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AI explanation
As air pollution decreased in St. Marys, Pennsylvania, the smog particles that were once the arsonist's accomplices dispersed, leaving would-be fires high and dry. With their usual partners in crime nowhere to be found, arson rates across the United States simply went up in smoke. It seems that for these fire-starters, the polluted air was their fuel, and without it, their fiery shenanigans just couldn't catch on. Who would have thought that cleaning up the air in one small town could have such a *blazing* impact nationwide?
Model: dalle-3
Prompt: Generate an image of a low-polygonal scene in St. Marys, Pennsylvania, with buildings and streets. The town should be transitioning from a polluted, smog-covered atmosphere to clear, blue skies. Show the dispersion of smog particles and the disappearance of shadowy figures who represent the would-be arsonist's accomplices. The image should also suggest a decrease in arson rates across the United States due to the absence of their natural partners in crime, as the polluted air, their potential fuel, is no longer present. 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 St. Marys, Pennsylvania and Arson 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: Cutsy art illustration Low poly inspired by bauhaus Celtic art inspired by bauhaus
ChatGPT: Low poly
Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Air pollution in St. Marys, Pennsylvania and Arson in United States, in the following situation: As air pollution decreased in St. Marys, Pennsylvania, the smog particles that were once the arsonist's accomplices dispersed, leaving would-be fires high and dry. With their usual partners in crime nowhere to be found, arson rates across the United States simply went up in smoke. It seems that for these fire-starters, the polluted air was their fuel, and without it, their fiery shenanigans just couldn't catch on. Who would have thought that cleaning up the air in one small town could have such a *blazing* impact nationwide?. Keep the description simple.
ChatGPT: In St. Marys, Pennsylvania, as the air pollution decreased, the once thick smog particles that enveloped the town dispersed. The clear skies and fresh air made the would-be arsonist's accomplices disappear. Across the United States, without their natural partners in crime, the arson rates went up in smoke. It turns out, the polluted air was their fuel, and without it, their fiery shenanigans just couldn't catch on.
Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ Low poly ] and depicting this scene: In St. Marys, Pennsylvania, as the air pollution decreased, the once thick smog particles that enveloped the town dispersed. The clear skies and fresh air made the would-be arsonist's accomplices disappear. Across the United States, without their natural partners in crime, the arson rates went up in smoke. It turns out, the polluted air was their fuel, and without it, their fiery shenanigans just couldn't catch on. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a low-polygonal scene in St. Marys, Pennsylvania, with buildings and streets. The town should be transitioning from a polluted, smog-covered atmosphere to clear, blue skies. Show the dispersion of smog particles and the disappearance of shadowy figures who represent the would-be arsonist's accomplices. The image should also suggest a decrease in arson rates across the United States due to the absence of their natural partners in crime, as the polluted air, their potential fuel, is no longer present.
*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.
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 St. Marys, Pennsylvania caused Arson in United States to decrease.
AI academic paper
 |
Up in Smoke: Uncovering the Fiery Relationship Between Air Pollution in St. Marys, Pennsylvania, and Arson in the United States The Journal of Pyroclastic Studies Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You write titles and abstracts of goofy academic research papers.
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, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between Air pollution in St. Marys, Pennsylvania and Arson in United States. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Make the title punny if you can come up with clever pun. If not, make it sound serious.
Your research team used data from Environmental Protection Agency and FBI Criminal Justice Information Services to assess this nagging question. You found a correlation coefficient of 0.8640177 and p < 0.01 for 1990 to 2022.
Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)
[[TITLE]]
Lorem ipsum dolor sit
[[ABSTRACT]]
Lorem ipsum dolor sit
ChatGPT:
[[TITLE]]
Up in Smoke: Uncovering the Fiery Relationship Between Air Pollution in St. Marys, Pennsylvania, and Arson in the United States
[[ABSTRACT]]
This paper delves into the burning question of whether there is a connection between air pollution in St. Marys, Pennsylvania, and arson across the United States. Our research team utilized data from the Environmental Protection Agency and the FBI Criminal Justice Information Services to ignite an investigation into this smoky relationship. The findings revealed a striking correlation coefficient of 0.8640177 and p < 0.01 between air pollution levels in St. Marys and the incidence of arson from 1990 to 2022.
Our analysis not only sheds light on this fiery connection but also kindles a new perspective on environmental factors and criminal behavior. These findings ignite further research avenues and spark discussions on tackling both air pollution and arson. After all, as the saying goes, where there’s smoke, there’s fire – and where there’s correlation, there’s causation!
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the introduction 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 introduction section of an academic research paper presenting the findings of the connection between Air pollution in St. Marys, Pennsylvania and Arson in United States. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Here is the title and abstract of the paper:
[[TITLE]]
Up in Smoke: Uncovering the Fiery Relationship Between Air Pollution in St. Marys, Pennsylvania, and Arson in the United States
[[ABSTRACT]]
This paper delves into the burning question of whether there is a connection between air pollution in St. Marys, Pennsylvania, and arson across the United States. Our research team utilized data from the Environmental Protection Agency and the FBI Criminal Justice Information Services to ignite an investigation into this smoky relationship. The findings revealed a striking correlation coefficient of 0.8640177 and p < 0.01 between air pollution levels in St. Marys and the incidence of arson from 1990 to 2022.
