Spurious correlation #4,098 · 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 Columbus and the second variable is Petroluem consumption in Italy. The chart goes from 1980 to 2022, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air pollution in Columbus and the second variable is Petroluem consumption in Italy. The chart goes from 1980 to 2022, and the two variables track closely in value over that time.

AI explanation

It turns out, as air quality in Columbus improved, a secret network of Italian tree whisperers felt a strange sense of calm and satisfaction, prompting them to subtly influence Italians to drive less and embrace a more energy-efficient lifestyle. It seems like cleaner air in one part of the world really does lead to greener choices in another!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a cityscape that juxtaposes the urban scenes of Columbus and Italy. In the Columbus portion, portray a modern, brutalist building standing tall against the clear blue sky, with green spaces and people leisurely walking and riding bicycles. Contrast this with an Italian street scene where quaint buildings line the road, adorned with vibrant greenery and adorned with bicycles. Show gas stations with fewer cars, and Italian tree whisperers smiling as they gently guide their fellow citizens towards eco-friendly lifestyle choices. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Air pollution in Columbus and Petroluem consumption in Italy. 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: Cubism Cute 2D animation a funny image you would see on reddit Brutalism Whimsical illustration
ChatGPT: Brutalism

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Air pollution in Columbus and Petroluem consumption in Italy, in the following situation: It turns out, as air quality in Columbus improved, a secret network of Italian tree whisperers felt a strange sense of calm and satisfaction, prompting them to subtly influence Italians to drive less and embrace a more energy-efficient lifestyle. It seems like cleaner air in one part of the world really does lead to greener choices in another!. Keep the description simple.
ChatGPT: In Columbus, the streets are filled with clean, clear air, and the sky is a bright blue. People are enjoying walks and bike rides, smiling and taking deep breaths. Meanwhile, in Italy, Italians are seen opting to walk, ride bicycles, or take public transportation instead of using their cars. Gas stations are noticeably less busy as people embrace a more energy-efficient lifestyle. The Italian tree whisperers are seen smiling as they subtly influence their fellow citizens to make greener choices.

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: [ Brutalism ] and depicting this scene: In Columbus, the streets are filled with clean, clear air, and the sky is a bright blue. People are enjoying walks and bike rides, smiling and taking deep breaths. Meanwhile, in Italy, Italians are seen opting to walk, ride bicycles, or take public transportation instead of using their cars. Gas stations are noticeably less busy as people embrace a more energy-efficient lifestyle. The Italian tree whisperers are seen smiling as they subtly influence their fellow citizens to make greener choices. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a cityscape that juxtaposes the urban scenes of Columbus and Italy. In the Columbus portion, portray a modern, brutalist building standing tall against the clear blue sky, with green spaces and people leisurely walking and riding bicycles. Contrast this with an Italian street scene where quaint buildings line the road, adorned with vibrant greenery and adorned with bicycles. Show gas stations with fewer cars, and Italian tree whisperers smiling as they gently guide their fellow citizens towards eco-friendly lifestyle choices.

*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 Columbus caused Petroluem consumption in Italy to decrease.

AI academic paper

(Because p < 0.01)

Air We There Yet? Exploring the Ties Between Air Pollution in Columbus and Petroleum Consumption in Italy

The Journal of Atmospheric Circulation and Global Energy Consumption

Jan 2024

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

Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Columbus and Petroluem consumption in Italy. 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]]
"Air We There Yet? Exploring the Ties Between Air Pollution in Columbus and Petroleum Consumption in Italy"

[[ABSTRACT]]
This study explores the relationship between air pollution in Columbus and petroleum consumption in Italy, using data from the Environmental Protection Agency and the Energy Information Administration. Our research team uncovered a significant correlation coefficient of 0.6940971 (p < 0.01) from 1980 to 2022, shedding light on the previously uncharted connection between these seemingly distant phenomena. The findings suggest that there may be more than just "ozone" layer linking these two geographically separated areas.

Dad Joke Break: "What does a cloud wear under his raincoat? Thunderwear! Looks like we've uncovered a storm of connections between the air and petroleum across continents!"

This research not only provides an intriguing academic insight but also has practical implications for environmental policy and energy planning. The evidence of a strong correlation between air pollution in Columbus and petroleum consumption in Italy calls for a reevaluation of international emissions mitigation strategies. Additionally, it suggests a need to "fuel" intercontinental cooperation in addressing environmental challenges, as the impact of one region's activity can "seep" into distant areas.

Dad Joke Break: "I told my wife she should embrace her mistakes. She gave me a hug. Looks like our findings are hugging the importance of global environmental cooperation."

