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AI explanation
As the air quality in Springfield declined, it caused a chain reaction of events. This led to an unexpected surge in the global kerosene market. One theory suggests that the smog particles acted as tiny messengers, conveying a newfound appreciation for kerosene and its versatile usage. Additionally, it's believed that as the pollution levels rose, residents may have turned to creative survival strategies, inadvertently sparking a kerosene renaissance. This unforeseen connection has left experts in both environmental science and international trade scratching their heads, as they try to fathom the unconventional link between a small city in Ohio and the kerosene preferences in Syria.
Model: dalle-3
Prompt: Generate an image of a bustling city scene in Springfield, Ohio with a thick haze of smog hanging over the city. The air is filled with dark clouds of car exhaust as people struggle with sneezing fits. Show the power of their sneezes as they blow out candles on tables and street lamps. Additionally, depict a glimpse of Syria with kerosene lamps flickering and dimming as people try to keep their flames alight amidst the sudden shortage of kerosene caused by the global sneeze-induced candle blowing. Capture the chaotic energy of the scene with a focus on the impact of the sneezes and the struggle to maintain illumination in the midst of the environmental and social disruption. 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 Springfield, Ohio and Kerosene used in Syria. 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: Cute cartoon A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s Cutsy graphics Cyber folk Realistic
ChatGPT: Realistic
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 Springfield, Ohio and Kerosene used in Syria, in the following situation: Because the increase in air pollution in Springfield, Ohio led to a surge in sneeze-induced candle blowing, causing a global shortage of kerosene due to all the accidental extinguishing of flames in Syria.. Keep the description simple.
ChatGPT: In Springfield, Ohio, a thick haze of smog hangs over the city, with cars emitting dark clouds of exhaust into the air. Amidst the pollution, people are sneezing, and their sneezes are powerful enough to blow out candles on tables and in street lamps. In Syria, kerosene lamps flicker and dim as people struggle to keep their flames alight due to the sudden shortage of kerosene caused by the global sneeze-induced candle blowing.
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: [ Realistic ] and depicting this scene: In Springfield, Ohio, a thick haze of smog hangs over the city, with cars emitting dark clouds of exhaust into the air. Amidst the pollution, people are sneezing, and their sneezes are powerful enough to blow out candles on tables and in street lamps. In Syria, kerosene lamps flicker and dim as people struggle to keep their flames alight due to the sudden shortage of kerosene caused by the global sneeze-induced candle blowing. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a bustling city scene in Springfield, Ohio with a thick haze of smog hanging over the city. The air is filled with dark clouds of car exhaust as people struggle with sneezing fits. Show the power of their sneezes as they blow out candles on tables and street lamps. Additionally, depict a glimpse of Syria with kerosene lamps flickering and dimming as people try to keep their flames alight amidst the sudden shortage of kerosene caused by the global sneeze-induced candle blowing. Capture the chaotic energy of the scene with a focus on the impact of the sneezes and the struggle to maintain illumination in the midst of the environmental and social disruption.
*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 increases in Air pollution in Springfield, Ohio positively influenced Kerosene used in Syria.
AI academic paper
 |
The Burning Issues Linking Air Pollution in Springfield, Ohio and Kerosene Usage in Syria Journal of Global Environmental Interconnections Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.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 Springfield, Ohio and Kerosene used in Syria. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.
Make the title a clever pun.
Your research team used data from Environmental Protection Agency and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.6623015 and p < 0.01 for 1980 to 2021.
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]]
The "Burning Issues" Linking Air Pollution in Springfield, Ohio and Kerosene Usage in Syria
[[ABSTRACT]]
This study investigates the unforeseen interplay of air pollution levels in Springfield, Ohio, and the consumption of kerosene in Syria. By employing data from the Environmental Protection Agency and the Energy Information Administration, we sought to uncover potential connections between these seemingly disparate phenomena. Surprisingly, our analysis revealed a correlation coefficient of 0.6623015 and p < 0.01 for the period spanning 1980 to 2021, shedding light on a previously overlooked correlation. The findings not only present a curious conundrum for researchers interested in environmental and energy-related issues but also highlight the unexpected ways in which seemingly unrelated factors may be intertwined. This study underscores the importance of considering diverse and seemingly unrelated factors when investigating complex environmental interactions, even if they may initially appear to be as dissimilar as night and day.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.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 Springfield, Ohio and Kerosene used in Syria. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.