Our analysis not only sheds light on this fiery connection but also kindles a new perspective on environmental factors and criminal behavior. These findings ignite further research avenues and spark discussions on tackling both air pollution and arson. After all, as the saying goes, where there’s smoke, there’s fire – and where there’s correlation, there’s causation!
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
The interaction between environmental factors and criminal behavior has long been a subject of intense scrutiny and speculation. One might say it's a burning issue with plenty of fuel for discussion. In recent years, researchers have increasingly turned their attention to the potential influence of air pollution on criminal activities, igniting curiosity about the potential connections between the two. Our research delves into this smoky landscape to uncover whether there is indeed a fiery relationship between air pollution in St. Marys, Pennsylvania, and the incidence of arson across the United States.
As the old saying goes, "Where there's smoke, there's fire." Well, in this case, we're not just blowing hot air – we've conducted a comprehensive investigation to shed light on whether the presence of smoke from industrial and vehicular sources in St. Marys is contributing to an increase in arson cases nationwide. Perhaps there's more to this saying than meets the eye – or should we say, the air quality index?
The prevalence of arson as a criminal activity raises important questions about its potential association with environmental factors such as air pollution. As researchers, we're eager to fan the flames of inquiry and uncover whether there's a substantial link between these two seemingly disparate phenomena. After all, determining causality in research can sometimes feel like trying to put out a wildfire with a handheld fan – but we're not afraid to tackle the heat.
Statistics have often been likened to a double-edged sword – they cut through the fog of uncertainty, but they can also lead us down a garden path if we're not careful. With this in mind, our analysis aims to offer a rigorous examination of the data, providing a clear and compelling picture of the relationship between air pollution in St. Marys and arson cases across the United States. We're not just blowing smoke – our findings are rooted in a robust statistical framework, ready to withstand the winds of skepticism.
This paper sets out to ignite discussions, spark further research endeavors, and fan the flames of curiosity within the academic and policy communities. Our aim is to not only present our findings but to kindle a new perspective on the complex interplay between environmental factors and criminal behavior. So, grab a seat by the fire – metaphorically speaking, of course – and let's delve into the smoldering connection between air pollution and arson. After all, what's research without a little heat?
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 St. Marys, Pennsylvania and Arson 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 name a couple popular internet memes that are related to one of the topics.
Here is the title and abstract of the paper:
[[TITLE]]
Up in Smoke: Uncovering the Fiery Relationship Between Air Pollution in St. Marys, Pennsylvania, and Arson in the United States
[[ABSTRACT]]
This paper delves into the burning question of whether there is a connection between air pollution in St. Marys, Pennsylvania, and arson across the United States. Our research team utilized data from the Environmental Protection Agency and the FBI Criminal Justice Information Services to ignite an investigation into this smoky relationship. The findings revealed a striking correlation coefficient of 0.8640177 and p < 0.01 between air pollution levels in St. Marys and the incidence of arson from 1990 to 2022.
Our analysis not only sheds light on this fiery connection but also kindles a new perspective on environmental factors and criminal behavior. These findings ignite further research avenues and spark discussions on tackling both air pollution and arson. After all, as the saying goes, where there’s smoke, there’s fire – and where there’s correlation, there’s causation!
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The interaction between environmental factors and criminal behavior has long been a subject of intense scrutiny and speculation. One might say it's a burning issue with plenty of fuel for discussion. In recent years, researchers have increasingly turned their attention to the potential influence of air pollution on criminal activities, igniting curiosity about the potential connections between the two. Our research delves into this smoky landscape to uncover whether there is indeed a fiery relationship between air pollution in St. Marys, Pennsylvania, and the incidence of arson across the United States.
As the old saying goes, "Where there's smoke, there's fire." Well, in this case, we're not just blowing hot air – we've conducted a comprehensive investigation to shed light on whether the presence of smoke from industrial and vehicular sources in St. Marys is contributing to an increase in arson cases nationwide. Perhaps there's more to this saying than meets the eye – or should we say, the air quality index?
The prevalence of arson as a criminal activity raises important questions about its potential association with environmental factors such as air pollution. As researchers, we're eager to fan the flames of inquiry and uncover whether there's a substantial link between these two seemingly disparate phenomena. After all, determining causality in research can sometimes feel like trying to put out a wildfire with a handheld fan – but we're not afraid to tackle the heat.
Statistics have often been likened to a double-edged sword – they cut through the fog of uncertainty, but they can also lead us down a garden path if we're not careful. With this in mind, our analysis aims to offer a rigorous examination of the data, providing a clear and compelling picture of the relationship between air pollution in St. Marys and arson cases across the United States. We're not just blowing smoke – our findings are rooted in a robust statistical framework, ready to withstand the winds of skepticism.
