Spurious correlation #4,981 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air pollution in Columbia, South Carolina and the second variable is US birth rates of triplets or more. The chart goes from 2002 to 2021, 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 Air pollution in Columbia, South Carolina and the second variable is US birth rates of triplets or more. The chart goes from 2002 to 2021, and the two variables track closely in value over that time.

AI explanation

The cleaner air led to fewer airborne fertility-enhancing particles, causing a decline in the occurrence of naturally conceived triplets or more in the area. As a result, there was a noticeable decrease in the birth rates of these rare, but remarkable, multiples.

^{Show image generation prompt} Model: dalle-3
Prompt: Prompt: Create an image in the style of a woodblock painting that portrays a serene, sunlit day in Columbia, South Carolina. The city skyline stands tall against a clear blue sky, with visible greenery in the surroundings. Show the maternity ward of a hospital, quieter than before, with a noticeable decrease in naturally conceived triplets or more due to reduced airborne fertility-enhancing particles. Keep the visual depiction simple and elegant, capturing the tranquility of the scene. 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: Air pollution in Columbia, South Carolina and US birth rates of triplets or more. 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 photo-realistic image Cybernetic art Surrealism Voxel art Woodblock painting
ChatGPT: Woodblock painting

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 Air pollution in Columbia, South Carolina and US birth rates of triplets or more, in the following situation: The cleaner air led to fewer airborne fertility-enhancing particles, causing a decline in the occurrence of naturally conceived triplets or more in the area. As a result, there was a noticeable decrease in the birth rates of these rare, but remarkable, multiples.. Keep the description simple.
ChatGPT: In a clear, sunny day in Columbia, South Carolina, the city skyline stood against the backdrop of a blue sky. The air appeared cleaner, with visible greenery and little haze. At the hospital, the maternity ward seemed quieter than before, and a noticeable decrease in the occurrence of naturally conceived triplets or more was observed. The reduction in airborne fertility-enhancing particles had led to lower birth rates of these rare but remarkable multiples.

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: [ Woodblock painting ] and depicting this scene: In a clear, sunny day in Columbia, South Carolina, the city skyline stood against the backdrop of a blue sky. The air appeared cleaner, with visible greenery and little haze. At the hospital, the maternity ward seemed quieter than before, and a noticeable decrease in the occurrence of naturally conceived triplets or more was observed. The reduction in airborne fertility-enhancing particles had led to lower birth rates of these rare but remarkable multiples. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Create an image in the style of a woodblock painting that portrays a serene, sunlit day in Columbia, South Carolina. The city skyline stands tall against a clear blue sky, with visible greenery in the surroundings. Show the maternity ward of a hospital, quieter than before, with a noticeable decrease in naturally conceived triplets or more due to reduced airborne fertility-enhancing particles. Keep the visual depiction simple and elegant, capturing the tranquility of the scene.

*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 Air pollution in Columbia, South Carolina caused US birth rates of triplets or more to decrease.

AI academic paper

(Because p < 0.01)

Breath of Fresh Air: Examining the Relationship Between Air Pollution in Columbia, South Carolina and U.S. Triplet Birth Rates

Journal of Ecological Epidemiology

Jan 2024

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Air pollution in Columbia, South Carolina and US birth rates of triplets or more. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Perhaps you also got inspiration from some board games that are vaugely related.

Here is the title and abstract of the paper:
[[TITLE]]
"Breath of Fresh Air: Examining the Relationship Between Air Pollution in Columbia, South Carolina and U.S. Triplet Birth Rates"

[[ABSTRACT]]
In this study, we set out to investigate the potential connection between air pollution levels in Columbia, South Carolina, and the birth rates of triplets or more across the United States. The persistent question of whether the quality of the air we breathe has an impact on the frequency of multiple births has long intrigued researchers and baffled expectant parents alike, prompting us to delve into this peculiar inquiry.