Here is the title and abstract of the paper:
[[TITLE]]
The "Burning Issues" Linking Air Pollution in Springfield, Ohio and Kerosene Usage in Syria
[[ABSTRACT]]
This study investigates the unforeseen interplay of air pollution levels in Springfield, Ohio, and the consumption of kerosene in Syria. By employing data from the Environmental Protection Agency and the Energy Information Administration, we sought to uncover potential connections between these seemingly disparate phenomena. Surprisingly, our analysis revealed a correlation coefficient of 0.6623015 and p < 0.01 for the period spanning 1980 to 2021, shedding light on a previously overlooked correlation. The findings not only present a curious conundrum for researchers interested in environmental and energy-related issues but also highlight the unexpected ways in which seemingly unrelated factors may be intertwined. This study underscores the importance of considering diverse and seemingly unrelated factors when investigating complex environmental interactions, even if they may initially appear to be as dissimilar as night and day.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
INTRODUCTION
Air pollution and kerosene usage - two seemingly unrelated topics with no apparent link. In the grand scheme of things, one might be forgiven for assuming that the air quality in Springfield, Ohio and the use of kerosene in Syria have as much in common as a fish and a bicycle. However, as we delve deeper into the murky depths of environmental data, we begin to see a flicker of connection, like a distant light at the end of a dark, convoluted tunnel.
The intertwining of these "burning issues" may seem as improbable as finding a needle in a haystack or a vegetarian at a barbecue joint, but bear with us as we unravel the unexpected relationship between them. While some may raise an eyebrow at the thought of linking air pollution in a small Midwestern city with the consumption of kerosene in a Middle Eastern country, the numbers don't lie - much like a persistent toddler, they insist on being noticed and demand attention.
It is worth noting that the journey to uncover this correlation was not without its challenges. One could say it was akin to navigating a maze blindfolded or trying to find a specific grain of sand on a beach. Nevertheless, our diligent pursuit of empirical evidence has led us to a revelation that has raised eyebrows and turned heads - much like a sudden pop quiz or a forthcoming deadline.
So, with data in hand and statistics at the ready, let us explore the curious juxtaposition of pollution in Springfield and the use of kerosene in Syria. Who knows, by the end of this journey, we might just find that these two seemingly disconnected phenomena have more in common than meets the eye - like long-lost cousins or forgotten acquaintances at a high school reunion.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.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 Springfield, Ohio and Kerosene used in Syria. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 name some movies that you watched that are tangentially related to the topic.
Here is the title and abstract of the paper:
[[TITLE]]
The "Burning Issues" Linking Air Pollution in Springfield, Ohio and Kerosene Usage in Syria
[[ABSTRACT]]
This study investigates the unforeseen interplay of air pollution levels in Springfield, Ohio, and the consumption of kerosene in Syria. By employing data from the Environmental Protection Agency and the Energy Information Administration, we sought to uncover potential connections between these seemingly disparate phenomena. Surprisingly, our analysis revealed a correlation coefficient of 0.6623015 and p < 0.01 for the period spanning 1980 to 2021, shedding light on a previously overlooked correlation. The findings not only present a curious conundrum for researchers interested in environmental and energy-related issues but also highlight the unexpected ways in which seemingly unrelated factors may be intertwined. This study underscores the importance of considering diverse and seemingly unrelated factors when investigating complex environmental interactions, even if they may initially appear to be as dissimilar as night and day.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
Air pollution and kerosene usage - two seemingly unrelated topics with no apparent link. In the grand scheme of things, one might be forgiven for assuming that the air quality in Springfield, Ohio and the use of kerosene in Syria have as much in common as a fish and a bicycle. However, as we delve deeper into the murky depths of environmental data, we begin to see a flicker of connection, like a distant light at the end of a dark, convoluted tunnel.
The intertwining of these "burning issues" may seem as improbable as finding a needle in a haystack or a vegetarian at a barbecue joint, but bear with us as we unravel the unexpected relationship between them. While some may raise an eyebrow at the thought of linking air pollution in a small Midwestern city with the consumption of kerosene in a Middle Eastern country, the numbers don't lie - much like a persistent toddler, they insist on being noticed and demand attention.
It is worth noting that the journey to uncover this correlation was not without its challenges. One could say it was akin to navigating a maze blindfolded or trying to find a specific grain of sand on a beach. Nevertheless, our diligent pursuit of empirical evidence has led us to a revelation that has raised eyebrows and turned heads - much like a sudden pop quiz or a forthcoming deadline.
So, with data in hand and statistics at the ready, let us explore the curious juxtaposition of pollution in Springfield and the use of kerosene in Syria. Who knows, by the end of this journey, we might just find that these two seemingly disconnected phenomena have more in common than meets the eye - like long-lost cousins or forgotten acquaintances at a high school reunion.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
The literature review aims to explore the unexpected correlation between air pollution in Springfield, Ohio, and the utilization of kerosene in Syria. While the initial proposition of such a relationship might seem akin to finding a unicorn in a forest, the authors find evidence from various sources to support this intriguing connection.
Smith et al. (2015) conducted a comprehensive study on air quality in urban areas, highlighting the impact of industrial emissions on local pollution levels. Meanwhile, Doe and Jones (2018) delved into the complexities of energy consumption patterns in developing countries, shedding light on the usage of traditional fuels such as kerosene. These serious, well-respected researchers provided the foundational knowledge necessary to begin untangling the web of interconnectedness between seemingly unrelated phenomena.
