Spurious correlation #2,221 · 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 Des Moines and the second variable is Arson in Iowa. The chart goes from 2001 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 Des Moines and the second variable is Arson in Iowa. The chart goes from 2001 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the air quality improved, it became easier for the arsonists to just take a deep breath and let go of their fiery tendencies. With cleaner air, they found more peaceful ways to ignite their passions, like taking up hot yoga or participating in intense marshmallow roasting competitions. The arson rate simply couldn't keep smoldering in such pristine atmospheric conditions!

^{Show image generation prompt} Model: dalle-3
Prompt: Prompt: Generate an image using [ Charcoal ] that illustrates a hazy, smoke-filled cityscape of Des Moines, with a building engulfed in flames as emergency vehicles rush in. The scene should capture the tense atmosphere as firefighters struggle to contain the arson-caused blaze, amidst the murky, smoky air. The focus should be on the contrast between the dark, thick smoke and the bright, fiery flames. 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: Less than ideal air quality in Des Moines and Arson in Iowa. 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: Concept art Brutalism Charcoal inspired by bauhaus Voxel art
ChatGPT: Charcoal

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 Less than ideal air quality in Des Moines and Arson in Iowa together. Keep the description simple.
ChatGPT: In Des Moines, a hazy sky hangs over the city, with the scent of smoke lingering in the air. Emergency vehicles rush to the scene of a building engulfed in flames. The murky air exacerbates the situation as firefighters work to contain the blaze caused by arson.

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: [ Charcoal ] and depicting this scene: In Des Moines, a hazy sky hangs over the city, with the scent of smoke lingering in the air. Emergency vehicles rush to the scene of a building engulfed in flames. The murky air exacerbates the situation as firefighters work to contain the blaze caused by arson. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image using [ Charcoal ] that illustrates a hazy, smoke-filled cityscape of Des Moines, with a building engulfed in flames as emergency vehicles rush in. The scene should capture the tense atmosphere as firefighters struggle to contain the arson-caused blaze, amidst the murky, smoky air. The focus should be on the contrast between the dark, thick smoke and the bright, fiery flames.

*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 Des Moines caused Arson in Iowa to decrease. Make it feel plausible.

AI academic paper

(Because p < 0.01)

Fanning the Flames: The Smoky Link Between Air Pollution in Des Moines and Arson in Iowa

The Journal of Environmental Criminology and Atmospheric Chemistry

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 Des Moines and Arson in Iowa. Make lots of jokes, goofy observations, and puns.

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 devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading CVS receipts.

Here is the title and abstract of the paper:
[[TITLE]]
Fanning the Flames: The Smoky Link Between Air Pollution in Des Moines and Arson in Iowa

[[ABSTRACT]]
This study examines the relationship between air pollution in Des Moines and arson in Iowa, seeking to shed light on the fiery connection between these two apparently unrelated phenomena. Using data from the Environmental Protection Agency and FBI Criminal Justice Information Services from 2001 to 2022, a strong correlation coefficient of 0.8330212 was found, with a p-value less than 0.01, indicating a statistically significant association. The implications of these findings are far-reaching, suggesting that air pollution may not only affect public health but also have unintended consequences for fire-related incidents. The results highlight the need for further investigation into the potential impact of air quality on fire behavior and the formulation of more incendiary environmental policies.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The old adage "where there's smoke, there's fire" takes on a whole new meaning in the context of our research. While most people might not immediately connect air pollution and arson, our study aims to bridge the gap between these two fiery phenomena.
Picture this: a lone arsonist, strolling through the smog-filled streets of Des Moines, feeling the heat of the polluted air and thinking, "You know what would complement this toxic atmosphere? A good old-fashioned fire." While the scenario might sound like the start of a quirky crime novel, our research takes a more academic approach to explore the potential link between air pollution and arson in Iowa.
As we delve into this unconventional connection, it's vital to acknowledge the inherent complexity of both air quality and fire-related incidents. On the one hand, air pollution in urban areas like Des Moines has been a pressing concern, with its own set of respiratory hazards and environmental repercussions. On the other hand, arson, with its mysterious allure and destructive potential, has long captured the imagination of both researchers and Hollywood scriptwriters.
In an unexpected turn of events, our investigation uncovers a correlation between air pollution levels and arson incidents that is as clear as day - or as murky as smoke, depending on how you look at it. The statistical analysis of data from the Environmental Protection Agency and FBI Criminal Justice Information Services reveals a correlation coefficient that even arsonists would find "hot" – a scorching 0.8330212, coupled with a p-value less than 0.01, signaling a fiery, statistically significant association.
The implications of these fiery findings extend far beyond the research lab and into the very fabric of urban safety and environmental policy. It appears that the impact of air quality reaches further than just our lungs, crawling its way into the realm of unexpected fire-starters. With these sparks of insight in mind, our study ignites the need for further investigation into the potential interplay between air pollution and fire behavior, casting a spotlight on the formulation of more "incendiary" environmental policies.
Join us as we sift through the ashes of conventional wisdom and ignite a discussion that will leave you pondering the power of the flame, both literal and metaphorical. Buckle up, because this is going to be one smokin' ride through the world of unexpected connections and burning questions.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The relationship between air pollution and arson has not been extensively studied in the scholarly literature. However, a number of pertinent studies have shed light on the separate phenomena of air pollution and arson. Smith et al. (2015) conducted a comprehensive analysis of air quality in urban areas, highlighting the detrimental effects of particulate matter and volatile organic compounds. Doe and Jones (2017) examined the patterns of arson incidents across various regions, uncovering sociodemographic and environmental factors that may influence the incidence of arson.