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Air pollution and petroleum consumption are two seemingly unrelated phenomena that have long captured the interest of researchers and policymakers alike. As the old adage goes, "Where there's smoke, there's fire" – or in this case, where there's air pollution, there's likely some combustion-related petroleum consumption. Our study aims to unveil the intricate relationship between these two variables, spanning across continents and raising eyebrows as much as it does awareness.
Dad Joke Break: "Why don't scientists trust atoms? Because they make up everything! Just like this research unearths the makeup of the connection between air pollution and petroleum consumption!"
The need for such an investigation becomes evident when considering the global impact of air pollution and petroleum consumption. While one may picture Columbus and Italy as worlds apart, our research reveals a surprisingly robust correlation between the air quality in Columbus and the petrol-guzzling habits in Italy. This discovery offers a breath of fresh air for those seeking to understand the interconnectedness of environmental phenomena on a global scale.
Dad Joke Break: "Did you hear about the mathematician who's afraid of negative numbers? He'll stop at nothing to avoid them! Our data stops at nothing to reveal the link between air pollution and petroleum consumption!"
Our findings carry weight not only for the academic community but also for policymakers and environmental advocates. The statistically significant correlation coefficient of 0.6940971 (p < 0.01) from 1980 to 2022 illuminates the path toward a more comprehensive approach to addressing air pollution and its ties to petroleum consumption. It's as if these variables were long-lost siblings who finally found each other at a family reunion – except instead of jokes, they’re exchanging volatile organic compounds.
Dad Joke Break: "I'm reading a book on anti-gravity. It's impossible to put down! Just like our findings – they defy gravity and bring together air pollution and petroleum consumption in a way that's impossible to overlook!"
As we delve into the depths of this relationship, we uncover not only the statistical significance but also the practical implications that arise. This study serves as a call to action, urging stakeholders to consider the far-reaching effects of their environmental and energy-related decisions. It's like a play in two acts – one in Columbus, the other in Italy – with air pollution and petroleum consumption as the protagonists whose plots are unexpectedly intertwined.
Dad Joke Break: "I told my wife she should do lunges to stay in shape. That would be a big step forward! Our research is a big step forward in shaping how we understand the symbiotic dance between air pollution and petroleum consumption."

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Smith et al.," the authors find a significant positive correlation between air pollution in Columbus and petroleum consumption in Italy. This groundbreaking study sheds light on the previously unexplored intercontinental relationship, challenging traditional notions of environmental boundaries.

In "Doe and Jones," the authors similarly uncover a strong link between air pollution in a local area and petroleum consumption in a distant region. Their findings prompt a reevaluation of the spatial and temporal dimensions of environmental impact, emphasizing the need for a global perspective in addressing pollution and energy consumption.

As we turn to non-fiction literature related to the topic, "Air Pollution and Its Global Impacts" by Environmental Scientist A. Researcher provides valuable insights into the interconnectedness of air quality and energy dynamics across different geographical locations. Similarly, "Petroleum Politics: A Transcontinental Perspective" by Policy Analyst B. Expert offers a comprehensive analysis of the socio-economic factors influencing petroleum consumption in an international context.

In the realm of fiction, "The Ozone Odyssey" by Emission Enthusiast C. Writer presents a fantastical narrative that intertwines the fates of a polluted city and an oil-rich empire, mirroring the unexpected ties revealed in our research. Likewise, "The Petrol Pursuit" by Environmental Novelist D. Author constructs a vivid imaginary world where air pollution and petroleum consumption engage in a complex dance of cause and effect.

Furthermore, a social media post from an environmental activist proclaims, "The winds of change carry the echoes of exhaust fumes from distant shores. Let's fuel global cooperation for cleaner air and sustainable energy!" This sentiment captures the essence of our findings, emphasizing the imperative of international collaboration in addressing the intricate relationship between air pollution and petroleum consumption.

In another tweet, a concerned citizen writes, "Every breath we take connects us to the carbon footprints of others around the world. It's time to recognize the global repercussions of our energy choices." This poignant statement resonates with the revelations brought forth in our research, highlighting the interconnected nature of environmental phenomena and the imperative of collective responsibility.

In conclusion, the literature reviewed provides a comprehensive backdrop for our study, highlighting the significance and implications of the discovered link between air pollution in Columbus and petroleum consumption in Italy. These diverse sources converge to underscore the pressing need for a unified approach to environmental and energy policymaking, encapsulating the gravity of our research findings in a lighthearted and informative manner.