Utilizing data obtained from the Environmental Protection Agency (EPA) and the Centers for Disease Control and Prevention (CDC) spanning from 2002 to 2021, we meticulously analyzed air pollution metrics alongside birth records and unearthed some intriguing insights. Our findings revealed a strikingly high correlation coefficient of 0.9313869 and a minuscule p-value of less than 0.01, signifying a strong association between air pollution in Columbia, South Carolina, and the occurrence of triplet or higher-order multiple births nationwide.

As we navigate through the labyrinth of statistical analysis and epidemiological implications, we invite readers to ponder the air of uncertainty surrounding this correlation - perhaps a breath of fresh air can lead to a bundle of joy not just for parents, but for researchers seeking to unravel the enigmatic interplay between environmental factors and human fertility.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In recent years, the intersection of environmental factors and human health has been the subject of extensive scrutiny and speculation. One such area of interest delves into the impact of air pollution on reproductive outcomes, leading us to embark on a rather unconventional quest to explore the potential relationship between air pollution levels in Columbia, South Carolina, and the birth rates of triplets or more across the United States.
The idea that the air we breathe may play a role in the occurrence of multiple births may initially seem far-fetched, akin to inhaling a lungful of improbable speculation. However, as researchers, we are no strangers to delving into peculiar inquiries, often finding ourselves navigating through statistical thickets and data marshes in search of elusive correlations. The allure of uncovering connections that are as enigmatic as they are unexpected is akin to embarking on a scientific scavenger hunt, in which every obscure data point and statistical anomaly serves as a clue in unraveling the mysteries of human fertility.
Armed with data obtained from the Environmental Protection Agency (EPA) and the Centers for Disease Control and Prevention (CDC), our pursuit led us to meticulously analyze air pollution metrics alongside birth records, paving the way for a veritable symphony of statistical analysis and epidemiological deduction. The notion of teasing out a correlation between the smog of Columbia and the occurrence of triplets and higher-order multiple births across the expanse of the United States may seem as elusive as capturing an aerosol particle in a statistical net, but our findings illuminated an unexpected pathway through the maze of data.
As we journey through the landscape of correlation coefficients and p-values, the interplay of variables and the statistical dance of significance, we invite readers to accompany us on this academic odyssey. The ever-present air of uncertainty that pervades this peculiar correlation may indeed leave one breathless with anticipation, wondering if a breath of fresh air in Columbia could foster a symphony of triplet bundles nationwide, or if it is merely an ephemeral statistical wisp in the wind.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The pursuit of uncovering unexpected correlations and enigmatic relationships has led scholars and researchers alike down numerous intriguing avenues of inquiry. In the case of our investigation into the potential connection between air pollution in Columbia, South Carolina, and the birth rates of triplets and higher-order multiples across the United States, a review of existing literature revealed a landscape as varied and complex as the statistical analyses we have undertaken.

Smith, in their seminal work "Air Pollution and Reproductive Health," delved into the broader impact of air pollution on reproductive outcomes, shedding light on the intricate interplay between environmental factors and fertility. Doe's comprehensive study on "Environmental Exposures and Birth Outcomes" expanded upon this foundation, highlighting the pervasive influence of air quality on the gestational environment. These sobering studies served as our guides into the labyrinth of environmental epidemiology, paving the way for our own peculiar exploration.

As we navigated this scholarly terrain, we encountered a treasure trove of non-fiction works that, while not directly related to our topic, offered insight and inspiration from tangentially related fields. "The Air We Breathe: A Comprehensive Analysis of Atmospheric Composition" by Jones provided a comprehensive overview of air quality dynamics, serving as a breath of fresh air in our quest for understanding the nuances of pollution in the Southern skies. Concurrently, "Statistics for Epidemiology: Navigating the Data Jungle" by Wilson proved instrumental in arming us with the tools necessary to decode the statistical thickets we would encounter.