Turning to non-fiction literature, "The Air Pollution Crisis: Causes, Consequences, and Solutions" by Environmental Scientist discusses the chronic issue of air pollution and its multifaceted ramifications. Additionally, "Pyromania: Understanding the Mind of an Arsonist" by Forensic Psychologist delves into the psychology behind arson, offering insights into the motivations and behaviors of arsonists.

In the realm of fiction, "Smoke and Mirrors: A Detective Mystery" by Crime Novelist weaves a tale of intrigue and deception, centering on a series of perplexing arson cases in a polluted metropolis. Similarly, "Toxic Inferno: A Thriller Novel" by Bestselling Author captivates readers with a gripping narrative of environmental sabotage and fiery subterfuge.

Expanding the scope of the literature review, miscellaneous sources including obscure pamphlets, accidental recipe books for homemade smoke signals, and discarded grocery lists found at the local bodega have been considered. The analysis of various unconventional sources has provided a broader perspective on the potential interplay between air pollution and arson, albeit with a touch of absurdity.

In summary, while the existing literature offers valuable insights into air pollution and arson from a scientific and cultural standpoint, there remains a notable gap in research pertaining to the connection between these phenomena. This study seeks to address this gap and contribute to a more comprehensive understanding of the fiery relationship between air pollution in Des Moines and arson in Iowa.

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 Des Moines and Arson in Iowa. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and FBI Criminal Justice Information Services . You used data from 2001 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]]
Fanning the Flames: The Smoky Link Between Air Pollution in Des Moines and Arson in Iowa

[[ABSTRACT]]
This study examines the relationship between air pollution in Des Moines and arson in Iowa, seeking to shed light on the fiery connection between these two apparently unrelated phenomena. Using data from the Environmental Protection Agency and FBI Criminal Justice Information Services from 2001 to 2022, a strong correlation coefficient of 0.8330212 was found, with a p-value less than 0.01, indicating a statistically significant association. The implications of these findings are far-reaching, suggesting that air pollution may not only affect public health but also have unintended consequences for fire-related incidents. The results highlight the need for further investigation into the potential impact of air quality on fire behavior and the formulation of more incendiary environmental policies.

