psychological ramifications of individuals' names, proposing that appellations may shape cognition and behavior in inconspicuous ways.

In "The Geography of Names," Jones (2000) scrutinized regional variations in personal naming practices, shedding light on the intriguing dynamics of name popularity across different locales. Meanwhile, "The Name of the Wind" by Rothfuss (2007) captivated readers with its mystical account of a protagonist whose very name holds profound significance in shaping his destiny.

In the realm of internet culture, the "Distracted Boyfriend" meme has humorously captured the notion of unexpected attractions, much like the surprising correlation between the prevalence of the name "Dusty" and atmospheric dustiness in Toledo.

Now, turning to the realm of environmental quality, "Silent Spring" by Carson (1962) served as a pioneering exposé on the pernicious effects of environmental degradation, prompting a global awakening to the plight of air and water pollution. On a more whimsical note, "Cloudy with a Chance of Meatballs" by Barrett (1978) playfully contemplated the fantastical implications of unconventional meteorological phenomena, albeit unrelated to the specific correlation under scrutiny.

Despite the seemingly improbable connection between the popularity of the name "Dusty" and air pollution levels in Toledo, the current investigation embarks on a scholarly pursuit of uncovering the underlying mechanisms behind this quirky relationship. As we venture forth with the requisite rigor and a pinch of levity, the improbable linkage between nomenclature and atmospheric phenomena beckons us to tread cautiously, lest we stir up any more dusty surprises.

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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Popularity of the first name Dusty and Air pollution in Toledo. Make lots of 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 1980 to 2022

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Dusty Connections: Exploring the Link Between the Popularity of the Name Dusty and Air Pollution in Toledo"

[[ABSTRACT]]
This study delves into the whimsical world of first names and air quality by examining the correlation between the prevalence of the moniker “Dusty” and levels of airborne particles in Toledo. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, a correlation coefficient of 0.7560970 and p < 0.01 were uncovered for the period spanning 1980 to 2022. The findings reveal a surprisingly robust association between the popularity of the name "Dusty" and the presence of environmental dustiness, sparking curiosity about the underlying mechanisms behind this peculiar relationship. While the causal pathway remains a dusty mystery, this research offers a lighthearted yet intriguing insight into the potential influence of nomenclature on atmospheric conditions.

[[INTRODUCTION]]
The connection between a person's name and their destiny has long fascinated scholars and laypeople alike. From the fortune-telling implications of "Crystal" to the musical inclination of "Melody," there seems to be a certain serendipitous alignment between nomenclature and life's trajectory. In this context, the name "Dusty" evokes visions of open plains, cowboy boots, and perhaps a touch of nostalgia for some. However, could there be more to this name than meets the eye, or should we say, the dust particle?
In the bustling city of Toledo, Ohio, where industrial prowess meets the tranquility of Lake Erie, a peculiar correlation has been unearthed. It appears that the more individuals are christened "Dusty," the more particles of dust and other airborne pollutants seem to permeate the skies. While this discovery may initially seem as whimsical as cotton candy in a tornado, the empirical evidence paints a startling picture.
Drawing on data from the US Social Security Administration and the Environmental Protection Agency, this study investigates the intriguing relationship between the popularity of the first name "Dusty" and air pollution levels in Toledo. The correlation coefficient of 0.7560970 and statistically significant p-value (p < 0.01) indicate a robust association between these seemingly disparate phenomena. This finding prompts us to peer through the dusty veil of happenstance and ponder the underlying mechanisms at play.
While some may dismiss this correlation as a mere coincidence, the larger-than-expected effect size beckons us to consider potential explanations. Could it be that the frequency of "Dusty" adorning birth certificates exerts an inadvertent influence on local environmental conditions? Might there be subtle forces at work, involving the name "Dusty" as a harbinger of atmospheric dustiness?
As we embark on this scholarly expedition into the uncharted territory of nomenclatural whimsy, let us approach the ensuing analysis with both humor and inquiry. For hidden within the dust clouds of Toledo, there may lie an unprecedented revelation about the unforeseen consequence of a name.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

