Spurious correlation #2,083 · 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 Albuquerque and the second variable is Gasoline pumped in Guam. 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 Albuquerque and the second variable is Gasoline pumped in Guam. 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 in Albuquerque cleared up, it actually developed a peculiar magnetic property that started to attract the gasoline molecules in Guam. This unprecedented phenomenon led to a subtle but steady decrease in the amount of gasoline being pumped, as the gasoline couldn't help but be drawn towards the cleaner air in Albuquerque. It's a classic case of environmental magnetism leading to an unintentional fuel fiasco!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image depicting a low poly style city skyline of Albuquerque with a hazy, polluted atmosphere. In the foreground, include a simplified representation of a gasoline pump in Guam, surrounded by cars lining up to refuel. The visual should convey the contrast between urban pollution and the necessity for fuel in a simple, yet impactful manner. 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: Poor air quality in Albuquerque and Gasoline pumped in Guam. 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: Sci-fi fantacy Art nouveau Psychedelic Low poly Celtic art
ChatGPT: Low poly

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 Poor air quality in Albuquerque and Gasoline pumped in Guam together. Keep the description simple.
ChatGPT: In Albuquerque, the city skyline is hazy with poor air quality, and in the foreground, a gasoline pump in Guam is visible with cars lining up to refuel.

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: [ Low poly ] and depicting this scene: In Albuquerque, the city skyline is hazy with poor air quality, and in the foreground, a gasoline pump in Guam is visible with cars lining up to refuel. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image depicting a low poly style city skyline of Albuquerque with a hazy, polluted atmosphere. In the foreground, include a simplified representation of a gasoline pump in Guam, surrounded by cars lining up to refuel. The visual should convey the contrast between urban pollution and the necessity for fuel in a simple, yet impactful manner.

*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 Albuquerque caused Gasoline pumped in Guam to decrease. Make it feel plausible.

AI academic paper

(Because p < 0.01)

The Gas and the Furious: Uncovering the Link Between Air Pollution in Albuquerque and Gasoline Pumped in Guam

The Journal of Environmental Comedic Research

Jan 2024

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

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Air pollution in Albuquerque and Gasoline pumped in Guam. 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 name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
The Gas and the Furious: Uncovering the Link Between Air Pollution in Albuquerque and Gasoline Pumped in Guam

[[ABSTRACT]]
In recent years, the pressing issue of air pollution has garnered increasing attention from researchers and policymakers alike. Simultaneously, the global gasoline trade has seen fluctuations that have left many scratching their heads. But what if these two seemingly separate phenomena were more closely connected than previously thought?

This study delves into the often-overlooked relationship between air pollution levels in Albuquerque and the quantity of gasoline pumped in Guam. By analyzing comprehensive data from the Environmental Protection Agency and the Energy Information Administration spanning over four decades, we sought to uncover any potential correlation between these seemingly unrelated variables.

Our findings revealed a surprising correlation coefficient of 0.8967719, with a remarkable level of statistical significance (p < 0.01) for the years 1980 to 2021. This robust correlation suggests that there may be a previously undetected linkage between air quality in Albuquerque and the volume of gasoline imported into Guam. It's almost as if these two entities are in a long-distance relationship – separated by miles of ocean and a dollop of statistical significance.

Furthermore, our study opens the door to probing the mechanisms underlying this association. Is there a causal relationship at play, or is this merely a coincidental correlation? As researchers, we must avoid jumping to hasty conclusions and instead delve deeper into the intricate dance of atmospheric dynamics and international fuel trade. It's almost as if the air in Albuquerque is sending a smoky signal across the Pacific, saying, "Guam, we need to talk."

This research not only sheds light on an unexpected link between air pollution and gasoline trade but also underscores the interconnectedness of global environmental and economic processes. Despite the geographical distance between these two locations, our findings suggest that they may be more intertwined than previously imagined. In the words of a wise dad, "Sometimes the world just decides to connect the dots in the most unexpected places."

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The correlation between air pollution and gasoline consumption may seem as unlikely as trying to find a needle in a haystack or attempting to squeeze blood from a turnip. Nevertheless, the Gas and the Furious: Uncovering the Link Between Air Pollution in Albuquerque and Gasoline Pumped in Guam presents a surprising investigation into the potential connection between these seemingly disparate variables. It's as if the universe decided to play a game of "6 degrees of pollution" between two geographically distant locations, much like how a dad can't resist a good pun even at the most inappropriate times.
For decades, air pollution has plagued metropolitan areas, casting a shadow of concern over public health and environmental well-being. Similarly, the global trade in gasoline has fluctuated and shifted, resembling a high-stakes game of musical chairs, leaving analysts to wonder if the music might stop at any moment. It's almost as if the air and gasoline decided to tango, leaving us to ponder the age-old question: "What's the fueling between them?"
Drawing inspiration from the unexpected connections in the world, our study aims to elucidate any potential relationship between the amount of air pollution in Albuquerque and the quantity of gasoline pumped in Guam. It's as if we are uncovering a hidden romance novel between these two elements, with each page turn revealing a new plot twist in this unlikely love story.
Through sophisticated data analysis and statistical modeling, our investigation unveils a remarkably strong correlation coefficient of 0.8967719 between these variables, akin to finding the perfect match between two puzzle pieces with the whole world as the puzzle. This unexpected alliance piques our scientific curiosity and leads us to ponder the intricate mechanisms and causality underlying this surprising correlation. It's almost as if the gasoline is whispering sweet nothings to the air, promising a future of reduced emissions and clean skies.
The significance of our findings extends far beyond the academic realm, highlighting the interconnectedness of seemingly separate aspects of the global environment and economy. Our research emphasizes the importance of recognizing that even the most unlikely of pairings may hold unforeseen connections. It's almost as if the universe is saying, "Hey, you thought air pollution and gasoline trade were unrelated? Think again!"

