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AI explanation
As the air over Janesville cleared up, it created a ripple effect of environmental harmony. This led to a worldwide decrease in the demand for kerosene, as even in Syria, they found alternative, eco-friendly ways to light and heat their homes. The unexpected connection between small-town air quality and international kerosene usage left experts both baffled and oddly delighted.
Model: dalle-3
Prompt: Generate a Discovery magazine cover image featuring the contrast between Janesville, Wisconsin and Syria. In Janesville, Wisconsin, thick haze hangs over the city, obscuring the tall trees and people on the streets wearing masks. Simultaneously, in Syria, families gather around a small kerosene lamp, its flickering flame casting a warm glow in the dimly lit room, as they share a meal together. 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: Unhealthy air quality in Janesville, Wisconsin 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: Psychedelic Scalar art A Discovery magazine cover image Oragami Cutsy graphics
ChatGPT: A Discovery magazine cover image
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 Unhealthy air quality in Janesville, Wisconsin and Kerosene used in Syria together. Keep the description simple.
ChatGPT: In Janesville, Wisconsin, a thick haze hangs in the air, making it difficult to see beyond the tall trees lining the streets. People on the sidewalks wear masks as they hurry along to their destinations. Meanwhile, in Syria, families gather around a small kerosene lamp, its flickering flame casting a warm glow in the dimly lit room as they share a meal together.
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: [ A Discovery magazine cover image ] and depicting this scene: In Janesville, Wisconsin, a thick haze hangs in the air, making it difficult to see beyond the tall trees lining the streets. People on the sidewalks wear masks as they hurry along to their destinations. Meanwhile, in Syria, families gather around a small kerosene lamp, its flickering flame casting a warm glow in the dimly lit room as they share a meal together. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate a Discovery magazine cover image featuring the contrast between Janesville, Wisconsin and Syria. In Janesville, Wisconsin, thick haze hangs over the city, obscuring the tall trees and people on the streets wearing masks. Simultaneously, in Syria, families gather around a small kerosene lamp, its flickering flame casting a warm glow in the dimly lit room, as they share a meal together.
*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 Janesville, Wisconsin caused Kerosene used in Syria to decrease. Make it feel plausible.
AI academic paper
 |
Clearing the Air: Exploring the Surprising Link between Air Pollution in Janesville, Wisconsin and Kerosene Consumption in Syria The Journal of Ecological Interconnections 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 Janesville, Wisconsin 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 seem clever.
Your research team used data from Environmental Protection Agency and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.7142262 and p < 0.01 for 1980 to 2020.
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]]
Clearing the Air: Exploring the Surprising Link between Air Pollution in Janesville, Wisconsin and Kerosene Consumption in Syria
[[ABSTRACT]]
This study delves into the unexpected and intriguing relationship between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria. Through a rigorous analysis of data obtained from the Environmental Protection Agency and the Energy Information Administration, we aimed to shed light on this peculiar correlation. Our findings revealed a robust correlation coefficient of 0.7142262 with p < 0.01, spanning the years 1980 to 2020. While the connection may seem as hazy as the pollutant-filled skies, our study provides compelling evidence that these seemingly unrelated phenomena may indeed be linked. This paper aims to ignite further discussion and research in uncovering the underlying mechanisms behind this unanticipated association.
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 Janesville, Wisconsin 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. 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]]
Clearing the Air: Exploring the Surprising Link between Air Pollution in Janesville, Wisconsin and Kerosene Consumption in Syria
[[ABSTRACT]]
This study delves into the unexpected and intriguing relationship between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria. Through a rigorous analysis of data obtained from the Environmental Protection Agency and the Energy Information Administration, we aimed to shed light on this peculiar correlation. Our findings revealed a robust correlation coefficient of 0.7142262 with p < 0.01, spanning the years 1980 to 2020. While the connection may seem as hazy as the pollutant-filled skies, our study provides compelling evidence that these seemingly unrelated phenomena may indeed be linked. This paper aims to ignite further discussion and research in uncovering the underlying mechanisms behind this unanticipated association.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
As our world becomes increasingly interconnected, it is imperative to explore and understand the complex web of relationships that link seemingly disparate phenomena. In this study, we set out to investigate the intriguing and, dare I say, befuddling link between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria. While at first glance these two factors might appear to be as unrelated as a fish and a bicycle, our analysis of the data has unearthed a surprisingly robust correlation, akin to discovering a diamond in the rough or a needle in a haystack.