Moving beyond the conventional research, "Breathe Easy: Tackling Air Pollution in Urban Environments" by Clean Air Institute (2019) and "Energy Transitions in the Middle East" by Green Energy Coalition (2017) offer valuable insights into the nuanced environmental and energy dynamics of the two regions under scrutiny. While seemingly straightforward, these texts offer more twists and turns than a mystery novel, with each page unravelling a different layer of the complex relationship between air quality and energy consumption.
On a different note, "The Kerosene Chronicles" by Hot Flames Publishing (2016) and "The Polluted City" by Smoggy Skies Press (2018) may not feature empirical data or statistical analyses, but their narrative threads hint at an intriguing connection between air pollution and kerosene usage. While purely fictional, these works spark an imaginative exploration of the potential interplay between the two phenomena.
Finally, the authors draw from their eclectic film-watching experiences to inform this literature review, as movies such as "The Toxic Avenger" and "Desert Heat" tangentially touch upon themes of pollution and energy use. While these cinematic references may not offer concrete evidence, they certainly add a dash of entertainment to an otherwise serious pursuit of knowledge.
In the grand tapestry of research, the literature review illuminates the unexpected byways and peculiar alleyways that lead to the revelation of this curious correlation between air pollution in Springfield, Ohio, and kerosene usage in Syria. Like a meandering river that eventually finds its way to the ocean, this exploration intertwines the thought-provoking with the whimsical, reminding researchers to approach their investigations with both gravity and a twinkle in their eyes.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.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 Springfield, Ohio and Kerosene used in Syria. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 Energy Information Administration . You used data from 1980 to 2021
Make up the research methods you don't know. Make them a bit goofy and convoluted.
Here is the title, abstract, and introduction of the paper:
[[TITLE]]
The "Burning Issues" Linking Air Pollution in Springfield, Ohio and Kerosene Usage in Syria
[[ABSTRACT]]
This study investigates the unforeseen interplay of air pollution levels in Springfield, Ohio, and the consumption of kerosene in Syria. By employing data from the Environmental Protection Agency and the Energy Information Administration, we sought to uncover potential connections between these seemingly disparate phenomena. Surprisingly, our analysis revealed a correlation coefficient of 0.6623015 and p < 0.01 for the period spanning 1980 to 2021, shedding light on a previously overlooked correlation. The findings not only present a curious conundrum for researchers interested in environmental and energy-related issues but also highlight the unexpected ways in which seemingly unrelated factors may be intertwined. This study underscores the importance of considering diverse and seemingly unrelated factors when investigating complex environmental interactions, even if they may initially appear to be as dissimilar as night and day.
[[INTRODUCTION]]
INTRODUCTION
Air pollution and kerosene usage - two seemingly unrelated topics with no apparent link. In the grand scheme of things, one might be forgiven for assuming that the air quality in Springfield, Ohio and the use of kerosene in Syria have as much in common as a fish and a bicycle. However, as we delve deeper into the murky depths of environmental data, we begin to see a flicker of connection, like a distant light at the end of a dark, convoluted tunnel.
The intertwining of these "burning issues" may seem as improbable as finding a needle in a haystack or a vegetarian at a barbecue joint, but bear with us as we unravel the unexpected relationship between them. While some may raise an eyebrow at the thought of linking air pollution in a small Midwestern city with the consumption of kerosene in a Middle Eastern country, the numbers don't lie - much like a persistent toddler, they insist on being noticed and demand attention.
It is worth noting that the journey to uncover this correlation was not without its challenges. One could say it was akin to navigating a maze blindfolded or trying to find a specific grain of sand on a beach. Nevertheless, our diligent pursuit of empirical evidence has led us to a revelation that has raised eyebrows and turned heads - much like a sudden pop quiz or a forthcoming deadline.
So, with data in hand and statistics at the ready, let us explore the curious juxtaposition of pollution in Springfield and the use of kerosene in Syria. Who knows, by the end of this journey, we might just find that these two seemingly disconnected phenomena have more in common than meets the eye - like long-lost cousins or forgotten acquaintances at a high school reunion.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
Data Collection:
The gathering of empirical evidence for this study was no mean feat. It involved meticulous trawling through the vast expanse of the internet, akin to embarking on a digital treasure hunt. The primary sources of data were the Environmental Protection Agency and the Energy Information Administration, serving as the academic equivalent of "X marks the spot."
Air Pollution Measurement in Springfield, Ohio:
To assess the air pollution levels in Springfield, Ohio, we harnessed the power of various air quality monitoring stations. These stations, scattered across the city like breadcrumbs in a forest, provided comprehensive data on pollutants such as particulate matter, sulfur dioxide, and nitrogen oxides. These measurements were then painstakingly compiled and analyzed, analogous to piecing together a jigsaw puzzle with intricate and elusive pieces.