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Previous research has delved into the intricate web of air pollution and its deleterious effects on public health and the environment. Smith, in "Air Quality and Its Implications for Urban Communities," examines the impact of air pollution on respiratory diseases and its economic consequences, painting a grim picture of the pervasive nature of this environmental hazard. Similarly, Doe and Jones, in "The Global Gasoline Trade: A Historical Perspective," explore the complex dynamics of international gasoline distribution and its far-reaching implications for energy security and economic stability. It's almost as if the literature on air pollution and gasoline trade is a gripping thriller, with each study uncovering a new plot twist in the saga of environmental and economic interplay.

Turning to the broader research landscape, "The Economics of Clean Air" by Johnson provides a comprehensive analysis of the costs and benefits associated with air quality improvements, shedding light on the intricate balance between environmental regulations and economic growth. Likewise, "Fueling the Future: A Global Perspective" by Brown offers a panoramic view of the intricate web of energy trade and its implications for global geopolitics and environmental sustainability. It's almost as if these books are the non-fictional equivalent of a chemistry experiment gone wrong – a potent mixture of economic analysis and environmental discourse with explosive potential for insight.

On the fictional front, we find works such as "The Polluted Paradise" by Green and "The Gasoline Gambit" by White, using air pollution and gasoline trade as thematic backdrops for gripping narratives of environmental activism and high-stakes industrial intrigue. It's almost as if these authors are fueling their creative engines with the smog of urban landscapes and the fumes of gasoline-laden harbors, crafting captivating tales that blend reality and imagination.

In the virtual realm, popular internet memes such as the "Air Pollution Pikachu" and "Gasoline Grumpy Cat" have humorously highlighted the interconnectedness of environmental concerns and energy consumption in the digital age. It's almost as if these memes are the comic relief in the otherwise serious discourse surrounding air pollution and gasoline trade, reminding us that even in the face of pressing global issues, a good laugh can be a breath of fresh air.

As the literature demonstrates, the relationship between air pollution in Albuquerque and gasoline pumped in Guam is a topic worthy of investigation, steeped in the complexities of environmental impact and international trade dynamics. It's almost as if this research is on a quest to unlock the hidden secrets of atmospheric romance and transoceanic flings, revealing a love story written in the particles of smog and the molecules of fuel.

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 Albuquerque and Gasoline pumped in Guam. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and 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]]
The Gas and the Furious: Uncovering the Link Between Air Pollution in Albuquerque and Gasoline Pumped in Guam

[[ABSTRACT]]
In recent years, the pressing issue of air pollution has garnered increasing attention from researchers and policymakers alike. Simultaneously, the global gasoline trade has seen fluctuations that have left many scratching their heads. But what if these two seemingly separate phenomena were more closely connected than previously thought?

This study delves into the often-overlooked relationship between air pollution levels in Albuquerque and the quantity of gasoline pumped in Guam. By analyzing comprehensive data from the Environmental Protection Agency and the Energy Information Administration spanning over four decades, we sought to uncover any potential correlation between these seemingly unrelated variables.

Our findings revealed a surprising correlation coefficient of 0.8967719, with a remarkable level of statistical significance (p < 0.01) for the years 1980 to 2021. This robust correlation suggests that there may be a previously undetected linkage between air quality in Albuquerque and the volume of gasoline imported into Guam. It's almost as if these two entities are in a long-distance relationship – separated by miles of ocean and a dollop of statistical significance.

Furthermore, our study opens the door to probing the mechanisms underlying this association. Is there a causal relationship at play, or is this merely a coincidental correlation? As researchers, we must avoid jumping to hasty conclusions and instead delve deeper into the intricate dance of atmospheric dynamics and international fuel trade. It's almost as if the air in Albuquerque is sending a smoky signal across the Pacific, saying, "Guam, we need to talk."

This research not only sheds light on an unexpected link between air pollution and gasoline trade but also underscores the interconnectedness of global environmental and economic processes. Despite the geographical distance between these two locations, our findings suggest that they may be more intertwined than previously imagined. In the words of a wise dad, "Sometimes the world just decides to connect the dots in the most unexpected places."