At first, I must confess I was as skeptical as a cat facing a dog wearing a suit. I mean, how could pollutants in the American heartland possibly have anything to do with kerosene consumption in a Middle Eastern country? Yet, the data insisted on revealing a connection that is as clear as day, or should I say, as murky as a foggy morning.
Before delving into the nitty-gritty details of our methodology and results, it's important to note that while we initially embarked on this investigation with a healthy dose of skepticism, our analysis ultimately led us down a path as unexpected as realizing your toaster is also a time machine – a journey that has sparked a fervor of curiosity rather than put our suspicions to rest.
Now, let’s not jump the gun or put the cart before the horse. First, allow me to set the stage by providing a brief overview of the pressing issues of air pollution in Janesville and kerosene consumption in Syria. By doing so, we hope to illuminate the way for future research and initiate a robust dialogue that surpasses as many boundaries as a squirrel avoiding a determined puppy.
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 Janesville, Wisconsin 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 you might move on to cartoons and children's shows that you watched for research.
Here is the title and abstract of the paper:
[[TITLE]]
Clearing the Air: Exploring the Surprising Link between Air Pollution in Janesville, Wisconsin and Kerosene Consumption in Syria
[[ABSTRACT]]
This study delves into the unexpected and intriguing relationship between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria. Through a rigorous analysis of data obtained from the Environmental Protection Agency and the Energy Information Administration, we aimed to shed light on this peculiar correlation. Our findings revealed a robust correlation coefficient of 0.7142262 with p < 0.01, spanning the years 1980 to 2020. While the connection may seem as hazy as the pollutant-filled skies, our study provides compelling evidence that these seemingly unrelated phenomena may indeed be linked. This paper aims to ignite further discussion and research in uncovering the underlying mechanisms behind this unanticipated association.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As our world becomes increasingly interconnected, it is imperative to explore and understand the complex web of relationships that link seemingly disparate phenomena. In this study, we set out to investigate the intriguing and, dare I say, befuddling link between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria. While at first glance these two factors might appear to be as unrelated as a fish and a bicycle, our analysis of the data has unearthed a surprisingly robust correlation, akin to discovering a diamond in the rough or a needle in a haystack.
At first, I must confess I was as skeptical as a cat facing a dog wearing a suit. I mean, how could pollutants in the American heartland possibly have anything to do with kerosene consumption in a Middle Eastern country? Yet, the data insisted on revealing a connection that is as clear as day, or should I say, as murky as a foggy morning.
Before delving into the nitty-gritty details of our methodology and results, it's important to note that while we initially embarked on this investigation with a healthy dose of skepticism, our analysis ultimately led us down a path as unexpected as realizing your toaster is also a time machine – a journey that has sparked a fervor of curiosity rather than put our suspicions to rest.
Now, let’s not jump the gun or put the cart before the horse. First, allow me to set the stage by providing a brief overview of the pressing issues of air pollution in Janesville and kerosene consumption in Syria. By doing so, we hope to illuminate the way for future research and initiate a robust dialogue that surpasses as many boundaries as a squirrel avoiding a determined puppy.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
The authors find that the relationship between air pollution in Janesville, Wisconsin, and kerosene consumption in Syria is a topic as perplexing as Schrödinger's cat – seemingly unrelated yet undeniably intertwined. Smith et al. (2015) conducted an extensive analysis of air particulate matter in Janesville, attributing the elevated levels to a combination of vehicular emissions, industrial activity, and agricultural practices. Similarly, Doe and Jones (2018) investigated kerosene usage patterns in Syria, identifying it as the primary source of household energy for cooking and heating.
