Spurious correlation #1,353 · 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 Kerosene used in Brazil. The chart goes from 1980 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 Chicago and the second variable is Kerosene used in Brazil. The chart goes from 1980 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the air pollution in Chicago decreased, it created a ripple effect that traveled all the way to Brazil. This unexpected connection can be attributed to the little-known phenomenon of atmospheric dominoes, where changes in one city's air quality can knock over a chain of events leading to reduced kerosene usage in another country. It's a testament to the truly global impact of local environmental improvements.

^{Show image generation prompt} Model: dalle-3
Prompt: [ Whimsical illustration ] In a bustling city, thick smog hangs in the air, blurring the towering buildings into dreamy silhouettes. People adorned in colorful masks traverse the streets, each figure a whimsical display of resilience against the polluted skies. Meanwhile, in a tranquil Brazilian village, families gather under the soft glow of kerosene lamps as the sun slips below the horizon. The warm light bathes the quaint dwellings and the surrounding foliage with a magical, cozy aura. 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 situation described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here is a situation: Because the decrease in unhealthy air quality in Chicago caused fewer people to light their farts on fire, leading to a decrease in demand for kerosene in Brazil for putting out accidental flaming farts.. Given that situation, which of the following image descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand and the tone of the explanation. Please respond with only one of the following potential descriptions: Low poly Cutsy art illustration Whimsical illustration A scene from Skyrim Macabre
ChatGPT: Whimsical illustration

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated and the explanation described. Do not reference graphs or charts; describe physical objects.
User prompt: Please describe a visual scene that prominently depicts both Unhealthy air quality in Chicago and Kerosene used in Brazil Keep the description simple.
ChatGPT: In a busy street in Chicago, thick smog hangs in the air, making it difficult to see the buildings clearly. People are wearing masks to protect themselves from the polluted air. Meanwhile, in a small village in Brazil, families are using kerosene lamps to light up their homes as the sun sets, the dim light casting a warm glow on the surroundings.

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: [ Whimsical illustration ] and depicting this scene: In a busy street in Chicago, thick smog hangs in the air, making it difficult to see the buildings clearly. People are wearing masks to protect themselves from the polluted air. Meanwhile, in a small village in Brazil, families are using kerosene lamps to light up their homes as the sun sets, the dim light casting a warm glow on the surroundings. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ Whimsical illustration ] In a bustling city, thick smog hangs in the air, blurring the towering buildings into dreamy silhouettes. People adorned in colorful masks traverse the streets, each figure a whimsical display of resilience against the polluted skies. Meanwhile, in a tranquil Brazilian village, families gather under the soft glow of kerosene lamps as the sun slips below the horizon. The warm light bathes the quaint dwellings and the surrounding foliage with a magical, cozy aura.

*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 Kerosene used in Brazil to decrease. Make it feel plausible.

AI academic paper

(Because p < 0.01)

Up in the Air: Unraveling the Correlation Between Chicago Air Pollution and Brazilian Kerosene Consumption

Journal of Transcontinental Environmental Studies

Jan 2024

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

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Air pollution in Chicago and Kerosene used in Brazil. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
"Up in the Air: Unraveling the Correlation Between Chicago Air Pollution and Brazilian Kerosene Consumption"

[[ABSTRACT]]
The potential connection between air pollution in urban areas and the consumption of kerosene in far-off lands has long piqued the curiosity of researchers and policymakers alike. In this paper, we delve into this unconventional relationship, employing a meticulous analysis of data from the Environmental Protection Agency and the Energy Information Administration. Our findings reveal a striking correlation coefficient of 0.8139423 and a statistically significant p-value of less than 0.01 for the period spanning from 1980 to 2021.

As we examined the intricate interplay between air quality in Chicago and kerosene consumption in Brazil, we stumbled upon some surprising insights. It appears that the particles emitted into the atmosphere from Chicago's urban activities may be taking an unexpected South American detour. This phenomenon, whimsically dubbed the "Gust of Global Exchange," demonstrates that air pollution knows no geographic boundaries - much like a persistent knock-knock joke, it simply cannot be contained.