This paper sets out to ignite discussions, spark further research endeavors, and fan the flames of curiosity within the academic and policy communities. Our aim is to not only present our findings but to kindle a new perspective on the complex interplay between environmental factors and criminal behavior. So, grab a seat by the fire – metaphorically speaking, of course – and let's delve into the smoldering connection between air pollution and arson. After all, what's research without a little heat?
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
The existing body of literature on the relationship between air pollution and criminal activities provides a foundation for understanding the potential link between these two seemingly disparate phenomena. Smith et al. (2015) emphasize the importance of considering environmental factors in the examination of criminal behavior, highlighting the need to explore the influence of air quality on such activities. However, the burning question of whether air pollution serves as a contributing factor to arson across the United States has yet to be fully extinguished.
In "Doe and Jones' study," the authors find that air pollution levels in heavily industrialized areas have been associated with increased respiratory health problems and environmental degradation. However, the matchstick that ignites the link between these findings and the incidence of arson in the broader context of the United States remains elusive.
Turning to non-fiction works, "The Air Pollution Casebook" and "Criminal Minds: Environmental Edition" delve into the potential intersections of air quality and criminal behavior, providing comprehensive analyses that offer sparks of insight into the complex relationship between these two domains. However, these books fail to address the burning question at the heart of our investigation: does the smoke from St. Marys, Pennsylvania, possess the capacity to fan the flames of arson across the United States?
On a lighter note, figurative and fictional works such as "Smoke Signals: A Criminal Conspiracy" and "The Arsonist's Alibi" offer captivating narratives that add fuel to the fiery speculation surrounding the potential connection between air pollution and arson. Yet, amidst the smokescreen of creativity and imagination, the empirical evidence required to draw definitive conclusions remains absent.
Ah, the sweet smell of data analysis. In the realm of internet culture, the infamous "This is fine" meme depicts a dog calmly sipping coffee in a room engulfed in flames, humorously capturing the essence of our research journey as we navigate the heated discussion surrounding air pollution and arson. While such memes may provide a moment of levity, the underlying question persists: does the correlation between air pollution in St. Marys and arson in the United States warrant serious investigation, or is it merely a mirage in the hazy landscape of research inquiries?
As we kindle the flame of inquiry and navigate the intricate web of statistical analysis, it is crucial to approach this topic with both academic rigor and a touch of humor. After all, in the world of research, a well-placed dad joke can be the spark that ignites newfound curiosity and engagement. So, let's stoke the fires of investigation and embark on a quest to uncover the smoldering truth behind the connection between air pollution and arson.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 St. Marys, Pennsylvania and Arson in United States. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and FBI Criminal Justice Information Services . You used data from 1990 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 Fiery Relationship Between Air Pollution in St. Marys, Pennsylvania, and Arson in the United States
[[ABSTRACT]]
This paper delves into the burning question of whether there is a connection between air pollution in St. Marys, Pennsylvania, and arson across the United States. Our research team utilized data from the Environmental Protection Agency and the FBI Criminal Justice Information Services to ignite an investigation into this smoky relationship. The findings revealed a striking correlation coefficient of 0.8640177 and p < 0.01 between air pollution levels in St. Marys and the incidence of arson from 1990 to 2022.
Our analysis not only sheds light on this fiery connection but also kindles a new perspective on environmental factors and criminal behavior. These findings ignite further research avenues and spark discussions on tackling both air pollution and arson. After all, as the saying goes, where there’s smoke, there’s fire – and where there’s correlation, there’s causation!
[[INTRODUCTION]]
The interaction between environmental factors and criminal behavior has long been a subject of intense scrutiny and speculation. One might say it's a burning issue with plenty of fuel for discussion. In recent years, researchers have increasingly turned their attention to the potential influence of air pollution on criminal activities, igniting curiosity about the potential connections between the two. Our research delves into this smoky landscape to uncover whether there is indeed a fiery relationship between air pollution in St. Marys, Pennsylvania, and the incidence of arson across the United States.
As the old saying goes, "Where there's smoke, there's fire." Well, in this case, we're not just blowing hot air – we've conducted a comprehensive investigation to shed light on whether the presence of smoke from industrial and vehicular sources in St. Marys is contributing to an increase in arson cases nationwide. Perhaps there's more to this saying than meets the eye – or should we say, the air quality index?
The prevalence of arson as a criminal activity raises important questions about its potential association with environmental factors such as air pollution. As researchers, we're eager to fan the flames of inquiry and uncover whether there's a substantial link between these two seemingly disparate phenomena. After all, determining causality in research can sometimes feel like trying to put out a wildfire with a handheld fan – but we're not afraid to tackle the heat.
Statistics have often been likened to a double-edged sword – they cut through the fog of uncertainty, but they can also lead us down a garden path if we're not careful. With this in mind, our analysis aims to offer a rigorous examination of the data, providing a clear and compelling picture of the relationship between air pollution in St. Marys and arson cases across the United States. We're not just blowing smoke – our findings are rooted in a robust statistical framework, ready to withstand the winds of skepticism.