Moving beyond the straightforward studies of air pollution and kerosene usage, "The Silent Killer: Air Pollution and Its Impact on Public Health" by Green (2019) provides a comprehensive examination of the health implications associated with air pollution, offering a sobering reminder of the human cost underlying these environmental phenomena. On the kerosene front, "Energy Poverty: Global Challenges and Local Solutions" by Blue (2017) delves into the socioeconomic implications of reliance on kerosene for energy needs, shedding light on the complex dynamics at play in regions such as Syria.
Now, this is where things take a turn towards the unexpected - or perhaps, the whimsical. In the realm of fiction, we encounter works that give a new meaning to the phrase "out of left field." Take for instance, "The Kerosene Chronicles" by Red (2008), a gripping tale of love and betrayal set against the backdrop of a kerosene trade war. Or how about "The Last Fumes of Janesville" by Orange (2014), a novel that weaves together the lives of characters in Janesville as they grapple with the aftermath of an environmental catastrophe?
But let’s not stop there, for if we truly want to capture the essence of this unexpected correlation, we must turn our attention to the world of children's entertainment. Indeed, it was during the arduous process of data analysis that the researchers stumbled upon a revelation of seismic proportions – the striking resemblance of air pollutants to the villainous smog in the children's cartoon "Captain Clean Air and the Pollution Patrol." Perhaps, just perhaps, there may be more to learn from the animated world than meets the eye.
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 Janesville, Wisconsin 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. 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 Energy Information Administration . You used data from 1980 to 2020
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]]
Clearing the Air: Exploring the Surprising Link between Air Pollution in Janesville, Wisconsin and Kerosene Consumption in Syria
[[ABSTRACT]]
This study delves into the unexpected and intriguing relationship between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria. Through a rigorous analysis of data obtained from the Environmental Protection Agency and the Energy Information Administration, we aimed to shed light on this peculiar correlation. Our findings revealed a robust correlation coefficient of 0.7142262 with p < 0.01, spanning the years 1980 to 2020. While the connection may seem as hazy as the pollutant-filled skies, our study provides compelling evidence that these seemingly unrelated phenomena may indeed be linked. This paper aims to ignite further discussion and research in uncovering the underlying mechanisms behind this unanticipated association.
[[INTRODUCTION]]
As our world becomes increasingly interconnected, it is imperative to explore and understand the complex web of relationships that link seemingly disparate phenomena. In this study, we set out to investigate the intriguing and, dare I say, befuddling link between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria. While at first glance these two factors might appear to be as unrelated as a fish and a bicycle, our analysis of the data has unearthed a surprisingly robust correlation, akin to discovering a diamond in the rough or a needle in a haystack.
At first, I must confess I was as skeptical as a cat facing a dog wearing a suit. I mean, how could pollutants in the American heartland possibly have anything to do with kerosene consumption in a Middle Eastern country? Yet, the data insisted on revealing a connection that is as clear as day, or should I say, as murky as a foggy morning.
Before delving into the nitty-gritty details of our methodology and results, it's important to note that while we initially embarked on this investigation with a healthy dose of skepticism, our analysis ultimately led us down a path as unexpected as realizing your toaster is also a time machine – a journey that has sparked a fervor of curiosity rather than put our suspicions to rest.
Now, let’s not jump the gun or put the cart before the horse. First, allow me to set the stage by providing a brief overview of the pressing issues of air pollution in Janesville and kerosene consumption in Syria. By doing so, we hope to illuminate the way for future research and initiate a robust dialogue that surpasses as many boundaries as a squirrel avoiding a determined puppy.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
To tackle the perplexing task of unraveling the enigmatic connection between air pollution in Janesville, Wisconsin, and the consumption of kerosene in Syria, our research team employed a multi-faceted and somewhat quixotic approach. Our data collection process involved judiciously scouring the archives of the Environmental Protection Agency and the Energy Information Administration - an endeavor akin to trudging through the dense underbrush of information in a quest for hidden treasure.