Venturing further, we encountered an unexpected source of inspiration within the realm of fiction literature. Michael Crichton's "The Andromeda Strain" presented a riveting exploration of airborne pathogens and environmental contamination, serving as a cautionary tale of the perils of uncontrolled environmental crises. Furthermore, the dystopian landscape of Margaret Atwood's "Oryx and Crake" led us through an evocative journey of ecological collapse, resonating with the essence of our pursuit to unveil the impact of pollution on human fertility.

In a whimsical twist of fate, our pursuit was not devoid of lighthearted revelry, as we gleaned unexpected insights from the world of board games. The ludic exploration of environmental calamities in the board game "Pandemic" underscored the interconnectedness of ecosystems, translating the complexities of environmental epidemiology into a playful metaphor. Parallel to this, the strategic maneuvering and statistical acumen required in "Settlers of Catan" offered a lighthearted mirroring of the analytical prowess demanded in our own research endeavors.

As we synthesized these diverse influences, our pursuit of understanding the impact of Columbia's air on the occurrence of triplet births across the United States assumed a kaleidoscopic quality, drawing from a mosaic of scholarly, fictional, and playfully imagined sources. In the pages that follow, we invite readers to embark on a journey through this diverse tapestry of influence and inspiration, as we unearth the startling revelations and unexpected curiosities that emerged from our exploration.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the 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 Air pollution in Columbia, South Carolina and US birth rates of triplets or more. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 Environmental Protection Agency and CDC . You used data from 2002 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 Air: Examining the Relationship Between Air Pollution in Columbia, South Carolina and U.S. Triplet Birth Rates"

[[ABSTRACT]]
In this study, we set out to investigate the potential connection between air pollution levels in Columbia, South Carolina, and the birth rates of triplets or more across the United States. The persistent question of whether the quality of the air we breathe has an impact on the frequency of multiple births has long intrigued researchers and baffled expectant parents alike, prompting us to delve into this peculiar inquiry.

Utilizing data obtained from the Environmental Protection Agency (EPA) and the Centers for Disease Control and Prevention (CDC) spanning from 2002 to 2021, we meticulously analyzed air pollution metrics alongside birth records and unearthed some intriguing insights. Our findings revealed a strikingly high correlation coefficient of 0.9313869 and a minuscule p-value of less than 0.01, signifying a strong association between air pollution in Columbia, South Carolina, and the occurrence of triplet or higher-order multiple births nationwide.

As we navigate through the labyrinth of statistical analysis and epidemiological implications, we invite readers to ponder the air of uncertainty surrounding this correlation - perhaps a breath of fresh air can lead to a bundle of joy not just for parents, but for researchers seeking to unravel the enigmatic interplay between environmental factors and human fertility.

[[INTRODUCTION]]
In recent years, the intersection of environmental factors and human health has been the subject of extensive scrutiny and speculation. One such area of interest delves into the impact of air pollution on reproductive outcomes, leading us to embark on a rather unconventional quest to explore the potential relationship between air pollution levels in Columbia, South Carolina, and the birth rates of triplets or more across the United States.
The idea that the air we breathe may play a role in the occurrence of multiple births may initially seem far-fetched, akin to inhaling a lungful of improbable speculation. However, as researchers, we are no strangers to delving into peculiar inquiries, often finding ourselves navigating through statistical thickets and data marshes in search of elusive correlations. The allure of uncovering connections that are as enigmatic as they are unexpected is akin to embarking on a scientific scavenger hunt, in which every obscure data point and statistical anomaly serves as a clue in unraveling the mysteries of human fertility.
Armed with data obtained from the Environmental Protection Agency (EPA) and the Centers for Disease Control and Prevention (CDC), our pursuit led us to meticulously analyze air pollution metrics alongside birth records, paving the way for a veritable symphony of statistical analysis and epidemiological deduction. The notion of teasing out a correlation between the smog of Columbia and the occurrence of triplets and higher-order multiple births across the expanse of the United States may seem as elusive as capturing an aerosol particle in a statistical net, but our findings illuminated an unexpected pathway through the maze of data.
As we journey through the landscape of correlation coefficients and p-values, the interplay of variables and the statistical dance of significance, we invite readers to accompany us on this academic odyssey. The ever-present air of uncertainty that pervades this peculiar correlation may indeed leave one breathless with anticipation, wondering if a breath of fresh air in Columbia could foster a symphony of triplet bundles nationwide, or if it is merely an ephemeral statistical wisp in the wind.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To tackle the enigmatic relationship between air pollution levels in Columbia, South Carolina, and the birth rates of triplets or more across the United States, our research team embarked on a methodological journey that blended the art of intricate data collection with the science of analytical wizardry.

