Spurious correlation #2,489 · 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 Chicago and the second variable is Physical album shipment volume in the United States. The chart goes from 1999 to 2022, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air pollution in Chicago and the second variable is Physical album shipment volume in the United States. The chart goes from 1999 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the air in Chicago cleared up, it also cleared the minds of the music industry bigwigs. They suddenly realized that maybe, just maybe, people prefer streaming and digital downloads over lugging around bulky physical albums. Plus, with cleaner air, folks were more inclined to step out and buy concert tickets instead of staying cooped up, listening to old school CDs. It's as if the smog was the only thing keeping physical albums afloat!

^{Show image generation prompt} Model: dalle-3
Prompt: [ A photo-realistic image ] Create an image of a Chicago warehouse interior with meticulously detailed stacks of physical albums neatly organized on shelves. As the ambient lighting casts a warm glow, the albums are depicted as no longer sticking together due to a decrease in static electricity, resulting from decreased air pollution. Show a sense of order and reduced clumping with the albums shipping out in lower quantities, representing the decline in shipment volume of physical albums in the United States. Capture the atmosphere of change and progress as the albums stand individually, reflecting the impact of environmental factors on the music industry. 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 Chicago and Physical album shipment volume in the United States. 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: Celtic art A photo-realistic image Art nouveau Photorealism Oragami
ChatGPT: A photo-realistic image

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Air pollution in Chicago and Physical album shipment volume in the United States, in the following situation: The decrease in air pollution led to a decrease in static electricity, which meant that physical albums were no longer sticking to each other in the warehouses, resulting in lower shipment volume.. Keep the description simple.
ChatGPT: In a Chicago warehouse, stacks of physical albums are no longer sticking together due to the decrease in static electricity caused by the decreased air pollution. As a result, the shipment volume of physical albums in the United States has decreased, with the albums no longer clumping together and shipping out in lower quantities.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A photo-realistic image ] and depicting this scene: In a Chicago warehouse, stacks of physical albums are no longer sticking together due to the decrease in static electricity caused by the decreased air pollution. As a result, the shipment volume of physical albums in the United States has decreased, with the albums no longer clumping together and shipping out in lower quantities. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ A photo-realistic image ] Create an image of a Chicago warehouse interior with meticulously detailed stacks of physical albums neatly organized on shelves. As the ambient lighting casts a warm glow, the albums are depicted as no longer sticking together due to a decrease in static electricity, resulting from decreased air pollution. Show a sense of order and reduced clumping with the albums shipping out in lower quantities, representing the decline in shipment volume of physical albums in the United States. Capture the atmosphere of change and progress as the albums stand individually, reflecting the impact of environmental factors on the music industry.

*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 Chicago caused Physical album shipment volume in the United States to decrease.

AI academic paper

(Because p < 0.01)

The Air We Breathe and the Musical Beat: Uncovering the Melodious Link Between Chicago's Air Pollution and Physical Album Shipments in the United States

The Journal of Sonic Ecology

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 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 Chicago and Physical album shipment volume in the United States. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Statista . You used data from 1999 to 2022

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
The Air We Breathe and the Musical Beat: Uncovering the Melodious Link Between Chicago's Air Pollution and Physical Album Shipments in the United States

[[ABSTRACT]]
In this research paper, we investigate the hitherto unexplored relationship between air pollution levels in Chicago and physical album shipment volumes in the United States. Leveraging data from the Environmental Protection Agency and Statista, we sought to bridge the gap between environmental factors and the musical landscape. Our findings reveal a surprising correlation coefficient of 0.8417364 and a p-value of less than 0.01 for the years 1999 to 2022, indicating a strong connection between Chi-town's polluted air and the rhythms of physical album sales across the nation. Our study sheds light on the harmonious interplay between pollution and music consumption, underscoring the need for further research to uncover the underlying mechanisms. So, take a deep breath and join us on this intriguing journey through the symphony of air quality and album shipments.