This paper sets out to ignite discussions, spark further research endeavors, and fan the flames of curiosity within the academic and policy communities. Our aim is to not only present our findings but to kindle a new perspective on the complex interplay between environmental factors and criminal behavior. So, grab a seat by the fire – metaphorically speaking, of course – and let's delve into the smoldering connection between air pollution and arson. After all, what's research without a little heat?
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
To gather the necessary data for this scorching investigation, our research team accessed information from the Environmental Protection Agency's Air Quality System and the FBI Criminal Justice Information Services. We used air pollution data from St. Marys, Pennsylvania, primarily focusing on the levels of particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) emissions. As for the arson data, we obtained detailed reports from the Uniform Crime Reporting Program, encompassing the annual count of arson incidents in various locations across the United States.
In order to stoke the flames of rigor and credibility in our analysis, we employed a sophisticated statistical approach, involving multiple regression analysis and time series modeling. This approach allowed us to capture the dynamic relationship between air pollution in St. Marys and the occurrence of arson incidents over the period from 1990 to 2022. It's safe to say that when it comes to data analysis, we don't just throw statistics into the wind – we carefully tend to the statistical hearth.
We also took into account potential confounding variables, such as socio-economic factors, population density, and weather patterns, to ensure that our findings didn't go up in smoke due to omitted variable bias. After all, we can't let our analysis go astray like a wayward ember – it has to be robust enough to withstand scrutiny from all angles.
Furthermore, to kindle a comprehensive understanding of the association between air pollution and arson, we conducted spatial analysis using geographic information system (GIS) mapping to visually depict the spatial distribution of both air pollution levels and arson hotspots across the United States. We're not just playing with fire here – we're harnessing the power of geographic visualization to illuminate potential clusters and trends.
Finally, we meticulously assessed the statistical significance of our findings using p-values and confidence intervals, ensuring that our conclusions didn't go up in flames due to mere chance. In the world of statistical analysis, we firmly believe in keeping our feet on solid ground – but that doesn't mean we can't enjoy a good pun while we're at it.
Ultimately, our methodology was designed to blaze a trail through the complexities of this research question, generating findings that withstand rigorous scrutiny and ignite further scholarly inquiry. After all, when it comes to exploring the interplay between air pollution and arson, we don't just dabble in statistics – we set the data alight with rigorous methods and incisive analysis.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 St. Marys, Pennsylvania and Arson in United States. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and FBI Criminal Justice Information Services .
For the time period 1990 to 2022, you found a correlation 0.8640177, r-squared of 0.7465265, and p < 0.01.
One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.
Here is the title and abstract of the paper:
[[TITLE]]
Up in Smoke: Uncovering the Fiery Relationship Between Air Pollution in St. Marys, Pennsylvania, and Arson in the United States
[[ABSTRACT]]
This paper delves into the burning question of whether there is a connection between air pollution in St. Marys, Pennsylvania, and arson across the United States. Our research team utilized data from the Environmental Protection Agency and the FBI Criminal Justice Information Services to ignite an investigation into this smoky relationship. The findings revealed a striking correlation coefficient of 0.8640177 and p < 0.01 between air pollution levels in St. Marys and the incidence of arson from 1990 to 2022.
Our analysis not only sheds light on this fiery connection but also kindles a new perspective on environmental factors and criminal behavior. These findings ignite further research avenues and spark discussions on tackling both air pollution and arson. After all, as the saying goes, where there’s smoke, there’s fire – and where there’s correlation, there’s causation!
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
The interaction between environmental factors and criminal behavior has long been a subject of intense scrutiny and speculation. One might say it's a burning issue with plenty of fuel for discussion. In recent years, researchers have increasingly turned their attention to the potential influence of air pollution on criminal activities, igniting curiosity about the potential connections between the two. Our research delves into this smoky landscape to uncover whether there is indeed a fiery relationship between air pollution in St. Marys, Pennsylvania, and the incidence of arson across the United States.
As the old saying goes, "Where there's smoke, there's fire." Well, in this case, we're not just blowing hot air – we've conducted a comprehensive investigation to shed light on whether the presence of smoke from industrial and vehicular sources in St. Marys is contributing to an increase in arson cases nationwide. Perhaps there's more to this saying than meets the eye – or should we say, the air quality index?
The prevalence of arson as a criminal activity raises important questions about its potential association with environmental factors such as air pollution. As researchers, we're eager to fan the flames of inquiry and uncover whether there's a substantial link between these two seemingly disparate phenomena. After all, determining causality in research can sometimes feel like trying to put out a wildfire with a handheld fan – but we're not afraid to tackle the heat.
Statistics have often been likened to a double-edged sword – they cut through the fog of uncertainty, but they can also lead us down a garden path if we're not careful. With this in mind, our analysis aims to offer a rigorous examination of the data, providing a clear and compelling picture of the relationship between air pollution in St. Marys and arson cases across the United States. We're not just blowing smoke – our findings are rooted in a robust statistical framework, ready to withstand the winds of skepticism.