Data Collection:
Armed with a quest for correlation and an insatiable thirst for statistical enlightenment, we scoured the digital realm, like brave explorers in the wilds of the internet, to gather information from the Environmental Protection Agency (EPA) and the Centers for Disease Control and Prevention (CDC). We meticulously compiled air pollution metrics, birth records, and other relevant data from the fruitful years of 2002 to 2021, casting our net far and wide across the virtual seas of information.

Air Pollution Measures:
We harnessed the robust data on air quality, clutching onto metric after metric as if they were shipwrecked survivors in the stormy seas of statistical analysis. Our team explored various indices of air pollution, including but not limited to particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3), unraveling a tapestry of atmospheric constituents that whispered the tale of Columbia's atmospheric complexities.

Birth Records:
In our pursuit of unraveling the mysteries of multiple births, we combed through the vast archives of birth records, sifting through the digital annals with the diligence of genealogists seeking precious familial connections. Within this trove of births, we meticulously identified and isolated the occurrences of triplets or higher-order multiple births, each entry a newfound piece in the puzzle of statistical significance.

Statistical Analysis:
The culmination of our methodological escapade was the intricate symphony of statistical analysis, where variables danced like particles in a statistical collider, colliding and interacting to reveal the hidden truths within the data. Utilizing a potpourri of analytical tools, including correlation coefficients, regression models, and hypothesis testing, we untangled the statistical knot, revealing the elusive relationship between air pollution in Columbia, South Carolina, and the birth rates of triplets or more across the expanse of the United States.

By navigating through this windy maze of methodological intricacy, we emerged with newfound insights, shedding light on the unexpected correlation that lies at the intersection of environmental factors and human fertility. Our methodological voyage may have been as convoluted as a tangled statistical vine, but it has led us to illuminate a connection as puzzling as it is intriguing.

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Air pollution in Columbia, South Carolina and US birth rates of triplets or more. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 Air: Examining the Relationship Between Air Pollution in Columbia, South Carolina and U.S. Triplet Birth Rates"

[[ABSTRACT]]
In this study, we set out to investigate the potential connection between air pollution levels in Columbia, South Carolina, and the birth rates of triplets or more across the United States. The persistent question of whether the quality of the air we breathe has an impact on the frequency of multiple births has long intrigued researchers and baffled expectant parents alike, prompting us to delve into this peculiar inquiry.

Utilizing data obtained from the Environmental Protection Agency (EPA) and the Centers for Disease Control and Prevention (CDC) spanning from 2002 to 2021, we meticulously analyzed air pollution metrics alongside birth records and unearthed some intriguing insights. Our findings revealed a strikingly high correlation coefficient of 0.9313869 and a minuscule p-value of less than 0.01, signifying a strong association between air pollution in Columbia, South Carolina, and the occurrence of triplet or higher-order multiple births nationwide.

As we navigate through the labyrinth of statistical analysis and epidemiological implications, we invite readers to ponder the air of uncertainty surrounding this correlation - perhaps a breath of fresh air can lead to a bundle of joy not just for parents, but for researchers seeking to unravel the enigmatic interplay between environmental factors and human fertility.

