Download png, svg
AI explanation
Fewer Dawns meant a later rise, giving smog a bit less time to shine!Model: dalle-3
Prompt: Prompt: [ A photo-realistic image ] In Anchorage, as the popularity of the name Dawn decreased, the streets gradually quieted at dawn. Fewer cars could be seen on the roads as less people woke up early to catch the sunrise. With the decrease in traffic, the air in Anchorage became cleaner, and the morning sky began to show signs of reduced pollution. Enhanced Visual: A serene cityscape of Anchorage at dawn, with empty roads and a soft, pollution-free morning sky as the backdrop. The subtle light of the breaking dawn gently illuminates the buildings, creating a peaceful and tranquil atmosphere. The absence of car traffic contributes to the silence of the streets, emphasizing the calm and stillness of the early morning - a visual representation of the decreasing popularity of the name Dawn in the city. 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 Dawn and Air pollution in Anchorage. 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: Woodblock painting Surrealism A photo-realistic image Charcoal Parallax art
ChatGPT: A photo-realistic image
Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Popularity of the first name Dawn and Air pollution in Anchorage, in the following situation: As the popularity of the name Dawn decreased, fewer babies were born with that name, leading to a decrease in the number of people waking up early to watch the sunrise, resulting in less traffic and lower air pollution in Anchorage.. Keep the description simple.
ChatGPT: In Anchorage, as the popularity of the name Dawn decreased, the streets gradually quieted at dawn. Fewer cars could be seen on the roads as less people woke up early to catch the sunrise. With the decrease in traffic, the air in Anchorage became cleaner, and the morning sky began to show signs of reduced 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 photo-realistic image ] and depicting this scene: In Anchorage, as the popularity of the name Dawn decreased, the streets gradually quieted at dawn. Fewer cars could be seen on the roads as less people woke up early to catch the sunrise. With the decrease in traffic, the air in Anchorage became cleaner, and the morning sky began to show signs of reduced pollution. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: [ A photo-realistic image ] In Anchorage, as the popularity of the name Dawn decreased, the streets gradually quieted at dawn. Fewer cars could be seen on the roads as less people woke up early to catch the sunrise. With the decrease in traffic, the air in Anchorage became cleaner, and the morning sky began to show signs of reduced pollution. Enhanced Visual: A serene cityscape of Anchorage at dawn, with empty roads and a soft, pollution-free morning sky as the backdrop. The subtle light of the breaking dawn gently illuminates the buildings, creating a peaceful and tranquil atmosphere. The absence of car traffic contributes to the silence of the streets, emphasizing the calm and stillness of the early morning - a visual representation of the decreasing popularity of the name Dawn in the city.
*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.
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 Dawn caused Air pollution in Anchorage to decrease. Include one good pun.
AI academic paper
Breath of Fresh Dawn: The Polluted Origins of a Name The Journal of Linguistic Ecology Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between Popularity of the first name Dawn and Air pollution in Anchorage. Make lots of jokes, goofy observations, and puns.
Make the title seem clever.
Your research team used data from US Social Security Administration and Environmental Protection Agency to assess this nagging question. You found a correlation coefficient of 0.8981184 and p < 0.01 for 1980 to 2021.
Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)
[[TITLE]]
Lorem ipsum dolor sit
[[ABSTRACT]]
Lorem ipsum dolor sit
ChatGPT:
[[TITLE]]
Breath of Fresh Dawn: The Polluted Origins of a Name
[[ABSTRACT]]
In this study, we unveil a correlation between the popularity of the first name Dawn and air pollution levels in Anchorage. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, we delve into the surprising and, one might say, aromatic relationship between a common name and the quality of the air. Our findings reveal a statistically robust connection, with a correlation coefficient of 0.8981184 and p < 0.01 between the years 1980 and 2021. We discuss the implications of these findings, pondering whether there might be a celestial explanation for this atmospheric association. Our research challenges the notion that a name is only an identity marker and raises the possibility that it might also carry fragrant hints of environmental destiny.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the introduction section of an academic research paper presenting the findings of the connection between Popularity of the first name Dawn and Air pollution in Anchorage. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Here is the title and abstract of the paper:
[[TITLE]]
Breath of Fresh Dawn: The Polluted Origins of a Name
[[ABSTRACT]]
In this study, we unveil a correlation between the popularity of the first name Dawn and air pollution levels in Anchorage. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, we delve into the surprising and, one might say, aromatic relationship between a common name and the quality of the air. Our findings reveal a statistically robust connection, with a correlation coefficient of 0.8981184 and p < 0.01 between the years 1980 and 2021. We discuss the implications of these findings, pondering whether there might be a celestial explanation for this atmospheric association. Our research challenges the notion that a name is only an identity marker and raises the possibility that it might also carry fragrant hints of environmental destiny.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
Socrates once said, "The only true wisdom is in knowing you know nothing." However, he clearly didn't have access to the groundbreaking research we are about to present. In the annals of scholarly exploration, one might expect to stumble upon discoveries about the cosmos, the mysteries of the ocean depths, or the inner workings of the human mind. But here, dear readers, we bring you an unexpected and rather pungent revelation: the aromatic interplay between the popularity of the first name Dawn and the air quality in Anchorage.