The present study employed a meticulously crafted and, some might say, delightfully unconventional methodology in order to investigate the purported connection between the popularity of the first name "Dusty" and air pollution levels in Toledo. The data collection process entailed an extensive trawl through the archives of the US Social Security Administration, which bestowed upon us a treasure trove of nomenclatural trends spanning the years 1980 to 2022. This period allowed for a comprehensive examination of the ebb and flow of "Dusty" as a chosen appellation across different epochs, each bearing its own unique atmospheric nuances.

Upon triumphantly securing the historical nomenclatural data, our research team imparted upon itself the noble responsibility of seeking out the atmospheric intricacies in the environs of Toledo. With the solemnity of a scholar and the enthusiasm of a miner digging for gold, we delved into the Environmental Protection Agency's records, sifting through the minutiae of airborne particulate matter and gaseous emissions. This endeavor required the deployment of highly sophisticated algorithms, which operated akin to a prospector panning for name-dust correlations within the pollutant-laden streams of atmospheric data.

The theoretical underpinning of this study stemmed from the notion that the prevalence of the name "Dusty" might exert an unforeseen gravitational pull on environmental dustiness, as if the mere utterance of this appellation could summon airborne particles to waltz through the Toledo skies with an unanticipated fervor. By adopting a time-series approach, we endeavored to capture the undulating tides of nomenclatural prominence and atmospheric opacity, teasing out any underlying patterns that could lay bare the dust-laden dance between a name and the particles it may inadvertently conjure.

Once the data sets were secured, the correlation analysis unfolded with the solemn precision of a waltz between two seemingly incongruent partners. This statistical ballet revealed a correlation coefficient of 0.7560970, accompanied by a p-value of less than 0.01, lending considerable weight to the parallel rise and fall of "Dusty" and atmospheric dustiness. The observed coherence compelled us to contemplate the tantalizing possibility of a hidden force at play, wherein the mere phonetics of a name could cast a whimsical spell on the very fabric of Toledo's aerial ambience.

To fortify our findings and ensure the robustness of the observed correlation, we employed stringent sensitivity analyses and diagnostic tests, akin to subjecting a captivating magic trick to the scrutiny of the discerning eye. The result was an unyielding affirmation of the serendipitous alliance between the popularity of "Dusty" and the atmospheric particulates that grace Toledo's atmosphere.

In summary, our unorthodox yet whimsically rigorous methodology bore testament to the indelible interconnectedness of nomenclature and atmospheric reality, unearthing a correlation that challenges preconceived notions and emboldens us to embrace the delightful unpredictability of scholarly exploration.

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

Please make up the results section of an academic research paper presenting the findings of the connection between Popularity of the first name Dusty and Air pollution in Toledo. Make lots of 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 1980 to 2022, you found a correlation 0.7560970, r-squared of 0.5716826, 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]]
"Dusty Connections: Exploring the Link Between the Popularity of the Name Dusty and Air Pollution in Toledo"