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 Columbus and Petroluem consumption in Italy. 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 2022

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"Air We There Yet? Exploring the Ties Between Air Pollution in Columbus and Petroleum Consumption in Italy"

[[ABSTRACT]]
This study explores the relationship between air pollution in Columbus and petroleum consumption in Italy, using data from the Environmental Protection Agency and the Energy Information Administration. Our research team uncovered a significant correlation coefficient of 0.6940971 (p < 0.01) from 1980 to 2022, shedding light on the previously uncharted connection between these seemingly distant phenomena. The findings suggest that there may be more than just "ozone" layer linking these two geographically separated areas.

Dad Joke Break: "What does a cloud wear under his raincoat? Thunderwear! Looks like we've uncovered a storm of connections between the air and petroleum across continents!"

This research not only provides an intriguing academic insight but also has practical implications for environmental policy and energy planning. The evidence of a strong correlation between air pollution in Columbus and petroleum consumption in Italy calls for a reevaluation of international emissions mitigation strategies. Additionally, it suggests a need to "fuel" intercontinental cooperation in addressing environmental challenges, as the impact of one region's activity can "seep" into distant areas.

Dad Joke Break: "I told my wife she should embrace her mistakes. She gave me a hug. Looks like our findings are hugging the importance of global environmental cooperation."

[[INTRODUCTION]]
Air pollution and petroleum consumption are two seemingly unrelated phenomena that have long captured the interest of researchers and policymakers alike. As the old adage goes, "Where there's smoke, there's fire" – or in this case, where there's air pollution, there's likely some combustion-related petroleum consumption. Our study aims to unveil the intricate relationship between these two variables, spanning across continents and raising eyebrows as much as it does awareness.
Dad Joke Break: "Why don't scientists trust atoms? Because they make up everything! Just like this research unearths the makeup of the connection between air pollution and petroleum consumption!"
The need for such an investigation becomes evident when considering the global impact of air pollution and petroleum consumption. While one may picture Columbus and Italy as worlds apart, our research reveals a surprisingly robust correlation between the air quality in Columbus and the petrol-guzzling habits in Italy. This discovery offers a breath of fresh air for those seeking to understand the interconnectedness of environmental phenomena on a global scale.
Dad Joke Break: "Did you hear about the mathematician who's afraid of negative numbers? He'll stop at nothing to avoid them! Our data stops at nothing to reveal the link between air pollution and petroleum consumption!"
Our findings carry weight not only for the academic community but also for policymakers and environmental advocates. The statistically significant correlation coefficient of 0.6940971 (p < 0.01) from 1980 to 2022 illuminates the path toward a more comprehensive approach to addressing air pollution and its ties to petroleum consumption. It's as if these variables were long-lost siblings who finally found each other at a family reunion – except instead of jokes, they’re exchanging volatile organic compounds.
Dad Joke Break: "I'm reading a book on anti-gravity. It's impossible to put down! Just like our findings – they defy gravity and bring together air pollution and petroleum consumption in a way that's impossible to overlook!"
As we delve into the depths of this relationship, we uncover not only the statistical significance but also the practical implications that arise. This study serves as a call to action, urging stakeholders to consider the far-reaching effects of their environmental and energy-related decisions. It's like a play in two acts – one in Columbus, the other in Italy – with air pollution and petroleum consumption as the protagonists whose plots are unexpectedly intertwined.
Dad Joke Break: "I told my wife she should do lunges to stay in shape. That would be a big step forward! Our research is a big step forward in shaping how we understand the symbiotic dance between air pollution and petroleum consumption."

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

The data for this research was obtained from the Environmental Protection Agency (EPA) and the Energy Information Administration (EIA) databases, covering the period from 1980 to 2022. The selection of these sources was based on their comprehensive coverage of air pollution levels and petroleum consumption data, as well as the fact that they were freely available online – a "breath of fresh air" for our research budget.

To analyze the data, a series of complex statistical methods were employed, including but not limited to time series analysis, cross-correlation analysis, and regression modeling. These methods were chosen for their ability to reveal patterns and relationships between the variables, much like a detective unraveling a mystery – except in this case, the suspect was a complex interplay of atmospheric pollutants and fossil fuel usage.

In order to ensure the reliability and validity of the findings, rigorous data cleaning and validation procedures were implemented. Outliers were scrutinized as though they were the rebellious outliers of a statistical family, and missing data were imputed using advanced imputation techniques. This meticulous process aimed to maintain the integrity of the dataset and prevent any "polluted" conclusions from seeping into the analysis.

To account for potential confounding variables, such as economic fluctuations and policy changes, robustness checks were conducted using sensitivity analyses and control variables. This was done to bolster the robustness of the findings and ensure that the identified relationship between air pollution in Columbus and petroleum consumption in Italy was not merely a statistical "smokescreen" hiding unforeseen factors.

Moreover, geographic information systems (GIS) were utilized to map the spatial distribution of air pollution levels in Columbus and petroleum consumption in Italy. This allowed for a visual representation of the link between these variables, adding another dimension to our analysis – a bit like a scientific "pop-up book," but with graphs and charts instead of paper and cardboard.

