Spurious correlation #4,548 · 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 Salisbury, Maryland and the second variable is The divorce rate in Maryland. The chart goes from 1999 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 Salisbury, Maryland and the second variable is The divorce rate in Maryland. The chart goes from 1999 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the air cleared up in Salisbury, so did the marital air in Maryland. It turns out, breathing in cleaner air led to less friction at home. Perhaps there's a correlation between air pollution and arguments getting airtime. Or maybe with pollution out of the way, couples could finally see things clearly, including that it's not smog to blame for their problems. Who knew that the key to lowering the divorce rate was just a breath of fresh air in more ways than one!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a cyberpunk vision of Salisbury, Maryland, with sleek, futuristic buildings towering over the city. Within this cyberpunk landscape, depict a couple walking hand in hand, with neon lights reflecting off the clean streets. In the background, show a holographic display of the declining divorce rate in Maryland against the digital skyline, symbolizing the positive effects of the improved air quality in this futuristic setting. 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 Salisbury, Maryland and The divorce rate in Maryland. 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: Cybernetic art 3D Pixar Style Cyberpunk Art nouveau Pop art
ChatGPT: Cyberpunk

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 Salisbury, Maryland and The divorce rate in Maryland, in the following situation: As the air cleared up in Salisbury, so did the marital air in Maryland. It turns out, breathing in cleaner air led to less friction at home. Perhaps there's a correlation between air pollution and arguments getting airtime. Or maybe with pollution out of the way, couples could finally see things clearly, including that it's not smog to blame for their problems. Who knew that the key to lowering the divorce rate was just a breath of fresh air in more ways than one!. Keep the description simple.
ChatGPT: Amidst the newly pristine air of Salisbury, Maryland, couples are seen walking hand in hand against a backdrop of clear blue skies and fresh, green trees. As they stroll, the tension seems to lift, and smiles replace frowns. Meanwhile, in the distance, a graph showing the declining divorce rate in Maryland is displayed against a clear horizon, indicating that the improved air quality has coincided with a decrease in marital discord.

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: [ Cyberpunk ] and depicting this scene: Amidst the newly pristine air of Salisbury, Maryland, couples are seen walking hand in hand against a backdrop of clear blue skies and fresh, green trees. As they stroll, the tension seems to lift, and smiles replace frowns. Meanwhile, in the distance, a graph showing the declining divorce rate in Maryland is displayed against a clear horizon, indicating that the improved air quality has coincided with a decrease in marital discord. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a cyberpunk vision of Salisbury, Maryland, with sleek, futuristic buildings towering over the city. Within this cyberpunk landscape, depict a couple walking hand in hand, with neon lights reflecting off the clean streets. In the background, show a holographic display of the declining divorce rate in Maryland against the digital skyline, symbolizing the positive effects of the improved air quality in this futuristic setting.

*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 Salisbury, Maryland caused The divorce rate in Maryland to decrease. Include one good pun.

AI academic paper

(Because p < 0.01)

Air We Done Yet? Exploring the Smoggy Link Between Air Pollution and Divorce Rates in Maryland

International Journal of Environmental Psychology

Jan 2024

Reminder: This paper is AI-generated. Not real!

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Air pollution in Salisbury, Maryland and The divorce rate in Maryland. Make lots of jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
"Air We Done Yet? Exploring the Smoggy Link Between Air Pollution and Divorce Rates in Maryland"

[[ABSTRACT]]
There has been much debate over whether air pollution is merely a respiratory hazard or if it also has the ability to wreak havoc on romantic relationships. In this study, we delve into the fog of uncertainty to investigate the correlation between air pollution levels in Salisbury, Maryland, and the divorce rate in the state of Maryland. Our research team utilized data from the Environmental Protection Agency and CDC National Vital Statistics to conduct a thorough analysis from 1999 to 2021, or as we like to call it, the "air for divorce" period.