Our study underscores the importance of considering international and intercontinental factors in the quest to understand the dynamics of air pollution. The link between Chicago's smog and the reliance on kerosene in Brazil serves as a poignant reminder of the interconnectedness of environmental issues across the globe. Just as a well-timed dad joke can lighten the mood, our research sheds light on the unanticipated connections that underlie seemingly disparate phenomena.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The pervasive issue of air pollution has garnered immense attention from both the scientific community and society at large, akin to a particularly catchy earworm that refuses to fade from memory. Concurrently, the global consumption of kerosene, most commonly wielded as a source of illumination and energy, has been an area of interest for researchers delving into the intricate web of energy usage. Despite these seemingly unrelated domains, the possibility of a link between the air pollution levels in Chicago and the prominent utilization of kerosene in Brazil has ignited a fervent curiosity within the scientific community. As we embark on this investigative journey, it becomes imperative to ascertain whether the association between these two variables is grounded in empirical evidence or merely an illusory correlation, akin to a lab-coat clad magician pulling statistics out of a hat.
Intriguingly, our inquiry leads us to the peculiar juxtaposition of the Windy City's atmospheric quality and the far-off glow of Brazilian kerosene lamps - as if the gusts of air pollution from Chicago have taken on a life of their own, embarking on a transcontinental odyssey. This serendipitous rendezvous presents an opportunity to unravel the enigmatic connection between domestic emissions and their transoceanic endeavors, not unlike a globetrotting detective ferreting out clues in unexpected locales. Indeed, the "Gust of Global Exchange" phenomenon encapsulates the whimsical nature of our planet's interconnected environmental dynamics, as if the world were woven together by an invisible thread of ecological banter.
The task at hand entails a multidimensional exploration, carefully navigating the labyrinthine pathways of environmental data and statistical analyses. With the gravity of our findings lingering in the air like an unspoken punchline, we aim to shed light on the interconnectedness of seemingly disparate ecological factors, thereby elevating the discourse surrounding environmental sustainability. This research endeavor, much like an unexpected quip in a solemn lecture hall, endeavors to infuse levity into the often weighty subject of environmental inquiry while maintaining the steadfast rigor that characterizes scientific investigation.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Smith and Doe's groundbreaking study on urban air pollution," the authors find an intricate web of pollutants emanating from diverse sources such as vehicular emissions, industrial activities, and residential energy usage. These findings lay the foundation for understanding the complex composition of air pollution in urban centers, reminiscent of a colorful tapestry woven by an industrious yet slightly mischievous textile artist.

Similarly, "Jones' comprehensive analysis of kerosene consumption in developing countries" elucidates the pervasive reliance on kerosene for domestic lighting and cooking purposes. The study highlights the challenges posed by limited access to electricity in underserved regions, painting a poignant picture of communities illuminated by the warm glow of kerosene lamps, akin to fireflies dancing in the night – albeit with a distinctly less whimsical environmental impact.

Venturing beyond the realm of empirical research, "The Big Book of Air Pollution" by environmental expert Dr. Cleanair, and "Kerosene Chronicles: Illuminating Tales from Around the World" by energy historian Luminous Lenny, provide comprehensive narratives on the historical evolution and contemporary manifestations of air pollution and kerosene usage, respectively. Dr. Cleanair's work, much like a stern-faced scientist with a hidden penchant for puns, meticulously documents the progression of air quality research. Meanwhile, Luminous Lenny's literary endeavor sheds light on the global reverberations of kerosene consumption, illuminating the interconnectedness of seemingly distinct communities and their preferred choice of illumination – not unlike a global game of "spot the difference" played out with flickering kerosene lamps.

In a surprising twist, "Kerosene Chronicles" is packed with unexpected humor and witty anecdotes, incorporating stories of adventurous travelers and their encounters with kerosene-fueled contraptions. The author's playful approach to a seemingly mundane subject could be likened to a lighthearted jest amidst a solemn gathering of historians – much like a kerosene lamp at a power outage support group, providing a flickering sense of mirth in the midst of darkness.

Furthermore, during my perusal of social media channels, an anonymous post humorously remarked on the potential global travels of Chicago's air pollutants, suggesting that the Windy City's emissions might be on a quest for adventure, not unlike a group of intrepid backpackers - affirming the old adage that "even air pollution deserves a vacation" in its own peculiar way.

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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Air pollution in Chicago and Kerosene used in Brazil. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 Energy Information Administration . You used data from 1980 to 2021

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Up in the Air: Unraveling the Correlation Between Chicago Air Pollution and Brazilian Kerosene Consumption"

[[ABSTRACT]]
The potential connection between air pollution in urban areas and the consumption of kerosene in far-off lands has long piqued the curiosity of researchers and policymakers alike. In this paper, we delve into this unconventional relationship, employing a meticulous analysis of data from the Environmental Protection Agency and the Energy Information Administration. Our findings reveal a striking correlation coefficient of 0.8139423 and a statistically significant p-value of less than 0.01 for the period spanning from 1980 to 2021.

As we examined the intricate interplay between air quality in Chicago and kerosene consumption in Brazil, we stumbled upon some surprising insights. It appears that the particles emitted into the atmosphere from Chicago's urban activities may be taking an unexpected South American detour. This phenomenon, whimsically dubbed the "Gust of Global Exchange," demonstrates that air pollution knows no geographic boundaries - much like a persistent knock-knock joke, it simply cannot be contained.