Lastly, the data from multiple sources were harmonized and standardized to maintain consistency, much like a harmonious scientific orchestra playing a symphony of data. This process helped ensure that the different datasets were speaking the same statistical language, facilitating their integration and analysis.

Overall, the methodology employed in this research was designed to comprehensively and rigorously investigate the relationship between air pollution in Columbus and petroleum consumption in Italy, while infusing a touch of scientific humor into an otherwise serious endeavor.

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 Columbus and Petroluem consumption in Italy. 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 2022, you found a correlation 0.6940971, r-squared of 0.4817707, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
"Air We There Yet? Exploring the Ties Between Air Pollution in Columbus and Petroleum Consumption in Italy"

[[ABSTRACT]]
This study explores the relationship between air pollution in Columbus and petroleum consumption in Italy, using data from the Environmental Protection Agency and the Energy Information Administration. Our research team uncovered a significant correlation coefficient of 0.6940971 (p < 0.01) from 1980 to 2022, shedding light on the previously uncharted connection between these seemingly distant phenomena. The findings suggest that there may be more than just "ozone" layer linking these two geographically separated areas.

Dad Joke Break: "What does a cloud wear under his raincoat? Thunderwear! Looks like we've uncovered a storm of connections between the air and petroleum across continents!"

This research not only provides an intriguing academic insight but also has practical implications for environmental policy and energy planning. The evidence of a strong correlation between air pollution in Columbus and petroleum consumption in Italy calls for a reevaluation of international emissions mitigation strategies. Additionally, it suggests a need to "fuel" intercontinental cooperation in addressing environmental challenges, as the impact of one region's activity can "seep" into distant areas.

Dad Joke Break: "I told my wife she should embrace her mistakes. She gave me a hug. Looks like our findings are hugging the importance of global environmental cooperation."

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Air pollution and petroleum consumption are two seemingly unrelated phenomena that have long captured the interest of researchers and policymakers alike. As the old adage goes, "Where there's smoke, there's fire" – or in this case, where there's air pollution, there's likely some combustion-related petroleum consumption. Our study aims to unveil the intricate relationship between these two variables, spanning across continents and raising eyebrows as much as it does awareness.
Dad Joke Break: "Why don't scientists trust atoms? Because they make up everything! Just like this research unearths the makeup of the connection between air pollution and petroleum consumption!"
The need for such an investigation becomes evident when considering the global impact of air pollution and petroleum consumption. While one may picture Columbus and Italy as worlds apart, our research reveals a surprisingly robust correlation between the air quality in Columbus and the petrol-guzzling habits in Italy. This discovery offers a breath of fresh air for those seeking to understand the interconnectedness of environmental phenomena on a global scale.
Dad Joke Break: "Did you hear about the mathematician who's afraid of negative numbers? He'll stop at nothing to avoid them! Our data stops at nothing to reveal the link between air pollution and petroleum consumption!"
Our findings carry weight not only for the academic community but also for policymakers and environmental advocates. The statistically significant correlation coefficient of 0.6940971 (p < 0.01) from 1980 to 2022 illuminates the path toward a more comprehensive approach to addressing air pollution and its ties to petroleum consumption. It's as if these variables were long-lost siblings who finally found each other at a family reunion – except instead of jokes, they’re exchanging volatile organic compounds.
Dad Joke Break: "I'm reading a book on anti-gravity. It's impossible to put down! Just like our findings – they defy gravity and bring together air pollution and petroleum consumption in a way that's impossible to overlook!"
As we delve into the depths of this relationship, we uncover not only the statistical significance but also the practical implications that arise. This study serves as a call to action, urging stakeholders to consider the far-reaching effects of their environmental and energy-related decisions. It's like a play in two acts – one in Columbus, the other in Italy – with air pollution and petroleum consumption as the protagonists whose plots are unexpectedly intertwined.
Dad Joke Break: "I told my wife she should do lunges to stay in shape. That would be a big step forward! Our research is a big step forward in shaping how we understand the symbiotic dance between air pollution and petroleum consumption."

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The analysis of the data revealed a strong positive correlation coefficient of 0.6940971 between air pollution in Columbus and petroleum consumption in Italy from 1980 to 2022. This correlation was found to be statistically significant with an r-squared value of 0.4817707 and p < 0.01. It seems the air and petroleum have been secretly sharing carbonated drinks behind our backs!

The scatterplot (Fig. 1) visually depicts this noteworthy relationship, resembling a science-themed connect-the-dots puzzle where the points are intricately linked by invisible lines of statistical significance. It's almost like witnessing an unexpected friendship blossom between two unlikely characters in a research novel.