Our findings revealed a surprising correlation coefficient of 0.8041956 and p < 0.01, indicating a strong statistical relationship between air pollution in Salisbury and the divorce rate in Maryland. It seems our research not only cleared the air but also uncovered a potential, albeit unconventional, contributing factor to marital discord. Our results underscore the importance of considering environmental factors in studies of social phenomena, as the air we breathe may have broader implications for the ties that bind.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
The relationship between air pollution and its impact on human health has been well-studied and documented. However, the potential influence of air pollution on social dynamics, particularly on romantic relationships, has remained largely unexplored. In the words of Shakespeare, "Is the smoggy air the cause, or rather fear of it?" Our study sought to shed light on this question by examining the intriguing association between air pollution levels in Salisbury, Maryland, and the divorce rate in the state of Maryland.
As we embark on this research journey, it is essential to address the elephant in the room – or should we say, the smog in the room? The idea that air pollution could play a role in marital strife may initially seem far-fetched, a bit like the elusive search for a breath of fresh air in the bustling city. However, as researchers, it is our duty to unpack the unexpected, to venture into uncharted territories, and to boldly go where no scholarly investigation has gone before – even if that means wading into the fog of potential puns and wordplay.
Our inquiry into the "air for divorce" period from 1999 to 2021 sought to disentangle the complexities of human relationships and environmental influences, and in doing so, we took a deep breath – albeit cautiously, given the air quality concerns. Our goal was to examine whether there exists a tangible link between the atmospheric haze and marital discord, or if this supposed association is merely an unsubstantiated gust of wind.
This study is not just blowing smoke; it grapples with a critical question that has been lingering in the air, much like a pesky air pollutant that refuses to dissipate. By exploring the potential connection between air pollution in Salisbury, a city known for its picturesque landscapes and savory seafood, and the divorce rate in Maryland, a state renowned for its blue crabs and historical charm, we endeavor to offer a breath of fresh insight into the interplay of environmental factors and human relationships.
As we delve deeper into the realm of air pollution and its unexpected ramifications, we invite our readers to join us on this scholarly adventure. Buckle up, because this research is about to take flight – hopefully, into cleaner, fresher air. Together, let us push the boundaries of conventional wisdom and unearth the surprising connections that lie beneath the surface, much like hidden treasure awaiting discovery.
Now, with a hefty supply of air fresheners and statistical analyses in tow, let us proceed to unveil the findings of our investigation, as we navigate the intricate dance between particulate matter and matters of the heart.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The existing body of literature on the correlation between environmental factors and social phenomena offers a kaleidoscope of perspectives, much like gazing through the hazy lens of air pollution. Smith et al. (2015) conducted a seminal study on the impact of air quality on psychological well-being, laying the groundwork for our understanding of the potential psychological effects of polluted air. Meanwhile, Doe and Jones (2018) explored the intersection of environmental stressors and marital satisfaction, albeit without delving specifically into air pollution as a contributing factor.

Turning to the non-fiction realm, "The Air We Breathe: A Comprehensive Analysis of Environmental Health" by Environmental Institute (2019) provides invaluable insights into the multifaceted implications of air pollution, from its physiological effects to its broader societal repercussions. Similarly, "Love in the Time of Smog: Navigating Relationships in Polluted Environments" by Public Health Perspectives (2020) offers a nuanced exploration of how environmental conditions may intersect with romantic relationships, albeit with a focus on global contexts.

Venturing into the world of fiction, "Cloudy with a Chance of Heartache" by Novel Author (2017) presents a whimsical yet thought-provoking narrative that intertwines the whimsy of romance with the looming presence of environmental degradation, offering a metaphorical glimpse into the potential impact of air pollution on love. Furthermore, "Mist Connections: A Love Story Amidst Airborne Particulate Matter" by Fictional Writer (2016) weaves a tale of unlikely romance amidst a backdrop of thick smog, encapsulating the ethereal essence of love under the veil of environmental adversity.

In our quest for unconventional inspiration, our research team also drew insights from cinematic portrayals of environmental challenges and human relationships. Films such as "The Air Affair" (2014) and "Gone with the Wind... and Smog" (2019) offered both entertainment and a semblance of thematic relevance, nudging us to contemplate the intertwined nature of air pollution and interpersonal dynamics in creative and unconventional ways.

As we navigate the labyrinthine landscape of scholarly literature, it becomes evident that the intersection of air pollution and romantic relationships, though underexplored, holds the potential for intriguing revelations – and, dare we say, a breath of fresh air in the realm of social science 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 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 Salisbury, Maryland and The divorce rate in Maryland. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and CDC National Vital Statistics . You used data from 1999 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]]
"Air We Done Yet? Exploring the Smoggy Link Between Air Pollution and Divorce Rates in Maryland"

[[ABSTRACT]]
There has been much debate over whether air pollution is merely a respiratory hazard or if it also has the ability to wreak havoc on romantic relationships. In this study, we delve into the fog of uncertainty to investigate the correlation between air pollution levels in Salisbury, Maryland, and the divorce rate in the state of Maryland. Our research team utilized data from the Environmental Protection Agency and CDC National Vital Statistics to conduct a thorough analysis from 1999 to 2021, or as we like to call it, the "air for divorce" period.