[[INTRODUCTION]]
Music, melodies, and pollution - what a strange trio, you might think. But hold on to your scientific hat, because we are about to embark on a rhythmic journey that will make your head spin faster than a vinyl record on a turntable. In this symphony of a research paper, we delve into the little-explored relationship between air pollution levels in Chicago and the shipment volumes of physical albums in the United States.
Picture this: the smoggy, windswept city of Chicago, home to deep-dish pizza and the echoes of blues and jazz, holds a mysterious connection to the rhythms of album sales across the nation. It's like the wind blowing through the alleyways is whispering a tune that resonates with the hearts of music lovers everywhere. Or perhaps, it's the pollution particles doing a jig with the musical notes, creating an unlikely but catchy harmony.
But fear not, dear readers - we haven't fallen off the musical scale into the realm of whimsy. Our inquiry into this peculiar pairing is backed by data, statistics, and a hefty dose of academic rigor. We've trawled through the Environmental Protection Agency's archives and crunched numbers from Statista, all in the name of uncovering the melody in the madness.
So, as we dust off our microscopes and tune our data analysis software, let's venture deep into the heart of this enigmatic duet between polluted air and the physical albums flying off the shelves. It's a tale that will make even the most stoic scientist tap their foot to the beat of statistical significance.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

In order to unravel the enigmatic entanglement of air pollution and physical album shipments, we employed a mixture of quantitative analysis, field observations, and a sprinkle of musical inspiration. Our methodology was as carefully orchestrated as a conductor leading a symphony, albeit with more spreadsheets and less baton waving.

1. Data Collection:
We amassed air quality data from the Environmental Protection Agency, meticulously sifting through years of pollution measurements like archaeologists unearthing ancient artifacts. Our team combed through pollutant concentrations of sulfur dioxide, nitrogen dioxide, carbon monoxide, and ozone, transforming these ominous-sounding gases into variables ripe for statistical manipulation. Like a DJ crafting a playlist, we selected Chicago as our focal point, embracing the city's smog as the protagonist in this scientific saga.

2. Album Shipment Volume Assessment:
To capture the pulsating rhythms of physical album shipments, we turned to the musical maestros at Statista. Their treasure trove of industry data became our stage, allowing us to track the ebb and flow of album sales across the seas of commerce. We monitored the shipment volumes of vinyl, CDs, and even the occasional cassette tape, ensuring that no musical format was left out in the cold. Our goal? To align these musical tidings with Chicago's polluted airs, creating a symphonic duet of data points and jazzy statistics.

3. Statistical Conjuring:
Armed with our data arsenal, we donned our statistical wizard hats and let loose the powers of correlation analysis. Our aim was crystal clear: to ascertain the strength of the relationship between Chicago's air pollution levels and the waves of physical album shipments throughout the United States. We performed Pearson correlations with the precision of a surgeon, uncovering a coefficient so compelling that it could make even the most steadfast scientists hum a merry tune.

4. Time Travel Through Data:
Our quest for knowledge spanned from the bygone year of 1999 to the present day of 2022, capturing a snapshot of the hums and hollers emanating from Chicago's atmospheric symphony. By examining this expansive time frame, we aimed to tease out any temporal melodies that might sway the tides of album shipments, all while keeping an eye on the ebb and flow of pollution's grim notes.

5. Qualitative Interlude:
In addition to our quantitative endeavors, we ventured into the field, immersing ourselves in the pulse of Chicago's bustling streets. As we inhaled the city's atmospheric ensemble and listened to the beat of its music scene, we sought to complement our data-driven insights with a touch of qualitative understanding. This added layer of observation allowed us to capture the essence of Chicago's musical tapestry, breathing life into our quantitative findings like a crescendo in a grand symphony.

6. Ethical Footnote:
Throughout our research, we upheld the highest ethical standards, ensuring that our inquiry into air pollution and album shipments did not compose any harm to the environment or the music industry. We tip our hats to the IRB for their virtuoso oversight and dedication to the harmonious conduct of scientific investigation.

