Spurious correlation #2,893 · 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 Minneapolis and the second variable is Kerosene used in United States. 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 Minneapolis and the second variable is Kerosene used in United States. The chart goes from 1980 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As air quality improved in Minneapolis, the demand for kerosene heaters went down. You could say the cold truth is that when it comes to clean air, Minneapolis was really raising the bar!

^{Show image generation prompt} Model: dalle-3
Prompt: Prompt: Generate an image that looks like a scene from 'Star Wars', but in a futuristic world where downtown Minneapolis is depicted with a clearer skyline due to decreased air pollution. A graceful flock of pigeons joyously soar through the open sky, performing majestic aerial displays that have drawn crowds from across the country. The city streets are quieter, and the awe-inspiring bird airshows have replaced the previous hustle and bustle associated with pollution. 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 Minneapolis and Kerosene used in United States. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s Steampunk Voxel art An image that looks like it is a scene from 'Star Wars' Psychedelic
ChatGPT: An image that looks like it is a scene from 'Star Wars'

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 Minneapolis and Kerosene used in United States, in the following situation: Because as air pollution decreased in Minneapolis, the local pigeons were finally able to fly more freely and gracefully. This inspired a nationwide movement of pigeons performing airshows, leading to a decrease in kerosene usage as people flocked to watch these majestic aerial displays instead of flying their own planes.. Keep the description simple.
ChatGPT: In downtown Minneapolis, the skyline is now clearer as the air pollution has decreased. The local pigeons, now unfazed by the hazy air, joyously soar in a graceful flock, twirling and diving elegantly through the open sky. Across the country, crowds gather to witness these majestic aerial displays performed by the pigeons, their wings cutting through the air harmoniously. The city streets are quieter as the kerosene usage decreases, replaced by the awe and wonder of the mesmerizing bird airshows.

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: [ An image that looks like it is a scene from 'Star Wars' ] and depicting this scene: In downtown Minneapolis, the skyline is now clearer as the air pollution has decreased. The local pigeons, now unfazed by the hazy air, joyously soar in a graceful flock, twirling and diving elegantly through the open sky. Across the country, crowds gather to witness these majestic aerial displays performed by the pigeons, their wings cutting through the air harmoniously. The city streets are quieter as the kerosene usage decreases, replaced by the awe and wonder of the mesmerizing bird airshows. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image that looks like a scene from 'Star Wars', but in a futuristic world where downtown Minneapolis is depicted with a clearer skyline due to decreased air pollution. A graceful flock of pigeons joyously soar through the open sky, performing majestic aerial displays that have drawn crowds from across the country. The city streets are quieter, and the awe-inspiring bird airshows have replaced the previous hustle and bustle associated with pollution.

*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 Minneapolis caused Kerosene used in United States to decrease. Include one good pun.

AI academic paper

(Because p < 0.01)

Up in Smoke: Uncovering the Relationship Between Air Pollution in Minneapolis and Kerosene Consumption in the United States

The Journal of Ecological Entanglements

Jan 2024

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

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

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

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

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
"Up in Smoke: Uncovering the Relationship Between Air Pollution in Minneapolis and Kerosene Consumption in the United States"

[[ABSTRACT]]
This paper investigates the link between air pollution levels in Minneapolis and kerosene usage in the United States over the span of 1980 to 2022, utilizing data from the Environmental Protection Agency and the Energy Information Administration. Our analysis reveals a striking correlation coefficient of 0.8414787 and p < 0.01, indicating a robust connection between these two variables.

Like a stubborn smog cloud, the relationship between air pollution and kerosene consumption has been shrouded in mystery. However, our research sheds light on this puzzling link and uncovers evidence that leaves no room for doubt. It's as clear as the air in a post-thunderstorm sky!

The findings of this study have significant implications for environmental policy and energy regulation, suggesting that reductions in kerosene usage could lead to improvements in air quality in urban areas such as Minneapolis. It's time to stop fueling the fire of pollution and ignite a cleaner, greener future.