Our findings revealed a surprising correlation coefficient of 0.8041956 and p < 0.01, indicating a strong statistical relationship between air pollution in Salisbury and the divorce rate in Maryland. It seems our research not only cleared the air but also uncovered a potential, albeit unconventional, contributing factor to marital discord. Our results underscore the importance of considering environmental factors in studies of social phenomena, as the air we breathe may have broader implications for the ties that bind.

[[INTRODUCTION]]
INTRODUCTION
The relationship between air pollution and its impact on human health has been well-studied and documented. However, the potential influence of air pollution on social dynamics, particularly on romantic relationships, has remained largely unexplored. In the words of Shakespeare, "Is the smoggy air the cause, or rather fear of it?" Our study sought to shed light on this question by examining the intriguing association between air pollution levels in Salisbury, Maryland, and the divorce rate in the state of Maryland.
As we embark on this research journey, it is essential to address the elephant in the room – or should we say, the smog in the room? The idea that air pollution could play a role in marital strife may initially seem far-fetched, a bit like the elusive search for a breath of fresh air in the bustling city. However, as researchers, it is our duty to unpack the unexpected, to venture into uncharted territories, and to boldly go where no scholarly investigation has gone before – even if that means wading into the fog of potential puns and wordplay.
Our inquiry into the "air for divorce" period from 1999 to 2021 sought to disentangle the complexities of human relationships and environmental influences, and in doing so, we took a deep breath – albeit cautiously, given the air quality concerns. Our goal was to examine whether there exists a tangible link between the atmospheric haze and marital discord, or if this supposed association is merely an unsubstantiated gust of wind.
This study is not just blowing smoke; it grapples with a critical question that has been lingering in the air, much like a pesky air pollutant that refuses to dissipate. By exploring the potential connection between air pollution in Salisbury, a city known for its picturesque landscapes and savory seafood, and the divorce rate in Maryland, a state renowned for its blue crabs and historical charm, we endeavor to offer a breath of fresh insight into the interplay of environmental factors and human relationships.
As we delve deeper into the realm of air pollution and its unexpected ramifications, we invite our readers to join us on this scholarly adventure. Buckle up, because this research is about to take flight – hopefully, into cleaner, fresher air. Together, let us push the boundaries of conventional wisdom and unearth the surprising connections that lie beneath the surface, much like hidden treasure awaiting discovery.
Now, with a hefty supply of air fresheners and statistical analyses in tow, let us proceed to unveil the findings of our investigation, as we navigate the intricate dance between particulate matter and matters of the heart.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To untangle the web of airborne intrigue and marital discord, our research team embarked on a data-driven odyssey, like Odysseus navigating the seas of statistical significance. First, we leveraged data from the Environmental Protection Agency (EPA) to capture the atmospheric nuances in Salisbury, Maryland, the city where the air may hold more than just a hint of romance. This involved delving into air quality measurements, including levels of pollutants such as particulate matter, nitrogen dioxide, and volatile organic compounds – a veritable bouquet of chemical complexities.

Next, we turned our attention to the CDC National Vital Statistics, searching for the fingerprints of divorce rates in the state of Maryland. Our trusty data analysis tools sifted through the relational comings and goings, seeking patterns that could illuminate the potential interplay between air pollution and matrimonial reckonings.

We gathered data from the period between 1999 and 2021, a span of time we affectionately dubbed the "air for divorce" era, where love may have mixed with the winds of change and pollution in the air. This timeframe allowed us to capture the ebb and flow of air quality and marital dissolutions, observing how the two danced – or perhaps, coughed and sneezed – in tandem.

With a wave of statistical methods – including regression analyses, time series modeling, and perhaps a touch of the mystical arts – we sought to tease out the association between air pollution and divorce rates. Casting our nets wide, we navigated the treacherous waters of confounding variables and potential lurking biases, all while keeping an eye out for the glimmers of truth amidst the statistical noise.

To validate our findings, we employed robust statistical tests, leaving no stone unturned in our quest for scholarly rigour. Our pursuit of empirical evidence mirrored the passion of a hopeless romantic seeking the elusive validation of true love – or in our case, the improbable nexus between unseen pollutants and the unraveling of marital bonds.

In sum, our methodology represented a tightrope walk between scientific rigor and a touch of whimsy, as we endeavored to shine a spotlight on the atmospheric nuances of love and the unexpected influence of air pollution on the fabric of human relationships.

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

Please make up the results section of an academic research paper presenting the findings of the connection between Air pollution in Salisbury, Maryland and The divorce rate in Maryland. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and CDC National Vital Statistics .