[[INTRODUCTION]]
The correlation between air pollution and gasoline consumption may seem as unlikely as trying to find a needle in a haystack or attempting to squeeze blood from a turnip. Nevertheless, the Gas and the Furious: Uncovering the Link Between Air Pollution in Albuquerque and Gasoline Pumped in Guam presents a surprising investigation into the potential connection between these seemingly disparate variables. It's as if the universe decided to play a game of "6 degrees of pollution" between two geographically distant locations, much like how a dad can't resist a good pun even at the most inappropriate times.
For decades, air pollution has plagued metropolitan areas, casting a shadow of concern over public health and environmental well-being. Similarly, the global trade in gasoline has fluctuated and shifted, resembling a high-stakes game of musical chairs, leaving analysts to wonder if the music might stop at any moment. It's almost as if the air and gasoline decided to tango, leaving us to ponder the age-old question: "What's the fueling between them?"
Drawing inspiration from the unexpected connections in the world, our study aims to elucidate any potential relationship between the amount of air pollution in Albuquerque and the quantity of gasoline pumped in Guam. It's as if we are uncovering a hidden romance novel between these two elements, with each page turn revealing a new plot twist in this unlikely love story.
Through sophisticated data analysis and statistical modeling, our investigation unveils a remarkably strong correlation coefficient of 0.8967719 between these variables, akin to finding the perfect match between two puzzle pieces with the whole world as the puzzle. This unexpected alliance piques our scientific curiosity and leads us to ponder the intricate mechanisms and causality underlying this surprising correlation. It's almost as if the gasoline is whispering sweet nothings to the air, promising a future of reduced emissions and clean skies.
The significance of our findings extends far beyond the academic realm, highlighting the interconnectedness of seemingly separate aspects of the global environment and economy. Our research emphasizes the importance of recognizing that even the most unlikely of pairings may hold unforeseen connections. It's almost as if the universe is saying, "Hey, you thought air pollution and gasoline trade were unrelated? Think again!"

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To investigate the potential interconnection between air pollution in Albuquerque and gasoline consumption in Guam, our research team employed a comprehensive methodological approach that was as meticulous as a cat grooming itself – with a few more Excel spreadsheets involved.

First, we gathered data from the Environmental Protection Agency and the Energy Information Administration, covering the period from 1980 to 2021. This extensive timeframe allowed us to capture the long-term trends and variations in both air pollution levels and gasoline consumption, akin to patiently waiting for a pot to boil – but in this case, the pot contained a bubbling cauldron of statistical correlations rather than soup.

The data collection process involved combing through a multitude of databases, websites, and digital repositories, essentially becoming digital treasure hunters on a quest for the elusive nuggets of information. It's almost as if we were panning for data gold in the cyber-rivers of the information superhighway.

Upon gathering the requisite datasets, we conducted rigorous cleaning and validation procedures to ensure the integrity and reliability of the information, just like tidying up a cluttered garage to make space for a statistical Ferrari. This entailed identifying and rectifying any missing, erroneous, or inconsistent data points with the precision of a diamond cutter – our data had to sparkle like a dad's collection of witty one-liners.

Once the data underwent thorough vetting and scrubbing, we embarked on a sophisticated analysis utilizing advanced statistical techniques, including correlation analysis, regression modeling, and time series analysis. This phase of the study was akin to navigating a labyrinth of mathematical equations and computer code, with each algorithm and model serving as a guide through the statistical wilderness. It's almost as if we were part of an elite statistical SWAT team, raiding the fortress of uncertainty to extract the truth hidden within the numbers.

The correlation analysis allowed us to assess the strength and direction of the relationship between air pollution levels in Albuquerque and the volume of gasoline pumped in Guam, resembling a matchmaking service for environmental and economic variables. Meanwhile, the regression modeling enabled us to delve into the potential causal mechanisms underlying this connection, acting as detectives in a mystery novel trying to uncover the culprit behind the unexpected correlation. It's almost as if we were unraveling a statistical whodunit – "The Case of the Cozy Carbon Dioxide and the Mysterious Octane."

Moreover, the time series analysis provided valuable insights into the temporal patterns and dynamics of both air pollution and gasoline consumption, akin to observing the ebb and flow of a never-ending statistical tide. This approach allowed us to discern any long-term trends, seasonal fluctuations, and abrupt shifts, akin to monitoring the heart rate of a statistical patient experiencing the highs and lows of environmental and economic events.

In summary, our methodology employed a judicious combination of data collection, cleaning, and analysis methods, akin to assembling a complex yet captivating jigsaw puzzle of environmental and economic data. Our approach was as methodical as a symphony conductor leading a statistical orchestra, with each note and movement contributing to the harmonious unveiling of the unexpected link between air pollution in Albuquerque and gasoline pumped in Guam.

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

Please make up the results section of an academic research paper presenting the findings of the connection between Air pollution in Albuquerque and Gasoline pumped in Guam. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Energy Information Administration .

For the time period 1980 to 2021, you found a correlation 0.8967719, r-squared of 0.8041999, 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]]
The Gas and the Furious: Uncovering the Link Between Air Pollution in Albuquerque and Gasoline Pumped in Guam

[[ABSTRACT]]
In recent years, the pressing issue of air pollution has garnered increasing attention from researchers and policymakers alike. Simultaneously, the global gasoline trade has seen fluctuations that have left many scratching their heads. But what if these two seemingly separate phenomena were more closely connected than previously thought?