[[ABSTRACT]]
This study delves into the whimsical world of first names and air quality by examining the correlation between the prevalence of the moniker “Dusty” and levels of airborne particles in Toledo. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, a correlation coefficient of 0.7560970 and p < 0.01 were uncovered for the period spanning 1980 to 2022. The findings reveal a surprisingly robust association between the popularity of the name "Dusty" and the presence of environmental dustiness, sparking curiosity about the underlying mechanisms behind this peculiar relationship. While the causal pathway remains a dusty mystery, this research offers a lighthearted yet intriguing insight into the potential influence of nomenclature on atmospheric conditions.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The connection between a person's name and their destiny has long fascinated scholars and laypeople alike. From the fortune-telling implications of "Crystal" to the musical inclination of "Melody," there seems to be a certain serendipitous alignment between nomenclature and life's trajectory. In this context, the name "Dusty" evokes visions of open plains, cowboy boots, and perhaps a touch of nostalgia for some. However, could there be more to this name than meets the eye, or should we say, the dust particle?
In the bustling city of Toledo, Ohio, where industrial prowess meets the tranquility of Lake Erie, a peculiar correlation has been unearthed. It appears that the more individuals are christened "Dusty," the more particles of dust and other airborne pollutants seem to permeate the skies. While this discovery may initially seem as whimsical as cotton candy in a tornado, the empirical evidence paints a startling picture.
Drawing on data from the US Social Security Administration and the Environmental Protection Agency, this study investigates the intriguing relationship between the popularity of the first name "Dusty" and air pollution levels in Toledo. The correlation coefficient of 0.7560970 and statistically significant p-value (p < 0.01) indicate a robust association between these seemingly disparate phenomena. This finding prompts us to peer through the dusty veil of happenstance and ponder the underlying mechanisms at play.
While some may dismiss this correlation as a mere coincidence, the larger-than-expected effect size beckons us to consider potential explanations. Could it be that the frequency of "Dusty" adorning birth certificates exerts an inadvertent influence on local environmental conditions? Might there be subtle forces at work, involving the name "Dusty" as a harbinger of atmospheric dustiness?
As we embark on this scholarly expedition into the uncharted territory of nomenclatural whimsy, let us approach the ensuing analysis with both humor and inquiry. For hidden within the dust clouds of Toledo, there may lie an unprecedented revelation about the unforeseen consequence of a name.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The analysis revealed a notably strong correlation between the prevalence of the name "Dusty" and levels of airborne particles in Toledo. The correlation coefficient of 0.7560970 suggests a robust positive relationship, indicating that as the popularity of the name "Dusty" increased, so did the levels of air pollution in the region over the period from 1980 to 2022.

Furthermore, the r-squared value of 0.5716826 highlights that approximately 57.17% of the variation in air pollution levels can be explained by the prevalence of the name "Dusty." This finding underscores the substantial influence that the seemingly whimsical choice of a name can have on environmental conditions, as if the winds of fate are indeed intertwined with the dust particles in the air.

The statistically significant p-value of less than 0.01 provides strong evidence against the null hypothesis, indicating that the observed correlation is unlikely to be a chance occurrence. It seems that there is more to the connection between the name "Dusty" and atmospheric dustiness than meets the eye, or perhaps, lingers in the air.

The scatterplot presented in Fig. 1 (see below) vividly illustrates the positive correlation between the two variables, with each dot representing a year's data point. The clustering of the data points along a clear ascending trajectory embodies the harmony of nomenclature and air quality, as if the very essence of the name "Dusty" permeates the environmental landscape of Toledo.

In conclusion, the findings of this investigation shed light on the unexpected link between the prevalence of the name "Dusty" and air pollution levels in Toledo. While the exact causal mechanisms behind this association remain shrouded in the proverbial dust cloud, the results spark curiosity and laughter in equal measure, leaving researchers and readers alike with a feeling of amused wonderment.

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Popularity of the first name Dusty and Air pollution in Toledo. Make lots of 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]]
"Dusty Connections: Exploring the Link Between the Popularity of the Name Dusty and Air Pollution in Toledo"

[[ABSTRACT]]
This study delves into the whimsical world of first names and air quality by examining the correlation between the prevalence of the moniker “Dusty” and levels of airborne particles in Toledo. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, a correlation coefficient of 0.7560970 and p < 0.01 were uncovered for the period spanning 1980 to 2022. The findings reveal a surprisingly robust association between the popularity of the name "Dusty" and the presence of environmental dustiness, sparking curiosity about the underlying mechanisms behind this peculiar relationship. While the causal pathway remains a dusty mystery, this research offers a lighthearted yet intriguing insight into the potential influence of nomenclature on atmospheric conditions.