For the time period 1999 to 2021, you found a correlation 0.8041956, r-squared of 0.6467305, 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]]
"Air We Done Yet? Exploring the Smoggy Link Between Air Pollution and Divorce Rates in Maryland"

[[ABSTRACT]]
There has been much debate over whether air pollution is merely a respiratory hazard or if it also has the ability to wreak havoc on romantic relationships. In this study, we delve into the fog of uncertainty to investigate the correlation between air pollution levels in Salisbury, Maryland, and the divorce rate in the state of Maryland. Our research team utilized data from the Environmental Protection Agency and CDC National Vital Statistics to conduct a thorough analysis from 1999 to 2021, or as we like to call it, the "air for divorce" period.

Our findings revealed a surprising correlation coefficient of 0.8041956 and p < 0.01, indicating a strong statistical relationship between air pollution in Salisbury and the divorce rate in Maryland. It seems our research not only cleared the air but also uncovered a potential, albeit unconventional, contributing factor to marital discord. Our results underscore the importance of considering environmental factors in studies of social phenomena, as the air we breathe may have broader implications for the ties that bind.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
INTRODUCTION
The relationship between air pollution and its impact on human health has been well-studied and documented. However, the potential influence of air pollution on social dynamics, particularly on romantic relationships, has remained largely unexplored. In the words of Shakespeare, "Is the smoggy air the cause, or rather fear of it?" Our study sought to shed light on this question by examining the intriguing association between air pollution levels in Salisbury, Maryland, and the divorce rate in the state of Maryland.
As we embark on this research journey, it is essential to address the elephant in the room – or should we say, the smog in the room? The idea that air pollution could play a role in marital strife may initially seem far-fetched, a bit like the elusive search for a breath of fresh air in the bustling city. However, as researchers, it is our duty to unpack the unexpected, to venture into uncharted territories, and to boldly go where no scholarly investigation has gone before – even if that means wading into the fog of potential puns and wordplay.
Our inquiry into the "air for divorce" period from 1999 to 2021 sought to disentangle the complexities of human relationships and environmental influences, and in doing so, we took a deep breath – albeit cautiously, given the air quality concerns. Our goal was to examine whether there exists a tangible link between the atmospheric haze and marital discord, or if this supposed association is merely an unsubstantiated gust of wind.
This study is not just blowing smoke; it grapples with a critical question that has been lingering in the air, much like a pesky air pollutant that refuses to dissipate. By exploring the potential connection between air pollution in Salisbury, a city known for its picturesque landscapes and savory seafood, and the divorce rate in Maryland, a state renowned for its blue crabs and historical charm, we endeavor to offer a breath of fresh insight into the interplay of environmental factors and human relationships.
As we delve deeper into the realm of air pollution and its unexpected ramifications, we invite our readers to join us on this scholarly adventure. Buckle up, because this research is about to take flight – hopefully, into cleaner, fresher air. Together, let us push the boundaries of conventional wisdom and unearth the surprising connections that lie beneath the surface, much like hidden treasure awaiting discovery.
Now, with a hefty supply of air fresheners and statistical analyses in tow, let us proceed to unveil the findings of our investigation, as we navigate the intricate dance between particulate matter and matters of the heart.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The statistical analyses conducted on the data collected from Salisbury, Maryland, and the state of Maryland from 1999 to 2021 yielded intriguing results. Our investigation revealed a substantial correlation coefficient of 0.8041956 between air pollution levels in Salisbury and the divorce rate in the state of Maryland. If this correlation were a movie, it would be a blockbuster hit – a real tear-jerker, or in this case, a lung-clogger.

The strong correlation was further supported by an r-squared value of 0.6467305, explaining approximately 64.67% of the variability in the divorce rate in Maryland due to changes in air pollution levels in Salisbury. This result suggests that air pollution may not only affect respiratory health but also have a notable impact on the interpersonal dynamics of households, providing a whole new meaning to the phrase "love is in the air."

Moreover, the p-value of less than 0.01 indicates that the observed relationship between air pollution and divorce rate is statistically significant, further cementing the validity of our findings. It seems the air in Salisbury may have a hand in stirring up more than just a gentle breeze of marital discord.

To visually capture the strength of the relationship between air pollution and divorce rate, we present Figure 1, a scatterplot that depicts the unmistakable correlation between these two variables. This plot serves as a poignant reminder that beneath the surface of seemingly unrelated phenomena, there may exist hidden connections waiting to be unearthed – much like discovering a forgotten love note in an old pair of jeans.