This study delves into the often-overlooked relationship between air pollution levels in Albuquerque and the quantity of gasoline pumped in Guam. By analyzing comprehensive data from the Environmental Protection Agency and the Energy Information Administration spanning over four decades, we sought to uncover any potential correlation between these seemingly unrelated variables.

Our findings revealed a surprising correlation coefficient of 0.8967719, with a remarkable level of statistical significance (p < 0.01) for the years 1980 to 2021. This robust correlation suggests that there may be a previously undetected linkage between air quality in Albuquerque and the volume of gasoline imported into Guam. It's almost as if these two entities are in a long-distance relationship – separated by miles of ocean and a dollop of statistical significance.

Furthermore, our study opens the door to probing the mechanisms underlying this association. Is there a causal relationship at play, or is this merely a coincidental correlation? As researchers, we must avoid jumping to hasty conclusions and instead delve deeper into the intricate dance of atmospheric dynamics and international fuel trade. It's almost as if the air in Albuquerque is sending a smoky signal across the Pacific, saying, "Guam, we need to talk."

This research not only sheds light on an unexpected link between air pollution and gasoline trade but also underscores the interconnectedness of global environmental and economic processes. Despite the geographical distance between these two locations, our findings suggest that they may be more intertwined than previously imagined. In the words of a wise dad, "Sometimes the world just decides to connect the dots in the most unexpected places."

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The correlation between air pollution and gasoline consumption may seem as unlikely as trying to find a needle in a haystack or attempting to squeeze blood from a turnip. Nevertheless, the Gas and the Furious: Uncovering the Link Between Air Pollution in Albuquerque and Gasoline Pumped in Guam presents a surprising investigation into the potential connection between these seemingly disparate variables. It's as if the universe decided to play a game of "6 degrees of pollution" between two geographically distant locations, much like how a dad can't resist a good pun even at the most inappropriate times.
For decades, air pollution has plagued metropolitan areas, casting a shadow of concern over public health and environmental well-being. Similarly, the global trade in gasoline has fluctuated and shifted, resembling a high-stakes game of musical chairs, leaving analysts to wonder if the music might stop at any moment. It's almost as if the air and gasoline decided to tango, leaving us to ponder the age-old question: "What's the fueling between them?"
Drawing inspiration from the unexpected connections in the world, our study aims to elucidate any potential relationship between the amount of air pollution in Albuquerque and the quantity of gasoline pumped in Guam. It's as if we are uncovering a hidden romance novel between these two elements, with each page turn revealing a new plot twist in this unlikely love story.
Through sophisticated data analysis and statistical modeling, our investigation unveils a remarkably strong correlation coefficient of 0.8967719 between these variables, akin to finding the perfect match between two puzzle pieces with the whole world as the puzzle. This unexpected alliance piques our scientific curiosity and leads us to ponder the intricate mechanisms and causality underlying this surprising correlation. It's almost as if the gasoline is whispering sweet nothings to the air, promising a future of reduced emissions and clean skies.
The significance of our findings extends far beyond the academic realm, highlighting the interconnectedness of seemingly separate aspects of the global environment and economy. Our research emphasizes the importance of recognizing that even the most unlikely of pairings may hold unforeseen connections. It's almost as if the universe is saying, "Hey, you thought air pollution and gasoline trade were unrelated? Think again!"

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The results of our investigation unveiled a correlation coefficient of 0.8967719 between air pollution levels in Albuquerque and the quantity of gasoline pumped in Guam for the years 1980 to 2021. This robust correlation, with an r-squared of 0.8041999 and p < 0.01, hints at a surprising interplay between these seemingly distant phenomena. It's like discovering that two strangers you met at different parties are actually long-lost siblings - a real plot twist in the movie of scientific research.

Our analysis indicated a strong linear relationship between the two variables, with each increase in air pollution in Albuquerque corresponding to a proportional rise in gasoline pumped in Guam. It’s as if these two variables were engaged in an intricate dance, choreographed by unseen forces that transcend the vast expanse of the Pacific Ocean. Perhaps the air pollution in Albuquerque is secretly moonlighting as a cupid, orchestrating a romance with gasoline consumption in Guam.

The scatterplot (Fig. 1) captures this striking correlation, laying bare the unexpected connection between air pollution in one corner of the world and gasoline consumption in a seemingly unrelated territory. It's almost like catching a glimpse of a secret rendezvous between two old friends who everyone thought had lost touch - a statistical "ah-ha" moment akin to solving a particularly tricky crossword puzzle clue.

These findings challenge conventional wisdom and call for a reevaluation of the intricate relationship between air quality in urban environments and the global trade of petroleum products. It's as if the universe is nudging us and saying, "Hey, pay attention to the unexpected romance brewing here."

This revelation not only emphasizes the potential interdependence between environmental and economic factors but also underscores the need for further investigation into the nuanced dynamics that underpin this peculiar correlation. Who would have thought that the air pollution in Albuquerque had a trans-Pacific pen pal in the form of gasoline consumption in Guam? It's like stumbling upon a surprising twist in the plot of a mystery novel, one that leaves you reeling with both astonishment and curiosity.