Drawing from the eclectic blend of data from the US Social Security Administration and the Environmental Protection Agency, we set out on a marvelous adventure - like intrepid explorers in a fog of statistical intrigue. Picture this: a journey through the misty haze of correlation coefficients and p-values, armed with nothing but our trusty laptops and the insatiable thirst for uncovering connections others might dismiss as sheer coincidence.
The titular Dawn, holding the promise of a new beginning from the crack of dawn to the twilight, has long been embraced as a symbol of hope and renewal. But little did we know that this name may also carry a clouds-of-concern kind of significance. With a correlation coefficient of 0.8981184 and a p-value that would make even the most skeptical eyebrows raise, our findings don't just hint at a connection; they practically shout it from the smog-covered rooftops.
So, what does this all mean, you might wonder? Is there a cosmic clue lurking amidst the fumes, suggesting that the universe conspires to shape the fate of the air and the destinies of those bearing the name Dawn? Or perhaps, there's a more practical explanation - one that involves years of data, rigorous analysis, and a lot of head-scratching over what on earth (or in the air, to be precise) could be causing this correlation.
In this paper, we embark on an odyssey into the uncharted territory of name-based air quality association, challenging conventional wisdom and introducing a dash of humor into the often-serious world of academic research. Prepare to be enchanted, amused, and somewhat perplexed - for the journey ahead promises to be as enlightening as it is unexpectedly fragrant.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Dawn and Air pollution in Anchorage. 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 cite some social media posts you read that seem to be related.
Here is the title and abstract of the paper:
[[TITLE]]
Breath of Fresh Dawn: The Polluted Origins of a Name
[[ABSTRACT]]
In this study, we unveil a correlation between the popularity of the first name Dawn and air pollution levels in Anchorage. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, we delve into the surprising and, one might say, aromatic relationship between a common name and the quality of the air. Our findings reveal a statistically robust connection, with a correlation coefficient of 0.8981184 and p < 0.01 between the years 1980 and 2021. We discuss the implications of these findings, pondering whether there might be a celestial explanation for this atmospheric association. Our research challenges the notion that a name is only an identity marker and raises the possibility that it might also carry fragrant hints of environmental destiny.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Socrates once said, "The only true wisdom is in knowing you know nothing." However, he clearly didn't have access to the groundbreaking research we are about to present. In the annals of scholarly exploration, one might expect to stumble upon discoveries about the cosmos, the mysteries of the ocean depths, or the inner workings of the human mind. But here, dear readers, we bring you an unexpected and rather pungent revelation: the aromatic interplay between the popularity of the first name Dawn and the air quality in Anchorage.
Drawing from the eclectic blend of data from the US Social Security Administration and the Environmental Protection Agency, we set out on a marvelous adventure - like intrepid explorers in a fog of statistical intrigue. Picture this: a journey through the misty haze of correlation coefficients and p-values, armed with nothing but our trusty laptops and the insatiable thirst for uncovering connections others might dismiss as sheer coincidence.
The titular Dawn, holding the promise of a new beginning from the crack of dawn to the twilight, has long been embraced as a symbol of hope and renewal. But little did we know that this name may also carry a clouds-of-concern kind of significance. With a correlation coefficient of 0.8981184 and a p-value that would make even the most skeptical eyebrows raise, our findings don't just hint at a connection; they practically shout it from the smog-covered rooftops.
So, what does this all mean, you might wonder? Is there a cosmic clue lurking amidst the fumes, suggesting that the universe conspires to shape the fate of the air and the destinies of those bearing the name Dawn? Or perhaps, there's a more practical explanation - one that involves years of data, rigorous analysis, and a lot of head-scratching over what on earth (or in the air, to be precise) could be causing this correlation.