Kerosene Usage in Syria:
The quantification of kerosene consumption in Syria was a multifaceted endeavor. Drawing from energy consumption reports and fuel usage statistics, we endeavored to paint a comprehensive picture of the kerosene landscape in Syria. This process involved navigating through a labyrinth of data, reminiscent of maneuvering through a complex web of interconnected nodes, or perhaps unraveling the layers of an enigmatic puzzle.
Data Analysis:
With a robust dataset in hand, the analysis phase commenced with the fervor of a detective unraveling a mystery. We employed sophisticated statistical methods to identify potential relationships between air pollution in Springfield and kerosene usage in Syria. The implementation of correlation analysis and time series modeling resembled the act of coaxing secrets from a reticent informer, teasing out hidden patterns and connections.
Temporal Considerations:
The temporal dimension of the data was a crucial aspect of the analysis. Extending from 1980 to 2021, this lengthy time span allowed for the exploration of long-term trends and fluctuations in air pollution levels in Springfield and kerosene consumption in Syria. It provided a broad canvas on which to trace the evolving relationship between these disparate variables, much like observing the ebb and flow of ocean tides over the course of several decades.
Limitations:
It is important to acknowledge the limitations of our methodology. While our approach could unearth intriguing associations, it is not without its constraints. The reliance on existing datasets may have introduced inherent biases, akin to viewing the world through a particular set of tinted glasses. Furthermore, the complexity of environmental and energy-related interactions presents an ongoing challenge, reminiscent of chasing a playful kitten through a maze of knickknacks.
Overall, the methodology employed for this study epitomizes the blend of determination, innovation, and perhaps a touch of whimsy necessary to unravel the intricate connection between air pollution in Springfield, Ohio, and kerosene usage in Syria.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.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 Springfield, Ohio and Kerosene used in Syria. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 Energy Information Administration .
For the time period 1980 to 2021, you found a correlation 0.6623015, r-squared of 0.4386432, and p < 0.01.
One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.
Here is the title and abstract of the paper:
[[TITLE]]
The "Burning Issues" Linking Air Pollution in Springfield, Ohio and Kerosene Usage in Syria
[[ABSTRACT]]
This study investigates the unforeseen interplay of air pollution levels in Springfield, Ohio, and the consumption of kerosene in Syria. By employing data from the Environmental Protection Agency and the Energy Information Administration, we sought to uncover potential connections between these seemingly disparate phenomena. Surprisingly, our analysis revealed a correlation coefficient of 0.6623015 and p < 0.01 for the period spanning 1980 to 2021, shedding light on a previously overlooked correlation. The findings not only present a curious conundrum for researchers interested in environmental and energy-related issues but also highlight the unexpected ways in which seemingly unrelated factors may be intertwined. This study underscores the importance of considering diverse and seemingly unrelated factors when investigating complex environmental interactions, even if they may initially appear to be as dissimilar as night and day.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
INTRODUCTION
Air pollution and kerosene usage - two seemingly unrelated topics with no apparent link. In the grand scheme of things, one might be forgiven for assuming that the air quality in Springfield, Ohio and the use of kerosene in Syria have as much in common as a fish and a bicycle. However, as we delve deeper into the murky depths of environmental data, we begin to see a flicker of connection, like a distant light at the end of a dark, convoluted tunnel.
The intertwining of these "burning issues" may seem as improbable as finding a needle in a haystack or a vegetarian at a barbecue joint, but bear with us as we unravel the unexpected relationship between them. While some may raise an eyebrow at the thought of linking air pollution in a small Midwestern city with the consumption of kerosene in a Middle Eastern country, the numbers don't lie - much like a persistent toddler, they insist on being noticed and demand attention.
It is worth noting that the journey to uncover this correlation was not without its challenges. One could say it was akin to navigating a maze blindfolded or trying to find a specific grain of sand on a beach. Nevertheless, our diligent pursuit of empirical evidence has led us to a revelation that has raised eyebrows and turned heads - much like a sudden pop quiz or a forthcoming deadline.
So, with data in hand and statistics at the ready, let us explore the curious juxtaposition of pollution in Springfield and the use of kerosene in Syria. Who knows, by the end of this journey, we might just find that these two seemingly disconnected phenomena have more in common than meets the eye - like long-lost cousins or forgotten acquaintances at a high school reunion.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
Upon conducting our rigorous analysis of the data, we unearthed a surprising connection between air pollution levels in Springfield, Ohio, and the consumption of kerosene in Syria. The correlation coefficient of 0.6623015 and an r-squared of 0.4386432 for the time period of 1980 to 2021 left us feeling as bewildered as a cat chasing its own tail. The statistical significance with p < 0.01 added a touch of certainty to our unexpected findings, akin to stumbling upon a hidden treasure while cleaning out the attic.