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 Albuquerque and Gasoline pumped in Guam. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

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

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

[[TITLE]]
The Gas and the Furious: Uncovering the Link Between Air Pollution in Albuquerque and Gasoline Pumped in Guam

[[ABSTRACT]]
In recent years, the pressing issue of air pollution has garnered increasing attention from researchers and policymakers alike. Simultaneously, the global gasoline trade has seen fluctuations that have left many scratching their heads. But what if these two seemingly separate phenomena were more closely connected than previously thought?

This study delves into the often-overlooked relationship between air pollution levels in Albuquerque and the quantity of gasoline pumped in Guam. By analyzing comprehensive data from the Environmental Protection Agency and the Energy Information Administration spanning over four decades, we sought to uncover any potential correlation between these seemingly unrelated variables.

Our findings revealed a surprising correlation coefficient of 0.8967719, with a remarkable level of statistical significance (p < 0.01) for the years 1980 to 2021. This robust correlation suggests that there may be a previously undetected linkage between air quality in Albuquerque and the volume of gasoline imported into Guam. It's almost as if these two entities are in a long-distance relationship – separated by miles of ocean and a dollop of statistical significance.

Furthermore, our study opens the door to probing the mechanisms underlying this association. Is there a causal relationship at play, or is this merely a coincidental correlation? As researchers, we must avoid jumping to hasty conclusions and instead delve deeper into the intricate dance of atmospheric dynamics and international fuel trade. It's almost as if the air in Albuquerque is sending a smoky signal across the Pacific, saying, "Guam, we need to talk."

This research not only sheds light on an unexpected link between air pollution and gasoline trade but also underscores the interconnectedness of global environmental and economic processes. Despite the geographical distance between these two locations, our findings suggest that they may be more intertwined than previously imagined. In the words of a wise dad, "Sometimes the world just decides to connect the dots in the most unexpected places."

[[LITERATURE REVIEW]]
Previous research has delved into the intricate web of air pollution and its deleterious effects on public health and the environment. Smith, in "Air Quality and Its Implications for Urban Communities," examines the impact of air pollution on respiratory diseases and its economic consequences, painting a grim picture of the pervasive nature of this environmental hazard. Similarly, Doe and Jones, in "The Global Gasoline Trade: A Historical Perspective," explore the complex dynamics of international gasoline distribution and its far-reaching implications for energy security and economic stability. It's almost as if the literature on air pollution and gasoline trade is a gripping thriller, with each study uncovering a new plot twist in the saga of environmental and economic interplay.
Turning to the broader research landscape, "The Economics of Clean Air" by Johnson provides a comprehensive analysis of the costs and benefits associated with air quality improvements, shedding light on the intricate balance between environmental regulations and economic growth. Likewise, "Fueling the Future: A Global Perspective" by Brown offers a panoramic view of the intricate web of energy trade and its implications for global geopolitics and environmental sustainability. It's almost as if these books are the non-fictional equivalent of a chemistry experiment gone wrong – a potent mixture of economic analysis and environmental discourse with explosive potential for insight.
On the fictional front, we find works such as "The Polluted Paradise" by Green and "The Gasoline Gambit" by White, using air pollution and gasoline trade as thematic backdrops for gripping narratives of environmental activism and high-stakes industrial intrigue. It's almost as if these authors are fueling their creative engines with the smog of urban landscapes and the fumes of gasoline-laden harbors, crafting captivating tales that blend reality and imagination.
In the virtual realm, popular internet memes such as the "Air Pollution Pikachu" and "Gasoline Grumpy Cat" have humorously highlighted the interconnectedness of environmental concerns and energy consumption in the digital age. It's almost as if these memes are the comic relief in the otherwise serious discourse surrounding air pollution and gasoline trade, reminding us that even in the face of pressing global issues, a good laugh can be a breath of fresh air.
As the literature demonstrates, the relationship between air pollution in Albuquerque and gasoline pumped in Guam is a topic worthy of investigation, steeped in the complexities of environmental impact and international trade dynamics. It's almost as if this research is on a quest to unlock the hidden secrets of atmospheric romance and transoceanic flings, revealing a love story written in the particles of smog and the molecules of fuel.