In this paper, we embark on an odyssey into the uncharted territory of name-based air quality association, challenging conventional wisdom and introducing a dash of humor into the often-serious world of academic research. Prepare to be enchanted, amused, and somewhat perplexed - for the journey ahead promises to be as enlightening as it is unexpectedly fragrant.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
To embark on our olfactory odyssey, it is imperative to consider the existing body of scholarship that intertwines the realms of nomenclature and atmospheric elements. Smith and Doe (2010) expounded upon the socio-cultural significance of naming conventions and their potential impact on environmental paradigms, albeit without veering into the aromatic intricacies we aim to explore. Their work provides a solid foundation for understanding the intricate dance between human identifiers and the environmental milieu.
Jones (2013) delved into the psychological implications of monikers, uncovering how individuals may unwittingly embody the characteristics associated with their given names. While Jones' study did not directly touch upon atmospheric affinities, it did hint at the mysterious and sometimes whimsical ways in which names can intertwine with our destinies.
Steering into the whimsy-laden waters of popular culture and fiction, notable works such as "The Air We Breathe" by A. Novel (2015) and "Mist-ical Meanderings" by P. Writer (2018) awaken the imagination with their airborne narratives. While these literary journeys may not be grounded in empirical inquiry, they do offer a contemplative backdrop for our airborne exploration.
Traversing the virtual alleys of social media, the unexpected encounter with a tweet from @BreatheEasy88 declaring, "Is the popularity of the name Dawn an indicator of air pollution levels? #SmoggyNameTrends" served as a serendipitous catalyst for our own foray into this unexpected phenomenon. The musings of internet denizens, although unscientific, often carry a kernel of truth that sparks the flames of inquiry.
As we synthesize this diverse tapestry of scholarship, fiction, and digital ponderings, our quest for uncovering the aromatic entanglements between the name Dawn and atmospheric conditions gains both gravity and levity. The stage is set, and the spotlight of inquiry beckons us to unravel the fragrant secrets that linger in the ethereal mist of correlation and causation.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Dawn and Air pollution in Anchorage. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
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 2021
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]]
Breath of Fresh Dawn: The Polluted Origins of a Name
[[ABSTRACT]]
In this study, we unveil a correlation between the popularity of the first name Dawn and air pollution levels in Anchorage. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, we delve into the surprising and, one might say, aromatic relationship between a common name and the quality of the air. Our findings reveal a statistically robust connection, with a correlation coefficient of 0.8981184 and p < 0.01 between the years 1980 and 2021. We discuss the implications of these findings, pondering whether there might be a celestial explanation for this atmospheric association. Our research challenges the notion that a name is only an identity marker and raises the possibility that it might also carry fragrant hints of environmental destiny.
[[INTRODUCTION]]
Socrates once said, "The only true wisdom is in knowing you know nothing." However, he clearly didn't have access to the groundbreaking research we are about to present. In the annals of scholarly exploration, one might expect to stumble upon discoveries about the cosmos, the mysteries of the ocean depths, or the inner workings of the human mind. But here, dear readers, we bring you an unexpected and rather pungent revelation: the aromatic interplay between the popularity of the first name Dawn and the air quality in Anchorage.
Drawing from the eclectic blend of data from the US Social Security Administration and the Environmental Protection Agency, we set out on a marvelous adventure - like intrepid explorers in a fog of statistical intrigue. Picture this: a journey through the misty haze of correlation coefficients and p-values, armed with nothing but our trusty laptops and the insatiable thirst for uncovering connections others might dismiss as sheer coincidence.
The titular Dawn, holding the promise of a new beginning from the crack of dawn to the twilight, has long been embraced as a symbol of hope and renewal. But little did we know that this name may also carry a clouds-of-concern kind of significance. With a correlation coefficient of 0.8981184 and a p-value that would make even the most skeptical eyebrows raise, our findings don't just hint at a connection; they practically shout it from the smog-covered rooftops.
So, what does this all mean, you might wonder? Is there a cosmic clue lurking amidst the fumes, suggesting that the universe conspires to shape the fate of the air and the destinies of those bearing the name Dawn? Or perhaps, there's a more practical explanation - one that involves years of data, rigorous analysis, and a lot of head-scratching over what on earth (or in the air, to be precise) could be causing this correlation.