With our methodological score firmly etched, we approached our analysis with the precision of a virtuoso musician on the cusp of a grand performance. Our endeavor was not merely a research study; it was a melodic adventure through the unseen rhythms of Chicago's polluted air and the nation's musical tapestry.

But fear not, for the real duet lies in the results and discussion that awaits, promising an orchestra of intriguing findings and toe-tapping interpretations. As we raise the curtain on our statistical symphony, join us in uncovering the melodious link between the air we breathe and the beats that move us.

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 Chicago and Physical album shipment volume in the United States. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
The Air We Breathe and the Musical Beat: Uncovering the Melodious Link Between Chicago's Air Pollution and Physical Album Shipments in the United States

[[ABSTRACT]]
In this research paper, we investigate the hitherto unexplored relationship between air pollution levels in Chicago and physical album shipment volumes in the United States. Leveraging data from the Environmental Protection Agency and Statista, we sought to bridge the gap between environmental factors and the musical landscape. Our findings reveal a surprising correlation coefficient of 0.8417364 and a p-value of less than 0.01 for the years 1999 to 2022, indicating a strong connection between Chi-town's polluted air and the rhythms of physical album sales across the nation. Our study sheds light on the harmonious interplay between pollution and music consumption, underscoring the need for further research to uncover the underlying mechanisms. So, take a deep breath and join us on this intriguing journey through the symphony of air quality and album shipments.

[[LITERATURE REVIEW]]
The connection between environmental factors and consumer behavior has long been of interest to researchers. Smith et al. (2010) examined the impact of air pollution on consumer habits, focusing primarily on purchasing patterns in urban areas. Their findings suggested that air quality does indeed influence consumer decisions, albeit in unexpected ways. Meanwhile, Doe and Jones (2015) delved into the realm of music consumption and its ties to geographic location, uncovering intriguing correlations between regional pollution levels and musical preferences.
Moving from the serious scholarly work to more diverse sources, we can draw upon non-fiction books such as "The Air We Breathe" by Andrea Barrett and "This Changes Everything: Capitalism vs. The Climate" by Naomi Klein for insights into the complexities of environmental issues. On the fictional side, consider the classic novel "Great Expectations" by Charles Dickens (after all, who wouldn't have great expectations for this research?) and "The Pollution Monster" by Brock Cole, a whimsical tale that brings a fantastical element to our discussion.
In expanding our exploration to the world of pop culture, we find that children's cartoons and television shows can also offer valuable perspectives on environmental themes. For instance, taking a leaf out of the "Captain Planet and the Planeteers" playbook, we might uncover the "power of pollution" in shaping societal attitudes and behaviors.
Just as a mixtape seamlessly transitions from one track to another, our review of the literature has taken us on a wild ride through scholarly articles, novels, and children's entertainment. But fear not, for this whimsical detour is all in the service of enhancing our understanding of the harmonious dance between air pollution in Chicago and the shipment volumes of physical albums in the United States.

[[RESULTS]]
The results of our analysis revealed an intriguing connection between air pollution levels in Chicago and physical album shipment volumes in the United States. With a correlation coefficient of 0.8417364, an r-squared value of 0.7085201, and a p-value of less than 0.01, we found evidence of a strong and statistically significant relationship between these seemingly disparate variables. It seems that the melodies of music are not just carried by sound waves but are also intertwined with the very air we breathe—talk about hitting a high note in research!
Figure 1 showcases the impressive correlation between air pollution in Chicago and physical album shipment volumes in the United States. It's a sight to behold, like witnessing a perfect duet between two unexpected partners—the windy city's pollution and the melodies packaged in physical albums transcending geographical boundaries.
But what does all this mean? Well, our results suggest that as air pollution levels in Chicago increase, there is a corresponding surge in the shipment volumes of physical albums across the United States. It's as if the hazy air is whispering to the masses, "Hey, maybe it's time to dust off those old vinyl records and groove to the tunes of yesteryear!"
While we can't pin down the exact reasons behind this harmonious relationship just yet, our findings call for further exploration into the intriguing interplay between environmental factors and music consumption. Is there something in the polluted air that triggers a nostalgic craving for physical music, or are the music gods simply playing a cosmic joke on us all? We're not entirely sure, but we're excited to delve deeper into this sonorous saga.
In conclusion, our study highlights the enigmatic connection between air pollution and physical album shipments, inviting researchers to join us in deciphering this musical mystery. So, as you ponder the implications of this unexpected correlation, remember that science can be just as melodious as a symphony—albeit with a hint of statistical significance and a chorus of curious researchers tapping their feet to the beat of discovery.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our findings not only hit all the right notes but also harmonize with prior research, validating and amplifying the existing body of knowledge on the intersection of environmental factors and consumer behaviors. Smith et al.'s (2010) study, which highlighted the influence of air pollution on consumer habits, seems to have stumbled upon a surprising musical link, much like finding a hidden track on a well-worn vinyl record. Meanwhile, the work of Doe and Jones (2015) provided a rhythmic undertone to our own exploration, reinforcing the notion that regional pollution levels can orchestrate consumer preferences, including the choice of physical albums over digital ones.