[[RESULTS]]
The results of our investigation unveiled a correlation coefficient of 0.8967719 between air pollution levels in Albuquerque and the quantity of gasoline pumped in Guam for the years 1980 to 2021. This robust correlation, with an r-squared of 0.8041999 and p < 0.01, hints at a surprising interplay between these seemingly distant phenomena. It's like discovering that two strangers you met at different parties are actually long-lost siblings - a real plot twist in the movie of scientific research.
Our analysis indicated a strong linear relationship between the two variables, with each increase in air pollution in Albuquerque corresponding to a proportional rise in gasoline pumped in Guam. It’s as if these two variables were engaged in an intricate dance, choreographed by unseen forces that transcend the vast expanse of the Pacific Ocean. Perhaps the air pollution in Albuquerque is secretly moonlighting as a cupid, orchestrating a romance with gasoline consumption in Guam.
The scatterplot (Fig. 1) captures this striking correlation, laying bare the unexpected connection between air pollution in one corner of the world and gasoline consumption in a seemingly unrelated territory. It's almost like catching a glimpse of a secret rendezvous between two old friends who everyone thought had lost touch - a statistical "ah-ha" moment akin to solving a particularly tricky crossword puzzle clue.
These findings challenge conventional wisdom and call for a reevaluation of the intricate relationship between air quality in urban environments and the global trade of petroleum products. It's as if the universe is nudging us and saying, "Hey, pay attention to the unexpected romance brewing here."
This revelation not only emphasizes the potential interdependence between environmental and economic factors but also underscores the need for further investigation into the nuanced dynamics that underpin this peculiar correlation. Who would have thought that the air pollution in Albuquerque had a trans-Pacific pen pal in the form of gasoline consumption in Guam? It's like stumbling upon a surprising twist in the plot of a mystery novel, one that leaves you reeling with both astonishment and curiosity.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our findings have illuminated a compelling relationship between air pollution levels in Albuquerque and the quantity of gasoline pumped in Guam, one that challenges conventional wisdom and calls for in-depth exploration. The robust correlation coefficient of 0.8967719 indicates a strong linear association between these seemingly disparate variables, supporting the prior research that has probed the interconnectedness of environmental quality and economic activities. It's as if the air pollution and gasoline trade are waltzing in a synchronized routine, showcasing an unexpected chemistry that defies geographical boundaries.

Building on prior studies that have delved into the multifaceted impacts of air pollution on public health and the environment, our results underscore the far-reaching implications of these atmospheric dynamics. It's almost as if the air quality in Albuquerque is sending a clear signal across the oceans, saying, "I have a crush on your gasoline consumption, Guam." Our findings echo the somber narrative painted by Smith, emphasizing the pervasive nature of air pollution and its potential to transcend local boundaries to impact global processes. As the old saying goes, "Where there's smog, there's fire - or at least, a strong linear relationship with gasoline consumption."

Furthermore, our discovery of a substantial correlation between air pollution in Albuquerque and gasoline pumped in Guam lends support to the prior literature on the intricate web of global energy trade. The unexpected connection between these two variables leads us to consider whether air quality in one part of the world can inadvertently influence the energy consumption patterns in a seemingly far-off land. It's like a long-distance relationship – except in this case, it's the pollutants and the petroleum products that are exchanging meaningful glances across vast expanse of the Pacific.

While the precise mechanisms behind this correlation remain elusive, our results fuel the call for additional research to unravel the intricate dance of atmospheric romance and transoceanic flings. It's almost as if these findings have set the stage for a new act in the drama of environmental research, one in which air pollution and gasoline trade take center stage in an unexpected love story written in statistical significance and data points. Who would have thought that the smog of Albuquerque had a trans-Pacific pen pal in the form of Guam's gasoline consumption? It's like discovering a secret admirer in an unexpected place, leaving us both mystified and intrigued.

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 Albuquerque and Gasoline pumped in Guam. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
The Gas and the Furious: Uncovering the Link Between Air Pollution in Albuquerque and Gasoline Pumped in Guam

[[ABSTRACT]]
In recent years, the pressing issue of air pollution has garnered increasing attention from researchers and policymakers alike. Simultaneously, the global gasoline trade has seen fluctuations that have left many scratching their heads. But what if these two seemingly separate phenomena were more closely connected than previously thought?

This study delves into the often-overlooked relationship between air pollution levels in Albuquerque and the quantity of gasoline pumped in Guam. By analyzing comprehensive data from the Environmental Protection Agency and the Energy Information Administration spanning over four decades, we sought to uncover any potential correlation between these seemingly unrelated variables.

Our findings revealed a surprising correlation coefficient of 0.8967719, with a remarkable level of statistical significance (p < 0.01) for the years 1980 to 2021. This robust correlation suggests that there may be a previously undetected linkage between air quality in Albuquerque and the volume of gasoline imported into Guam. It's almost as if these two entities are in a long-distance relationship – separated by miles of ocean and a dollop of statistical significance.

Furthermore, our study opens the door to probing the mechanisms underlying this association. Is there a causal relationship at play, or is this merely a coincidental correlation? As researchers, we must avoid jumping to hasty conclusions and instead delve deeper into the intricate dance of atmospheric dynamics and international fuel trade. It's almost as if the air in Albuquerque is sending a smoky signal across the Pacific, saying, "Guam, we need to talk."

This research not only sheds light on an unexpected link between air pollution and gasoline trade but also underscores the interconnectedness of global environmental and economic processes. Despite the geographical distance between these two locations, our findings suggest that they may be more intertwined than previously imagined. In the words of a wise dad, "Sometimes the world just decides to connect the dots in the most unexpected places."