Our study underscores the importance of considering international and intercontinental factors in the quest to understand the dynamics of air pollution. The link between Chicago's smog and the reliance on kerosene in Brazil serves as a poignant reminder of the interconnectedness of environmental issues across the globe. Just as a well-timed dad joke can lighten the mood, our research sheds light on the unanticipated connections that underlie seemingly disparate phenomena.

[[INTRODUCTION]]
The pervasive issue of air pollution has garnered immense attention from both the scientific community and society at large, akin to a particularly catchy earworm that refuses to fade from memory. Concurrently, the global consumption of kerosene, most commonly wielded as a source of illumination and energy, has been an area of interest for researchers delving into the intricate web of energy usage. Despite these seemingly unrelated domains, the possibility of a link between the air pollution levels in Chicago and the prominent utilization of kerosene in Brazil has ignited a fervent curiosity within the scientific community. As we embark on this investigative journey, it becomes imperative to ascertain whether the association between these two variables is grounded in empirical evidence or merely an illusory correlation, akin to a lab-coat clad magician pulling statistics out of a hat.
Intriguingly, our inquiry leads us to the peculiar juxtaposition of the Windy City's atmospheric quality and the far-off glow of Brazilian kerosene lamps - as if the gusts of air pollution from Chicago have taken on a life of their own, embarking on a transcontinental odyssey. This serendipitous rendezvous presents an opportunity to unravel the enigmatic connection between domestic emissions and their transoceanic endeavors, not unlike a globetrotting detective ferreting out clues in unexpected locales. Indeed, the "Gust of Global Exchange" phenomenon encapsulates the whimsical nature of our planet's interconnected environmental dynamics, as if the world were woven together by an invisible thread of ecological banter.
The task at hand entails a multidimensional exploration, carefully navigating the labyrinthine pathways of environmental data and statistical analyses. With the gravity of our findings lingering in the air like an unspoken punchline, we aim to shed light on the interconnectedness of seemingly disparate ecological factors, thereby elevating the discourse surrounding environmental sustainability. This research endeavor, much like an unexpected quip in a solemn lecture hall, endeavors to infuse levity into the often weighty subject of environmental inquiry while maintaining the steadfast rigor that characterizes scientific investigation.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

Data Collection:
The comprehensive data utilized in this study was predominantly extracted from the Environmental Protection Agency and the Energy Information Administration. Akin to a seasoned detective combing through evidence at a crime scene, our research team meticulously sifted through decades of air quality indices for Chicago and kerosene consumption statistics for Brazil - a pursuit that demanded diligence, precision, and a sizeable amount of caffeinated beverages. The data covering the period from 1980 to 2021 was then subjected to rigorous scrutiny, akin to a sommelier discerning the subtle notes of a fine wine - except in this case, the vintage was the statistical kind.

Correlation Analysis:
To unravel the potential link between air pollution in Chicago and kerosene consumption in Brazil, we employed the Pearson correlation coefficient, a quantitative measure of the strength and direction of the linear relationship between two variables. The resultant coefficient, much like a confounding pun, revealed a striking correlation of 0.8139423, indicating a strong positive association between the two variables. This finding elicited a response in our research team similar to that of a perfectly executed dad joke - a mix of surprise, amusement, and a hint of validation for our painstaking efforts.

Regression Modeling:
In addition to the correlation analysis, we conducted a series of regression models to further elucidate the intricate connection between Chicago's air pollution and Brazilian kerosene consumption. The models were carefully crafted, much like a master chef concocting a delicate souffle, to control for potential confounding variables and elucidate the nuanced interplay between the focal variables. The statistically significant p-value of less than 0.01 in the regression analysis provided robust evidence of the substantial influence of Chicago's air quality on kerosene consumption in Brazil, leaving us with a sense of certitude akin to the flawless delivery of a well-timed dad joke.

Time Series Analysis:
The investigation delved into time series analysis to discern temporal patterns and trends in both air pollution levels in Chicago and kerosene usage in Brazil. This intricate analysis allowed us to trace the ebbs and flows of these variables over the decades, much like an astute music critic identifying the subtle shifts in a symphony. The findings from the time series analysis added a layer of depth to our understanding of the dynamic relationship between these two seemingly distant phenomena, much like the unexpected depth of a pun that leaves one chuckling days later.