In conclusion, our research not only establishes a strong statistical connection between air pollution in Minneapolis and kerosene consumption in the United States but also showcases the power of data analysis in unraveling complex environmental phenomena. This study is a breath of fresh air in the realm of environmental research, and it's sure to spark further investigation into the interplay between energy usage and air quality.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The pervasive haze of air pollution continues to loom over many urban areas, affecting public health and environmental quality. Despite concerted efforts to improve air quality, the sources and determinants of air pollution remain a subject of ongoing investigation. One such source that has flown under the radar is the use of kerosene, a commonly overlooked contributor to air pollution. It's time to shed light on this dark horse of pollution!
Kerosene, often used for heating, cooking, and lighting in both residential and industrial settings, has quietly played a role in the emission of pollutants into the atmosphere. As the saying goes, "Where there's smoke, there's fire" – and where there's kerosene, there's likely some combustion-related pollutants causing a stir in the air.
In this study, we delve into the relationship between air pollution in Minneapolis and kerosene consumption in the United States. By analyzing extensive data spanning over four decades, we aim to unravel the intricate dance between these variables and illuminate the implications for environmental and energy policies. It's time to clear the air about kerosene's role in pollution and ignite a new understanding of its impact.
Our investigation not only deepens our understanding of the link between air pollution and kerosene usage but also brings to light the potential avenues for mitigating air pollution through targeted interventions. It's time to extinguish the misconceptions and fan the flames of knowledge on this critical issue.
Get ready to breathe in the findings of our study, as we bring a breath of fresh air to the conversation surrounding air pollution and kerosene consumption. This research is more than just hot air – it's a beacon of insight into the dynamics of urban air quality and energy usage.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The association between air pollution and kerosene consumption has been a subject of ongoing scrutiny in environmental research. Smith and Jones (2015) conducted a comprehensive analysis of air quality and kerosene usage patterns, laying the groundwork for subsequent investigations in this domain. Their findings pointed to a potential link between these two factors, setting the stage for further exploration.

In "The Role of Fossil Fuels in Environmental Degradation," Doe (2018) provides a detailed exposition on the impact of kerosene usage on air quality, citing empirical evidence of its contribution to particulate matter and greenhouse gas emissions. The author emphasizes the need for holistic approaches to address the environmental ramifications of kerosene consumption, creating a beacon of awareness in the dim haze of pollution studies.

Now, turning to more unconventional sources, "Kerosene Chronicles: Tales of Illumination and Pollution" offers a narrative blend of fiction and factual insights into the world of kerosene use, providing a unique perspective on its societal and environmental effects. The book paints an evocative picture of the interplay between kerosene and air pollution, shedding light on the darker side of this commonly used fuel.

In another fictional work, "The Mysteries of Minneapolis: Uncovering Urban Enigmas," the protagonist stumbles upon a cryptic link between air pollution levels in Minneapolis and the clandestine activities of kerosene vendors. While purely speculative, the narrative serves as a reminder of the enigmatic nature of environmental connections and the need for thorough investigation.

Drawing from real-time discussions, several social media posts have surfaced, attributing reductions in air quality to kerosene-related activities, with one user humorously remarking, "Looks like the fumes from kerosene are really igniting some smoggy situations in our city! #KeroseneCrisis" Such online musings, while informal, highlight the public's awareness of the potential impact of kerosene on urban air pollution.

It appears that the scholarly discourse surrounding air pollution and kerosene usage has been met with a mix of rigorous analysis and imaginative storytelling, underscoring the multifaceted nature of this research domain. As we embark on our own investigation, it is clear that unraveling the complexities of this connection will require a balanced blend of empirical evidence and perhaps a sprinkle of literary inspiration.

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 Minneapolis and Kerosene used in United States. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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]]
"Up in Smoke: Uncovering the Relationship Between Air Pollution in Minneapolis and Kerosene Consumption in the United States"

[[ABSTRACT]]
This paper investigates the link between air pollution levels in Minneapolis and kerosene usage in the United States over the span of 1980 to 2022, utilizing data from the Environmental Protection Agency and the Energy Information Administration. Our analysis reveals a striking correlation coefficient of 0.8414787 and p < 0.01, indicating a robust connection between these two variables.

Like a stubborn smog cloud, the relationship between air pollution and kerosene consumption has been shrouded in mystery. However, our research sheds light on this puzzling link and uncovers evidence that leaves no room for doubt. It's as clear as the air in a post-thunderstorm sky!

The findings of this study have significant implications for environmental policy and energy regulation, suggesting that reductions in kerosene usage could lead to improvements in air quality in urban areas such as Minneapolis. It's time to stop fueling the fire of pollution and ignite a cleaner, greener future.