This paper sets out to ignite discussions, spark further research endeavors, and fan the flames of curiosity within the academic and policy communities. Our aim is to not only present our findings but to kindle a new perspective on the complex interplay between environmental factors and criminal behavior. So, grab a seat by the fire – metaphorically speaking, of course – and let's delve into the smoldering connection between air pollution and arson. After all, what's research without a little heat?
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The data analysis revealed a robust correlation coefficient of 0.8640177 between air pollution levels in St. Marys, Pennsylvania, and the incidence of arson across the United States from 1990 to 2022. This correlation coefficient indicates a strong positive relationship between the two variables, suggesting that as air pollution levels increased in St. Marys, there was a corresponding rise in the occurrence of arson nationwide.
We found an r-squared value of 0.7465265, indicating that approximately 74.7% of the variability in arson cases can be explained by the variation in air pollution levels in St. Marys. In other words, the majority of the variation in arson occurrences across the United States can be attributed to changes in air pollution levels in this small Pennsylvania town. It seems that when it comes to explaining arson, the air quality in St. Marys is quite the hot topic.
The statistical significance of the correlation was confirmed through the p-value, which was less than 0.01. This means that the likelihood of observing such a strong correlation between air pollution in St. Marys and arson in the United States by random chance is less than 1%. In other words, the relationship we uncovered is as rare as finding a firefighter with a fear of heights – highly significant and not something you come across every day.
Fig. 1 represents the scatterplot illustrating the strong positive correlation between air pollution levels in St. Marys, Pennsylvania, and the incidence of arson across the United States. The upward trend in the data points is as clear as smoke billowing from a bonfire, leaving little doubt about the interconnectedness of these two variables.
Overall, the results of our analysis provide compelling evidence of a noteworthy association between air pollution in St. Marys, Pennsylvania, and arson occurrences across the United States. It seems that where there's smog, there's fire – and the data certainly fuels that argument. In the realm of statistical connections, this correlation is nothing to brush aside – it's a meaningful finding that sparks further inquiries into the interplay between environmental factors and criminal behavior. After all, in the world of research, uncovering such strong associations is a breath of fresh air – or perhaps in this case, a breath of sooty air.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 St. Marys, Pennsylvania and Arson in United States. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Limit your response to 500 tokens.
Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.
Do not write a conclusion. I will add a conclusion after this.
[[TITLE]]
Up in Smoke: Uncovering the Fiery Relationship Between Air Pollution in St. Marys, Pennsylvania, and Arson in the United States
[[ABSTRACT]]
This paper delves into the burning question of whether there is a connection between air pollution in St. Marys, Pennsylvania, and arson across the United States. Our research team utilized data from the Environmental Protection Agency and the FBI Criminal Justice Information Services to ignite an investigation into this smoky relationship. The findings revealed a striking correlation coefficient of 0.8640177 and p < 0.01 between air pollution levels in St. Marys and the incidence of arson from 1990 to 2022.
Our analysis not only sheds light on this fiery connection but also kindles a new perspective on environmental factors and criminal behavior. These findings ignite further research avenues and spark discussions on tackling both air pollution and arson. After all, as the saying goes, where there’s smoke, there’s fire – and where there’s correlation, there’s causation!
[[LITERATURE REVIEW]]
The existing body of literature on the relationship between air pollution and criminal activities provides a foundation for understanding the potential link between these two seemingly disparate phenomena. Smith et al. (2015) emphasize the importance of considering environmental factors in the examination of criminal behavior, highlighting the need to explore the influence of air quality on such activities. However, the burning question of whether air pollution serves as a contributing factor to arson across the United States has yet to be fully extinguished.
In "Doe and Jones' study," the authors find that air pollution levels in heavily industrialized areas have been associated with increased respiratory health problems and environmental degradation. However, the matchstick that ignites the link between these findings and the incidence of arson in the broader context of the United States remains elusive.
Turning to non-fiction works, "The Air Pollution Casebook" and "Criminal Minds: Environmental Edition" delve into the potential intersections of air quality and criminal behavior, providing comprehensive analyses that offer sparks of insight into the complex relationship between these two domains. However, these books fail to address the burning question at the heart of our investigation: does the smoke from St. Marys, Pennsylvania, possess the capacity to fan the flames of arson across the United States?
On a lighter note, figurative and fictional works such as "Smoke Signals: A Criminal Conspiracy" and "The Arsonist's Alibi" offer captivating narratives that add fuel to the fiery speculation surrounding the potential connection between air pollution and arson. Yet, amidst the smokescreen of creativity and imagination, the empirical evidence required to draw definitive conclusions remains absent.
Ah, the sweet smell of data analysis. In the realm of internet culture, the infamous "This is fine" meme depicts a dog calmly sipping coffee in a room engulfed in flames, humorously capturing the essence of our research journey as we navigate the heated discussion surrounding air pollution and arson. While such memes may provide a moment of levity, the underlying question persists: does the correlation between air pollution in St. Marys and arson in the United States warrant serious investigation, or is it merely a mirage in the hazy landscape of research inquiries?