Granger Causality Test:
In exploring the potential direction of causality between air pollution in Chicago and kerosene consumption in Brazil, we employed the Granger causality test. This test enabled us to discern whether past values of one variable provide information about future values of the other, shedding light on the potential lead-lag relationship between the variables. The definitive results of the Granger causality test, much like the punchline to a well-constructed joke, provided clarity on the influential direction of the relationship - solidifying our understanding of the dynamics at play in this unconventional ecological commingling.

In summary, our methodological approach encompassed a judicious amalgamation of statistical analyses and data exploration to unearth the intriguing correlation between air pollution in Chicago and kerosene consumption in Brazil. Just as a clever pun can illuminate a conversation, our methodology aimed to shed light on the unexpected connections that underlie complex environmental phenomena, albeit with a touch of academic flair and a sprinkle of good-natured humor.

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

Please make up the results section of an academic research paper presenting the findings of the connection between Air pollution in Chicago and Kerosene used in Brazil. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 Energy Information Administration .

For the time period 1980 to 2021, you found a correlation 0.8139423, r-squared of 0.6625020, 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]]
"Up in the Air: Unraveling the Correlation Between Chicago Air Pollution and Brazilian Kerosene Consumption"

[[ABSTRACT]]
The potential connection between air pollution in urban areas and the consumption of kerosene in far-off lands has long piqued the curiosity of researchers and policymakers alike. In this paper, we delve into this unconventional relationship, employing a meticulous analysis of data from the Environmental Protection Agency and the Energy Information Administration. Our findings reveal a striking correlation coefficient of 0.8139423 and a statistically significant p-value of less than 0.01 for the period spanning from 1980 to 2021.

As we examined the intricate interplay between air quality in Chicago and kerosene consumption in Brazil, we stumbled upon some surprising insights. It appears that the particles emitted into the atmosphere from Chicago's urban activities may be taking an unexpected South American detour. This phenomenon, whimsically dubbed the "Gust of Global Exchange," demonstrates that air pollution knows no geographic boundaries - much like a persistent knock-knock joke, it simply cannot be contained.

Our study underscores the importance of considering international and intercontinental factors in the quest to understand the dynamics of air pollution. The link between Chicago's smog and the reliance on kerosene in Brazil serves as a poignant reminder of the interconnectedness of environmental issues across the globe. Just as a well-timed dad joke can lighten the mood, our research sheds light on the unanticipated connections that underlie seemingly disparate phenomena.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The pervasive issue of air pollution has garnered immense attention from both the scientific community and society at large, akin to a particularly catchy earworm that refuses to fade from memory. Concurrently, the global consumption of kerosene, most commonly wielded as a source of illumination and energy, has been an area of interest for researchers delving into the intricate web of energy usage. Despite these seemingly unrelated domains, the possibility of a link between the air pollution levels in Chicago and the prominent utilization of kerosene in Brazil has ignited a fervent curiosity within the scientific community. As we embark on this investigative journey, it becomes imperative to ascertain whether the association between these two variables is grounded in empirical evidence or merely an illusory correlation, akin to a lab-coat clad magician pulling statistics out of a hat.
Intriguingly, our inquiry leads us to the peculiar juxtaposition of the Windy City's atmospheric quality and the far-off glow of Brazilian kerosene lamps - as if the gusts of air pollution from Chicago have taken on a life of their own, embarking on a transcontinental odyssey. This serendipitous rendezvous presents an opportunity to unravel the enigmatic connection between domestic emissions and their transoceanic endeavors, not unlike a globetrotting detective ferreting out clues in unexpected locales. Indeed, the "Gust of Global Exchange" phenomenon encapsulates the whimsical nature of our planet's interconnected environmental dynamics, as if the world were woven together by an invisible thread of ecological banter.
The task at hand entails a multidimensional exploration, carefully navigating the labyrinthine pathways of environmental data and statistical analyses. With the gravity of our findings lingering in the air like an unspoken punchline, we aim to shed light on the interconnectedness of seemingly disparate ecological factors, thereby elevating the discourse surrounding environmental sustainability. This research endeavor, much like an unexpected quip in a solemn lecture hall, endeavors to infuse levity into the often weighty subject of environmental inquiry while maintaining the steadfast rigor that characterizes scientific investigation.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The analysis of the data collected over the period from 1980 to 2021 revealed a noteworthy correlation coefficient of 0.8139423 between air pollution levels in Chicago and kerosene consumption in Brazil. This robust correlation suggests that as air pollution increased in the Windy City, so did the consumption of kerosene in the distant lands of Brazil. One might say that the relationship between these two variables is as clear as the air in a windy city after a heavy rain – undeniable.

The r-squared value of 0.6625020 indicates that approximately 66.25% of the variance in Brazilian kerosene consumption can be explained by the variation in air pollution levels in Chicago. It’s as if these variables have been in a long-distance relationship, with most of the ups and downs accounted for by the other.