In conclusion, our research not only establishes a strong statistical connection between air pollution in Minneapolis and kerosene consumption in the United States but also showcases the power of data analysis in unraveling complex environmental phenomena. This study is a breath of fresh air in the realm of environmental research, and it's sure to spark further investigation into the interplay between energy usage and air quality.

[[INTRODUCTION]]
The pervasive haze of air pollution continues to loom over many urban areas, affecting public health and environmental quality. Despite concerted efforts to improve air quality, the sources and determinants of air pollution remain a subject of ongoing investigation. One such source that has flown under the radar is the use of kerosene, a commonly overlooked contributor to air pollution. It's time to shed light on this dark horse of pollution!
Kerosene, often used for heating, cooking, and lighting in both residential and industrial settings, has quietly played a role in the emission of pollutants into the atmosphere. As the saying goes, "Where there's smoke, there's fire" – and where there's kerosene, there's likely some combustion-related pollutants causing a stir in the air.
In this study, we delve into the relationship between air pollution in Minneapolis and kerosene consumption in the United States. By analyzing extensive data spanning over four decades, we aim to unravel the intricate dance between these variables and illuminate the implications for environmental and energy policies. It's time to clear the air about kerosene's role in pollution and ignite a new understanding of its impact.
Our investigation not only deepens our understanding of the link between air pollution and kerosene usage but also brings to light the potential avenues for mitigating air pollution through targeted interventions. It's time to extinguish the misconceptions and fan the flames of knowledge on this critical issue.
Get ready to breathe in the findings of our study, as we bring a breath of fresh air to the conversation surrounding air pollution and kerosene consumption. This research is more than just hot air – it's a beacon of insight into the dynamics of urban air quality and energy usage.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To unravel the enigmatic relationship between air pollution in Minneapolis and kerosene consumption in the United States, an array of methodological approaches were employed, akin to untangling a knot of tangled kite strings. Data on air pollution levels in Minneapolis was obtained from the Environmental Protection Agency, while kerosene consumption data for the United States was sourced from the Energy Information Administration. The use of data from 1980 to 2022 allowed for a comprehensive analysis of trends and patterns, akin to studying the evolution of dance moves over several decades.

The statistical analysis involved crunching numbers, cross-referencing figures, and conducting correlation analyses that would make even the most stoic mathematician do a double take. The correlation coefficient between air pollution levels in Minneapolis and kerosene consumption in the United States was computed with a robust significance level. Much like solving a captivating mystery novel, this analysis revealed a striking correlation coefficient of 0.8414787 and p < 0.01, leaving even the most skeptical of onlookers with raised eyebrows and dropped jaws at the strength of the connection.

Furthermore, to capture the nuanced dynamics of this relationship, time series modeling techniques were applied to the data, resembling the delicate art of interpreting the movements of a flock of migratory birds. These techniques allowed for the identification of temporal patterns and fluctuations in air pollution levels vis-à-vis kerosene consumption, akin to tracing the ebb and flow of the tides.

In addition to quantitative analyses, qualitative methods were also utilized through expert interviews and literature reviews. These sources provided contextual insights and historical perspectives on the usage and impact of kerosene, adding depth to the understanding of its role in the atmospheric symphony of pollutants.

At the risk of sounding inflated, our research team took a multi-faceted, comprehensive approach to investigate the relationship between air pollution in Minneapolis and kerosene consumption in the United States. This methodological medley offered a panoramic view of the complex interplay between these variables, akin to observing a kaleidoscope turning and revealing its intricate patterns.

It's important to note that while our methodology may sound convoluted, it was executed with precision and rigor, akin to a tightly choreographed ballet performance. This allowed for a robust and nuanced exploration of the connection between air pollution and kerosene usage, shedding light on this cloudy issue like a weatherman predicting sunshine after a storm.

Now, to lighten the mood a bit - Why did the kerosene refuse to play hide and seek? Because it was always getting caught!

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 Minneapolis and Kerosene used in United States. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"Up in Smoke: Uncovering the Relationship Between Air Pollution in Minneapolis and Kerosene Consumption in the United States"

[[ABSTRACT]]
This paper investigates the link between air pollution levels in Minneapolis and kerosene usage in the United States over the span of 1980 to 2022, utilizing data from the Environmental Protection Agency and the Energy Information Administration. Our analysis reveals a striking correlation coefficient of 0.8414787 and p < 0.01, indicating a robust connection between these two variables.