[[LITERATURE REVIEW]]
The pursuit of uncovering unexpected correlations and enigmatic relationships has led scholars and researchers alike down numerous intriguing avenues of inquiry. In the case of our investigation into the potential connection between air pollution in Columbia, South Carolina, and the birth rates of triplets and higher-order multiples across the United States, a review of existing literature revealed a landscape as varied and complex as the statistical analyses we have undertaken.
Smith, in their seminal work "Air Pollution and Reproductive Health," delved into the broader impact of air pollution on reproductive outcomes, shedding light on the intricate interplay between environmental factors and fertility. Doe's comprehensive study on "Environmental Exposures and Birth Outcomes" expanded upon this foundation, highlighting the pervasive influence of air quality on the gestational environment. These sobering studies served as our guides into the labyrinth of environmental epidemiology, paving the way for our own peculiar exploration.
As we navigated this scholarly terrain, we encountered a treasure trove of non-fiction works that, while not directly related to our topic, offered insight and inspiration from tangentially related fields. "The Air We Breathe: A Comprehensive Analysis of Atmospheric Composition" by Jones provided a comprehensive overview of air quality dynamics, serving as a breath of fresh air in our quest for understanding the nuances of pollution in the Southern skies. Concurrently, "Statistics for Epidemiology: Navigating the Data Jungle" by Wilson proved instrumental in arming us with the tools necessary to decode the statistical thickets we would encounter.
Venturing further, we encountered an unexpected source of inspiration within the realm of fiction literature. Michael Crichton's "The Andromeda Strain" presented a riveting exploration of airborne pathogens and environmental contamination, serving as a cautionary tale of the perils of uncontrolled environmental crises. Furthermore, the dystopian landscape of Margaret Atwood's "Oryx and Crake" led us through an evocative journey of ecological collapse, resonating with the essence of our pursuit to unveil the impact of pollution on human fertility.
In a whimsical twist of fate, our pursuit was not devoid of lighthearted revelry, as we gleaned unexpected insights from the world of board games. The ludic exploration of environmental calamities in the board game "Pandemic" underscored the interconnectedness of ecosystems, translating the complexities of environmental epidemiology into a playful metaphor. Parallel to this, the strategic maneuvering and statistical acumen required in "Settlers of Catan" offered a lighthearted mirroring of the analytical prowess demanded in our own research endeavors.
As we synthesized these diverse influences, our pursuit of understanding the impact of Columbia's air on the occurrence of triplet births across the United States assumed a kaleidoscopic quality, drawing from a mosaic of scholarly, fictional, and playfully imagined sources. In the pages that follow, we invite readers to embark on a journey through this diverse tapestry of influence and inspiration, as we unearth the startling revelations and unexpected curiosities that emerged from our exploration.

[[RESULTS]]
Our analysis revealed a remarkably high correlation coefficient of 0.9313869 between air pollution levels in Columbia, South Carolina, and the birth rates of triplets or more across the United States from 2002 to 2021. The r-squared value of 0.8674816 suggested that approximately 86.75% of the variability in triplet birth rates could be explained by variations in air pollution levels, a statistic that left us more breathless than a leisurely stroll through a polluted city.
The p-value of less than 0.01 indicated a significant relationship between these variables, prompting us to ponder whether a gust of fresh air in the birthplace of Doublemint gum could indeed lead to an increase in triplet joy throughout the nation, or if we were simply inhaling a statistical fluke. This association was vividly portrayed in our scatterplot (Fig. 1), where the data points formed a pattern more striking than a particularly delightful game of connect-the-dots.
As researchers, we often find ourselves wading through a sea of numbers, much like a fish navigating an ocean of statistical intrigue. In this case, our findings seemed to suggest that the air in Columbia may have a notable impact on the likelihood of multiple births across the United States, a revelation that could ruffle more feathers than a sudden gust of wind. While some may find it difficult to fathom that the air we breathe could influence our chances of a multiple bundles of joy, the statistics don't lie – they're as straightforward as a line graph on a particularly honest day.
These results open the door to a myriad of questions and implications, inviting further exploration into the peculiar interconnectedness of environmental factors and human fertility. As we peel back the layers of this enigmatic correlation, we are reminded that in the realm of statistical sleuthing, every unexpected discovery is a breath of fresh air in the pursuit of scientific understanding.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study align with and enrich the existing literature, providing a deeper understanding of the potential relationship between air pollution in Columbia, South Carolina, and the birth rates of triplets or more across the United States. Our findings corroborate previous research by Smith and Doe, who laid the groundwork for exploring the influence of air quality on reproductive outcomes. As our statistical analysis revealed a remarkably high correlation coefficient and a minuscule p-value, akin to discovering a hidden treasure trove amidst the statistical jungle, we can confidently assert that the peculiar interconnectedness between air pollution and triplet births deserves further inquiry.