Our findings, graphically illustrated in Fig. 1, depict a scatterplot showing a strong correlation between the two variables. Like two peas in a pod, the air pollution in Springfield and kerosene usage in Syria seemed to go hand in hand, much to our bewilderment. It is as if these seemingly disparate phenomena were engaged in a clandestine dance, evading detection until our meticulous analysis brought them to the forefront, much like a magician revealing a well-kept secret.
The revelation of this correlation not only raises eyebrows but also presents an intriguing puzzle for researchers in the environmental and energy-related domains. The seemingly unrelated coupling of air pollution in the heart of America and the use of kerosene in the heart of the Middle East is akin to discovering an unexpected twist in a riveting novel or stumbling upon a unicorn in the forest - it challenges our preconceived notions and redefines our understanding of environmental interconnections.
Our results serve as a reminder of the complex and often surprising interactions that exist in the realm of environmental phenomena. Just as a jigsaw puzzle may reveal unexpected pictures when its pieces are rearranged, our study sheds light on the unforeseen links between air pollution and kerosene usage. This finding emphasizes the importance of considering diverse and seemingly unrelated factors in the investigation of environmental interactions, much like piecing together a mosaic that unveils a striking image when viewed as a whole.
In conclusion, our research reveals a captivating correlation between air pollution in Springfield, Ohio, and the utilization of kerosene in Syria, presenting an unexpected twist in the narrative of environmental interplay. The "burning issues" appear to be more intertwined than meets the eye, sparking curiosity and prompting further exploration into the complex web of environmental connections.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.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 Springfield, Ohio and Kerosene used in Syria. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
The "Burning Issues" Linking Air Pollution in Springfield, Ohio and Kerosene Usage in Syria
[[ABSTRACT]]
This study investigates the unforeseen interplay of air pollution levels in Springfield, Ohio, and the consumption of kerosene in Syria. By employing data from the Environmental Protection Agency and the Energy Information Administration, we sought to uncover potential connections between these seemingly disparate phenomena. Surprisingly, our analysis revealed a correlation coefficient of 0.6623015 and p < 0.01 for the period spanning 1980 to 2021, shedding light on a previously overlooked correlation. The findings not only present a curious conundrum for researchers interested in environmental and energy-related issues but also highlight the unexpected ways in which seemingly unrelated factors may be intertwined. This study underscores the importance of considering diverse and seemingly unrelated factors when investigating complex environmental interactions, even if they may initially appear to be as dissimilar as night and day.
[[LITERATURE REVIEW]]
The literature review aims to explore the unexpected correlation between air pollution in Springfield, Ohio, and the utilization of kerosene in Syria. While the initial proposition of such a relationship might seem akin to finding a unicorn in a forest, the authors find evidence from various sources to support this intriguing connection.
Smith et al. (2015) conducted a comprehensive study on air quality in urban areas, highlighting the impact of industrial emissions on local pollution levels. Meanwhile, Doe and Jones (2018) delved into the complexities of energy consumption patterns in developing countries, shedding light on the usage of traditional fuels such as kerosene. These serious, well-respected researchers provided the foundational knowledge necessary to begin untangling the web of interconnectedness between seemingly unrelated phenomena.
Moving beyond the conventional research, "Breathe Easy: Tackling Air Pollution in Urban Environments" by Clean Air Institute (2019) and "Energy Transitions in the Middle East" by Green Energy Coalition (2017) offer valuable insights into the nuanced environmental and energy dynamics of the two regions under scrutiny. While seemingly straightforward, these texts offer more twists and turns than a mystery novel, with each page unravelling a different layer of the complex relationship between air quality and energy consumption.
On a different note, "The Kerosene Chronicles" by Hot Flames Publishing (2016) and "The Polluted City" by Smoggy Skies Press (2018) may not feature empirical data or statistical analyses, but their narrative threads hint at an intriguing connection between air pollution and kerosene usage. While purely fictional, these works spark an imaginative exploration of the potential interplay between the two phenomena.
Finally, the authors draw from their eclectic film-watching experiences to inform this literature review, as movies such as "The Toxic Avenger" and "Desert Heat" tangentially touch upon themes of pollution and energy use. While these cinematic references may not offer concrete evidence, they certainly add a dash of entertainment to an otherwise serious pursuit of knowledge.
In the grand tapestry of research, the literature review illuminates the unexpected byways and peculiar alleyways that lead to the revelation of this curious correlation between air pollution in Springfield, Ohio, and kerosene usage in Syria. Like a meandering river that eventually finds its way to the ocean, this exploration intertwines the thought-provoking with the whimsical, reminding researchers to approach their investigations with both gravity and a twinkle in their eyes.
[[RESULTS]]
Upon conducting our rigorous analysis of the data, we unearthed a surprising connection between air pollution levels in Springfield, Ohio, and the consumption of kerosene in Syria. The correlation coefficient of 0.6623015 and an r-squared of 0.4386432 for the time period of 1980 to 2021 left us feeling as bewildered as a cat chasing its own tail. The statistical significance with p < 0.01 added a touch of certainty to our unexpected findings, akin to stumbling upon a hidden treasure while cleaning out the attic.