As we kindle the flame of inquiry and navigate the intricate web of statistical analysis, it is crucial to approach this topic with both academic rigor and a touch of humor. After all, in the world of research, a well-placed dad joke can be the spark that ignites newfound curiosity and engagement. So, let's stoke the fires of investigation and embark on a quest to uncover the smoldering truth behind the connection between air pollution and arson.
[[RESULTS]]
The data analysis revealed a robust correlation coefficient of 0.8640177 between air pollution levels in St. Marys, Pennsylvania, and the incidence of arson across the United States from 1990 to 2022. This correlation coefficient indicates a strong positive relationship between the two variables, suggesting that as air pollution levels increased in St. Marys, there was a corresponding rise in the occurrence of arson nationwide.
We found an r-squared value of 0.7465265, indicating that approximately 74.7% of the variability in arson cases can be explained by the variation in air pollution levels in St. Marys. In other words, the majority of the variation in arson occurrences across the United States can be attributed to changes in air pollution levels in this small Pennsylvania town. It seems that when it comes to explaining arson, the air quality in St. Marys is quite the hot topic.
The statistical significance of the correlation was confirmed through the p-value, which was less than 0.01. This means that the likelihood of observing such a strong correlation between air pollution in St. Marys and arson in the United States by random chance is less than 1%. In other words, the relationship we uncovered is as rare as finding a firefighter with a fear of heights – highly significant and not something you come across every day.
Fig. 1 represents the scatterplot illustrating the strong positive correlation between air pollution levels in St. Marys, Pennsylvania, and the incidence of arson across the United States. The upward trend in the data points is as clear as smoke billowing from a bonfire, leaving little doubt about the interconnectedness of these two variables.
Overall, the results of our analysis provide compelling evidence of a noteworthy association between air pollution in St. Marys, Pennsylvania, and arson occurrences across the United States. It seems that where there's smog, there's fire – and the data certainly fuels that argument. In the realm of statistical connections, this correlation is nothing to brush aside – it's a meaningful finding that sparks further inquiries into the interplay between environmental factors and criminal behavior. After all, in the world of research, uncovering such strong associations is a breath of fresh air – or perhaps in this case, a breath of sooty air.
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Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The results of our investigation have illuminated a significant correlation between air pollution in St. Marys, Pennsylvania, and the incidence of arson across the United States. Our findings not only bolster previous research suggesting a potential link between environmental factors and criminal activities but also fuel further inquiry into the mechanisms underlying this fiery relationship.
As we set out on our research journey, we encountered various theories and speculations regarding the potential nexus between air pollution and arson. The literature review offered insights from both academic and fictional sources, hinting at the possibility of a smoldering connection. We must take these sources seriously, even if "The Arsonist's Alibi" sounds like a bestseller from a fire enthusiast's book club.
The robust correlation coefficient and statistically significant p-value derived from our analysis provide compelling support for the hypothesis that air pollution levels in St. Marys, Pennsylvania, are positively associated with the incidence of arson across the United States. This association, akin to a hot topic at a bonfire summit, underscores the importance of considering air quality as a potential contributing factor to criminal behavior.
In line with the findings of Smith et al. (2015) and the enigmatic "Doe and Jones," our research reaffirms the relevance of environmental factors, particularly air pollution, in understanding patterns of criminal activities. It appears that when it comes to arson, the smoke from St. Marys may indeed be signaling a deeper, albeit hazy, connection with criminal behavior nationwide. It's undeniable that where there's smog, there's fire, both metaphorically and statistically.
Our study's r-squared value, indicating that approximately 74.7% of the variability in arson cases can be explained by the variation in air pollution levels in St. Marys, further demonstrates the substantial influence of this small Pennsylvania town on nationwide arson trends. One could say that when it comes to fanning the flames of arson, the air quality in St. Marys is doing a pretty hot job – pardon the pun.
In conclusion, our findings not only corroborate prior research on the intersection of air quality and criminal behavior but also stoke the flames of interest in further investigations. As we navigate the complex relationship between air pollution and arson, it is essential to approach this topic with a mix of academic rigor and a dash of humor. After all, in the realm of research, a well-placed dad joke may just be the spark that ignites a newfound appreciation for statistical findings. So, let's continue to fan the flames of inquiry and shed light on the smoky mysteries surrounding this unlikely connection. And remember, when it comes to the correlation between air pollution and arson – where there's smoke, there's fire, and where there's fire, there's a potential governmental regulation waiting to be drafted.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 St. Marys, Pennsylvania and Arson in United States. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.
Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Up in Smoke: Uncovering the Fiery Relationship Between Air Pollution in St. Marys, Pennsylvania, and Arson in the United States
[[ABSTRACT]]
This paper delves into the burning question of whether there is a connection between air pollution in St. Marys, Pennsylvania, and arson across the United States. Our research team utilized data from the Environmental Protection Agency and the FBI Criminal Justice Information Services to ignite an investigation into this smoky relationship. The findings revealed a striking correlation coefficient of 0.8640177 and p < 0.01 between air pollution levels in St. Marys and the incidence of arson from 1990 to 2022.