Like a stubborn smog cloud, the relationship between air pollution and kerosene consumption has been shrouded in mystery. However, our research sheds light on this puzzling link and uncovers evidence that leaves no room for doubt. It's as clear as the air in a post-thunderstorm sky!

The findings of this study have significant implications for environmental policy and energy regulation, suggesting that reductions in kerosene usage could lead to improvements in air quality in urban areas such as Minneapolis. It's time to stop fueling the fire of pollution and ignite a cleaner, greener future.

In conclusion, our research not only establishes a strong statistical connection between air pollution in Minneapolis and kerosene consumption in the United States but also showcases the power of data analysis in unraveling complex environmental phenomena. This study is a breath of fresh air in the realm of environmental research, and it's sure to spark further investigation into the interplay between energy usage and air quality.

[[LITERATURE REVIEW]]
The association between air pollution and kerosene consumption has been a subject of ongoing scrutiny in environmental research. Smith and Jones (2015) conducted a comprehensive analysis of air quality and kerosene usage patterns, laying the groundwork for subsequent investigations in this domain. Their findings pointed to a potential link between these two factors, setting the stage for further exploration.
In "The Role of Fossil Fuels in Environmental Degradation," Doe (2018) provides a detailed exposition on the impact of kerosene usage on air quality, citing empirical evidence of its contribution to particulate matter and greenhouse gas emissions. The author emphasizes the need for holistic approaches to address the environmental ramifications of kerosene consumption, creating a beacon of awareness in the dim haze of pollution studies.
Now, turning to more unconventional sources, "Kerosene Chronicles: Tales of Illumination and Pollution" offers a narrative blend of fiction and factual insights into the world of kerosene use, providing a unique perspective on its societal and environmental effects. The book paints an evocative picture of the interplay between kerosene and air pollution, shedding light on the darker side of this commonly used fuel.
In another fictional work, "The Mysteries of Minneapolis: Uncovering Urban Enigmas," the protagonist stumbles upon a cryptic link between air pollution levels in Minneapolis and the clandestine activities of kerosene vendors. While purely speculative, the narrative serves as a reminder of the enigmatic nature of environmental connections and the need for thorough investigation.
Drawing from real-time discussions, several social media posts have surfaced, attributing reductions in air quality to kerosene-related activities, with one user humorously remarking, "Looks like the fumes from kerosene are really igniting some smoggy situations in our city! #KeroseneCrisis" Such online musings, while informal, highlight the public's awareness of the potential impact of kerosene on urban air pollution.
It appears that the scholarly discourse surrounding air pollution and kerosene usage has been met with a mix of rigorous analysis and imaginative storytelling, underscoring the multifaceted nature of this research domain. As we embark on our own investigation, it is clear that unraveling the complexities of this connection will require a balanced blend of empirical evidence and perhaps a sprinkle of literary inspiration.

[[RESULTS]]
The analysis of the data revealed a striking correlation coefficient of 0.8414787 between air pollution levels in Minneapolis and kerosene consumption in the United States over the period of 1980 to 2022. This robust correlation suggests a strong relationship between these two variables. It's as if they were two peas in a pollution pod!
Furthermore, the r-squared value of 0.7080863 indicates that approximately 70.81% of the variation in air pollution levels in Minneapolis can be explained by changes in kerosene consumption in the United States. This finding underscores the substantial influence of kerosene usage on urban air quality. Talk about a kerosene "wow" moment!
The statistical significance, with a p-value of less than 0.01, provides strong evidence that the observed correlation is not due to random chance. It's safe to say that this connection between air pollution and kerosene consumption is statistically significant – no smoke and mirrors here!
The scatterplot (Fig. 1) visually depicts the strong positive correlation between air pollution levels in Minneapolis and kerosene consumption in the United States. Each data point seems to be shouting, "Look at us, we're in this together!"
In summary, the results of our analysis demonstrate a robust and significant association between air pollution in Minneapolis and kerosene usage in the United States. This finding not only clarifies the relationship between these two variables but also ignites the conversation about the role of kerosene in urban air quality. It's time to clear the air and light the way for cleaner skies!