Furthermore, the p-value of less than 0.01 provides compelling evidence to reject the null hypothesis and accept the alternative hypothesis that there is indeed a significant relationship between air pollution in Chicago and kerosene consumption in Brazil. It seems this correlation is as statistically significant as a well-timed punchline at a science conference.

The scatterplot (Fig. 1) illustrates the strong positive correlation between the two variables, resembling a constellation of data points forming a mathematical joke that only statisticians can fully appreciate. The plot paints a vivid picture of the "Gust of Global Exchange," depicting how the winds of air pollution in Chicago might be inexplicably blowing in the direction of Brazilian kerosene consumption, much like a cosmic joke played by the universe itself.

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Air pollution in Chicago and Kerosene used in Brazil. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
"Up in the Air: Unraveling the Correlation Between Chicago Air Pollution and Brazilian Kerosene Consumption"

[[ABSTRACT]]
The potential connection between air pollution in urban areas and the consumption of kerosene in far-off lands has long piqued the curiosity of researchers and policymakers alike. In this paper, we delve into this unconventional relationship, employing a meticulous analysis of data from the Environmental Protection Agency and the Energy Information Administration. Our findings reveal a striking correlation coefficient of 0.8139423 and a statistically significant p-value of less than 0.01 for the period spanning from 1980 to 2021.

As we examined the intricate interplay between air quality in Chicago and kerosene consumption in Brazil, we stumbled upon some surprising insights. It appears that the particles emitted into the atmosphere from Chicago's urban activities may be taking an unexpected South American detour. This phenomenon, whimsically dubbed the "Gust of Global Exchange," demonstrates that air pollution knows no geographic boundaries - much like a persistent knock-knock joke, it simply cannot be contained.

Our study underscores the importance of considering international and intercontinental factors in the quest to understand the dynamics of air pollution. The link between Chicago's smog and the reliance on kerosene in Brazil serves as a poignant reminder of the interconnectedness of environmental issues across the globe. Just as a well-timed dad joke can lighten the mood, our research sheds light on the unanticipated connections that underlie seemingly disparate phenomena.

[[LITERATURE REVIEW]]
In "Smith and Doe's groundbreaking study on urban air pollution," the authors find an intricate web of pollutants emanating from diverse sources such as vehicular emissions, industrial activities, and residential energy usage. These findings lay the foundation for understanding the complex composition of air pollution in urban centers, reminiscent of a colorful tapestry woven by an industrious yet slightly mischievous textile artist.
Similarly, "Jones' comprehensive analysis of kerosene consumption in developing countries" elucidates the pervasive reliance on kerosene for domestic lighting and cooking purposes. The study highlights the challenges posed by limited access to electricity in underserved regions, painting a poignant picture of communities illuminated by the warm glow of kerosene lamps, akin to fireflies dancing in the night – albeit with a distinctly less whimsical environmental impact.
Venturing beyond the realm of empirical research, "The Big Book of Air Pollution" by environmental expert Dr. Cleanair, and "Kerosene Chronicles: Illuminating Tales from Around the World" by energy historian Luminous Lenny, provide comprehensive narratives on the historical evolution and contemporary manifestations of air pollution and kerosene usage, respectively. Dr. Cleanair's work, much like a stern-faced scientist with a hidden penchant for puns, meticulously documents the progression of air quality research. Meanwhile, Luminous Lenny's literary endeavor sheds light on the global reverberations of kerosene consumption, illuminating the interconnectedness of seemingly distinct communities and their preferred choice of illumination – not unlike a global game of "spot the difference" played out with flickering kerosene lamps.
In a surprising twist, "Kerosene Chronicles" is packed with unexpected humor and witty anecdotes, incorporating stories of adventurous travelers and their encounters with kerosene-fueled contraptions. The author's playful approach to a seemingly mundane subject could be likened to a lighthearted jest amidst a solemn gathering of historians – much like a kerosene lamp at a power outage support group, providing a flickering sense of mirth in the midst of darkness.
Furthermore, during my perusal of social media channels, an anonymous post humorously remarked on the potential global travels of Chicago's air pollutants, suggesting that the Windy City's emissions might be on a quest for adventure, not unlike a group of intrepid backpackers - affirming the old adage that "even air pollution deserves a vacation" in its own peculiar way.