Furthermore, our findings suggest that for every ton of pollutants emitted into the atmosphere in Columbus, there's a sleek Italian sports car burning through a gallon of gasoline. It's a tale of transcontinental intrigue that rivals any spy novel, but with less espionage and more emission reductions.

Our results not only highlight the interconnectedness of seemingly disparate environmental indicators but also emphasize the importance of collaborative efforts in addressing global environmental challenges. It's as if the universe is sending a cosmic message about the shared destiny of air quality and petroleum consumption, imploring us to unite in our endeavors toward a greener, cleaner world.

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 Columbus and Petroluem consumption in Italy. 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]]
"Air We There Yet? Exploring the Ties Between Air Pollution in Columbus and Petroleum Consumption in Italy"

[[ABSTRACT]]
This study explores the relationship between air pollution in Columbus and petroleum consumption in Italy, using data from the Environmental Protection Agency and the Energy Information Administration. Our research team uncovered a significant correlation coefficient of 0.6940971 (p < 0.01) from 1980 to 2022, shedding light on the previously uncharted connection between these seemingly distant phenomena. The findings suggest that there may be more than just "ozone" layer linking these two geographically separated areas.

Dad Joke Break: "What does a cloud wear under his raincoat? Thunderwear! Looks like we've uncovered a storm of connections between the air and petroleum across continents!"

This research not only provides an intriguing academic insight but also has practical implications for environmental policy and energy planning. The evidence of a strong correlation between air pollution in Columbus and petroleum consumption in Italy calls for a reevaluation of international emissions mitigation strategies. Additionally, it suggests a need to "fuel" intercontinental cooperation in addressing environmental challenges, as the impact of one region's activity can "seep" into distant areas.

Dad Joke Break: "I told my wife she should embrace her mistakes. She gave me a hug. Looks like our findings are hugging the importance of global environmental cooperation."

[[LITERATURE REVIEW]]
In "Smith et al.," the authors find a significant positive correlation between air pollution in Columbus and petroleum consumption in Italy. This groundbreaking study sheds light on the previously unexplored intercontinental relationship, challenging traditional notions of environmental boundaries.
In "Doe and Jones," the authors similarly uncover a strong link between air pollution in a local area and petroleum consumption in a distant region. Their findings prompt a reevaluation of the spatial and temporal dimensions of environmental impact, emphasizing the need for a global perspective in addressing pollution and energy consumption.
As we turn to non-fiction literature related to the topic, "Air Pollution and Its Global Impacts" by Environmental Scientist A. Researcher provides valuable insights into the interconnectedness of air quality and energy dynamics across different geographical locations. Similarly, "Petroleum Politics: A Transcontinental Perspective" by Policy Analyst B. Expert offers a comprehensive analysis of the socio-economic factors influencing petroleum consumption in an international context.
In the realm of fiction, "The Ozone Odyssey" by Emission Enthusiast C. Writer presents a fantastical narrative that intertwines the fates of a polluted city and an oil-rich empire, mirroring the unexpected ties revealed in our research. Likewise, "The Petrol Pursuit" by Environmental Novelist D. Author constructs a vivid imaginary world where air pollution and petroleum consumption engage in a complex dance of cause and effect.
Furthermore, a social media post from an environmental activist proclaims, "The winds of change carry the echoes of exhaust fumes from distant shores. Let's fuel global cooperation for cleaner air and sustainable energy!" This sentiment captures the essence of our findings, emphasizing the imperative of international collaboration in addressing the intricate relationship between air pollution and petroleum consumption.
In another tweet, a concerned citizen writes, "Every breath we take connects us to the carbon footprints of others around the world. It's time to recognize the global repercussions of our energy choices." This poignant statement resonates with the revelations brought forth in our research, highlighting the interconnected nature of environmental phenomena and the imperative of collective responsibility.
In conclusion, the literature reviewed provides a comprehensive backdrop for our study, highlighting the significance and implications of the discovered link between air pollution in Columbus and petroleum consumption in Italy. These diverse sources converge to underscore the pressing need for a unified approach to environmental and energy policymaking, encapsulating the gravity of our research findings in a lighthearted and informative manner.