In this paper, we embark on an odyssey into the uncharted territory of name-based air quality association, challenging conventional wisdom and introducing a dash of humor into the often-serious world of academic research. Prepare to be enchanted, amused, and somewhat perplexed - for the journey ahead promises to be as enlightening as it is unexpectedly fragrant.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
Now, dear readers, let us unveil the mystical and slightly befuddling methods through which we have unearthed the aromatic connection between the name Dawn and the atmosphere of Anchorage. Picture this: our journey to unravel this enigma is akin to a quest for the proverbial needle in a haystack, where the needle happens to be made of pure, unadulterated data, and the haystack is a metaphor for the vast expanse of statistical information. So, brace yourselves as we delve into the whimsical world of research methodology.
First off, to capture the essence of the name Dawn, we dived into the digital vaults of the US Social Security Administration, where the delightful blend of digits and letters forms the fabric of baby name popularity across decades. We extracted the annual counts of newborns bearing the name Dawn from 1980 to 2021 – a data treasure trove filled with both the expected peaks and the occasional fathomless troughs of popularity.
But wait, there’s more! To map the nebulous trails of air pollution in Anchorage, we embarked on a digital expedition through the sprawling landscape of the Environmental Protection Agency’s data archive. Here, we sought out air quality indices, gaseous emissions, and atmospheric musings from the same temporal realms as our name-centric escapade. With both datasets snugly tucked under our arm, we marched forth into the realm of statistical analysis with all the intrepidness of explorers facing statistical uncertainties.
Now, here’s where the enchanting alchemy of statistical wizardry enters the stage. We weaved the entrancing spells of correlation analysis, enrobing our datasets in the mystical embrace of Pearson’s correlation coefficient. As the numbers danced before our eyes, we found ourselves entangled in the hidden ties that bind the eponymous name and the airborne particles of Anchorage.
Our darling p-value, the trusty arbiter of statistical significance, stood guard at the gates of our findings, casting its illuminating glances upon the whispers of correlation and bestowing upon us the knowledge that the connection we uncovered was not a figment of statistical happenstance. With a jovial flip of the proverbial coin, we set the bar of significance at p < 0.01, ensuring that our findings bore the stamp of empirical pertinence.
In this merry dance of data, where the name Dawn pirouetted in sync with the ebb and flow of airborne particles, we harness the formidable powers of statistical analysis to bring forth the delightful revelation of a connection that straddles the realms of nomenclature and atmospheric intrigue. So, as we bid adieu to the methodology stage of our journey, we invite you, dear readers, to join us in the mirthful yet enlightening escapade that is our research endeavor.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Dawn and Air pollution in Anchorage. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
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 2021, you found a correlation 0.8981184, r-squared of 0.8066167, 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]]
Breath of Fresh Dawn: The Polluted Origins of a Name
[[ABSTRACT]]
In this study, we unveil a correlation between the popularity of the first name Dawn and air pollution levels in Anchorage. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, we delve into the surprising and, one might say, aromatic relationship between a common name and the quality of the air. Our findings reveal a statistically robust connection, with a correlation coefficient of 0.8981184 and p < 0.01 between the years 1980 and 2021. We discuss the implications of these findings, pondering whether there might be a celestial explanation for this atmospheric association. Our research challenges the notion that a name is only an identity marker and raises the possibility that it might also carry fragrant hints of environmental destiny.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
Socrates once said, "The only true wisdom is in knowing you know nothing." However, he clearly didn't have access to the groundbreaking research we are about to present. In the annals of scholarly exploration, one might expect to stumble upon discoveries about the cosmos, the mysteries of the ocean depths, or the inner workings of the human mind. But here, dear readers, we bring you an unexpected and rather pungent revelation: the aromatic interplay between the popularity of the first name Dawn and the air quality in Anchorage.
Drawing from the eclectic blend of data from the US Social Security Administration and the Environmental Protection Agency, we set out on a marvelous adventure - like intrepid explorers in a fog of statistical intrigue. Picture this: a journey through the misty haze of correlation coefficients and p-values, armed with nothing but our trusty laptops and the insatiable thirst for uncovering connections others might dismiss as sheer coincidence.
The titular Dawn, holding the promise of a new beginning from the crack of dawn to the twilight, has long been embraced as a symbol of hope and renewal. But little did we know that this name may also carry a clouds-of-concern kind of significance. With a correlation coefficient of 0.8981184 and a p-value that would make even the most skeptical eyebrows raise, our findings don't just hint at a connection; they practically shout it from the smog-covered rooftops.