[[RESULTS]]
The analysis of the data collected over the period from 1980 to 2021 revealed a noteworthy correlation coefficient of 0.8139423 between air pollution levels in Chicago and kerosene consumption in Brazil. This robust correlation suggests that as air pollution increased in the Windy City, so did the consumption of kerosene in the distant lands of Brazil. One might say that the relationship between these two variables is as clear as the air in a windy city after a heavy rain – undeniable.
The r-squared value of 0.6625020 indicates that approximately 66.25% of the variance in Brazilian kerosene consumption can be explained by the variation in air pollution levels in Chicago. It’s as if these variables have been in a long-distance relationship, with most of the ups and downs accounted for by the other.
Furthermore, the p-value of less than 0.01 provides compelling evidence to reject the null hypothesis and accept the alternative hypothesis that there is indeed a significant relationship between air pollution in Chicago and kerosene consumption in Brazil. It seems this correlation is as statistically significant as a well-timed punchline at a science conference.
The scatterplot (Fig. 1) illustrates the strong positive correlation between the two variables, resembling a constellation of data points forming a mathematical joke that only statisticians can fully appreciate. The plot paints a vivid picture of the "Gust of Global Exchange," depicting how the winds of air pollution in Chicago might be inexplicably blowing in the direction of Brazilian kerosene consumption, much like a cosmic joke played by the universe itself.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of the study confirm and build upon previous research, supporting the intricate connection between air pollution in Chicago and kerosene consumption in Brazil. The significant correlation coefficient and p-value obtained in the analysis underscore the robustness of this relationship, painting a compelling portrait of transcontinental environmental interdependence. It appears that the whimsically dubbed "Gust of Global Exchange" is more than just a playful moniker - it encapsulates a tangible phenomenon with far-reaching implications.

The unexpected correlation between the two disparate variables might prompt one to ponder, much like a riddle posed by a mischievous scientist, the potential mechanisms underlying this connection. One cannot help but consider the possibility of atmospheric dynamics and global air currents playing a role in facilitating the transport of pollutants from one site to another, not unlike the way a spontaneous gust of wind can carry a well-crafted pun across a crowded room. Moreover, the findings serve as a poignant reminder of the need to consider international and intercontinental factors in environmental research, illuminating the complex web of interactions that transcend geographic boundaries.

The literature review hinted at the complex tapestry of urban air pollution and the widespread reliance on kerosene, providing the theoretical foundation for our findings. Smith and Doe's exploration of urban air pollution, akin to the work of a meticulous textile artist, laid the groundwork for understanding the intricate composition of pollutants. Similarly, Jones' comprehensive analysis of kerosene consumption shed light on the challenges faced by communities reliant on this fuel source, akin to the glow of kerosene lamps illuminating underserved regions - a sobering reminder of the broader implications of energy choices.

In a twist of fate, the playful anecdotes and whimsical humor infused in the literature review seem to find resonance in the unexpected yet compelling relationship uncovered in our study. The "Kerosene Chronicles" and the lighthearted social media post hint at the unanticipated connections that underlie seemingly disparate phenomena, reminiscent of a well-timed dad joke amidst a serious academic discourse.

In conclusion, our study serves as a testament to the unpredictability of scientific inquiry and the hidden connections that lurk beneath the surface of seemingly unrelated variables. The correlation between Chicago air pollution and Brazilian kerosene consumption, much like a clever punchline, adds a touch of unexpected intrigue to the intricate web of environmental interdependence.

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Air pollution in Chicago and Kerosene used in Brazil. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
"Up in the Air: Unraveling the Correlation Between Chicago Air Pollution and Brazilian Kerosene Consumption"

[[ABSTRACT]]
The potential connection between air pollution in urban areas and the consumption of kerosene in far-off lands has long piqued the curiosity of researchers and policymakers alike. In this paper, we delve into this unconventional relationship, employing a meticulous analysis of data from the Environmental Protection Agency and the Energy Information Administration. Our findings reveal a striking correlation coefficient of 0.8139423 and a statistically significant p-value of less than 0.01 for the period spanning from 1980 to 2021.

As we examined the intricate interplay between air quality in Chicago and kerosene consumption in Brazil, we stumbled upon some surprising insights. It appears that the particles emitted into the atmosphere from Chicago's urban activities may be taking an unexpected South American detour. This phenomenon, whimsically dubbed the "Gust of Global Exchange," demonstrates that air pollution knows no geographic boundaries - much like a persistent knock-knock joke, it simply cannot be contained.

Our study underscores the importance of considering international and intercontinental factors in the quest to understand the dynamics of air pollution. The link between Chicago's smog and the reliance on kerosene in Brazil serves as a poignant reminder of the interconnectedness of environmental issues across the globe. Just as a well-timed dad joke can lighten the mood, our research sheds light on the unanticipated connections that underlie seemingly disparate phenomena.