The kaleidoscopic influences from diverse sources in our literature review have certainly contributed to both the substance and spirit of our investigation. Similarly, our findings provoke more pondering than a game of Pandemic, as we navigate the uncharted waters of environmental epidemiology. The statistical acumen required to decode the complexities of our data echoes the strategic maneuvering in Settlers of Catan, serving as a lively analogy to our research endeavors.

The correlation coefficient of 0.9313869 and its associated significance underscore the potential impact of environmental factors on human fertility, making our findings more captivating than a gripping work of fiction. Just as Michael Crichton's cautionary tale warned of environmental perils, our study highlights the significance of environmental crises on reproductive outcomes, shedding light on a puzzle as intriguing as the one in The Andromeda Strain.

Despite the claim that correlation does not imply causation, our statistical findings prompt us to consider the possibility that a breath of fresh air in Columbia could indeed contribute to a nationwide surge in triplet births. The implications of this correlation are as sheer as the surprise of stumbling upon a groundbreaking discovery in terra incognita. As we embark on further inquiry into this puzzling relationship, each unexpected revelation promises to be a breath of fresh air in our pursuit of scientific understanding.

By delving into the peculiar interplay between environmental factors and human fertility, our study transcends the ordinary realm of statistical inquiry, emerging as a testament to the captivating fusion of science and curiosity. As we navigate through this captivating voyage of statistical whimsy, we are reminded that uncovering enigmatic correlations is not just a quest for knowledge, but a delightful journey through the unexpected intricacies of research.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Air pollution in Columbia, South Carolina and US birth rates of triplets or more. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 Air: Examining the Relationship Between Air Pollution in Columbia, South Carolina and U.S. Triplet Birth Rates"

[[ABSTRACT]]
In this study, we set out to investigate the potential connection between air pollution levels in Columbia, South Carolina, and the birth rates of triplets or more across the United States. The persistent question of whether the quality of the air we breathe has an impact on the frequency of multiple births has long intrigued researchers and baffled expectant parents alike, prompting us to delve into this peculiar inquiry.

Utilizing data obtained from the Environmental Protection Agency (EPA) and the Centers for Disease Control and Prevention (CDC) spanning from 2002 to 2021, we meticulously analyzed air pollution metrics alongside birth records and unearthed some intriguing insights. Our findings revealed a strikingly high correlation coefficient of 0.9313869 and a minuscule p-value of less than 0.01, signifying a strong association between air pollution in Columbia, South Carolina, and the occurrence of triplet or higher-order multiple births nationwide.

As we navigate through the labyrinth of statistical analysis and epidemiological implications, we invite readers to ponder the air of uncertainty surrounding this correlation - perhaps a breath of fresh air can lead to a bundle of joy not just for parents, but for researchers seeking to unravel the enigmatic interplay between environmental factors and human fertility.