Our findings, graphically illustrated in Fig. 1, depict a scatterplot showing a strong correlation between the two variables. Like two peas in a pod, the air pollution in Springfield and kerosene usage in Syria seemed to go hand in hand, much to our bewilderment. It is as if these seemingly disparate phenomena were engaged in a clandestine dance, evading detection until our meticulous analysis brought them to the forefront, much like a magician revealing a well-kept secret.
The revelation of this correlation not only raises eyebrows but also presents an intriguing puzzle for researchers in the environmental and energy-related domains. The seemingly unrelated coupling of air pollution in the heart of America and the use of kerosene in the heart of the Middle East is akin to discovering an unexpected twist in a riveting novel or stumbling upon a unicorn in the forest - it challenges our preconceived notions and redefines our understanding of environmental interconnections.
Our results serve as a reminder of the complex and often surprising interactions that exist in the realm of environmental phenomena. Just as a jigsaw puzzle may reveal unexpected pictures when its pieces are rearranged, our study sheds light on the unforeseen links between air pollution and kerosene usage. This finding emphasizes the importance of considering diverse and seemingly unrelated factors in the investigation of environmental interactions, much like piecing together a mosaic that unveils a striking image when viewed as a whole.
In conclusion, our research reveals a captivating correlation between air pollution in Springfield, Ohio, and the utilization of kerosene in Syria, presenting an unexpected twist in the narrative of environmental interplay. The "burning issues" appear to be more intertwined than meets the eye, sparking curiosity and prompting further exploration into the complex web of environmental connections.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The findings of this study highlight the intriguing link between air pollution in Springfield, Ohio, and the use of kerosene in Syria, offering a fresh perspective on the complexity of environmental interconnections. While initially as improbable as finding a pearl in a landfill, the results of our analysis support the unexpected correlation that we unearthed. Smith et al. (2015) may have laid the foundation for understanding urban air quality, but our study takes it a step further, showing how a fateful dance between air pollution and kerosene usage unfolds across continents.
Doe and Jones (2018) may have shed light on the energy consumption patterns in developing countries, but the connection between kerosene usage and air pollution in Springfield, Ohio adds a newly discovered dimension to their insights. Like a detective stumbling upon a crucial piece of evidence in an unlikely place, our results corroborate the notion that seemingly unrelated phenomena can become entangled in the grand scheme of environmental dynamics.
The statistical significance of our findings reinforces the legitimacy of this unexpected correlation, akin to finding a diamond in the rough rather than a needle in a haystack. The scatterplot visualization of the strong correlation between air pollution and kerosene usage is a testament to the power of meticulous data analysis, revealing the hidden ties that bind environmental phenomena across disparate regions.
The revelation of this correlation challenges the conventional wisdom that air pollution and kerosene usage are isolated issues, much like discovering a treasure trove in an abandoned attic. The unexpected entwining of these two seemingly unrelated factors unveils a narrative worthy of a mystery novel, prompting a reevaluation of our understanding of the interconnectedness of environmental dynamics.
In essence, our research adds a twist to the conventional understanding of environmental interactions, akin to finding a unicorn in the forest – a delightful surprise that prompts us to reconsider the boundaries of environmental interconnectedness. The study not only underscores the unexpected ways in which seemingly unrelated factors can be intertwined but also serves as a reminder to approach environmental investigations with both reverence and a sense of wonder.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.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 Springfield, Ohio and Kerosene used in Syria. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
The "Burning Issues" Linking Air Pollution in Springfield, Ohio and Kerosene Usage in Syria
[[ABSTRACT]]
This study investigates the unforeseen interplay of air pollution levels in Springfield, Ohio, and the consumption of kerosene in Syria. By employing data from the Environmental Protection Agency and the Energy Information Administration, we sought to uncover potential connections between these seemingly disparate phenomena. Surprisingly, our analysis revealed a correlation coefficient of 0.6623015 and p < 0.01 for the period spanning 1980 to 2021, shedding light on a previously overlooked correlation. The findings not only present a curious conundrum for researchers interested in environmental and energy-related issues but also highlight the unexpected ways in which seemingly unrelated factors may be intertwined. This study underscores the importance of considering diverse and seemingly unrelated factors when investigating complex environmental interactions, even if they may initially appear to be as dissimilar as night and day.
[[INTRDUCTION]]
INTRODUCTION
Air pollution and kerosene usage - two seemingly unrelated topics with no apparent link. In the grand scheme of things, one might be forgiven for assuming that the air quality in Springfield, Ohio and the use of kerosene in Syria have as much in common as a fish and a bicycle. However, as we delve deeper into the murky depths of environmental data, we begin to see a flicker of connection, like a distant light at the end of a dark, convoluted tunnel.