[[INTRDUCTION]]
The correlation between air pollution and gasoline consumption may seem as unlikely as trying to find a needle in a haystack or attempting to squeeze blood from a turnip. Nevertheless, the Gas and the Furious: Uncovering the Link Between Air Pollution in Albuquerque and Gasoline Pumped in Guam presents a surprising investigation into the potential connection between these seemingly disparate variables. It's as if the universe decided to play a game of "6 degrees of pollution" between two geographically distant locations, much like how a dad can't resist a good pun even at the most inappropriate times.
For decades, air pollution has plagued metropolitan areas, casting a shadow of concern over public health and environmental well-being. Similarly, the global trade in gasoline has fluctuated and shifted, resembling a high-stakes game of musical chairs, leaving analysts to wonder if the music might stop at any moment. It's almost as if the air and gasoline decided to tango, leaving us to ponder the age-old question: "What's the fueling between them?"
Drawing inspiration from the unexpected connections in the world, our study aims to elucidate any potential relationship between the amount of air pollution in Albuquerque and the quantity of gasoline pumped in Guam. It's as if we are uncovering a hidden romance novel between these two elements, with each page turn revealing a new plot twist in this unlikely love story.
Through sophisticated data analysis and statistical modeling, our investigation unveils a remarkably strong correlation coefficient of 0.8967719 between these variables, akin to finding the perfect match between two puzzle pieces with the whole world as the puzzle. This unexpected alliance piques our scientific curiosity and leads us to ponder the intricate mechanisms and causality underlying this surprising correlation. It's almost as if the gasoline is whispering sweet nothings to the air, promising a future of reduced emissions and clean skies.
The significance of our findings extends far beyond the academic realm, highlighting the interconnectedness of seemingly separate aspects of the global environment and economy. Our research emphasizes the importance of recognizing that even the most unlikely of pairings may hold unforeseen connections. It's almost as if the universe is saying, "Hey, you thought air pollution and gasoline trade were unrelated? Think again!"

[[RESULTS]]
The results of our investigation unveiled a correlation coefficient of 0.8967719 between air pollution levels in Albuquerque and the quantity of gasoline pumped in Guam for the years 1980 to 2021. This robust correlation, with an r-squared of 0.8041999 and p < 0.01, hints at a surprising interplay between these seemingly distant phenomena. It's like discovering that two strangers you met at different parties are actually long-lost siblings - a real plot twist in the movie of scientific research.
Our analysis indicated a strong linear relationship between the two variables, with each increase in air pollution in Albuquerque corresponding to a proportional rise in gasoline pumped in Guam. It’s as if these two variables were engaged in an intricate dance, choreographed by unseen forces that transcend the vast expanse of the Pacific Ocean. Perhaps the air pollution in Albuquerque is secretly moonlighting as a cupid, orchestrating a romance with gasoline consumption in Guam.
The scatterplot (Fig. 1) captures this striking correlation, laying bare the unexpected connection between air pollution in one corner of the world and gasoline consumption in a seemingly unrelated territory. It's almost like catching a glimpse of a secret rendezvous between two old friends who everyone thought had lost touch - a statistical "ah-ha" moment akin to solving a particularly tricky crossword puzzle clue.
These findings challenge conventional wisdom and call for a reevaluation of the intricate relationship between air quality in urban environments and the global trade of petroleum products. It's as if the universe is nudging us and saying, "Hey, pay attention to the unexpected romance brewing here."
This revelation not only emphasizes the potential interdependence between environmental and economic factors but also underscores the need for further investigation into the nuanced dynamics that underpin this peculiar correlation. Who would have thought that the air pollution in Albuquerque had a trans-Pacific pen pal in the form of gasoline consumption in Guam? It's like stumbling upon a surprising twist in the plot of a mystery novel, one that leaves you reeling with both astonishment and curiosity.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study reveals a compelling correlation between air pollution levels in Albuquerque and gasoline consumption in Guam, showcasing a partnership that rivals the most unexpected of duos. It's like finding out that your eccentric neighbor and a famous celebrity share a secret hobby – shocking yet strangely endearing. This unexpected relationship challenges traditional theories and prompts a reevaluation of the intricate dance between urban air quality and global fuel consumption.

The statistical significance of this correlation, with an r-squared of 0.8041999 and p < 0.01, suggests a substantial link between these seemingly unrelated variables. It's like discovering that two seemingly disconnected plotlines in a movie are, in fact, part of the same grand narrative – a real "plot twist" in the saga of scientific inquiry.

Moving forward, investigating the mechanisms and potential causality behind this intriguing association will be crucial. Is there a direct cause-and-effect relationship at play, or are there hidden variables orchestrating this surprising tango between pollution and petroleum? It's almost as if the atmosphere in Albuquerque has developed a penchant for long-distance relationships, eagerly sending smoky signals across the Pacific to its gasoline companion in Guam.

This research not only highlights the interconnectedness of environmental and economic processes but also underscores the need for further scrutiny into the underlying dynamics of this unanticipated connection. It's like stumbling upon a well-kept secret – one that leaves you both astounded and eager to unravel its mysteries. As a wise dad might say, "Who knew that air pollution and gasoline trade had such an intriguing bond? It’s like they were made for each other – a dynamic duo for the ages!"

Given the substantial findings of our study, it is our firm belief that no further research in this area is necessary. It's as if the universe has given us a definitive answer, albeit an unexpected one.

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 Gas and the Furious: Uncovering the Link Between Air Pollution in Albuquerque and Gasoline Pumped in Guam. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Environmental Comedic Research

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 Gas and the Furious: Uncovering the Link Between Air Pollution in Albuquerque and Gasoline Pumped in Guam. Respond only with the name of a fictional organization.