Overall, our results offer compelling evidence of a meaningful association between air pollution levels in Salisbury, Maryland, and the divorce rate in the state of Maryland. While the implications of this relationship are as of yet unclear, they certainly blow a breath of fresh air into the realm of environmental and social interactions.

With these findings in hand, it is evident that our understanding of the impact of air pollution extends beyond the confines of respiratory health and seeps into the intricate dance of human relationships. It appears that the air we breathe may indeed carry echoes of love and heartache, intertwining with our lives in ways we never imagined. As we bask in the breeze of these unexpected results, let us not forget that when it comes to matters of the heart, even the air may have a role to play.

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 Salisbury, Maryland and The divorce rate in Maryland. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"Air We Done Yet? Exploring the Smoggy Link Between Air Pollution and Divorce Rates in Maryland"

[[ABSTRACT]]
There has been much debate over whether air pollution is merely a respiratory hazard or if it also has the ability to wreak havoc on romantic relationships. In this study, we delve into the fog of uncertainty to investigate the correlation between air pollution levels in Salisbury, Maryland, and the divorce rate in the state of Maryland. Our research team utilized data from the Environmental Protection Agency and CDC National Vital Statistics to conduct a thorough analysis from 1999 to 2021, or as we like to call it, the "air for divorce" period.

Our findings revealed a surprising correlation coefficient of 0.8041956 and p < 0.01, indicating a strong statistical relationship between air pollution in Salisbury and the divorce rate in Maryland. It seems our research not only cleared the air but also uncovered a potential, albeit unconventional, contributing factor to marital discord. Our results underscore the importance of considering environmental factors in studies of social phenomena, as the air we breathe may have broader implications for the ties that bind.

[[LITERATURE REVIEW]]
The existing body of literature on the correlation between environmental factors and social phenomena offers a kaleidoscope of perspectives, much like gazing through the hazy lens of air pollution. Smith et al. (2015) conducted a seminal study on the impact of air quality on psychological well-being, laying the groundwork for our understanding of the potential psychological effects of polluted air. Meanwhile, Doe and Jones (2018) explored the intersection of environmental stressors and marital satisfaction, albeit without delving specifically into air pollution as a contributing factor.
Turning to the non-fiction realm, "The Air We Breathe: A Comprehensive Analysis of Environmental Health" by Environmental Institute (2019) provides invaluable insights into the multifaceted implications of air pollution, from its physiological effects to its broader societal repercussions. Similarly, "Love in the Time of Smog: Navigating Relationships in Polluted Environments" by Public Health Perspectives (2020) offers a nuanced exploration of how environmental conditions may intersect with romantic relationships, albeit with a focus on global contexts.
Venturing into the world of fiction, "Cloudy with a Chance of Heartache" by Novel Author (2017) presents a whimsical yet thought-provoking narrative that intertwines the whimsy of romance with the looming presence of environmental degradation, offering a metaphorical glimpse into the potential impact of air pollution on love. Furthermore, "Mist Connections: A Love Story Amidst Airborne Particulate Matter" by Fictional Writer (2016) weaves a tale of unlikely romance amidst a backdrop of thick smog, encapsulating the ethereal essence of love under the veil of environmental adversity.
In our quest for unconventional inspiration, our research team also drew insights from cinematic portrayals of environmental challenges and human relationships. Films such as "The Air Affair" (2014) and "Gone with the Wind... and Smog" (2019) offered both entertainment and a semblance of thematic relevance, nudging us to contemplate the intertwined nature of air pollution and interpersonal dynamics in creative and unconventional ways.
As we navigate the labyrinthine landscape of scholarly literature, it becomes evident that the intersection of air pollution and romantic relationships, though underexplored, holds the potential for intriguing revelations – and, dare we say, a breath of fresh air in the realm of social science research.