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study provide compelling evidence supporting the prior research that has delved into the association between air pollution in Minneapolis and kerosene consumption in the United States. The findings not only affirm the earlier indications of a potential link between these two variables but also illuminate the substantial influence of kerosene usage on urban air quality. It's like finding the missing piece of a pollution puzzle!

The correlation coefficient of 0.8414787 observed in our analysis aligns closely with the preliminary suggestions of Smith and Jones (2015), paving the way for a deeper understanding of the intricate relationship between air pollution and kerosene consumption. It's as if we're all part of a scholarly game of "connect the dots" – with kerosene and air pollution being the star players!

Moreover, the r-squared value of 0.7080863 underscores the explanatory power of kerosene consumption in predicting air pollution levels in Minneapolis, echoing the sentiments expressed by Doe (2018) in highlighting the considerable impact of this energy source on environmental degradation. It's clear that kerosene is not just a "fuel" for thought – it's a key contributor to the atmospheric composition.

The statistical significance of our findings, with a p-value of less than 0.01, reinforces the credibility of the observed correlation, echoing the sentiments of "Kerosene Chronicles: Tales of Illumination and Pollution," albeit in a non-fictional, empirical context. As the data would have it, the association between air pollution and kerosene consumption is not just a flight of fancy – it's a bona fide scientific reality. It's as real as the air we breathe!

The scatterplot (Fig. 1) visually corroborates the strength of the relationship between air pollution levels in Minneapolis and kerosene consumption in the United States, providing a graphic representation of the interconnectedness of these variables. It's as if the data points are saying, "We're not just statistics – we're part of a meaningful narrative about the impact of kerosene on urban air quality!"

In conclusion, the results of our investigation affirm the substantial connection between air pollution in Minneapolis and kerosene usage in the United States, reinforcing the need for concerted efforts to address the environmental implications of kerosene consumption. This study not only adds a chapter to the ongoing saga of air quality research but also kindles the flames of awareness regarding the influence of kerosene on urban atmospheres. It's time to shed light on this important relationship and strive for cleaner skies!

And remember, when it comes to air pollution and kerosene usage, we must "wick" it seriously!

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 Minneapolis and Kerosene used in United States. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Up in Smoke: Uncovering the Relationship Between Air Pollution in Minneapolis and Kerosene Consumption in the United States"

[[ABSTRACT]]
This paper investigates the link between air pollution levels in Minneapolis and kerosene usage in the United States over the span of 1980 to 2022, utilizing data from the Environmental Protection Agency and the Energy Information Administration. Our analysis reveals a striking correlation coefficient of 0.8414787 and p < 0.01, indicating a robust connection between these two variables.

Like a stubborn smog cloud, the relationship between air pollution and kerosene consumption has been shrouded in mystery. However, our research sheds light on this puzzling link and uncovers evidence that leaves no room for doubt. It's as clear as the air in a post-thunderstorm sky!

The findings of this study have significant implications for environmental policy and energy regulation, suggesting that reductions in kerosene usage could lead to improvements in air quality in urban areas such as Minneapolis. It's time to stop fueling the fire of pollution and ignite a cleaner, greener future.

In conclusion, our research not only establishes a strong statistical connection between air pollution in Minneapolis and kerosene consumption in the United States but also showcases the power of data analysis in unraveling complex environmental phenomena. This study is a breath of fresh air in the realm of environmental research, and it's sure to spark further investigation into the interplay between energy usage and air quality.

[[INTRDUCTION]]
The pervasive haze of air pollution continues to loom over many urban areas, affecting public health and environmental quality. Despite concerted efforts to improve air quality, the sources and determinants of air pollution remain a subject of ongoing investigation. One such source that has flown under the radar is the use of kerosene, a commonly overlooked contributor to air pollution. It's time to shed light on this dark horse of pollution!
Kerosene, often used for heating, cooking, and lighting in both residential and industrial settings, has quietly played a role in the emission of pollutants into the atmosphere. As the saying goes, "Where there's smoke, there's fire" – and where there's kerosene, there's likely some combustion-related pollutants causing a stir in the air.
In this study, we delve into the relationship between air pollution in Minneapolis and kerosene consumption in the United States. By analyzing extensive data spanning over four decades, we aim to unravel the intricate dance between these variables and illuminate the implications for environmental and energy policies. It's time to clear the air about kerosene's role in pollution and ignite a new understanding of its impact.
Our investigation not only deepens our understanding of the link between air pollution and kerosene usage but also brings to light the potential avenues for mitigating air pollution through targeted interventions. It's time to extinguish the misconceptions and fan the flames of knowledge on this critical issue.
Get ready to breathe in the findings of our study, as we bring a breath of fresh air to the conversation surrounding air pollution and kerosene consumption. This research is more than just hot air – it's a beacon of insight into the dynamics of urban air quality and energy usage.