[[LITERATURE REVIEW]]
Numerous scholarly inquiries have probed the enthralling nexus between nomenclature and its purported influence on diverse aspects of human experience. Smith and Doe (2010) endeavored to unravel the enigmatic bond between personal monikers and life trajectories, postulating the existence of subtle yet persistent effects. Jones et al. (2015) delved into the psychological ramifications of individuals' names, proposing that appellations may shape cognition and behavior in inconspicuous ways.
In "The Geography of Names," Jones (2000) scrutinized regional variations in personal naming practices, shedding light on the intriguing dynamics of name popularity across different locales. Meanwhile, "The Name of the Wind" by Rothfuss (2007) captivated readers with its mystical account of a protagonist whose very name holds profound significance in shaping his destiny.
In the realm of internet culture, the "Distracted Boyfriend" meme has humorously captured the notion of unexpected attractions, much like the surprising correlation between the prevalence of the name "Dusty" and atmospheric dustiness in Toledo.
Now, turning to the realm of environmental quality, "Silent Spring" by Carson (1962) served as a pioneering exposé on the pernicious effects of environmental degradation, prompting a global awakening to the plight of air and water pollution. On a more whimsical note, "Cloudy with a Chance of Meatballs" by Barrett (1978) playfully contemplated the fantastical implications of unconventional meteorological phenomena, albeit unrelated to the specific correlation under scrutiny.
Despite the seemingly improbable connection between the popularity of the name "Dusty" and air pollution levels in Toledo, the current investigation embarks on a scholarly pursuit of uncovering the underlying mechanisms behind this quirky relationship. As we venture forth with the requisite rigor and a pinch of levity, the improbable linkage between nomenclature and atmospheric phenomena beckons us to tread cautiously, lest we stir up any more dusty surprises.

[[RESULTS]]
The analysis revealed a notably strong correlation between the prevalence of the name "Dusty" and levels of airborne particles in Toledo. The correlation coefficient of 0.7560970 suggests a robust positive relationship, indicating that as the popularity of the name "Dusty" increased, so did the levels of air pollution in the region over the period from 1980 to 2022.
Furthermore, the r-squared value of 0.5716826 highlights that approximately 57.17% of the variation in air pollution levels can be explained by the prevalence of the name "Dusty." This finding underscores the substantial influence that the seemingly whimsical choice of a name can have on environmental conditions, as if the winds of fate are indeed intertwined with the dust particles in the air.
The statistically significant p-value of less than 0.01 provides strong evidence against the null hypothesis, indicating that the observed correlation is unlikely to be a chance occurrence. It seems that there is more to the connection between the name "Dusty" and atmospheric dustiness than meets the eye, or perhaps, lingers in the air.
The scatterplot presented in Fig. 1 (see below) vividly illustrates the positive correlation between the two variables, with each dot representing a year's data point. The clustering of the data points along a clear ascending trajectory embodies the harmony of nomenclature and air quality, as if the very essence of the name "Dusty" permeates the environmental landscape of Toledo.
In conclusion, the findings of this investigation shed light on the unexpected link between the prevalence of the name "Dusty" and air pollution levels in Toledo. While the exact causal mechanisms behind this association remain shrouded in the proverbial dust cloud, the results spark curiosity and laughter in equal measure, leaving researchers and readers alike with a feeling of amused wonderment.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of the current study have provided empirical support for the seemingly whimsical yet surprisingly robust correlation between the popularity of the name "Dusty" and levels of air pollution in Toledo. These findings align with prior research that has delved into the intriguing influence of nomenclature on various aspects of human experience. Smith and Doe's (2010) exploration of the subtle yet persistent effects of personal monikers resonates with the current investigation, as it underlines the potential impact of a name on the environmental conditions within a specific geographic region. Likewise, Jones et al.'s (2015) proposition that appellations may shape cognition and behavior in inconspicuous ways finds resonance in the striking correlation uncovered in this study, hinting at the unassuming yet tangible influence of the name "Dusty" on atmospheric dustiness in Toledo.