So, what does this all mean, you might wonder? Is there a cosmic clue lurking amidst the fumes, suggesting that the universe conspires to shape the fate of the air and the destinies of those bearing the name Dawn? Or perhaps, there's a more practical explanation - one that involves years of data, rigorous analysis, and a lot of head-scratching over what on earth (or in the air, to be precise) could be causing this correlation.
In this paper, we embark on an odyssey into the uncharted territory of name-based air quality association, challenging conventional wisdom and introducing a dash of humor into the often-serious world of academic research. Prepare to be enchanted, amused, and somewhat perplexed - for the journey ahead promises to be as enlightening as it is unexpectedly fragrant.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
**Results**
The data analysis unmasked a surprisingly robust correlation between the popularity of the first name Dawn and air pollution levels in Anchorage. With a correlation coefficient of 0.8981184 and an r-squared of 0.8066167, our findings stank -I mean, stood- as a testament to the unanticipated aroma-association between a name and the air we breathe.
Indeed, as Figure 1 reveals, the scatterplot graphically illustrates the strong positive relationship between the popularity of the name Dawn and air pollution levels in Anchorage, with a smell... I mean, cell, *clearly* evident trendline slicing through the fog of statistical uncertainty.
One might be forgiven for thinking that our data had somehow become entangled in an odorous web of coincidence, but the p-value of less than 0.01 aptly dispelled any olfactory illusions. In essence, the likelihood of this connection being due to mere chance is about as probable as finding a needle in a haystack - or should I say, as probable as finding a fresh, unscented breeze in a bustling metropolis.
Our findings dared to challenge the traditional notion that a name is nothing more than a label, suggesting instead that it carries the aromatic whiff of environmental significance, as if the universe itself had conspired to intertwine the fate of the air with the destinies of those bearing the name Dawn.
These results demand further exploration and contemplation; after all, who could have expected such a striking aroma - I mean, correlation - to emerge from the statistical woodwork? Our research, while undoubtedly pungent in its implications, opens the door to a world of aromatic enigmas, teasing us with the possibility that a name may harbor more than meets the nose.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Dawn and Air pollution in Anchorage. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
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]]
Breath of Fresh Dawn: The Polluted Origins of a Name
[[ABSTRACT]]
In this study, we unveil a correlation between the popularity of the first name Dawn and air pollution levels in Anchorage. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, we delve into the surprising and, one might say, aromatic relationship between a common name and the quality of the air. Our findings reveal a statistically robust connection, with a correlation coefficient of 0.8981184 and p < 0.01 between the years 1980 and 2021. We discuss the implications of these findings, pondering whether there might be a celestial explanation for this atmospheric association. Our research challenges the notion that a name is only an identity marker and raises the possibility that it might also carry fragrant hints of environmental destiny.
[[LITERATURE REVIEW]]
To embark on our olfactory odyssey, it is imperative to consider the existing body of scholarship that intertwines the realms of nomenclature and atmospheric elements. Smith and Doe (2010) expounded upon the socio-cultural significance of naming conventions and their potential impact on environmental paradigms, albeit without veering into the aromatic intricacies we aim to explore. Their work provides a solid foundation for understanding the intricate dance between human identifiers and the environmental milieu.
Jones (2013) delved into the psychological implications of monikers, uncovering how individuals may unwittingly embody the characteristics associated with their given names. While Jones' study did not directly touch upon atmospheric affinities, it did hint at the mysterious and sometimes whimsical ways in which names can intertwine with our destinies.
Steering into the whimsy-laden waters of popular culture and fiction, notable works such as "The Air We Breathe" by A. Novel (2015) and "Mist-ical Meanderings" by P. Writer (2018) awaken the imagination with their airborne narratives. While these literary journeys may not be grounded in empirical inquiry, they do offer a contemplative backdrop for our airborne exploration.
Traversing the virtual alleys of social media, the unexpected encounter with a tweet from @BreatheEasy88 declaring, "Is the popularity of the name Dawn an indicator of air pollution levels? #SmoggyNameTrends" served as a serendipitous catalyst for our own foray into this unexpected phenomenon. The musings of internet denizens, although unscientific, often carry a kernel of truth that sparks the flames of inquiry.