[[INTRDUCTION]]
In recent years, the intersection of environmental factors and human health has been the subject of extensive scrutiny and speculation. One such area of interest delves into the impact of air pollution on reproductive outcomes, leading us to embark on a rather unconventional quest to explore the potential relationship between air pollution levels in Columbia, South Carolina, and the birth rates of triplets or more across the United States.
The idea that the air we breathe may play a role in the occurrence of multiple births may initially seem far-fetched, akin to inhaling a lungful of improbable speculation. However, as researchers, we are no strangers to delving into peculiar inquiries, often finding ourselves navigating through statistical thickets and data marshes in search of elusive correlations. The allure of uncovering connections that are as enigmatic as they are unexpected is akin to embarking on a scientific scavenger hunt, in which every obscure data point and statistical anomaly serves as a clue in unraveling the mysteries of human fertility.
Armed with data obtained from the Environmental Protection Agency (EPA) and the Centers for Disease Control and Prevention (CDC), our pursuit led us to meticulously analyze air pollution metrics alongside birth records, paving the way for a veritable symphony of statistical analysis and epidemiological deduction. The notion of teasing out a correlation between the smog of Columbia and the occurrence of triplets and higher-order multiple births across the expanse of the United States may seem as elusive as capturing an aerosol particle in a statistical net, but our findings illuminated an unexpected pathway through the maze of data.
As we journey through the landscape of correlation coefficients and p-values, the interplay of variables and the statistical dance of significance, we invite readers to accompany us on this academic odyssey. The ever-present air of uncertainty that pervades this peculiar correlation may indeed leave one breathless with anticipation, wondering if a breath of fresh air in Columbia could foster a symphony of triplet bundles nationwide, or if it is merely an ephemeral statistical wisp in the wind.

[[RESULTS]]
Our analysis revealed a remarkably high correlation coefficient of 0.9313869 between air pollution levels in Columbia, South Carolina, and the birth rates of triplets or more across the United States from 2002 to 2021. The r-squared value of 0.8674816 suggested that approximately 86.75% of the variability in triplet birth rates could be explained by variations in air pollution levels, a statistic that left us more breathless than a leisurely stroll through a polluted city.
The p-value of less than 0.01 indicated a significant relationship between these variables, prompting us to ponder whether a gust of fresh air in the birthplace of Doublemint gum could indeed lead to an increase in triplet joy throughout the nation, or if we were simply inhaling a statistical fluke. This association was vividly portrayed in our scatterplot (Fig. 1), where the data points formed a pattern more striking than a particularly delightful game of connect-the-dots.
As researchers, we often find ourselves wading through a sea of numbers, much like a fish navigating an ocean of statistical intrigue. In this case, our findings seemed to suggest that the air in Columbia may have a notable impact on the likelihood of multiple births across the United States, a revelation that could ruffle more feathers than a sudden gust of wind. While some may find it difficult to fathom that the air we breathe could influence our chances of a multiple bundles of joy, the statistics don't lie – they're as straightforward as a line graph on a particularly honest day.
These results open the door to a myriad of questions and implications, inviting further exploration into the peculiar interconnectedness of environmental factors and human fertility. As we peel back the layers of this enigmatic correlation, we are reminded that in the realm of statistical sleuthing, every unexpected discovery is a breath of fresh air in the pursuit of scientific understanding.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has illuminated a compelling association between air pollution levels in Columbia, South Carolina, and the birth rates of triplets or more across the United States. The remarkably high correlation coefficient and the minuscule p-value have left us marveling at the potential influence of Columbia's air on the nation's triplet birth rates – it's almost as though the city's air has been conducting a symphony of its own. These findings nudge at the notion that perhaps a breath of fresh air in Columbia could lead to a breathless surge of triplet bundles nationwide, a correlation more captivating than an unexpected plot twist in a statistical thriller.

The statistical dance of significance has indeed led us to ponder the possibility that the air we breathe may hold a key to unlocking the mysteries of human fertility – a notion more enchanting than a statistical fairy tale. Nevertheless, as we draw the curtain on this peculiar correlation, we assert with utmost confidence that no further research in this area is needed. After all, why keep breathing new life into an already pungent topic?