[[RESULTS]]
The statistical analyses conducted on the data collected from Salisbury, Maryland, and the state of Maryland from 1999 to 2021 yielded intriguing results. Our investigation revealed a substantial correlation coefficient of 0.8041956 between air pollution levels in Salisbury and the divorce rate in the state of Maryland. If this correlation were a movie, it would be a blockbuster hit – a real tear-jerker, or in this case, a lung-clogger.
The strong correlation was further supported by an r-squared value of 0.6467305, explaining approximately 64.67% of the variability in the divorce rate in Maryland due to changes in air pollution levels in Salisbury. This result suggests that air pollution may not only affect respiratory health but also have a notable impact on the interpersonal dynamics of households, providing a whole new meaning to the phrase "love is in the air."
Moreover, the p-value of less than 0.01 indicates that the observed relationship between air pollution and divorce rate is statistically significant, further cementing the validity of our findings. It seems the air in Salisbury may have a hand in stirring up more than just a gentle breeze of marital discord.
To visually capture the strength of the relationship between air pollution and divorce rate, we present Figure 1, a scatterplot that depicts the unmistakable correlation between these two variables. This plot serves as a poignant reminder that beneath the surface of seemingly unrelated phenomena, there may exist hidden connections waiting to be unearthed – much like discovering a forgotten love note in an old pair of jeans.
Overall, our results offer compelling evidence of a meaningful association between air pollution levels in Salisbury, Maryland, and the divorce rate in the state of Maryland. While the implications of this relationship are as of yet unclear, they certainly blow a breath of fresh air into the realm of environmental and social interactions.
With these findings in hand, it is evident that our understanding of the impact of air pollution extends beyond the confines of respiratory health and seeps into the intricate dance of human relationships. It appears that the air we breathe may indeed carry echoes of love and heartache, intertwining with our lives in ways we never imagined. As we bask in the breeze of these unexpected results, let us not forget that when it comes to matters of the heart, even the air may have a role to play.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

It appears that our investigation into the tangled web of air pollution and divorce rates has unraveled some intriguing findings. Firstly, let's revisit some of the quirky literature we stumbled upon during the literature review. While "Mist Connections: A Love Story Amidst Airborne Particulate Matter" and "Cloudy with a Chance of Heartache" may have sounded like fictional accounts, our results suggest that there might be more truth to these narratives than meets the eye. It seems the mist of air pollution may indeed cast a shadow over romantic entanglements, perhaps leading to misty-eyed conversations and tearful goodbyes.

Our findings align with the pioneering work of Smith et al. (2015), who laid the groundwork for understanding the psychological ramifications of poor air quality. While they focused on individual well-being, our research sheds light on the potential ripple effects of air pollution on societal dynamics, particularly within the realm of marital relationships. Additionally, the nuanced exploration of environmental conditions intersecting with romantic relationships in "Love in the Time of Smog" has found empirical support in our study – a testament to the far-reaching implications of polluted air on matters of the heart.

Turning to our statistical results, the robust correlation coefficient and r-squared value emphasize the strong relationship between air pollution and divorce rates. If statistics were characters in a novel, they would be the unassuming sidekicks who surprise everyone by stealing the show with their undeniable chemistry. Furthermore, the p-value of less than 0.01 adds a touch of statistical significance to our results, akin to the unexpected plot twist that leaves audiences in awe.

The scatterplot presented in Figure 1 serves as a visual testament to the unmistakable link between air pollution levels and divorce rates, offering a poignant reminder that beneath the surface of seemingly disparate phenomena, there may exist hidden connections waiting to be unveiled. It's almost as though air pollution and divorce rates are engaged in an intricate dance, where one partner's misstep leads to an unexpected turn in the other's routine – a tale of love and discord set against the backdrop of environmental adversity.

In summary, our study lends empirical weight to the whimsical narratives and serious research alike that have hinted at the potential impact of air pollution on romantic relationships. This unexpected connection between environmental factors and social phenomena underscores the need for a holistic approach to understanding human interactions, incorporating not only conventional psychological and behavioral variables but also environmental influences. As we continue to sift through the air of uncertainty, one thing is clear: the ties that bind us may be more intertwined with the air we breathe than we previously imagined.

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 Salisbury, Maryland and The divorce rate in Maryland. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Air We Done Yet? Exploring the Smoggy Link Between Air Pollution and Divorce Rates in Maryland"

[[ABSTRACT]]
There has been much debate over whether air pollution is merely a respiratory hazard or if it also has the ability to wreak havoc on romantic relationships. In this study, we delve into the fog of uncertainty to investigate the correlation between air pollution levels in Salisbury, Maryland, and the divorce rate in the state of Maryland. Our research team utilized data from the Environmental Protection Agency and CDC National Vital Statistics to conduct a thorough analysis from 1999 to 2021, or as we like to call it, the "air for divorce" period.

Our findings revealed a surprising correlation coefficient of 0.8041956 and p < 0.01, indicating a strong statistical relationship between air pollution in Salisbury and the divorce rate in Maryland. It seems our research not only cleared the air but also uncovered a potential, albeit unconventional, contributing factor to marital discord. Our results underscore the importance of considering environmental factors in studies of social phenomena, as the air we breathe may have broader implications for the ties that bind.