[[INTRODUCTION]]
The old adage "where there's smoke, there's fire" takes on a whole new meaning in the context of our research. While most people might not immediately connect air pollution and arson, our study aims to bridge the gap between these two fiery phenomena.
Picture this: a lone arsonist, strolling through the smog-filled streets of Des Moines, feeling the heat of the polluted air and thinking, "You know what would complement this toxic atmosphere? A good old-fashioned fire." While the scenario might sound like the start of a quirky crime novel, our research takes a more academic approach to explore the potential link between air pollution and arson in Iowa.
As we delve into this unconventional connection, it's vital to acknowledge the inherent complexity of both air quality and fire-related incidents. On the one hand, air pollution in urban areas like Des Moines has been a pressing concern, with its own set of respiratory hazards and environmental repercussions. On the other hand, arson, with its mysterious allure and destructive potential, has long captured the imagination of both researchers and Hollywood scriptwriters.
In an unexpected turn of events, our investigation uncovers a correlation between air pollution levels and arson incidents that is as clear as day - or as murky as smoke, depending on how you look at it. The statistical analysis of data from the Environmental Protection Agency and FBI Criminal Justice Information Services reveals a correlation coefficient that even arsonists would find "hot" – a scorching 0.8330212, coupled with a p-value less than 0.01, signaling a fiery, statistically significant association.
The implications of these fiery findings extend far beyond the research lab and into the very fabric of urban safety and environmental policy. It appears that the impact of air quality reaches further than just our lungs, crawling its way into the realm of unexpected fire-starters. With these sparks of insight in mind, our study ignites the need for further investigation into the potential interplay between air pollution and fire behavior, casting a spotlight on the formulation of more "incendiary" environmental policies.
Join us as we sift through the ashes of conventional wisdom and ignite a discussion that will leave you pondering the power of the flame, both literal and metaphorical. Buckle up, because this is going to be one smokin' ride through the world of unexpected connections and burning questions.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

The methodology employed in this study aimed to illuminate the fiery linkage between air pollution in Des Moines and arson in Iowa by employing a multi-pronged approach. The data collection process involved mining information from the Environmental Protection Agency (EPA) and FBI Criminal Justice Information Services. The data from these sources spanned the years 2001 to 2022, providing a robust timeframe for analysis.

To establish the levels of air pollution in Des Moines, the EPA's Air Quality System (AQS) database served as the primary source. This comprehensive database compiles air quality monitoring data from thousands of stations across the United States, offering a wealth of information regarding airborne particulate matter, volatile organic compounds, and various other pollutants that paint the city's air in shades of concern.

Concurrently, to capture the incidence of arson in Iowa, data from the FBI's Uniform Crime Reporting (UCR) Program was utilized. This repository of crime data offers a window into the prevalence of arson incidents, allowing for the quantification of its correlation with air pollution levels.

Once the data was curated and cleansed, statistical analyses were applied to ascertain the degree of association between these seemingly incongruous elements. The correlation coefficient was calculated, yielding a scorching value of 0.8330212, indicative of a compelling relationship. Furthermore, the p-value, swooping in at less than 0.01, lent statistical credence to the observed association, dissipating any lingering doubts about its significance.

In a nod to the unconventional nature of our investigation, the team also ventured into the realm of qualitative analysis. Anecdotal evidence and expert opinions from firefighters and environmental policymakers were sought, allowing for a more nuanced understanding of the potential mechanisms underpinning the observed correlation. Their perspectives added a layer of depth to our findings, akin to stoking the embers of knowledge and kindling new insights into this unexplored nexus.

While this methodology may appear lighthearted in its exposition, the approach was underpinned by rigor, precision, and a burning desire to unravel the enigmatic intertwining of air pollution and arson. Through this methodical examination, the findings presented herein bear the hallmark of scholarly inquiry, albeit flavored with a tinge of irreverence for the unexpected detours in the pursuit of knowledge.

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 Des Moines and Arson in Iowa. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and FBI Criminal Justice Information Services .

For the time period 2001 to 2022, you found a correlation 0.8330212, r-squared of 0.6939243, 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]]
Fanning the Flames: The Smoky Link Between Air Pollution in Des Moines and Arson in Iowa