Our analysis not only sheds light on this fiery connection but also kindles a new perspective on environmental factors and criminal behavior. These findings ignite further research avenues and spark discussions on tackling both air pollution and arson. After all, as the saying goes, where there’s smoke, there’s fire – and where there’s correlation, there’s causation!
[[INTRDUCTION]]
The interaction between environmental factors and criminal behavior has long been a subject of intense scrutiny and speculation. One might say it's a burning issue with plenty of fuel for discussion. In recent years, researchers have increasingly turned their attention to the potential influence of air pollution on criminal activities, igniting curiosity about the potential connections between the two. Our research delves into this smoky landscape to uncover whether there is indeed a fiery relationship between air pollution in St. Marys, Pennsylvania, and the incidence of arson across the United States.
As the old saying goes, "Where there's smoke, there's fire." Well, in this case, we're not just blowing hot air – we've conducted a comprehensive investigation to shed light on whether the presence of smoke from industrial and vehicular sources in St. Marys is contributing to an increase in arson cases nationwide. Perhaps there's more to this saying than meets the eye – or should we say, the air quality index?
The prevalence of arson as a criminal activity raises important questions about its potential association with environmental factors such as air pollution. As researchers, we're eager to fan the flames of inquiry and uncover whether there's a substantial link between these two seemingly disparate phenomena. After all, determining causality in research can sometimes feel like trying to put out a wildfire with a handheld fan – but we're not afraid to tackle the heat.
Statistics have often been likened to a double-edged sword – they cut through the fog of uncertainty, but they can also lead us down a garden path if we're not careful. With this in mind, our analysis aims to offer a rigorous examination of the data, providing a clear and compelling picture of the relationship between air pollution in St. Marys and arson cases across the United States. We're not just blowing smoke – our findings are rooted in a robust statistical framework, ready to withstand the winds of skepticism.
This paper sets out to ignite discussions, spark further research endeavors, and fan the flames of curiosity within the academic and policy communities. Our aim is to not only present our findings but to kindle a new perspective on the complex interplay between environmental factors and criminal behavior. So, grab a seat by the fire – metaphorically speaking, of course – and let's delve into the smoldering connection between air pollution and arson. After all, what's research without a little heat?
[[RESULTS]]
The data analysis revealed a robust correlation coefficient of 0.8640177 between air pollution levels in St. Marys, Pennsylvania, and the incidence of arson across the United States from 1990 to 2022. This correlation coefficient indicates a strong positive relationship between the two variables, suggesting that as air pollution levels increased in St. Marys, there was a corresponding rise in the occurrence of arson nationwide.
We found an r-squared value of 0.7465265, indicating that approximately 74.7% of the variability in arson cases can be explained by the variation in air pollution levels in St. Marys. In other words, the majority of the variation in arson occurrences across the United States can be attributed to changes in air pollution levels in this small Pennsylvania town. It seems that when it comes to explaining arson, the air quality in St. Marys is quite the hot topic.
The statistical significance of the correlation was confirmed through the p-value, which was less than 0.01. This means that the likelihood of observing such a strong correlation between air pollution in St. Marys and arson in the United States by random chance is less than 1%. In other words, the relationship we uncovered is as rare as finding a firefighter with a fear of heights – highly significant and not something you come across every day.
Fig. 1 represents the scatterplot illustrating the strong positive correlation between air pollution levels in St. Marys, Pennsylvania, and the incidence of arson across the United States. The upward trend in the data points is as clear as smoke billowing from a bonfire, leaving little doubt about the interconnectedness of these two variables.
Overall, the results of our analysis provide compelling evidence of a noteworthy association between air pollution in St. Marys, Pennsylvania, and arson occurrences across the United States. It seems that where there's smog, there's fire – and the data certainly fuels that argument. In the realm of statistical connections, this correlation is nothing to brush aside – it's a meaningful finding that sparks further inquiries into the interplay between environmental factors and criminal behavior. After all, in the world of research, uncovering such strong associations is a breath of fresh air – or perhaps in this case, a breath of sooty air.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our research has uncovered a compelling connection between air pollution in St. Marys, Pennsylvania, and the incidence of arson across the United States. The robust correlation coefficient of 0.8640177 and a significant p-value emphasize the fiery relationship between these variables. It seems that where there's smoke, there's indeed a statistical fire – and we're not just blowing hot air with that statement. This finding highlights the important role of environmental factors in influencing criminal behavior, igniting discussions about potential interventions and policy implications.
It's clear that the air quality in St. Marys has implications far beyond its immediate surroundings, fanning the flames of arson across the country. If this relationship were any more apparent, it would be like a smoke signal directly pointing to the influence of air pollution on criminal activities. As researchers, we aim to breathe new life into the discourse on environmental influences on crime, and these results certainly add fuel to that fire.
While our findings certainly provide a spark for future research endeavors, it's safe to say that no more research is needed in this area. After all, when it comes to the connection between air pollution in St. Marys and arson in the United States, we've already caused quite a stir – and there's no smoke without fire.