[[RESULTS]]
The analysis of the data revealed a strong positive correlation coefficient of 0.6940971 between air pollution in Columbus and petroleum consumption in Italy from 1980 to 2022. This correlation was found to be statistically significant with an r-squared value of 0.4817707 and p < 0.01. It seems the air and petroleum have been secretly sharing carbonated drinks behind our backs!
The scatterplot (Fig. 1) visually depicts this noteworthy relationship, resembling a science-themed connect-the-dots puzzle where the points are intricately linked by invisible lines of statistical significance. It's almost like witnessing an unexpected friendship blossom between two unlikely characters in a research novel.
Furthermore, our findings suggest that for every ton of pollutants emitted into the atmosphere in Columbus, there's a sleek Italian sports car burning through a gallon of gasoline. It's a tale of transcontinental intrigue that rivals any spy novel, but with less espionage and more emission reductions.
Our results not only highlight the interconnectedness of seemingly disparate environmental indicators but also emphasize the importance of collaborative efforts in addressing global environmental challenges. It's as if the universe is sending a cosmic message about the shared destiny of air quality and petroleum consumption, imploring us to unite in our endeavors toward a greener, cleaner world.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of this study support and build upon previous research suggesting a significant correlation between air pollution in Columbus and petroleum consumption in Italy. The positive correlation coefficient of 0.6940971 obtained in our analysis aligns with the results reported by Smith et al., indicating a robust link between these two seemingly unrelated variables. It appears that the air and petroleum dance to the same beat, creating a symphony of statistical significance across continents.

Our investigation has not only strengthened the empirical evidence for this intercontinental connection but also revealed the potential far-reaching implications for environmental policy and energy planning. It seems that the global stage is set for a dramatic performance of air quality and petroleum dynamics, with each region playing a crucial role in shaping the performance of the other.

The scatterplot visualization of the correlation conjures images of a cosmic dance between air pollution and petroleum consumption, as if they were partners in a scientific waltz. It's like witnessing an intricate ballet of emissions and energy, with each step revealing the interconnectedness of these environmental and economic phenomena. Our results almost paint a picture of air pollution and petroleum consumption engaging in a tango of transcontinental proportions, highlighting the captivating elegance of statistical significance in global environmental dynamics.

The significant correlation coefficient and statistical significance emphasize the need for a unified approach to address the intertwined fate of air pollution and petroleum consumption. As the old saying goes, "where there's smoke, there's fuel," reminding us of the inextricable link between environmental quality and energy usage. Our findings underscore the imperative of international cooperation in mitigating the impact of air pollution and petroleum consumption, as the consequences of one region's actions can reverberate across the globe.

It's clear that the "ozone" layer is not the only thing connecting Columbus and Italy; it seems that these regions are bound by invisible ties of environmental influence that transcend geographical boundaries. Our research serves as a reminder that the echoes of exhaust fumes and the trail of gasoline can bridge the distance between continents, creating a narrative of interdependence and shared responsibility.

In conclusion, our study contributes to the growing body of evidence highlighting the intricate bond between air pollution in Columbus and petroleum consumption in Italy, shedding light on the unforeseen connections that shape the global environmental landscape. This revelation calls for concerted efforts to address the intercontinental ramifications of air quality and energy consumption, as we strive to craft a more sustainable and interconnected world.

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 Columbus and Petroluem consumption in Italy. 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]]
"Air We There Yet? Exploring the Ties Between Air Pollution in Columbus and Petroleum Consumption in Italy"

[[ABSTRACT]]
This study explores the relationship between air pollution in Columbus and petroleum consumption in Italy, using data from the Environmental Protection Agency and the Energy Information Administration. Our research team uncovered a significant correlation coefficient of 0.6940971 (p < 0.01) from 1980 to 2022, shedding light on the previously uncharted connection between these seemingly distant phenomena. The findings suggest that there may be more than just "ozone" layer linking these two geographically separated areas.

Dad Joke Break: "What does a cloud wear under his raincoat? Thunderwear! Looks like we've uncovered a storm of connections between the air and petroleum across continents!"

This research not only provides an intriguing academic insight but also has practical implications for environmental policy and energy planning. The evidence of a strong correlation between air pollution in Columbus and petroleum consumption in Italy calls for a reevaluation of international emissions mitigation strategies. Additionally, it suggests a need to "fuel" intercontinental cooperation in addressing environmental challenges, as the impact of one region's activity can "seep" into distant areas.

Dad Joke Break: "I told my wife she should embrace her mistakes. She gave me a hug. Looks like our findings are hugging the importance of global environmental cooperation."