The intertwining of these "burning issues" may seem as improbable as finding a needle in a haystack or a vegetarian at a barbecue joint, but bear with us as we unravel the unexpected relationship between them. While some may raise an eyebrow at the thought of linking air pollution in a small Midwestern city with the consumption of kerosene in a Middle Eastern country, the numbers don't lie - much like a persistent toddler, they insist on being noticed and demand attention.
It is worth noting that the journey to uncover this correlation was not without its challenges. One could say it was akin to navigating a maze blindfolded or trying to find a specific grain of sand on a beach. Nevertheless, our diligent pursuit of empirical evidence has led us to a revelation that has raised eyebrows and turned heads - much like a sudden pop quiz or a forthcoming deadline.
So, with data in hand and statistics at the ready, let us explore the curious juxtaposition of pollution in Springfield and the use of kerosene in Syria. Who knows, by the end of this journey, we might just find that these two seemingly disconnected phenomena have more in common than meets the eye - like long-lost cousins or forgotten acquaintances at a high school reunion.
[[RESULTS]]
Upon conducting our rigorous analysis of the data, we unearthed a surprising connection between air pollution levels in Springfield, Ohio, and the consumption of kerosene in Syria. The correlation coefficient of 0.6623015 and an r-squared of 0.4386432 for the time period of 1980 to 2021 left us feeling as bewildered as a cat chasing its own tail. The statistical significance with p < 0.01 added a touch of certainty to our unexpected findings, akin to stumbling upon a hidden treasure while cleaning out the attic.
Our findings, graphically illustrated in Fig. 1, depict a scatterplot showing a strong correlation between the two variables. Like two peas in a pod, the air pollution in Springfield and kerosene usage in Syria seemed to go hand in hand, much to our bewilderment. It is as if these seemingly disparate phenomena were engaged in a clandestine dance, evading detection until our meticulous analysis brought them to the forefront, much like a magician revealing a well-kept secret.
The revelation of this correlation not only raises eyebrows but also presents an intriguing puzzle for researchers in the environmental and energy-related domains. The seemingly unrelated coupling of air pollution in the heart of America and the use of kerosene in the heart of the Middle East is akin to discovering an unexpected twist in a riveting novel or stumbling upon a unicorn in the forest - it challenges our preconceived notions and redefines our understanding of environmental interconnections.
Our results serve as a reminder of the complex and often surprising interactions that exist in the realm of environmental phenomena. Just as a jigsaw puzzle may reveal unexpected pictures when its pieces are rearranged, our study sheds light on the unforeseen links between air pollution and kerosene usage. This finding emphasizes the importance of considering diverse and seemingly unrelated factors in the investigation of environmental interactions, much like piecing together a mosaic that unveils a striking image when viewed as a whole.
In conclusion, our research reveals a captivating correlation between air pollution in Springfield, Ohio, and the utilization of kerosene in Syria, presenting an unexpected twist in the narrative of environmental interplay. The "burning issues" appear to be more intertwined than meets the eye, sparking curiosity and prompting further exploration into the complex web of environmental connections.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our study has illuminated a remarkable correlation between air pollution in Springfield, Ohio, and the consumption of kerosene in Syria, much like shining a flashlight in a dimly lit room reveals hidden treasures. Our findings not only demonstrate the unexpected interplay of seemingly unrelated variables but also serve as a testament to the unpredictable nature of environmental phenomena, reminiscent of a surprise plot twist in a melodramatic soap opera. The connection between these "burning issues" has left us pondering the mysterious ways in which environmental factors can intertwine, much like contemplating the intricate flavors in an exotic dish or the enigmatic behavior of a cat.
Nevertheless, it is incumbent upon us to recognize the limitations of our study. While we have uncovered a significant correlation, the precise mechanisms underpinning this connection remain as elusive as a magician's tricks. Furthermore, the generalizability of our findings to other regions and energy sources warrants further investigation, much like exploring uncharted territory or deciphering an ancient manuscript.
Therefore, we assert with confidence, perhaps even a touch of relief, that no further research is needed in this area. After all, delving into the mysterious link between air pollution in Ohio and kerosene usage in Syria has been akin to chasing a unicorn - an intriguing pursuit, but one that may not lead to tangible revelations. In the grand symphony of environmental research, our study has provided an unexpected, albeit amusing, interlude, and it may be time to shift our attention to less cryptic and more fruitful pursuits.
Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited The Burning Issues Linking Air Pollution in Springfield, Ohio and Kerosene Usage in Syria. Respond only with the name of a fictional academic journal.
ChatGPT:
Journal of Global Environmental Interconnections
Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited The Burning Issues Linking Air Pollution in Springfield, Ohio and Kerosene Usage in Syria. Respond only with the name of a fictional organization.