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 Fiery Relationship Between Air Pollution in St. Marys, Pennsylvania, and Arson in the United States. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Pyroclastic Studies
Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Up in Smoke: Uncovering the Fiery Relationship Between Air Pollution in St. Marys, Pennsylvania, and Arson in the United States. Respond only with the name of a fictional organization.
ChatGPT:
The Society for Environmental Criminology and Air Quality Research
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 Fiery Relationship Between Air Pollution in St. Marys, Pennsylvania, and Arson in the United States with an abstract of This paper delves into the burning question of whether there is a connection between air pollution in St. Marys, Pennsylvania, and arson across the United States. Our research team utilized data from the Environmental Protection Agency and the FBI Criminal Justice Information Services to ignite an investigation into this smoky relationship. The findings revealed a striking correlation coefficient of 0.8640177 and p < 0.01 between air pollution levels in St. Marys and the incidence of arson from 1990 to 2022.
Our analysis not only sheds light on this fiery connection but also kindles a new perspective on environmental factors and criminal behavior. These findings ignite further research avenues and spark discussions on tackling both air pollution and arson. After all, as the saying goes, where there’s smoke, there’s fire – and where there’s correlation, there’s causation!
ChatGPT:
air pollution, St. Marys Pennsylvania, arson, United States, correlation, Environmental Protection Agency, FBI Criminal Justice Information Services, criminal behavior, environmental factors
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
Discover a new correlation
View all correlations
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Data details
Air pollution in St. Marys, PennsylvaniaDetailed data title: Percentage of days with moderate or worse air quality in St. Marys, PA
Source: Environmental Protection Agency
See what else correlates with Air pollution in St. Marys, Pennsylvania
Arson in United States
Detailed data title: The arson rate per 100,000 residents in United States
Source: FBI Criminal Justice Information Services
See what else correlates with Arson in United States
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 = 0.7465265 (Coefficient of determination)
This means 74.7% of the change in the one variable (i.e., Arson in United States) is predictable based on the change in the other (i.e., Air pollution in St. Marys, Pennsylvania) over the 33 years from 1990 through 2022.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 9.4E-11. 0.0000000000939339138555067800
The p-value is a measure of how probable it is that we would randomly find a result this extreme. 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 0.86 in 9.4E-9% of random cases. Said differently, if you correlated 10,645,782,327 random variables You don't actually need 10 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 32 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 32 because we have two variables measured over a period of 33 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.
[ 0.74, 0.93 ] 95% correlation confidence interval (using the Fisher z-transformation)
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: 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.
| 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 St. Marys, Pennsylvania (Bad air quality days) | 0.242138 | 0.286111 | 0.168975 | 0.222561 | 0.193906 | 0.250951 | 0.192308 | 0.187726 | 0.247024 | 0.239669 | 0.172805 | 0.243626 | 0.191011 | 0.16156 | 0.127119 | 0.177326 | 0.121127 | 0.177285 | 0.133721 | 0.0758018 | 0.148045 | 0.0865922 | 0.162983 | 0.0803324 | 0.0576923 | 0.0662824 | 0.0722543 | 0.0467836 | 0.0740741 | 0.0336134 | 0.00558659 | 0.0502793 | 0.0275482 |
| Arson in United States (Arson rate) | 41.7 | 41 | 40.8 | 37.3 | 39.6 | 36.7 | 34.6 | 32.6 | 29.7 | 28.8 | 24.7 | 27.7 | 26.8 | 25 | 23.6 | 23.1 | 24.4 | 22.6 | 21.6 | 19.5 | 18.1 | 17.5 | 17.6 | 14.9 | 14.5 | 13.7 | 14.1 | 13.2 | 12 | 11 | 13.9 | 8.9 | 11.6 |
Why this works
- Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 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
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
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. 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([0.242138,0.286111,0.168975,0.222561,0.193906,0.250951,0.192308,0.187726,0.247024,0.239669,0.172805,0.243626,0.191011,0.16156,0.127119,0.177326,0.121127,0.177285,0.133721,0.0758018,0.148045,0.0865922,0.162983,0.0803324,0.0576923,0.0662824,0.0722543,0.0467836,0.0740741,0.0336134,0.00558659,0.0502793,0.0275482,])
array_2 = np.array([41.7,41,40.8,37.3,39.6,36.7,34.6,32.6,29.7,28.8,24.7,27.7,26.8,25,23.6,23.1,24.4,22.6,21.6,19.5,18.1,17.5,17.6,14.9,14.5,13.7,14.1,13.2,12,11,13.9,8.9,11.6,])
array_1_name = "Air pollution in St. Marys, Pennsylvania"
array_2_name = "Arson 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. 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.
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Download images for these variables:
- High resolution line chart
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 St. Marys, Pennsylvania
- Line chart for only Arson in United States
- AI-generated correlation image
- The spurious research paper: Up in Smoke: Uncovering the Fiery Relationship Between Air Pollution in St. Marys, Pennsylvania, and Arson in the United States
You're the rating guru we've been waiting for!
Correlation ID: 5679 · Black Variable ID: 22250 · Red Variable ID: 20038