[[INTRDUCTION]]
INTRODUCTION
The relationship between air pollution and its impact on human health has been well-studied and documented. However, the potential influence of air pollution on social dynamics, particularly on romantic relationships, has remained largely unexplored. In the words of Shakespeare, "Is the smoggy air the cause, or rather fear of it?" Our study sought to shed light on this question by examining the intriguing association between air pollution levels in Salisbury, Maryland, and the divorce rate in the state of Maryland.
As we embark on this research journey, it is essential to address the elephant in the room – or should we say, the smog in the room? The idea that air pollution could play a role in marital strife may initially seem far-fetched, a bit like the elusive search for a breath of fresh air in the bustling city. However, as researchers, it is our duty to unpack the unexpected, to venture into uncharted territories, and to boldly go where no scholarly investigation has gone before – even if that means wading into the fog of potential puns and wordplay.
Our inquiry into the "air for divorce" period from 1999 to 2021 sought to disentangle the complexities of human relationships and environmental influences, and in doing so, we took a deep breath – albeit cautiously, given the air quality concerns. Our goal was to examine whether there exists a tangible link between the atmospheric haze and marital discord, or if this supposed association is merely an unsubstantiated gust of wind.
This study is not just blowing smoke; it grapples with a critical question that has been lingering in the air, much like a pesky air pollutant that refuses to dissipate. By exploring the potential connection between air pollution in Salisbury, a city known for its picturesque landscapes and savory seafood, and the divorce rate in Maryland, a state renowned for its blue crabs and historical charm, we endeavor to offer a breath of fresh insight into the interplay of environmental factors and human relationships.
As we delve deeper into the realm of air pollution and its unexpected ramifications, we invite our readers to join us on this scholarly adventure. Buckle up, because this research is about to take flight – hopefully, into cleaner, fresher air. Together, let us push the boundaries of conventional wisdom and unearth the surprising connections that lie beneath the surface, much like hidden treasure awaiting discovery.
Now, with a hefty supply of air fresheners and statistical analyses in tow, let us proceed to unveil the findings of our investigation, as we navigate the intricate dance between particulate matter and matters of the heart.

[[RESULTS]]
The statistical analyses conducted on the data collected from Salisbury, Maryland, and the state of Maryland from 1999 to 2021 yielded intriguing results. Our investigation revealed a substantial correlation coefficient of 0.8041956 between air pollution levels in Salisbury and the divorce rate in the state of Maryland. If this correlation were a movie, it would be a blockbuster hit – a real tear-jerker, or in this case, a lung-clogger.
The strong correlation was further supported by an r-squared value of 0.6467305, explaining approximately 64.67% of the variability in the divorce rate in Maryland due to changes in air pollution levels in Salisbury. This result suggests that air pollution may not only affect respiratory health but also have a notable impact on the interpersonal dynamics of households, providing a whole new meaning to the phrase "love is in the air."
Moreover, the p-value of less than 0.01 indicates that the observed relationship between air pollution and divorce rate is statistically significant, further cementing the validity of our findings. It seems the air in Salisbury may have a hand in stirring up more than just a gentle breeze of marital discord.
To visually capture the strength of the relationship between air pollution and divorce rate, we present Figure 1, a scatterplot that depicts the unmistakable correlation between these two variables. This plot serves as a poignant reminder that beneath the surface of seemingly unrelated phenomena, there may exist hidden connections waiting to be unearthed – much like discovering a forgotten love note in an old pair of jeans.
Overall, our results offer compelling evidence of a meaningful association between air pollution levels in Salisbury, Maryland, and the divorce rate in the state of Maryland. While the implications of this relationship are as of yet unclear, they certainly blow a breath of fresh air into the realm of environmental and social interactions.
With these findings in hand, it is evident that our understanding of the impact of air pollution extends beyond the confines of respiratory health and seeps into the intricate dance of human relationships. It appears that the air we breathe may indeed carry echoes of love and heartache, intertwining with our lives in ways we never imagined. As we bask in the breeze of these unexpected results, let us not forget that when it comes to matters of the heart, even the air may have a role to play.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has blown away any doubts about the association between air pollution in Salisbury, Maryland, and the divorce rate in the state of Maryland. Our findings have revealed a correlation so strong, it's practically a match made in hazy heaven. It seems like when it comes to marital discord, the air in Salisbury is not one to 'dust' off lightly.

Our results open up a whole new realm of possibilities, suggesting that the air we breathe might just be the unsung hero or villain in the grand soap opera of human relationships. Who knew that smog could be a silent contributor to the drama of the heart? It's a plot twist worthy of Shakespearean acclaim!

With a correlation coefficient that could stop traffic and a p-value that would make any statistician do a double-take, it's safe to say that our research has made an 'air-tight' case for further exploration of the atmospheric influence on matters of the heart.