ChatGPT:
The Society for Global Air Quality and Energy Use
Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled The Burning Issues Linking Air Pollution in Springfield, Ohio and Kerosene Usage in Syria with an abstract of This study investigates the unforeseen interplay of air pollution levels in Springfield, Ohio, and the consumption of kerosene in Syria. By employing data from the Environmental Protection Agency and the Energy Information Administration, we sought to uncover potential connections between these seemingly disparate phenomena. Surprisingly, our analysis revealed a correlation coefficient of 0.6623015 and p < 0.01 for the period spanning 1980 to 2021, shedding light on a previously overlooked correlation. The findings not only present a curious conundrum for researchers interested in environmental and energy-related issues but also highlight the unexpected ways in which seemingly unrelated factors may be intertwined. This study underscores the importance of considering diverse and seemingly unrelated factors when investigating complex environmental interactions, even if they may initially appear to be as dissimilar as night and day.
ChatGPT:
air pollution, Springfield Ohio, kerosene usage, Syria, environmental impact, correlation analysis, energy consumption, EPA data, EIA data, environmental interplay, complex environmental interactions
*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 Springfield, OhioDetailed data title: Percentage of days 'unhealthy' or worse air quality in Springfield, OH
Source: Environmental Protection Agency
See what else correlates with Air pollution in Springfield, Ohio
Kerosene used in Syria
Detailed data title: Volume of kerosene used consumed in Syria in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Kerosene used in Syria
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 = 0.4386432 (Coefficient of determination)
This means 43.9% of the change in the one variable (i.e., Kerosene used in Syria) is predictable based on the change in the other (i.e., Air pollution in Springfield, Ohio) over the 42 years from 1980 through 2021.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.8E-6. 0.0000017763558689228162000000
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 0.66 in 0.00018% of random cases. Said differently, if you correlated 562,950 random variables You don't actually need 562 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 41 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 41 because we have two variables measured over a period of 42 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.
[ 0.45, 0.8 ] 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.
| 1980 | 1981 | 1982 | 1983 | 1984 | 1985 | 1986 | 1987 | 1988 | 1989 | 1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | |
| Air pollution in Springfield, Ohio (Bad air quality days) | 1.9943 | 3.02115 | 5.78231 | 7.30994 | 0 | 1.11111 | 2.2293 | 9.2827 | 14.4737 | 4.22535 | 4.6729 | 5.14019 | 0.934579 | 1.40187 | 5.14019 | 4.20561 | 6.07477 | 3.73832 | 7.47664 | 6.54206 | 1.7094 | 1.1583 | 8.36502 | 1.13636 | 0.377358 | 1.9084 | 0.377358 | 0.757576 | 0.380228 | 0 | 0 | 0 | 0.275482 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Kerosene used in Syria (Million Barrels/Day) | 3.00546 | 3.27869 | 3.30601 | 3.79781 | 4.20765 | 4.48087 | 4.5 | 4.3 | 5.6 | 4.9 | 4.5 | 5.5 | 4.8 | 4.9 | 5.2 | 3.4 | 3.1 | 5.2 | 5.7 | 6.3 | 4.41413 | 4.08737 | 4.08737 | 3.38849 | 3.40036 | 3.74852 | 1.56718 | 0.44474 | 0.316803 | 0.0635342 | 0.0423562 | 0.0635342 | 0.0633607 | 0.0423562 | 0.0423562 | 0.0423562 | 0.035694 | 0.0651781 | 0.0651781 | 0.0651781 | 0.0651781 | 0.0651781 |
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
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([1.9943,3.02115,5.78231,7.30994,0,1.11111,2.2293,9.2827,14.4737,4.22535,4.6729,5.14019,0.934579,1.40187,5.14019,4.20561,6.07477,3.73832,7.47664,6.54206,1.7094,1.1583,8.36502,1.13636,0.377358,1.9084,0.377358,0.757576,0.380228,0,0,0,0.275482,0,0,0,0,0,0,0,0,0,])
array_2 = np.array([3.00546,3.27869,3.30601,3.79781,4.20765,4.48087,4.5,4.3,5.6,4.9,4.5,5.5,4.8,4.9,5.2,3.4,3.1,5.2,5.7,6.3,4.41413,4.08737,4.08737,3.38849,3.40036,3.74852,1.56718,0.44474,0.316803,0.0635342,0.0423562,0.0635342,0.0633607,0.0423562,0.0423562,0.0423562,0.035694,0.0651781,0.0651781,0.0651781,0.0651781,0.0651781,])
array_1_name = "Air pollution in Springfield, Ohio"
array_2_name = "Kerosene used in Syria"
# 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.
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
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 Springfield, Ohio
- Line chart for only Kerosene used in Syria
- AI-generated correlation image
- The spurious research paper: The Burning Issues Linking Air Pollution in Springfield, Ohio and Kerosene Usage in Syria
Bravo! Your evaluation rocks!
Correlation ID: 3655 · Black Variable ID: 21304 · Red Variable ID: 24965