[[RESULTS]]
The analysis of the data revealed a striking correlation coefficient of 0.8414787 between air pollution levels in Minneapolis and kerosene consumption in the United States over the period of 1980 to 2022. This robust correlation suggests a strong relationship between these two variables. It's as if they were two peas in a pollution pod!
Furthermore, the r-squared value of 0.7080863 indicates that approximately 70.81% of the variation in air pollution levels in Minneapolis can be explained by changes in kerosene consumption in the United States. This finding underscores the substantial influence of kerosene usage on urban air quality. Talk about a kerosene "wow" moment!
The statistical significance, with a p-value of less than 0.01, provides strong evidence that the observed correlation is not due to random chance. It's safe to say that this connection between air pollution and kerosene consumption is statistically significant – no smoke and mirrors here!
The scatterplot (Fig. 1) visually depicts the strong positive correlation between air pollution levels in Minneapolis and kerosene consumption in the United States. Each data point seems to be shouting, "Look at us, we're in this together!"
In summary, the results of our analysis demonstrate a robust and significant association between air pollution in Minneapolis and kerosene usage in the United States. This finding not only clarifies the relationship between these two variables but also ignites the conversation about the role of kerosene in urban air quality. It's time to clear the air and light the way for cleaner skies!

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study provides compelling evidence for the strong relationship between air pollution levels in Minneapolis and kerosene consumption in the United States, spanning over four decades. This correlation, with a coefficient as high as a plane cruising at 30,000 feet, serves as a beacon of insight into the interconnectedness of energy usage and urban air quality. It's as if the pollution particles and kerosene molecules have been holding hands behind our backs all this time!

The implications of these findings are as clear as the view from a freshly cleaned car window – reductions in kerosene usage could serve as a breath of fresh air for urban environments, paving the way for improved public health and environmental quality. It's time to extinguish the misconceptions and ignite a new understanding of the impactful role of kerosene in urban air pollution.

The significant statistical association we've uncovered is as solid as a well-constructed chimney – with a p-value of less than 0.01, this connection between air pollution and kerosene consumption is no mirage in the desert of data analysis. It's time to stop fanning the flames of uncertainty and embrace the clarity of our findings.

Our study not only fills a gap in the literature but also sparks the flame of curiosity for further research in this domain. It's time to give this topic the warm embrace of scholarly attention. On a lighter note, it appears that the connection between air pollution and kerosene consumption is as strong as the adhesive on a "No Smoking" sign in a fireworks factory!

In summary, our findings make a compelling case for the intertwined nature of air pollution and kerosene usage, emphasizing the need for targeted interventions to improve urban air quality. It's time to clear the air about the role of kerosene in pollution and usher in a new era of cleaner, healthier skies. This study represents a gust of fresh air in the world of environmental research, and it's time to close the window on further investigation. No more research is needed in this area.

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited Up in Smoke: Uncovering the Relationship Between Air Pollution in Minneapolis and Kerosene Consumption in the United States. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Ecological Entanglements

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Up in Smoke: Uncovering the Relationship Between Air Pollution in Minneapolis and Kerosene Consumption in the United States. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Ecological Air and Kerosene Studies (SEAKS)

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Up in Smoke: Uncovering the Relationship Between Air Pollution in Minneapolis and Kerosene Consumption in the United States with an abstract of This paper investigates the link between air pollution levels in Minneapolis and kerosene usage in the United States over the span of 1980 to 2022, utilizing data from the Environmental Protection Agency and the Energy Information Administration. Our analysis reveals a striking correlation coefficient of 0.8414787 and p < 0.01, indicating a robust connection between these two variables.
Like a stubborn smog cloud, the relationship between air pollution and kerosene consumption has been shrouded in mystery. However, our research sheds light on this puzzling link and uncovers evidence that leaves no room for doubt. It's as clear as the air in a post-thunderstorm sky!
The findings of this study have significant implications for environmental policy and energy regulation, suggesting that reductions in kerosene usage could lead to improvements in air quality in urban areas such as Minneapolis. It's time to stop fueling the fire of pollution and ignite a cleaner, greener future.
In conclusion, our research not only establishes a strong statistical connection between air pollution in Minneapolis and kerosene consumption in the United States but also showcases the power of data analysis in unraveling complex environmental phenomena. This study is a breath of fresh air in the realm of environmental research, and it's sure to spark further investigation into the interplay between energy usage and air quality.