The literature review previously highlighted the unexpected connections that can emerge from the study of personal names, drawing parallels between the quirky correlation under investigation and seemingly unrelated phenomena such as internet memes and works of fantastical fiction. While these comparisons may appear playful in nature, they surprisingly offer insights into the multidimensionality of the relationship between nomenclature and atmospheric phenomena. Furthermore, the nod to environmental quality literature, including Carson's (1962) groundbreaking work on environmental degradation and Barrett's (1978) whimsical contemplation of unconventional meteorological phenomena, serves as a reminder that the synthesis of seemingly disparate domains can yield unforeseen associations, much like the peculiar correlation between the name "Dusty" and air pollution levels in Toledo.

The statistically significant correlation coefficient and p-value observed in the current study substantiate the existence of a genuine and substantial linkage between the prevalence of the name "Dusty" and atmospheric dustiness, challenging traditional notions of causality and prompting a reevaluation of the potential factors contributing to air quality variations. The r-squared value further underscores the considerable influence exerted by the name "Dusty" on air pollution levels, highlighting the widespread impact of nomenclature on environmental conditions.

As we navigate the deluge of data and dust particles, the present findings compel us to consider the enduring impact of first names on unexpected domains, reminding us that even the seemingly trivial choice of a name can hold sway over the atmospheric landscape. This investigation marks a departure from conventional inquiries into air pollution, infusing a lighthearted yet thought-provoking dimension into the discourse surrounding environmental factors. The convergence of the serious and the whimsical in this study invites further exploration into the interplay of nomenclature and atmospheric dynamics, beckoning researchers to peer through the proverbial dust cloud and unearth the hidden connections between names and environmental phenomena.

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Popularity of the first name Dusty and Air pollution in Toledo. Make lots of 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]]
"Dusty Connections: Exploring the Link Between the Popularity of the Name Dusty and Air Pollution in Toledo"

[[ABSTRACT]]
This study delves into the whimsical world of first names and air quality by examining the correlation between the prevalence of the moniker “Dusty” and levels of airborne particles in Toledo. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, a correlation coefficient of 0.7560970 and p < 0.01 were uncovered for the period spanning 1980 to 2022. The findings reveal a surprisingly robust association between the popularity of the name "Dusty" and the presence of environmental dustiness, sparking curiosity about the underlying mechanisms behind this peculiar relationship. While the causal pathway remains a dusty mystery, this research offers a lighthearted yet intriguing insight into the potential influence of nomenclature on atmospheric conditions.

[[INTRDUCTION]]
The connection between a person's name and their destiny has long fascinated scholars and laypeople alike. From the fortune-telling implications of "Crystal" to the musical inclination of "Melody," there seems to be a certain serendipitous alignment between nomenclature and life's trajectory. In this context, the name "Dusty" evokes visions of open plains, cowboy boots, and perhaps a touch of nostalgia for some. However, could there be more to this name than meets the eye, or should we say, the dust particle?
In the bustling city of Toledo, Ohio, where industrial prowess meets the tranquility of Lake Erie, a peculiar correlation has been unearthed. It appears that the more individuals are christened "Dusty," the more particles of dust and other airborne pollutants seem to permeate the skies. While this discovery may initially seem as whimsical as cotton candy in a tornado, the empirical evidence paints a startling picture.
Drawing on data from the US Social Security Administration and the Environmental Protection Agency, this study investigates the intriguing relationship between the popularity of the first name "Dusty" and air pollution levels in Toledo. The correlation coefficient of 0.7560970 and statistically significant p-value (p < 0.01) indicate a robust association between these seemingly disparate phenomena. This finding prompts us to peer through the dusty veil of happenstance and ponder the underlying mechanisms at play.
While some may dismiss this correlation as a mere coincidence, the larger-than-expected effect size beckons us to consider potential explanations. Could it be that the frequency of "Dusty" adorning birth certificates exerts an inadvertent influence on local environmental conditions? Might there be subtle forces at work, involving the name "Dusty" as a harbinger of atmospheric dustiness?
As we embark on this scholarly expedition into the uncharted territory of nomenclatural whimsy, let us approach the ensuing analysis with both humor and inquiry. For hidden within the dust clouds of Toledo, there may lie an unprecedented revelation about the unforeseen consequence of a name.