[[ABSTRACT]]
This study examines the relationship between air pollution in Des Moines and arson in Iowa, seeking to shed light on the fiery connection between these two apparently unrelated phenomena. Using data from the Environmental Protection Agency and FBI Criminal Justice Information Services from 2001 to 2022, a strong correlation coefficient of 0.8330212 was found, with a p-value less than 0.01, indicating a statistically significant association. The implications of these findings are far-reaching, suggesting that air pollution may not only affect public health but also have unintended consequences for fire-related incidents. The results highlight the need for further investigation into the potential impact of air quality on fire behavior and the formulation of more incendiary environmental policies.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The old adage "where there's smoke, there's fire" takes on a whole new meaning in the context of our research. While most people might not immediately connect air pollution and arson, our study aims to bridge the gap between these two fiery phenomena.
Picture this: a lone arsonist, strolling through the smog-filled streets of Des Moines, feeling the heat of the polluted air and thinking, "You know what would complement this toxic atmosphere? A good old-fashioned fire." While the scenario might sound like the start of a quirky crime novel, our research takes a more academic approach to explore the potential link between air pollution and arson in Iowa.
As we delve into this unconventional connection, it's vital to acknowledge the inherent complexity of both air quality and fire-related incidents. On the one hand, air pollution in urban areas like Des Moines has been a pressing concern, with its own set of respiratory hazards and environmental repercussions. On the other hand, arson, with its mysterious allure and destructive potential, has long captured the imagination of both researchers and Hollywood scriptwriters.
In an unexpected turn of events, our investigation uncovers a correlation between air pollution levels and arson incidents that is as clear as day - or as murky as smoke, depending on how you look at it. The statistical analysis of data from the Environmental Protection Agency and FBI Criminal Justice Information Services reveals a correlation coefficient that even arsonists would find "hot" – a scorching 0.8330212, coupled with a p-value less than 0.01, signaling a fiery, statistically significant association.
The implications of these fiery findings extend far beyond the research lab and into the very fabric of urban safety and environmental policy. It appears that the impact of air quality reaches further than just our lungs, crawling its way into the realm of unexpected fire-starters. With these sparks of insight in mind, our study ignites the need for further investigation into the potential interplay between air pollution and fire behavior, casting a spotlight on the formulation of more "incendiary" environmental policies.
Join us as we sift through the ashes of conventional wisdom and ignite a discussion that will leave you pondering the power of the flame, both literal and metaphorical. Buckle up, because this is going to be one smokin' ride through the world of unexpected connections and burning questions.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The statistical analysis of the data collected revealed a striking correlation coefficient of 0.8330212 between air pollution in Des Moines and arson incidents in Iowa from 2001 to 2022. This strong correlation was supported by an r-squared value of 0.6939243, indicating that approximately 69.4% of the variability in arson incidents can be explained by variations in air pollution levels. Furthermore, the p-value being less than 0.01 demonstrates a statistically significant association between the two variables.

In order to illustrate the robust relationship uncovered by the data, a scatterplot (Fig. 1) was constructed to visually depict the positive correlation between air pollution and arson incidents. The figure showcases the steady increase in arson occurrences as air pollution levels rise, painting a vivid picture of the smoky link between these two seemingly unrelated phenomena.

These findings not only add fuel to the fire of scientific inquiry but also kindle a deeper understanding of the potential impact of air quality on fire-related incidents. The results of this study may spark further research into the intricate interplay between environmental factors and human behavior, shedding light on the unexpected and provocative connections between air pollution and arson.

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 Des Moines and Arson in Iowa. Make lots of jokes, goofy observations, and puns.

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]]
Fanning the Flames: The Smoky Link Between Air Pollution in Des Moines and Arson in Iowa

[[ABSTRACT]]
This study examines the relationship between air pollution in Des Moines and arson in Iowa, seeking to shed light on the fiery connection between these two apparently unrelated phenomena. Using data from the Environmental Protection Agency and FBI Criminal Justice Information Services from 2001 to 2022, a strong correlation coefficient of 0.8330212 was found, with a p-value less than 0.01, indicating a statistically significant association. The implications of these findings are far-reaching, suggesting that air pollution may not only affect public health but also have unintended consequences for fire-related incidents. The results highlight the need for further investigation into the potential impact of air quality on fire behavior and the formulation of more incendiary environmental policies.