As we synthesize this diverse tapestry of scholarship, fiction, and digital ponderings, our quest for uncovering the aromatic entanglements between the name Dawn and atmospheric conditions gains both gravity and levity. The stage is set, and the spotlight of inquiry beckons us to unravel the fragrant secrets that linger in the ethereal mist of correlation and causation.
[[RESULTS]]
The data analysis unmasked a surprisingly robust correlation between the popularity of the first name Dawn and air pollution levels in Anchorage. With a correlation coefficient of 0.8981184 and an r-squared of 0.8066167, our findings stank -I mean, stood- as a testament to the unanticipated aroma-association between a name and the air we breathe.
Indeed, as Figure 1 reveals, the scatterplot graphically illustrates the strong positive relationship between the popularity of the name Dawn and air pollution levels in Anchorage, with a smell... I mean, cell, *clearly* evident trendline slicing through the fog of statistical uncertainty.
One might be forgiven for thinking that our data had somehow become entangled in an odorous web of coincidence, but the p-value of less than 0.01 aptly dispelled any olfactory illusions. In essence, the likelihood of this connection being due to mere chance is about as probable as finding a needle in a haystack - or should I say, as probable as finding a fresh, unscented breeze in a bustling metropolis.
Our findings dared to challenge the traditional notion that a name is nothing more than a label, suggesting instead that it carries the aromatic whiff of environmental significance, as if the universe itself had conspired to intertwine the fate of the air with the destinies of those bearing the name Dawn.
These results demand further exploration and contemplation; after all, who could have expected such a striking aroma - I mean, correlation - to emerge from the statistical woodwork? Our research, while undoubtedly pungent in its implications, opens the door to a world of aromatic enigmas, teasing us with the possibility that a name may harbor more than meets the nose.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The pungent connection uncovered in our study between the name Dawn and air pollution in Anchorage beckons us to challenge conventional paradigms surrounding the significance of nomenclature in environmental phenomena. The statistically robust correlation we observed echoes the previous research by Smith and Doe (2010), expanding upon the socio-cultural implications of naming conventions to include the aromatic nuances intertwined with environmental destinies. While our focus rested primarily on the aromatic entanglements between a name and atmospheric conditions, our findings corroborate the whimsical speculations of Jones (2013), hinting at the mysterious ways in which names can intertwine with our destinies, or in this case, the air we breathe.
The surprisingly robust correlation coefficient of 0.8981184 and the strikingly clear trendline depicted in Figure 1 leave little room for doubt regarding the aromatic intrigue at play. The p-value shunned any olfactory illusions and the r-squared of 0.8066167 offered a whiff... I mean, glimpse, into the aromatic mysteries that linger within the statistical confines.
Delving deeper into the whimsy-laden waters of popular culture and internet musings, our findings align with the serendipitous ponderings of @BreatheEasy88's Tweet, as unexpected as this connection might have seemed at first whiff. Our findings have substantiated the whimsical notions at play, demonstrating the almost fragrant correlation that lingers between the name Dawn and the atmospheric conditions in Anchorage.
While our research undoubtedly carries pungent implications, it raises a compelling question: could there be a celestial explanation for this aromatic association? Could the universe secretly conspire to intertwine the fate of the air with the destinies of those bearing the name Dawn? Our research implores us to consider the possibility that a name may harbor more than meets the nose, beckoning further exploration into these aromatic enigmas that tease us at the intersection of statistical significance and fragrant correlation.
As we close the lid on this aromatic expedition, the Breath of Fresh Dawn study poses a fragrant conundrum for future inquiry, ushering in a new era of pondering the aromatic interplay between nomenclature and atmospheric destinies. The wind of discovery whispers of aromatic secrets waiting to be unraveled, enticing the curious at heart to delve deeper into the fragrant tableau that lingers within the statistical labyrinth.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Dawn and Air pollution in Anchorage. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
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]]
Breath of Fresh Dawn: The Polluted Origins of a Name
[[ABSTRACT]]
In this study, we unveil a correlation between the popularity of the first name Dawn and air pollution levels in Anchorage. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, we delve into the surprising and, one might say, aromatic relationship between a common name and the quality of the air. Our findings reveal a statistically robust connection, with a correlation coefficient of 0.8981184 and p < 0.01 between the years 1980 and 2021. We discuss the implications of these findings, pondering whether there might be a celestial explanation for this atmospheric association. Our research challenges the notion that a name is only an identity marker and raises the possibility that it might also carry fragrant hints of environmental destiny.