ChatGPT:

Institute for Transcontinental Air Quality Studies

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 Gas and the Furious: Uncovering the Link Between Air Pollution in Albuquerque and Gasoline Pumped in Guam with an abstract of In recent years, the pressing issue of air pollution has garnered increasing attention from researchers and policymakers alike. Simultaneously, the global gasoline trade has seen fluctuations that have left many scratching their heads. But what if these two seemingly separate phenomena were more closely connected than previously thought?
This study delves into the often-overlooked relationship between air pollution levels in Albuquerque and the quantity of gasoline pumped in Guam. By analyzing comprehensive data from the Environmental Protection Agency and the Energy Information Administration spanning over four decades, we sought to uncover any potential correlation between these seemingly unrelated variables.
Our findings revealed a surprising correlation coefficient of 0.8967719, with a remarkable level of statistical significance (p < 0.01) for the years 1980 to 2021. This robust correlation suggests that there may be a previously undetected linkage between air quality in Albuquerque and the volume of gasoline imported into Guam. It's almost as if these two entities are in a long-distance relationship – separated by miles of ocean and a dollop of statistical significance.
Furthermore, our study opens the door to probing the mechanisms underlying this association. Is there a causal relationship at play, or is this merely a coincidental correlation? As researchers, we must avoid jumping to hasty conclusions and instead delve deeper into the intricate dance of atmospheric dynamics and international fuel trade. It's almost as if the air in Albuquerque is sending a smoky signal across the Pacific, saying, "Guam, we need to talk."
This research not only sheds light on an unexpected link between air pollution and gasoline trade but also underscores the interconnectedness of global environmental and economic processes. Despite the geographical distance between these two locations, our findings suggest that they may be more intertwined than previously imagined. In the words of a wise dad, "Sometimes the world just decides to connect the dots in the most unexpected places.

ChatGPT:

Air pollution, gasoline trade, correlation analysis, environmental data, air quality, gasoline import, atmospheric dynamics, statistical significance, environmental protection agency, energy information administration, global economic processes

*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 Albuquerque
Detailed data title: Percentage of days 'unhealthy' or worse air quality in Albuquerque, NM
Source: Environmental Protection Agency
See what else correlates with Air pollution in Albuquerque

Gasoline pumped in Guam
Detailed data title: Volume of gasoline pumped consumed in Guam in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Gasoline pumped in Guam

Correlation r = 0.8967719 (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 = 0.8041999 (Coefficient of determination)
This means 80.4% of the change in the one variable (i.e., Gasoline pumped in Guam) is predictable based on the change in the other (i.e., Air pollution in Albuquerque) over the 42 years from 1980 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 9.5E-16.^Show 0.0000000000000009534332493142
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 0.9 in 9.5E-14% of random cases. Said differently, if you correlated 1,048,841,123,087,846 random variables^Note You don't actually need 1 quadrillion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 41 degrees of freedom, ^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.

[ 0.81, 0.94 ] 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 Albuquerque (Bad air quality days)	5.7377	13.4247	6.0274	5.47945	2.45902	0.821918	1.09589	2.46575	0.546448	0.547945	0.547945	0	0	0	0.273973	0.273973	0	0	0	0.547945	0	0	0.547945	1.36986	0.273224	0.547945	0.821918	0.273973	0	0	0	0.821918	0.546448	0	0	0	0	0	0.273973	0	0.546448	0.547945
Gasoline pumped in Guam (Million Barrels/Day)	13.9462	19.5246	15.0619	14.504	5.02062	2.5661	4.3	1.6	2	3.6	2.3	2.2	4	4.2	5.6	3.9	3.4	5.1	3.3	3.7	3.79829	3.7072	3.5073	3.1589	2.00122	3.617	3.1126	2.8241	1.23222	1.581	1.5054	0.587	0.948933	0.808434	0.8	0.8	0.871993	1	1	1	0.95	1.001

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([5.7377,13.4247,6.0274,5.47945,2.45902,0.821918,1.09589,2.46575,0.546448,0.547945,0.547945,0,0,0,0.273973,0.273973,0,0,0,0.547945,0,0,0.547945,1.36986,0.273224,0.547945,0.821918,0.273973,0,0,0,0.821918,0.546448,0,0,0,0,0,0.273973,0,0.546448,0.547945,])
array_2 = np.array([13.9462,19.5246,15.0619,14.504,5.02062,2.5661,4.3,1.6,2,3.6,2.3,2.2,4,4.2,5.6,3.9,3.4,5.1,3.3,3.7,3.79829,3.7072,3.5073,3.1589,2.00122,3.617,3.1126,2.8241,1.23222,1.581,1.5054,0.587,0.948933,0.808434,0.8,0.8,0.871993,1,1,1,0.95,1.001,])
array_1_name = "Air pollution in Albuquerque"
array_2_name = "Gasoline pumped in Guam"

# 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 Albuquerque
Line chart for only Gasoline pumped in Guam
AI-generated correlation image
The spurious research paper: The Gas and the Furious: Uncovering the Link Between Air Pollution in Albuquerque and Gasoline Pumped in Guam

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Correlation ID: 2083 · Black Variable ID: 20244 · Red Variable ID: 24485


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