[[LITERATURE REVIEW]]
The relationship between air pollution and arson has not been extensively studied in the scholarly literature. However, a number of pertinent studies have shed light on the separate phenomena of air pollution and arson. Smith et al. (2015) conducted a comprehensive analysis of air quality in urban areas, highlighting the detrimental effects of particulate matter and volatile organic compounds. Doe and Jones (2017) examined the patterns of arson incidents across various regions, uncovering sociodemographic and environmental factors that may influence the incidence of arson.
Turning to non-fiction literature, "The Air Pollution Crisis: Causes, Consequences, and Solutions" by Environmental Scientist discusses the chronic issue of air pollution and its multifaceted ramifications. Additionally, "Pyromania: Understanding the Mind of an Arsonist" by Forensic Psychologist delves into the psychology behind arson, offering insights into the motivations and behaviors of arsonists.
In the realm of fiction, "Smoke and Mirrors: A Detective Mystery" by Crime Novelist weaves a tale of intrigue and deception, centering on a series of perplexing arson cases in a polluted metropolis. Similarly, "Toxic Inferno: A Thriller Novel" by Bestselling Author captivates readers with a gripping narrative of environmental sabotage and fiery subterfuge.
Expanding the scope of the literature review, miscellaneous sources including obscure pamphlets, accidental recipe books for homemade smoke signals, and discarded grocery lists found at the local bodega have been considered. The analysis of various unconventional sources has provided a broader perspective on the potential interplay between air pollution and arson, albeit with a touch of absurdity.
In summary, while the existing literature offers valuable insights into air pollution and arson from a scientific and cultural standpoint, there remains a notable gap in research pertaining to the connection between these phenomena. This study seeks to address this gap and contribute to a more comprehensive understanding of the fiery relationship between air pollution in Des Moines and arson in Iowa.

[[RESULTS]]
The statistical analysis of the data collected revealed a striking correlation coefficient of 0.8330212 between air pollution in Des Moines and arson incidents in Iowa from 2001 to 2022. This strong correlation was supported by an r-squared value of 0.6939243, indicating that approximately 69.4% of the variability in arson incidents can be explained by variations in air pollution levels. Furthermore, the p-value being less than 0.01 demonstrates a statistically significant association between the two variables.
In order to illustrate the robust relationship uncovered by the data, a scatterplot (Fig. 1) was constructed to visually depict the positive correlation between air pollution and arson incidents. The figure showcases the steady increase in arson occurrences as air pollution levels rise, painting a vivid picture of the smoky link between these two seemingly unrelated phenomena.
These findings not only add fuel to the fire of scientific inquiry but also kindle a deeper understanding of the potential impact of air quality on fire-related incidents. The results of this study may spark further research into the intricate interplay between environmental factors and human behavior, shedding light on the unexpected and provocative connections between air pollution and arson.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of this study provide compelling evidence for the existence of a robust association between air pollution in Des Moines and arson incidents in Iowa. These results not only fan the flames of curiosity but also kindle a deeper appreciation for the smoky link between environmental factors and fire-related behavior.

The statistical correlation coefficient of 0.8330212 is no mere fleeting spark; it is a blazing indication of the substantial relationship between air pollution and arson. This result aligns with the work of Smith et al. (2015), who highlighted the detrimental effects of particulate matter, and coincidentally, the rising temperatures resulting from arson. Doe and Jones (2017) also shed light on the sociodemographic and environmental factors influencing arson incidents, which may be exacerbated by poor air quality, further adding to the tinderbox of evidence supporting our findings.

The r-squared value of 0.6939243 indicates that approximately 69.4% of the variability in arson incidents can be explained by variations in air pollution levels. This suggests that while air pollution may not be the sole match lighting the fires of arson, it certainly contributes significantly to the heat of the issue, as highlighted in the literary work "Smoke and Mirrors: A Detective Mystery" by Crime Novelist, albeit in a more metaphorical sense.

Furthermore, the statistically significant association revealed by a p-value of less than 0.01 is a spark of hope for further investigation into the potential impact of air quality on fire behavior. Such findings not only ignite the flames of scientific curiosity but also shed light on the unexpected and provocative connections between air pollution and arson, much like a thrilling chapter from "Toxic Inferno: A Thriller Novel" by Bestselling Author.

This data-driven study not only adds fuel to the fire of scientific inquiry but also underscores the need for more incendiary environmental policies. It ignites the discussion on the multifaceted ramifications of air pollution, extending far beyond public health to encompass the potential unintended consequences for fire-related incidents. These results offer a compelling argument for policymakers to stoke the flames of environmental protection, recognizing the fiery implications of air quality on arson incidents.

In conclusion, the findings of this study not only illuminate the smoky link between air pollution in Des Moines and arson in Iowa, but also ignite a passion for further investigation into the interplay between environmental factors and fire-related behavior. The potential impact of air quality on arson incidents cannot be extinguished, and it is imperative to fan the flames of research in this domain to fully grasp the fiery connection between these seemingly unrelated phenomena.

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 Des Moines and Arson in Iowa. Make lots of jokes, goofy observations, and puns.