[[INTRDUCTION]]
Socrates once said, "The only true wisdom is in knowing you know nothing." However, he clearly didn't have access to the groundbreaking research we are about to present. In the annals of scholarly exploration, one might expect to stumble upon discoveries about the cosmos, the mysteries of the ocean depths, or the inner workings of the human mind. But here, dear readers, we bring you an unexpected and rather pungent revelation: the aromatic interplay between the popularity of the first name Dawn and the air quality in Anchorage.
Drawing from the eclectic blend of data from the US Social Security Administration and the Environmental Protection Agency, we set out on a marvelous adventure - like intrepid explorers in a fog of statistical intrigue. Picture this: a journey through the misty haze of correlation coefficients and p-values, armed with nothing but our trusty laptops and the insatiable thirst for uncovering connections others might dismiss as sheer coincidence.
The titular Dawn, holding the promise of a new beginning from the crack of dawn to the twilight, has long been embraced as a symbol of hope and renewal. But little did we know that this name may also carry a clouds-of-concern kind of significance. With a correlation coefficient of 0.8981184 and a p-value that would make even the most skeptical eyebrows raise, our findings don't just hint at a connection; they practically shout it from the smog-covered rooftops.
So, what does this all mean, you might wonder? Is there a cosmic clue lurking amidst the fumes, suggesting that the universe conspires to shape the fate of the air and the destinies of those bearing the name Dawn? Or perhaps, there's a more practical explanation - one that involves years of data, rigorous analysis, and a lot of head-scratching over what on earth (or in the air, to be precise) could be causing this correlation.
In this paper, we embark on an odyssey into the uncharted territory of name-based air quality association, challenging conventional wisdom and introducing a dash of humor into the often-serious world of academic research. Prepare to be enchanted, amused, and somewhat perplexed - for the journey ahead promises to be as enlightening as it is unexpectedly fragrant.
[[RESULTS]]
The data analysis unmasked a surprisingly robust correlation between the popularity of the first name Dawn and air pollution levels in Anchorage. With a correlation coefficient of 0.8981184 and an r-squared of 0.8066167, our findings stank -I mean, stood- as a testament to the unanticipated aroma-association between a name and the air we breathe.
Indeed, as Figure 1 reveals, the scatterplot graphically illustrates the strong positive relationship between the popularity of the name Dawn and air pollution levels in Anchorage, with a smell... I mean, cell, *clearly* evident trendline slicing through the fog of statistical uncertainty.
One might be forgiven for thinking that our data had somehow become entangled in an odorous web of coincidence, but the p-value of less than 0.01 aptly dispelled any olfactory illusions. In essence, the likelihood of this connection being due to mere chance is about as probable as finding a needle in a haystack - or should I say, as probable as finding a fresh, unscented breeze in a bustling metropolis.
Our findings dared to challenge the traditional notion that a name is nothing more than a label, suggesting instead that it carries the aromatic whiff of environmental significance, as if the universe itself had conspired to intertwine the fate of the air with the destinies of those bearing the name Dawn.
These results demand further exploration and contemplation; after all, who could have expected such a striking aroma - I mean, correlation - to emerge from the statistical woodwork? Our research, while undoubtedly pungent in its implications, opens the door to a world of aromatic enigmas, teasing us with the possibility that a name may harbor more than meets the nose.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our research has unraveled the pungent puzzle of the relationship between the popularity of the first name Dawn and air pollution in Anchorage. The statistically robust correlation coefficient of 0.8981184 and the p-value of less than 0.01 have left us with more than just food for thought; they've left us with aromatic musings and statistical seasoning.
Just as a researcher toils through heaps of data, our findings have sifted through the metaphorical air, revealing a scent-sational connection that is as astonishing as it is aromatic. After all, who would have thought that a name could possess such an atmospheric influence?
But fear not, dear reader, for this is where our aromatic odyssey reaches its termination. It's safe to say that no more research is needed in this specific area. As tempting as it may be to dive into the fragrant abyss of name-based environmental correlations, we must resist the urge.
Let's leave this peculiar aromatic association in its statistical curiosity cabinet - smelling unusual, yet confidently explored. The fetid fate of "Dawn" and the air quality in Anchorage shall remain an enigmatic, but thoroughly researched, part of the scholarly landscape.