As we ventured through the scholarly literature and partook in the whimsical delight of fictional narratives and popular culture references, it became increasingly evident that our study was not merely an isolated solo performance but rather a spirited ensemble piece, echoing and amplifying the curious connections between the windy city's air quality and the nation's musical inclinations. Just as a symphony gains depth from the interplay of various instruments, our research enriched the existing discourse by lending empirical support to the melodic correlations hinted at in diverse sources.

In light of our statistically significant correlation between air pollution in Chicago and physical album shipments in the United States, it seems that the old adage rings true: where there's smog, there's grog—err, I mean, music. Our results resonate with the metaphorical chords struck by the likes of Charles Dickens and the creators of "Captain Planet and the Planeteers," underscoring the multifaceted impact of environmental factors on cultural phenomena such as music consumption.

The strong correlation coefficient and r-squared value bear testimony to the symphonic dance between Chicago's polluted air and the nationwide shipment volumes of physical albums. It's as though Chi-town's pollution is playing lead guitar in a cosmic rock band, with physical album shipments as its adoring fans swaying to the infectious rhythm. This unexpected partnership between pollution and physical albums leaves us pondering the age-old question: is the urban air so thick with musical nostalgia that it triggers a surge in physical album sales, or are we witnessing a cosmic prank orchestrated by mischievous muses?

In closing, our study not only strikes a chord with prior research but also amplifies the enduring melody of environmental influence on consumer behaviors. We eagerly anticipate the next movement in this symphony of research, as we strive to unravel the lyrical mysteries underlying the intriguing relationship between air pollution and physical album shipments. So, as we bid adieu to this discussion, let us remember that while science and statistics may seem serious, they can also serenade us with unexpected connections and melodious musings.

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 Chicago and Physical album shipment volume in the United States. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
The Air We Breathe and the Musical Beat: Uncovering the Melodious Link Between Chicago's Air Pollution and Physical Album Shipments in the United States

[[ABSTRACT]]
In this research paper, we investigate the hitherto unexplored relationship between air pollution levels in Chicago and physical album shipment volumes in the United States. Leveraging data from the Environmental Protection Agency and Statista, we sought to bridge the gap between environmental factors and the musical landscape. Our findings reveal a surprising correlation coefficient of 0.8417364 and a p-value of less than 0.01 for the years 1999 to 2022, indicating a strong connection between Chi-town's polluted air and the rhythms of physical album sales across the nation. Our study sheds light on the harmonious interplay between pollution and music consumption, underscoring the need for further research to uncover the underlying mechanisms. So, take a deep breath and join us on this intriguing journey through the symphony of air quality and album shipments.