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]]
Fanning the Flames: The Smoky Link Between Air Pollution in Des Moines and Arson in Iowa

[[ABSTRACT]]
This study examines the relationship between air pollution in Des Moines and arson in Iowa, seeking to shed light on the fiery connection between these two apparently unrelated phenomena. Using data from the Environmental Protection Agency and FBI Criminal Justice Information Services from 2001 to 2022, a strong correlation coefficient of 0.8330212 was found, with a p-value less than 0.01, indicating a statistically significant association. The implications of these findings are far-reaching, suggesting that air pollution may not only affect public health but also have unintended consequences for fire-related incidents. The results highlight the need for further investigation into the potential impact of air quality on fire behavior and the formulation of more incendiary environmental policies.

[[INTRDUCTION]]
The old adage "where there's smoke, there's fire" takes on a whole new meaning in the context of our research. While most people might not immediately connect air pollution and arson, our study aims to bridge the gap between these two fiery phenomena.
Picture this: a lone arsonist, strolling through the smog-filled streets of Des Moines, feeling the heat of the polluted air and thinking, "You know what would complement this toxic atmosphere? A good old-fashioned fire." While the scenario might sound like the start of a quirky crime novel, our research takes a more academic approach to explore the potential link between air pollution and arson in Iowa.
As we delve into this unconventional connection, it's vital to acknowledge the inherent complexity of both air quality and fire-related incidents. On the one hand, air pollution in urban areas like Des Moines has been a pressing concern, with its own set of respiratory hazards and environmental repercussions. On the other hand, arson, with its mysterious allure and destructive potential, has long captured the imagination of both researchers and Hollywood scriptwriters.
In an unexpected turn of events, our investigation uncovers a correlation between air pollution levels and arson incidents that is as clear as day - or as murky as smoke, depending on how you look at it. The statistical analysis of data from the Environmental Protection Agency and FBI Criminal Justice Information Services reveals a correlation coefficient that even arsonists would find "hot" – a scorching 0.8330212, coupled with a p-value less than 0.01, signaling a fiery, statistically significant association.
The implications of these fiery findings extend far beyond the research lab and into the very fabric of urban safety and environmental policy. It appears that the impact of air quality reaches further than just our lungs, crawling its way into the realm of unexpected fire-starters. With these sparks of insight in mind, our study ignites the need for further investigation into the potential interplay between air pollution and fire behavior, casting a spotlight on the formulation of more "incendiary" environmental policies.
Join us as we sift through the ashes of conventional wisdom and ignite a discussion that will leave you pondering the power of the flame, both literal and metaphorical. Buckle up, because this is going to be one smokin' ride through the world of unexpected connections and burning questions.

[[RESULTS]]
The statistical analysis of the data collected revealed a striking correlation coefficient of 0.8330212 between air pollution in Des Moines and arson incidents in Iowa from 2001 to 2022. This strong correlation was supported by an r-squared value of 0.6939243, indicating that approximately 69.4% of the variability in arson incidents can be explained by variations in air pollution levels. Furthermore, the p-value being less than 0.01 demonstrates a statistically significant association between the two variables.
In order to illustrate the robust relationship uncovered by the data, a scatterplot (Fig. 1) was constructed to visually depict the positive correlation between air pollution and arson incidents. The figure showcases the steady increase in arson occurrences as air pollution levels rise, painting a vivid picture of the smoky link between these two seemingly unrelated phenomena.
These findings not only add fuel to the fire of scientific inquiry but also kindle a deeper understanding of the potential impact of air quality on fire-related incidents. The results of this study may spark further research into the intricate interplay between environmental factors and human behavior, shedding light on the unexpected and provocative connections between air pollution and arson.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has revealed a scorching correlation between air pollution in Des Moines and arson incidents in Iowa, illuminating a surprising link that begs the question: is there fire where there's pollution, or is there pollution where there's fire? This unanticipated connection has set the research world ablaze, challenging traditional notions of causality and raising eyebrows as well as temperatures.

From a practical standpoint, these findings have implications for both public safety and environmental policy. It seems that clean air isn't just about breathing easy; it's also about reducing the temptation to play with fire. The potential impact of air quality on fire-related incidents is not something to be brushed aside or swept under the rug - especially if that rug ends up becoming kindling.