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 Breath of Fresh Dawn: The Polluted Origins of a Name. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Linguistic Ecology
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 Breath of Fresh Dawn: The Polluted Origins of a Name. Respond only with the name of a fictional organization.
ChatGPT:
The Society for Ecological Linguistics and Etymology
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 Breath of Fresh Dawn: The Polluted Origins of a Name with an abstract of In this study, we unveil a correlation between the popularity of the first name Dawn and air pollution levels in Anchorage. Leveraging data from the US Social Security Administration and the Environmental Protection Agency, we delve into the surprising and, one might say, aromatic relationship between a common name and the quality of the air. Our findings reveal a statistically robust connection, with a correlation coefficient of 0.8981184 and p < 0.01 between the years 1980 and 2021. We discuss the implications of these findings, pondering whether there might be a celestial explanation for this atmospheric association. Our research challenges the notion that a name is only an identity marker and raises the possibility that it might also carry fragrant hints of environmental destiny.
ChatGPT:
"Dawn name popularity correlation air pollution", "Anchorage air pollution levels Dawn name correlation", "US Social Security Administration name popularity data", "Environmental Protection Agency air pollution data correlation", "Name influence on air quality", "Astrological explanation atmospheric association names", "Identity marker environmental destiny"
*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 DawnDetailed data title: Babies of all sexes born in the US named Dawn
Source: US Social Security Administration
See what else correlates with Popularity of the first name Dawn
Air pollution in Anchorage
Detailed data title: Percentage of days 'unhealthy' or worse air quality in Anchorage, AK
Source: Environmental Protection Agency
See what else correlates with Air pollution in Anchorage
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 = 0.8066167 (Coefficient of determination)
This means 80.7% of the change in the one variable (i.e., Air pollution in Anchorage) is predictable based on the change in the other (i.e., Popularity of the first name Dawn) over the 42 years from 1980 through 2021.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 7.4E-16. 0.0000000000000007426724801369
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.
But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.
Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.9 in 7.4E-14% of random cases. Said differently, if you correlated 1,346,488,562,247,070 random variables You don't actually need 1 quadrillion 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, 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.
[ 0.82, 0.94 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.
This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!
All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.
Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
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 | |
Popularity of the first name Dawn (Babies born) | 4496 | 3858 | 3102 | 2658 | 2117 | 1739 | 1463 | 1162 | 1061 | 864 | 749 | 676 | 619 | 497 | 397 | 325 | 260 | 318 | 264 | 231 | 240 | 179 | 196 | 200 | 157 | 125 | 129 | 122 | 114 | 113 | 92 | 94 | 90 | 78 | 94 | 99 | 85 | 103 | 100 | 86 | 83 | 96 |
Air pollution in Anchorage (Bad air quality days) | 7.37705 | 4.10959 | 4.65753 | 6.0274 | 3.27869 | 0.547945 | 0.821918 | 0 | 0 | 0.284091 | 0.550964 | 0 | 1.0989 | 0 | 0 | 0 | 0 | 0 | 0.276243 | 0.638978 | 0 | 0 | 0 | 0.645161 | 0.325733 | 0.330033 | 0 | 0 | 0 | 0 | 0 | 0.273973 | 0 | 0.273973 | 0.821918 | 0.273973 | 0 | 0.273973 | 0.273973 | 1.09589 | 0 | 0.273973 |
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
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
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.
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. 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([4496,3858,3102,2658,2117,1739,1463,1162,1061,864,749,676,619,497,397,325,260,318,264,231,240,179,196,200,157,125,129,122,114,113,92,94,90,78,94,99,85,103,100,86,83,96,])
array_2 = np.array([7.37705,4.10959,4.65753,6.0274,3.27869,0.547945,0.821918,0,0,0.284091,0.550964,0,1.0989,0,0,0,0,0,0.276243,0.638978,0,0,0,0.645161,0.325733,0.330033,0,0,0,0,0,0.273973,0,0.273973,0.821918,0.273973,0,0.273973,0.273973,1.09589,0,0.273973,])
array_1_name = "Popularity of the first name Dawn"
array_2_name = "Air pollution in Anchorage"
# 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. 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
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 Dawn
- Line chart for only Air pollution in Anchorage
- AI-generated correlation image
- The spurious research paper: Breath of Fresh Dawn: The Polluted Origins of a Name
Your correlation rating is out of this world!
Correlation ID: 3358 · Black Variable ID: 3387 · Red Variable ID: 20264