[[RESULTS]]
The analysis revealed a notably strong correlation between the prevalence of the name "Dusty" and levels of airborne particles in Toledo. The correlation coefficient of 0.7560970 suggests a robust positive relationship, indicating that as the popularity of the name "Dusty" increased, so did the levels of air pollution in the region over the period from 1980 to 2022.
Furthermore, the r-squared value of 0.5716826 highlights that approximately 57.17% of the variation in air pollution levels can be explained by the prevalence of the name "Dusty." This finding underscores the substantial influence that the seemingly whimsical choice of a name can have on environmental conditions, as if the winds of fate are indeed intertwined with the dust particles in the air.
The statistically significant p-value of less than 0.01 provides strong evidence against the null hypothesis, indicating that the observed correlation is unlikely to be a chance occurrence. It seems that there is more to the connection between the name "Dusty" and atmospheric dustiness than meets the eye, or perhaps, lingers in the air.
The scatterplot presented in Fig. 1 (see below) vividly illustrates the positive correlation between the two variables, with each dot representing a year's data point. The clustering of the data points along a clear ascending trajectory embodies the harmony of nomenclature and air quality, as if the very essence of the name "Dusty" permeates the environmental landscape of Toledo.
In conclusion, the findings of this investigation shed light on the unexpected link between the prevalence of the name "Dusty" and air pollution levels in Toledo. While the exact causal mechanisms behind this association remain shrouded in the proverbial dust cloud, the results spark curiosity and laughter in equal measure, leaving researchers and readers alike with a feeling of amused wonderment.

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Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, the exploration into the connection between the popularity of the first name "Dusty" and air pollution levels in Toledo has unveiled a surprisingly robust correlation. The findings suggest that as the prevalence of the name "Dusty" increased, so did the levels of airborne particles, lending new meaning to the phrase "dust in the wind." This correlation prompts both mirth and speculation, fostering an air of both bemusement and scientific inquiry.

While the mechanisms underlying this association remain as enigmatic as a dust bunny under the bed, the statistical evidence leaves little room for doubt regarding the existence of this intriguing relationship. The scatterplot depicting the positive correlation between the variables resembles a celestial dance, as if the name "Dusty" whispers through the wind, shaping the very environment it inhabits.

The unexpected nature of these findings invites us to consider the potential influences that nomenclature may wield over atmospheric conditions. Could it be that the mere mention of the name "Dusty" is enough to conjure an uptick in dustiness, or perhaps the very act of christening bestows an atmospheric legacy?

In light of these revelations, it is evident that this research opens the door to a realm of whimsical wonder, encouraging further exploration into the influence of names on environmental phenomena. However, for now, it seems that the dusty secrets of the connection between the name "Dusty" and air pollution have been sufficiently dusted off. It may be time to let the dust settle and turn our attention to other, less whimsical but equally compelling research pursuits. No further research into this particular connection is necessary, as it has been thoroughly (and humorously) dusted off.

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 Dusty Connections: Exploring the Link Between the Popularity of the Name Dusty and Air Pollution in Toledo. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Unlikely Correlations

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 Dusty Connections: Exploring the Link Between the Popularity of the Name Dusty and Air Pollution in Toledo. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Environmental Naming Patterns

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 Dusty Connections: Exploring the Link Between the Popularity of the Name Dusty and Air Pollution in Toledo with an abstract of This study delves into the whimsical world of first names and air quality by examining the correlation between the prevalence of the moniker “Dusty” and levels of airborne particles in Toledo. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, a correlation coefficient of 0.7560970 and p < 0.01 were uncovered for the period spanning 1980 to 2022. The findings reveal a surprisingly robust association between the popularity of the name "Dusty" and the presence of environmental dustiness, sparking curiosity about the underlying mechanisms behind this peculiar relationship. While the causal pathway remains a dusty mystery, this research offers a lighthearted yet intriguing insight into the potential influence of nomenclature on atmospheric conditions.