The implications of these results extend beyond the world of academia and research, presenting a burning platform for policymakers to consider when formulating environmental regulations. Perhaps it's time for urban planners to not only address air pollution but also throw some shade on potential arson hotspots.

In the immortal words of Smokey Bear, "Only you can prevent forest fires," and by extension, perhaps only we can prevent arson by keeping the air clean. With these insights in mind, we hope that this study ignites a fiery conversation that leads to more "smoke-free" urban environments and policies.

In the words of the great philosopher Ricky Martin, "She's into superstitions, black cats, and voodoo dolls," but let's not add arson to that list. Therefore, based on the scorching evidence presented, we assert that no further research is needed in this fiery field.

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 Fanning the Flames: The Smoky Link Between Air Pollution in Des Moines and Arson in Iowa. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Environmental Criminology and Atmospheric Chemistry

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 Fanning the Flames: The Smoky Link Between Air Pollution in Des Moines and Arson in Iowa. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Environmental Analysis and Wacky Correlations

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 Fanning the Flames: The Smoky Link Between Air Pollution in Des Moines and Arson in Iowa with an abstract of This study examines the relationship between air pollution in Des Moines and arson in Iowa, seeking to shed light on the fiery connection between these two apparently unrelated phenomena. Using data from the Environmental Protection Agency and FBI Criminal Justice Information Services from 2001 to 2022, a strong correlation coefficient of 0.8330212 was found, with a p-value less than 0.01, indicating a statistically significant association. The implications of these findings are far-reaching, suggesting that air pollution may not only affect public health but also have unintended consequences for fire-related incidents. The results highlight the need for further investigation into the potential impact of air quality on fire behavior and the formulation of more incendiary environmental policies.

ChatGPT:

air pollution, arson, Des Moines, Iowa, correlation, Environmental Protection Agency, FBI Criminal Justice Information Services, fire-related incidents, air quality, environmental policies

*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 Des Moines
Detailed data title: Percentage of days with moderate or worse air quality in Des Moines-West Des Moines, IA
Source: Environmental Protection Agency
See what else correlates with Air pollution in Des Moines

Arson in Iowa
Detailed data title: The arson rate per 100,000 residents in Iowa
Source: FBI Criminal Justice Information Services
See what else correlates with Arson in Iowa

Correlation r = 0.8330212 (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 = 0.6939243 (Coefficient of determination)
This means 69.4% of the change in the one variable (i.e., Arson in Iowa) is predictable based on the change in the other (i.e., Air pollution in Des Moines) over the 22 years from 2001 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.5E-6.^Show 0.0000014972272061760436000000
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 0.83 in 0.00015% of random cases. Said differently, if you correlated 667,901 random variables^Note You don't actually need 667 thousand 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 21 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 21 because we have two variables measured over a period of 22 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.

[ 0.63, 0.93 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

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

	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 Des Moines (Bad air quality days)	38.6301	35.0685	36.4384	29.235	39.726	29.3151	38.0822	36.612	29.0411	32.8767	31.7808	34.9727	28.7671	21.9178	19.1781	14.7541	20	22.1918	16.1644	15.847	22.1918	12.6027
Arson in Iowa (Arson rate)	20.8	21.8	20.8	21.5	20.1	23.9	21.3	20.1	18.7	15.9	16.9	18	14.8	13	14.1	12	13.5	9.5	11	13.3	10.4	7.9

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([38.6301,35.0685,36.4384,29.235,39.726,29.3151,38.0822,36.612,29.0411,32.8767,31.7808,34.9727,28.7671,21.9178,19.1781,14.7541,20,22.1918,16.1644,15.847,22.1918,12.6027,])
array_2 = np.array([20.8,21.8,20.8,21.5,20.1,23.9,21.3,20.1,18.7,15.9,16.9,18,14.8,13,14.1,12,13.5,9.5,11,13.3,10.4,7.9,])
array_1_name = "Air pollution in Des Moines"
array_2_name = "Arson in Iowa"

# 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 Des Moines
Line chart for only Arson in Iowa
AI-generated correlation image
The spurious research paper: Fanning the Flames: The Smoky Link Between Air Pollution in Des Moines and Arson in Iowa

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Correlation ID: 2221 · Black Variable ID: 20545 · Red Variable ID: 20043


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