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 Air: Examining the Relationship Between Air Pollution in Columbia, South Carolina and U.S. Triplet Birth Rates. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Ecological Epidemiology

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 Air: Examining the Relationship Between Air Pollution in Columbia, South Carolina and U.S. Triplet Birth Rates. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Atmospheric and Neonatal Phenomena Research (SANPR)

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 Air: Examining the Relationship Between Air Pollution in Columbia, South Carolina and U.S. Triplet Birth Rates with an abstract of In this study, we set out to investigate the potential connection between air pollution levels in Columbia, South Carolina, and the birth rates of triplets or more across the United States. The persistent question of whether the quality of the air we breathe has an impact on the frequency of multiple births has long intrigued researchers and baffled expectant parents alike, prompting us to delve into this peculiar inquiry.
Utilizing data obtained from the Environmental Protection Agency (EPA) and the Centers for Disease Control and Prevention (CDC) spanning from 2002 to 2021, we meticulously analyzed air pollution metrics alongside birth records and unearthed some intriguing insights. Our findings revealed a strikingly high correlation coefficient of 0.9313869 and a minuscule p-value of less than 0.01, signifying a strong association between air pollution in Columbia, South Carolina, and the occurrence of triplet or higher-order multiple births nationwide.
As we navigate through the labyrinth of statistical analysis and epidemiological implications, we invite readers to ponder the air of uncertainty surrounding this correlation - perhaps a breath of fresh air can lead to a bundle of joy not just for parents, but for researchers seeking to unravel the enigmatic interplay between environmental factors and human fertility.

ChatGPT:

air pollution, Columbia South Carolina, triplet birth rates, multiple birth rates, United States, Environmental Protection Agency, Centers for Disease Control and Prevention, EPA data, CDC data, air pollution metrics, birth records, correlation coefficient, p-value, statistical analysis, epidemiological implications, environmental factors, human fertility

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

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Data details

Air pollution in Columbia, South Carolina
Detailed data title: Percentage of days with moderate or worse air quality in Columbia, SC
Source: Environmental Protection Agency
See what else correlates with Air pollution in Columbia, South Carolina

US birth rates of triplets or more
Source: CDC
See what else correlates with US birth rates of triplets or more

Correlation r = 0.9313869 (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 = 0.8674816 (Coefficient of determination)
This means 86.7% of the change in the one variable (i.e., US birth rates of triplets or more) is predictable based on the change in the other (i.e., Air pollution in Columbia, South Carolina) over the 20 years from 2002 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.5E-9.^Show 0.0000000024909650761655788000
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 0.93 in 2.5E-7% of random cases. Said differently, if you correlated 401,450,831 random variables^Note You don't actually need 401 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 19 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 19 because we have two variables measured over a period of 20 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.

[ 0.83, 0.97 ] 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.

	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Air pollution in Columbia, South Carolina (Bad air quality days)	62.4658	60.274	65.3005	66.3014	64.9315	64.9315	54.3716	43.0137	50.137	56.7123	37.7049	29.863	34.5205	24.9315	30.6011	26.0274	23.0137	19.726	12.2951	26.0274
US birth rates of triplets or more (Birth rate per 100,000)	183	186	180	170	156	151	148	152	138	137	124.4	119.5	113.5	103.6	101.4	101.6	93	87.7	79.6	80

Why this works

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

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([62.4658,60.274,65.3005,66.3014,64.9315,64.9315,54.3716,43.0137,50.137,56.7123,37.7049,29.863,34.5205,24.9315,30.6011,26.0274,23.0137,19.726,12.2951,26.0274,])
array_2 = np.array([183,186,180,170,156,151,148,152,138,137,124.4,119.5,113.5,103.6,101.4,101.6,93,87.7,79.6,80,])
array_1_name = "Air pollution in Columbia, South Carolina"
array_2_name = "US birth rates of triplets or more"

# 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 Air pollution in Columbia, South Carolina
Line chart for only US birth rates of triplets or more
AI-generated correlation image
The spurious research paper: Breath of Fresh Air: Examining the Relationship Between Air Pollution in Columbia, South Carolina and U.S. Triplet Birth Rates

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Correlation ID: 4981 · Black Variable ID: 20485 · Red Variable ID: 55


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