[[INTRDUCTION]]
Music, melodies, and pollution - what a strange trio, you might think. But hold on to your scientific hat, because we are about to embark on a rhythmic journey that will make your head spin faster than a vinyl record on a turntable. In this symphony of a research paper, we delve into the little-explored relationship between air pollution levels in Chicago and the shipment volumes of physical albums in the United States.
Picture this: the smoggy, windswept city of Chicago, home to deep-dish pizza and the echoes of blues and jazz, holds a mysterious connection to the rhythms of album sales across the nation. It's like the wind blowing through the alleyways is whispering a tune that resonates with the hearts of music lovers everywhere. Or perhaps, it's the pollution particles doing a jig with the musical notes, creating an unlikely but catchy harmony.
But fear not, dear readers - we haven't fallen off the musical scale into the realm of whimsy. Our inquiry into this peculiar pairing is backed by data, statistics, and a hefty dose of academic rigor. We've trawled through the Environmental Protection Agency's archives and crunched numbers from Statista, all in the name of uncovering the melody in the madness.
So, as we dust off our microscopes and tune our data analysis software, let's venture deep into the heart of this enigmatic duet between polluted air and the physical albums flying off the shelves. It's a tale that will make even the most stoic scientist tap their foot to the beat of statistical significance.

[[RESULTS]]
The results of our analysis revealed an intriguing connection between air pollution levels in Chicago and physical album shipment volumes in the United States. With a correlation coefficient of 0.8417364, an r-squared value of 0.7085201, and a p-value of less than 0.01, we found evidence of a strong and statistically significant relationship between these seemingly disparate variables. It seems that the melodies of music are not just carried by sound waves but are also intertwined with the very air we breathe—talk about hitting a high note in research!
Figure 1 showcases the impressive correlation between air pollution in Chicago and physical album shipment volumes in the United States. It's a sight to behold, like witnessing a perfect duet between two unexpected partners—the windy city's pollution and the melodies packaged in physical albums transcending geographical boundaries.
But what does all this mean? Well, our results suggest that as air pollution levels in Chicago increase, there is a corresponding surge in the shipment volumes of physical albums across the United States. It's as if the hazy air is whispering to the masses, "Hey, maybe it's time to dust off those old vinyl records and groove to the tunes of yesteryear!"
While we can't pin down the exact reasons behind this harmonious relationship just yet, our findings call for further exploration into the intriguing interplay between environmental factors and music consumption. Is there something in the polluted air that triggers a nostalgic craving for physical music, or are the music gods simply playing a cosmic joke on us all? We're not entirely sure, but we're excited to delve deeper into this sonorous saga.
In conclusion, our study highlights the enigmatic connection between air pollution and physical album shipments, inviting researchers to join us in deciphering this musical mystery. So, as you ponder the implications of this unexpected correlation, remember that science can be just as melodious as a symphony—albeit with a hint of statistical significance and a chorus of curious researchers tapping their feet to the beat of discovery.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In the immortal words of Queen, "Is this the real life? Is this just fantasy?" Well, folks, it seems we're not in the realm of make-believe but rather at the intersection of air pollution and musical euphoria. Our research has struck a chord—quite literally—revealing a compelling connection between Chicago's polluted air and the shipment volumes of physical albums across the United States.

As we wrap up this cacophony of findings, it's clear that our study has hit a high note in uncovering the harmonious interplay between environmental factors and music consumption. The correlation coefficient of 0.8417364 and the p-value of < 0.01 are singing a chorus of statistical significance, urging us to pay heed to the melody in the madness.

Now, before you go thinking, "What in the world could polluted air possibly have to do with physical album shipments?" we'd like to wave our conductor's baton and remind you that science is full of surprises. Just like that unexpected key change in your favorite tune, this correlation has us dancing to a new rhythm, one that calls for further exploration and whimsical pondering.

But fear not, fellow researchers, for our findings provide a hearty serving of food for thought. Whether it's the smog whispering nostalgic tunes or the music gods playing a cosmic joke, our study beckons you to join the symphony of inquiry. And as for future research in this uncharted territory, we can confidently declare: "No more air pollution and music correlation studies needed!" This harmonious duo has had its time in the limelight, and it's now officially stealing the show. So, let's bid adieu to this intriguing saga and leave the audience on a euphonious high note. Cheers to the surprisingly musical world of data and discovery!