ChatGPT:

"Dusty name popularity," "air pollution correlation," "Toledo airborne particles," "US Social Security Administration data," "Environmental Protection Agency air quality," "correlation coefficient," "causal pathway air quality," "nomenclature influence on atmosphere"

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

Air pollution in Toledo
Detailed data title: Percentage of days 'unhealthy' or worse air quality in Toledo, OH
Source: Environmental Protection Agency
See what else correlates with Air pollution in Toledo

Correlation r = 0.7560970 (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 = 0.5716826 (Coefficient of determination)
This means 57.2% of the change in the one variable (i.e., Air pollution in Toledo) is predictable based on the change in the other (i.e., Popularity of the first name Dusty) over the 43 years from 1980 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 4.6E-9.^Show 0.0000000045524204224957070000
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 0.76 in 4.6E-7% of random cases. Said differently, if you correlated 219,663,367 random variables^Note You don't actually need 219 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 42 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 42 because we have two variables measured over a period of 43 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.59, 0.86 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	1980	1981	1982	1983	1984	1985	1986	1987	1988	1989	1990	1991	1992	1993	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Popularity of the first name Dusty (Babies born)	784	830	631	438	422	446	445	506	438	308	304	223	175	263	325	283	236	224	180	170	155	130	122	113	114	127	97	99	81	87	75	47	66	62	56	64	51	44	46	50	53	47	64
Air pollution in Toledo (Bad air quality days)	6.28415	6.30137	6.0274	4.65753	0.892857	0.821918	1.09589	1.36986	7.65027	2.19178	0.821918	1.64384	0.547945	1.64384	2.19178	2.46575	3.00546	1.09589	1.64384	2.19178	0.273973	3.0137	4.10959	1.64384	0.273224	1.64384	0	1.36986	0	0.273973	0.277778	0	0.819672	0	0	0	0	0	0.287356	0	0	0	0

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.
Outlandish outliers: There are "outliers" in this data.^Note In concept, "outlier" just means "way different than the rest of your dataset." When calculating a correlation like this, they are particularly impactful because a single outlier can substantially increase your correlation.

For the purposes of this project, I counted a point as an outlier if it the residual was two standard deviations from the mean.

(This bullet point only shows up in the details page on charts that do, in fact, have outliers.)
They stand out on the scatterplot above: notice the dots that are far away from any other dots. I intentionally mishandeled outliers, which makes the correlation look extra strong.

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([784,830,631,438,422,446,445,506,438,308,304,223,175,263,325,283,236,224,180,170,155,130,122,113,114,127,97,99,81,87,75,47,66,62,56,64,51,44,46,50,53,47,64,])
array_2 = np.array([6.28415,6.30137,6.0274,4.65753,0.892857,0.821918,1.09589,1.36986,7.65027,2.19178,0.821918,1.64384,0.547945,1.64384,2.19178,2.46575,3.00546,1.09589,1.64384,2.19178,0.273973,3.0137,4.10959,1.64384,0.273224,1.64384,0,1.36986,0,0.273973,0.277778,0,0.819672,0,0,0,0,0,0.287356,0,0,0,0,])
array_1_name = "Popularity of the first name Dusty"
array_2_name = "Air pollution in Toledo"

# 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 Dusty
Line chart for only Air pollution in Toledo
AI-generated correlation image
The spurious research paper: Dusty Connections: Exploring the Link Between the Popularity of the Name Dusty and Air Pollution in Toledo

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Correlation ID: 3168 · Black Variable ID: 3489 · Red Variable ID: 21339


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