Alas, like a turbulent relationship, our study must come to an end. We assert, with utmost confidence and a touch of whimsy, that no more research is needed in this area. After all, we don't want to be accused of 'polluting' the academic literature with an excessive amount of air-related puns.

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 Air We Done Yet? Exploring the Smoggy Link Between Air Pollution and Divorce Rates in Maryland. Respond only with the name of a fictional academic journal.

ChatGPT:

International Journal of Environmental Psychology

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 Air We Done Yet? Exploring the Smoggy Link Between Air Pollution and Divorce Rates in Maryland. Respond only with the name of a fictional organization.

ChatGPT:

The Association for the Advancement of Air Quality Science and Sustainability (AAAQSS)

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 Air We Done Yet? Exploring the Smoggy Link Between Air Pollution and Divorce Rates in Maryland with an abstract of There has been much debate over whether air pollution is merely a respiratory hazard or if it also has the ability to wreak havoc on romantic relationships. In this study, we delve into the fog of uncertainty to investigate the correlation between air pollution levels in Salisbury, Maryland, and the divorce rate in the state of Maryland. Our research team utilized data from the Environmental Protection Agency and CDC National Vital Statistics to conduct a thorough analysis from 1999 to 2021, or as we like to call it, the "air for divorce" period.
Our findings revealed a surprising correlation coefficient of 0.8041956 and p < 0.01, indicating a strong statistical relationship between air pollution in Salisbury and the divorce rate in Maryland. It seems our research not only cleared the air but also uncovered a potential, albeit unconventional, contributing factor to marital discord. Our results underscore the importance of considering environmental factors in studies of social phenomena, as the air we breathe may have broader implications for the ties that bind.

ChatGPT:

air pollution, divorce rates, Salisbury Maryland, environmental factors, respiratory hazards, correlation between air pollution and divorce, CDC National Vital Statistics, Environmental Protection Agency, marital discord, social phenomena, air pollution levels, statistical relationship

*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 Salisbury, Maryland
Detailed data title: Percentage of days with moderate or worse air quality in Salisbury, MD-DE
Source: Environmental Protection Agency
See what else correlates with Air pollution in Salisbury, Maryland

The divorce rate in Maryland
Source: CDC National Vital Statistics
See what else correlates with The divorce rate in Maryland

Correlation r = 0.8041956 (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 = 0.6467305 (Coefficient of determination)
This means 64.7% of the change in the one variable (i.e., The divorce rate in Maryland) is predictable based on the change in the other (i.e., Air pollution in Salisbury, Maryland) over the 23 years from 1999 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 3.8E-6.^Show 0.0000037636231173183850000000
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 0.8 in 0.00038% of random cases. Said differently, if you correlated 265,701 random variables^Note You don't actually need 265 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 22 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 22 because we have two variables measured over a period of 23 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.59, 0.91 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

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

	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Air pollution in Salisbury, Maryland (Bad air quality days)	0.473684	0.46595	0.501805	0.488971	0.392593	0.441065	0.501901	0.475655	0.498084	0.461538	0.27907	0.406557	0.241096	0.229508	0.205479	0.284932	0.265753	0.20765	0.161644	0.191781	0.180822	0.101093	0.120548
The divorce rate in Maryland (Divorce rate)	3.2	3.3	3	3.4	3.2	3.2	3.1	3	2.9	2.8	2.8	2.8	2.9	2.8	2.53356	2.54183	2.59556	2.68697	2.54272	2.40058	2.6619	1.67773	1.6024

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([0.473684,0.46595,0.501805,0.488971,0.392593,0.441065,0.501901,0.475655,0.498084,0.461538,0.27907,0.406557,0.241096,0.229508,0.205479,0.284932,0.265753,0.20765,0.161644,0.191781,0.180822,0.101093,0.120548,])
array_2 = np.array([3.2,3.3,3,3.4,3.2,3.2,3.1,3,2.9,2.8,2.8,2.8,2.9,2.8,2.53356,2.54183,2.59556,2.68697,2.54272,2.40058,2.6619,1.67773,1.6024,])
array_1_name = "Air pollution in Salisbury, Maryland"
array_2_name = "The divorce rate in Maryland"

# 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 Salisbury, Maryland
Line chart for only The divorce rate in Maryland
AI-generated correlation image
The spurious research paper: Air We Done Yet? Exploring the Smoggy Link Between Air Pollution and Divorce Rates in Maryland

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Correlation ID: 4548 · Black Variable ID: 21685 · Red Variable ID: 19803


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