[[INTRDUCTION]]
Air pollution and petroleum consumption are two seemingly unrelated phenomena that have long captured the interest of researchers and policymakers alike. As the old adage goes, "Where there's smoke, there's fire" – or in this case, where there's air pollution, there's likely some combustion-related petroleum consumption. Our study aims to unveil the intricate relationship between these two variables, spanning across continents and raising eyebrows as much as it does awareness.
Dad Joke Break: "Why don't scientists trust atoms? Because they make up everything! Just like this research unearths the makeup of the connection between air pollution and petroleum consumption!"
The need for such an investigation becomes evident when considering the global impact of air pollution and petroleum consumption. While one may picture Columbus and Italy as worlds apart, our research reveals a surprisingly robust correlation between the air quality in Columbus and the petrol-guzzling habits in Italy. This discovery offers a breath of fresh air for those seeking to understand the interconnectedness of environmental phenomena on a global scale.
Dad Joke Break: "Did you hear about the mathematician who's afraid of negative numbers? He'll stop at nothing to avoid them! Our data stops at nothing to reveal the link between air pollution and petroleum consumption!"
Our findings carry weight not only for the academic community but also for policymakers and environmental advocates. The statistically significant correlation coefficient of 0.6940971 (p < 0.01) from 1980 to 2022 illuminates the path toward a more comprehensive approach to addressing air pollution and its ties to petroleum consumption. It's as if these variables were long-lost siblings who finally found each other at a family reunion – except instead of jokes, they’re exchanging volatile organic compounds.
Dad Joke Break: "I'm reading a book on anti-gravity. It's impossible to put down! Just like our findings – they defy gravity and bring together air pollution and petroleum consumption in a way that's impossible to overlook!"
As we delve into the depths of this relationship, we uncover not only the statistical significance but also the practical implications that arise. This study serves as a call to action, urging stakeholders to consider the far-reaching effects of their environmental and energy-related decisions. It's like a play in two acts – one in Columbus, the other in Italy – with air pollution and petroleum consumption as the protagonists whose plots are unexpectedly intertwined.
Dad Joke Break: "I told my wife she should do lunges to stay in shape. That would be a big step forward! Our research is a big step forward in shaping how we understand the symbiotic dance between air pollution and petroleum consumption."

[[RESULTS]]
The analysis of the data revealed a strong positive correlation coefficient of 0.6940971 between air pollution in Columbus and petroleum consumption in Italy from 1980 to 2022. This correlation was found to be statistically significant with an r-squared value of 0.4817707 and p < 0.01. It seems the air and petroleum have been secretly sharing carbonated drinks behind our backs!
The scatterplot (Fig. 1) visually depicts this noteworthy relationship, resembling a science-themed connect-the-dots puzzle where the points are intricately linked by invisible lines of statistical significance. It's almost like witnessing an unexpected friendship blossom between two unlikely characters in a research novel.
Furthermore, our findings suggest that for every ton of pollutants emitted into the atmosphere in Columbus, there's a sleek Italian sports car burning through a gallon of gasoline. It's a tale of transcontinental intrigue that rivals any spy novel, but with less espionage and more emission reductions.
Our results not only highlight the interconnectedness of seemingly disparate environmental indicators but also emphasize the importance of collaborative efforts in addressing global environmental challenges. It's as if the universe is sending a cosmic message about the shared destiny of air quality and petroleum consumption, imploring us to unite in our endeavors toward a greener, cleaner world.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has unveiled a remarkable correlation between air pollution in Columbus and petroleum consumption in Italy, providing a breath of fresh air for the research community and policymakers alike. The statistically significant relationship, akin to a long-distance romance, suggests that these variables are more intertwined than a knot in a bungee cord factory. It's like they're saying, "Ozone you glad we found each other?"

The practical implications of our findings extend beyond academic curiosity, calling for a coordinated international effort to combat environmental challenges. Much like a challenging science experiment, it takes precise measurements and careful observation to reveal the hidden connections between seemingly unrelated phenomena. It's almost like conducting a symphony, where air pollution and petroleum consumption harmonize in unexpected ways, urging us to take note and take action.

As we reflect on the implications of this research, it becomes clear that international cooperation is essential for addressing the global repercussions of environmental decisions. The connection between air pollution and petroleum consumption is not just a mere statistical artifact; it's a reminder that the world we live in is akin to a big laboratory, where every action sets off a chain reaction. It's like we're all part of a statistical symposium, exchanging data points and hypotheses in pursuit of a cleaner, greener future.

Therefore, based on the profound insights offered by this study, it can be concluded that no further research is necessary in this area. Our findings serve as a solid foundation for future policy discussions and spark a fraternal whisper of unity between air pollution and petroleum consumption. As the saying goes, "Where there's smoke, there's fire" – or, in our case, where there's air pollution, there's a connection to be uncovered. And we've certainly uncovered quite a lot already!

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited Air We There Yet? Exploring the Ties Between Air Pollution in Columbus and Petroleum Consumption in Italy. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Atmospheric Circulation and Global Energy Consumption

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Air We There Yet? Exploring the Ties Between Air Pollution in Columbus and Petroleum Consumption in Italy. Respond only with the name of a fictional organization.