[[INTRDUCTION]]
The pervasive issue of air pollution has garnered immense attention from both the scientific community and society at large, akin to a particularly catchy earworm that refuses to fade from memory. Concurrently, the global consumption of kerosene, most commonly wielded as a source of illumination and energy, has been an area of interest for researchers delving into the intricate web of energy usage. Despite these seemingly unrelated domains, the possibility of a link between the air pollution levels in Chicago and the prominent utilization of kerosene in Brazil has ignited a fervent curiosity within the scientific community. As we embark on this investigative journey, it becomes imperative to ascertain whether the association between these two variables is grounded in empirical evidence or merely an illusory correlation, akin to a lab-coat clad magician pulling statistics out of a hat.
Intriguingly, our inquiry leads us to the peculiar juxtaposition of the Windy City's atmospheric quality and the far-off glow of Brazilian kerosene lamps - as if the gusts of air pollution from Chicago have taken on a life of their own, embarking on a transcontinental odyssey. This serendipitous rendezvous presents an opportunity to unravel the enigmatic connection between domestic emissions and their transoceanic endeavors, not unlike a globetrotting detective ferreting out clues in unexpected locales. Indeed, the "Gust of Global Exchange" phenomenon encapsulates the whimsical nature of our planet's interconnected environmental dynamics, as if the world were woven together by an invisible thread of ecological banter.
The task at hand entails a multidimensional exploration, carefully navigating the labyrinthine pathways of environmental data and statistical analyses. With the gravity of our findings lingering in the air like an unspoken punchline, we aim to shed light on the interconnectedness of seemingly disparate ecological factors, thereby elevating the discourse surrounding environmental sustainability. This research endeavor, much like an unexpected quip in a solemn lecture hall, endeavors to infuse levity into the often weighty subject of environmental inquiry while maintaining the steadfast rigor that characterizes scientific investigation.

[[RESULTS]]
The analysis of the data collected over the period from 1980 to 2021 revealed a noteworthy correlation coefficient of 0.8139423 between air pollution levels in Chicago and kerosene consumption in Brazil. This robust correlation suggests that as air pollution increased in the Windy City, so did the consumption of kerosene in the distant lands of Brazil. One might say that the relationship between these two variables is as clear as the air in a windy city after a heavy rain – undeniable.
The r-squared value of 0.6625020 indicates that approximately 66.25% of the variance in Brazilian kerosene consumption can be explained by the variation in air pollution levels in Chicago. It’s as if these variables have been in a long-distance relationship, with most of the ups and downs accounted for by the other.
Furthermore, the p-value of less than 0.01 provides compelling evidence to reject the null hypothesis and accept the alternative hypothesis that there is indeed a significant relationship between air pollution in Chicago and kerosene consumption in Brazil. It seems this correlation is as statistically significant as a well-timed punchline at a science conference.
The scatterplot (Fig. 1) illustrates the strong positive correlation between the two variables, resembling a constellation of data points forming a mathematical joke that only statisticians can fully appreciate. The plot paints a vivid picture of the "Gust of Global Exchange," depicting how the winds of air pollution in Chicago might be inexplicably blowing in the direction of Brazilian kerosene consumption, much like a cosmic joke played by the universe itself.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation into the unusual correlation between air pollution in Chicago and kerosene consumption in Brazil has uncovered a relationship as clear as the air in a windy city after a heavy rain – or perhaps not so clear, given the haze of air pollution. The robust correlation coefficient and statistically significant p-value provide compelling evidence of the "Gust of Global Exchange" phenomenon, echoing the timeless adage that what goes up must come down – in this case, pollutants traveling across continents.

The r-squared value suggests that the ups and downs of Brazilian kerosene consumption can be largely attributed to the ebb and flow of air pollution levels in the Windy City, much like how a pendulum swings predictably – unlike the oscillations of a lively debate in a room full of passionate scientists.

Our findings underscore the interconnectedness of environmental dynamics, illustrating that air pollution, much like a well-crafted joke, transcends geographical boundaries with an undeniable impact. This correlation is as statistically significant as a well-timed punchline at a science conference – leaving no room for doubt, much like a thorough peer review process.

Therefore, it seems that no more research is needed in this area - we've shed light on the far-reaching implications of seemingly localized environmental phenomena and uncovered a correlation more solid than the chemical bonds in a laboratory. It's time to leave this particular correlation to its own devices, like a well-behaved beaker in a chem lab.

That said, we hope our research adds a touch of levity to the weighty subject of environmental inquiry, much like an unexpected quip in a solemn lecture hall. After all, who says statistical analyses can't have a sense of humor?

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 Up in the Air: Unraveling the Correlation Between Chicago Air Pollution and Brazilian Kerosene Consumption. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Transcontinental Environmental Studies

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 Up in the Air: Unraveling the Correlation Between Chicago Air Pollution and Brazilian Kerosene Consumption. Respond only with the name of a fictional organization.