ChatGPT:

air pollution, kerosene consumption, Minneapolis, United States, Environmental Protection Agency, Energy Information Administration, correlation coefficient, environmental policy, energy regulation, urban areas, data analysis, environmental research

*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 Minneapolis
Detailed data title: Percentage of days with air quality at 'unhealthy for sensitive groups' or worse in Minneapolis-St. Paul-Bloomington, MN-WI
Source: Environmental Protection Agency
See what else correlates with Air pollution in Minneapolis

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

Correlation r = 0.8414787 (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 = 0.7080863 (Coefficient of determination)
This means 70.8% of the change in the one variable (i.e., Kerosene used in United States) is predictable based on the change in the other (i.e., Air pollution in Minneapolis) over the 43 years from 1980 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.6E-12.^Show 0.0000000000015903752215725854
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.84 in 1.6E-10% of random cases. Said differently, if you correlated 628,782,432,243 random variables^Note You don't actually need 628 billion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

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

[ 0.72, 0.91 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

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

	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 Minneapolis (Bad air quality days)	13.6612	12.0548	9.58904	17.5342	8.19672	7.94521	4.65753	9.86301	15.847	9.0411	3.0137	3.56164	3.55191	1.09589	2.73973	9.0411	2.45902	2.46575	3.0137	4.65753	6.55738	7.67123	4.65753	6.30137	2.45902	6.30137	2.73973	3.56164	1.0929	2.46575	3.28767	0.821918	2.18579	0.821918	0.547945	1.64384	1.0929	0.273973	1.36986	0.273973	0.819672	2.19178	0
Kerosene used in United States (Million Barrels/Day)	158	126.882	128.559	127.008	115.123	113.836	98.3589	94.5699	96.1175	84.1425	42.5671	46.3699	41.4235	49.6466	49.0329	54.063	61.7896	66.0301	78.0986	73.1123	67.3279	72.2904	43.3479	54.6274	64.2951	69.8083	53.6826	32.1391	14.2286	17.5474	19.9292	12.2408	5.27591	5.19713	8.99604	6.38585	8.67062	5.17747	5.41261	6.77142	7.49362	5.94343	5.25028

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([13.6612,12.0548,9.58904,17.5342,8.19672,7.94521,4.65753,9.86301,15.847,9.0411,3.0137,3.56164,3.55191,1.09589,2.73973,9.0411,2.45902,2.46575,3.0137,4.65753,6.55738,7.67123,4.65753,6.30137,2.45902,6.30137,2.73973,3.56164,1.0929,2.46575,3.28767,0.821918,2.18579,0.821918,0.547945,1.64384,1.0929,0.273973,1.36986,0.273973,0.819672,2.19178,0,])
array_2 = np.array([158,126.882,128.559,127.008,115.123,113.836,98.3589,94.5699,96.1175,84.1425,42.5671,46.3699,41.4235,49.6466,49.0329,54.063,61.7896,66.0301,78.0986,73.1123,67.3279,72.2904,43.3479,54.6274,64.2951,69.8083,53.6826,32.1391,14.2286,17.5474,19.9292,12.2408,5.27591,5.19713,8.99604,6.38585,8.67062,5.17747,5.41261,6.77142,7.49362,5.94343,5.25028,])
array_1_name = "Air pollution in Minneapolis"
array_2_name = "Kerosene used in United States"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Air pollution in Minneapolis
Line chart for only Kerosene used in United States
AI-generated correlation image
The spurious research paper: Up in Smoke: Uncovering the Relationship Between Air Pollution in Minneapolis and Kerosene Consumption in the United States

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Correlation ID: 2893 · Black Variable ID: 20906 · Red Variable ID: 25053


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