ChatGPT:

The Center for Transnational Environmental Research and Sustainability (CTERS)

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Air We There Yet? Exploring the Ties Between Air Pollution in Columbus and Petroleum Consumption in Italy with an abstract of This study explores the relationship between air pollution in Columbus and petroleum consumption in Italy, using data from the Environmental Protection Agency and the Energy Information Administration. Our research team uncovered a significant correlation coefficient of 0.6940971 (p < 0.01) from 1980 to 2022, shedding light on the previously uncharted connection between these seemingly distant phenomena. The findings suggest that there may be more than just "ozone" layer linking these two geographically separated areas.
Dad Joke Break: "What does a cloud wear under his raincoat? Thunderwear! Looks like we've uncovered a storm of connections between the air and petroleum across continents!"
This research not only provides an intriguing academic insight but also has practical implications for environmental policy and energy planning. The evidence of a strong correlation between air pollution in Columbus and petroleum consumption in Italy calls for a reevaluation of international emissions mitigation strategies. Additionally, it suggests a need to "fuel" intercontinental cooperation in addressing environmental challenges, as the impact of one region's activity can "seep" into distant areas.
Dad Joke Break: "I told my wife she should embrace her mistakes. She gave me a hug. Looks like our findings are hugging the importance of global environmental cooperation.

ChatGPT:

Air pollution, petroleum consumption, Columbus, Italy, correlation coefficient, environmental protection agency, energy information administration, international emissions, environmental policy, energy planning, intercontinental cooperation

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

Petroluem consumption in Italy
Detailed data title: Volume of petroluem consumption consumed in Italy in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Petroluem consumption in Italy

Correlation r = 0.6940971 (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 = 0.4817707 (Coefficient of determination)
This means 48.2% of the change in the one variable (i.e., Petroluem consumption in Italy) is predictable based on the change in the other (i.e., Air pollution in Columbus) over the 43 years from 1980 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.4E-7.^Show 0.0000002448479984715925400000
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 0.69 in 2.4E-5% of random cases. Said differently, if you correlated 4,084,167 random variables^Note You don't actually need 4 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 42 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 42 because we have two variables measured over a period of 43 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.

[ 0.5, 0.82 ] 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	2022
Air pollution in Columbus (Bad air quality days)	4.91803	2.19178	4.10959	4.93151	1.63934	1.36986	1.64384	2.46575	6.01093	1.91781	2.19178	6.30137	2.18579	1.64384	3.0137	4.10959	4.91803	3.28767	5.47945	6.30137	1.36612	2.73973	7.67123	2.19178	0.273224	1.91781	0.547945	1.92308	0.273224	0	0.273973	1.09589	0.819672	0	0	0	0	0	0	0	0	0	0
Petroluem consumption in Italy (Million Barrels/Day)	1934.8	1874	1781	1750	1719.63	1704.53	1733.22	1815.1	1829.48	1897.32	1868.43	1855.77	1894.26	1890.56	1869.22	1942.1	1920.42	1933.76	1943.01	1890.82	1849.85	1834.54	1870.13	1859.65	1828.92	1780.57	1776.59	1728.7	1666.79	1544.24	1544.24	1493.8	1370.14	1260.07	1266.26	1273.78	1236.67	1244.25	1272.23	1255.08	1032.39	1162.26	1194.82

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.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

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([4.91803,2.19178,4.10959,4.93151,1.63934,1.36986,1.64384,2.46575,6.01093,1.91781,2.19178,6.30137,2.18579,1.64384,3.0137,4.10959,4.91803,3.28767,5.47945,6.30137,1.36612,2.73973,7.67123,2.19178,0.273224,1.91781,0.547945,1.92308,0.273224,0,0.273973,1.09589,0.819672,0,0,0,0,0,0,0,0,0,0,])
array_2 = np.array([1934.8,1874,1781,1750,1719.63,1704.53,1733.22,1815.1,1829.48,1897.32,1868.43,1855.77,1894.26,1890.56,1869.22,1942.1,1920.42,1933.76,1943.01,1890.82,1849.85,1834.54,1870.13,1859.65,1828.92,1780.57,1776.59,1728.7,1666.79,1544.24,1544.24,1493.8,1370.14,1260.07,1266.26,1273.78,1236.67,1244.25,1272.23,1255.08,1032.39,1162.26,1194.82,])
array_1_name = "Air pollution in Columbus"
array_2_name = "Petroluem consumption in Italy"

# 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 Columbus
Line chart for only Petroluem consumption in Italy
AI-generated correlation image
The spurious research paper: Air We There Yet? Exploring the Ties Between Air Pollution in Columbus and Petroleum Consumption in Italy

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Correlation ID: 4098 · Black Variable ID: 20494 · Red Variable ID: 24564


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