ChatGPT:

The Global Atmospheric Research Institute

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 Up in the Air: Unraveling the Correlation Between Chicago Air Pollution and Brazilian Kerosene Consumption with an abstract of The potential connection between air pollution in urban areas and the consumption of kerosene in far-off lands has long piqued the curiosity of researchers and policymakers alike. In this paper, we delve into this unconventional relationship, employing a meticulous analysis of data from the Environmental Protection Agency and the Energy Information Administration. Our findings reveal a striking correlation coefficient of 0.8139423 and a statistically significant p-value of less than 0.01 for the period spanning from 1980 to 2021.
As we examined the intricate interplay between air quality in Chicago and kerosene consumption in Brazil, we stumbled upon some surprising insights. It appears that the particles emitted into the atmosphere from Chicago's urban activities may be taking an unexpected South American detour. This phenomenon, whimsically dubbed the "Gust of Global Exchange," demonstrates that air pollution knows no geographic boundaries - much like a persistent knock-knock joke, it simply cannot be contained.
Our study underscores the importance of considering international and intercontinental factors in the quest to understand the dynamics of air pollution. The link between Chicago's smog and the reliance on kerosene in Brazil serves as a poignant reminder of the interconnectedness of environmental issues across the globe. Just as a well-timed dad joke can lighten the mood, our research sheds light on the unanticipated connections that underlie seemingly disparate phenomena.

ChatGPT:

air pollution, Chicago, Brazilian kerosene consumption, correlation, Environmental Protection Agency, Energy Information Administration, urban air quality, international factors, intercontinental pollution, air pollution dynamics

*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

Kerosene used in Brazil
Detailed data title: Volume of kerosene used consumed in Brazil in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Kerosene used in Brazil

Correlation r = 0.8139423 (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 = 0.6625020 (Coefficient of determination)
This means 66.3% of the change in the one variable (i.e., Kerosene used in Brazil) is predictable based on the change in the other (i.e., Air pollution in Chicago) over the 42 years from 1980 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 5.6E-11.^Show 0.0000000000559631578641418100
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 0.81 in 5.6E-9% of random cases. Said differently, if you correlated 17,868,898,721 random variables^Note You don't actually need 17 billion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 41 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 41 because we have two variables measured over a period of 42 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.68, 0.9 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

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

	1980	1981	1982	1983	1984	1985	1986	1987	1988	1989	1990	1991	1992	1993	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Air pollution in Chicago (Bad air quality days)	29.235	18.6301	21.3699	26.0274	20.4918	16.1644	26.3014	18.6301	29.5082	23.0137	24.3836	20.8219	9.28962	8.49315	12.6027	16.4384	11.7486	9.86301	17.2603	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
Kerosene used in Brazil (Million Barrels/Day)	6.49636	6.13985	6.00404	5.54567	5.84559	6.1059	7	7.6	6.4	6.6	5.62704	5.45323	3.2589	4.14967	2.71575	2.6723	2.49849	1.36874	1.17321	2.23778	3.37924	5.27334	3.68499	3.24025	1.8797	0.953014	0.698877	0.423562	0.380164	0.381205	0.402384	0.487096	0.401284	0.254137	0.190603	0.0995	0	0	0	0.10863	0.087	0.096

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([29.235,18.6301,21.3699,26.0274,20.4918,16.1644,26.3014,18.6301,29.5082,23.0137,24.3836,20.8219,9.28962,8.49315,12.6027,16.4384,11.7486,9.86301,17.2603,21.0959,16.9399,24.3836,18.0822,15.8904,11.2022,20.274,6.57534,15.8904,12.2951,6.0274,9.58904,6.57534,13.6612,4.65753,4.93151,3.83562,7.65027,6.84932,7.12329,3.56164,6.55738,7.67123,])
array_2 = np.array([6.49636,6.13985,6.00404,5.54567,5.84559,6.1059,7,7.6,6.4,6.6,5.62704,5.45323,3.2589,4.14967,2.71575,2.6723,2.49849,1.36874,1.17321,2.23778,3.37924,5.27334,3.68499,3.24025,1.8797,0.953014,0.698877,0.423562,0.380164,0.381205,0.402384,0.487096,0.401284,0.254137,0.190603,0.0995,0,0,0,0.10863,0.087,0.096,])
array_1_name = "Air pollution in Chicago"
array_2_name = "Kerosene used in Brazil"

# 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 Kerosene used in Brazil
The spurious research paper: Up in the Air: Unraveling the Correlation Between Chicago Air Pollution and Brazilian Kerosene Consumption

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Correlation ID: 1353 · Black Variable ID: 20456 · Red Variable ID: 24231


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