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 The Air We Breathe and the Musical Beat: Uncovering the Melodious Link Between Chicago's Air Pollution and Physical Album Shipments in the United States. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Sonic Ecology

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited The Air We Breathe and the Musical Beat: Uncovering the Melodious Link Between Chicago's Air Pollution and Physical Album Shipments in the United States. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Harmonious Urban Environments and Soundscapes

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 The Air We Breathe and the Musical Beat: Uncovering the Melodious Link Between Chicago's Air Pollution and Physical Album Shipments in the United States with an abstract of In this research paper, we investigate the hitherto unexplored relationship between air pollution levels in Chicago and physical album shipment volumes in the United States. Leveraging data from the Environmental Protection Agency and Statista, we sought to bridge the gap between environmental factors and the musical landscape. Our findings reveal a surprising correlation coefficient of 0.8417364 and a p-value of less than 0.01 for the years 1999 to 2022, indicating a strong connection between Chi-town's polluted air and the rhythms of physical album sales across the nation. Our study sheds light on the harmonious interplay between pollution and music consumption, underscoring the need for further research to uncover the underlying mechanisms. So, take a deep breath and join us on this intriguing journey through the symphony of air quality and album shipments.

ChatGPT:

air pollution, Chicago, physical album shipment, United States, correlation, Environmental Protection Agency, Statista, music consumption, pollution and music, album sales, pollution levels, correlation coefficient, p-value, Environmental factors

*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 Chicago
Detailed data title: Percentage of days with air quality at 'unhealthy for sensitive groups' or worse in Chicago-Naperville-Elgin, IL-IN-WI
Source: Environmental Protection Agency
See what else correlates with Air pollution in Chicago

Physical album shipment volume in the United States
Source: Statista
See what else correlates with Physical album shipment volume in the United States

Correlation r = 0.8417364 (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 = 0.7085201 (Coefficient of determination)
This means 70.9% of the change in the one variable (i.e., Physical album shipment volume in the United States) is predictable based on the change in the other (i.e., Air pollution in Chicago) over the 24 years from 1999 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.5E-7.^Show 0.0000002535947600514176400000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.84 in 2.5E-5% of random cases. Said differently, if you correlated 3,943,299 random variables^Note You don't actually need 3 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 23 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 23 because we have two variables measured over a period of 24 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.

[ 0.66, 0.93 ] 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	2022
Air pollution in Chicago (Bad air quality days)	21.0959	16.9399	24.3836	18.0822	15.8904	11.2022	20.274	6.57534	15.8904	12.2951	6.0274	9.58904	6.57534	13.6612	4.65753	4.93151	3.83562	7.65027	6.84932	7.12329	3.56164	6.55738	7.67123	4.10959
Physical album shipment volume in the United States (Units)	938900000	942500000	881900000	803300000	746000000	767000000	705400000	619700000	511100000	368400000	292900000	253000000	240800000	198200000	172200000	142800000	122900000	97600000	87700000	52000000	47500000	31600000	46700000	33400000

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([21.0959,16.9399,24.3836,18.0822,15.8904,11.2022,20.274,6.57534,15.8904,12.2951,6.0274,9.58904,6.57534,13.6612,4.65753,4.93151,3.83562,7.65027,6.84932,7.12329,3.56164,6.55738,7.67123,4.10959,])
array_2 = np.array([938900000,942500000,881900000,803300000,746000000,767000000,705400000,619700000,511100000,368400000,292900000,253000000,240800000,198200000,172200000,142800000,122900000,97600000,87700000,52000000,47500000,31600000,46700000,33400000,])
array_1_name = "Air pollution in Chicago"
array_2_name = "Physical album shipment volume in the United States"

# 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 Chicago
Line chart for only Physical album shipment volume in the United States
AI-generated correlation image
The spurious research paper: The Air We Breathe and the Musical Beat: Uncovering the Melodious Link Between Chicago's Air Pollution and Physical Album Shipments in the United States

View another random correlation

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Correlation ID: 2489 · Black Variable ID: 20456 · Red Variable ID: 155


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