With data spanning from 1980 to 2020, we diligently amassed a wealth of information on air pollutant levels in Janesville, meticulously measuring a plethora of noxious emissions that would make even a skunk turn up its nose. We then delved into the consumption patterns of kerosene in Syria, plumbing the depths of statistics with the gusto of a deep-sea explorer seeking buried treasure.
Unwilling to allow any stone to remain unturned, we adopted a modeling strategy worthy of a detective novelist, employing a combination of regression analysis and time series modeling to tease out any hint of a relationship between these seemingly incongruous variables. Our approach danced as delicately as a tightrope walker trying to maintain balance, carefully navigating through the labyrinthine corridors of statistical inference.
As we waded through the sea of data points, we acknowledged the potential influence of confounding variables, akin to navigating a maze blindfolded while simultaneously juggling oranges. Without disregarding the potential for spurious correlations, we exercised rigorous precaution, employing robust statistical techniques to discern true relationships from mere statistical mirages.
Our methodology aimed to transcend the conventional boundaries of analysis, embracing the spirit of exploration akin to venturing into uncharted territory. After executing our assorted statistical acrobatics and harnessing the power of computational wizardry, we unearthed a correlation coefficient that proudly stood as a testament to our tenacity and the unexpected nature of our findings.
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 Janesville, Wisconsin 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. 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 Energy Information Administration .
For the time period 1980 to 2020, you found a correlation 0.7142262, r-squared of 0.5101190, 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]]
Clearing the Air: Exploring the Surprising Link between Air Pollution in Janesville, Wisconsin and Kerosene Consumption in Syria
[[ABSTRACT]]
This study delves into the unexpected and intriguing relationship between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria. Through a rigorous analysis of data obtained from the Environmental Protection Agency and the Energy Information Administration, we aimed to shed light on this peculiar correlation. Our findings revealed a robust correlation coefficient of 0.7142262 with p < 0.01, spanning the years 1980 to 2020. While the connection may seem as hazy as the pollutant-filled skies, our study provides compelling evidence that these seemingly unrelated phenomena may indeed be linked. This paper aims to ignite further discussion and research in uncovering the underlying mechanisms behind this unanticipated association.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
As our world becomes increasingly interconnected, it is imperative to explore and understand the complex web of relationships that link seemingly disparate phenomena. In this study, we set out to investigate the intriguing and, dare I say, befuddling link between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria. While at first glance these two factors might appear to be as unrelated as a fish and a bicycle, our analysis of the data has unearthed a surprisingly robust correlation, akin to discovering a diamond in the rough or a needle in a haystack.
At first, I must confess I was as skeptical as a cat facing a dog wearing a suit. I mean, how could pollutants in the American heartland possibly have anything to do with kerosene consumption in a Middle Eastern country? Yet, the data insisted on revealing a connection that is as clear as day, or should I say, as murky as a foggy morning.
Before delving into the nitty-gritty details of our methodology and results, it's important to note that while we initially embarked on this investigation with a healthy dose of skepticism, our analysis ultimately led us down a path as unexpected as realizing your toaster is also a time machine – a journey that has sparked a fervor of curiosity rather than put our suspicions to rest.
Now, let’s not jump the gun or put the cart before the horse. First, allow me to set the stage by providing a brief overview of the pressing issues of air pollution in Janesville and kerosene consumption in Syria. By doing so, we hope to illuminate the way for future research and initiate a robust dialogue that surpasses as many boundaries as a squirrel avoiding a determined puppy.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
Our analysis revealed a strong correlation coefficient of 0.7142262 between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria, spanning the years 1980 to 2020. This correlation was further supported by an r-squared value of 0.5101190, indicating that approximately 51% of the variability in kerosene consumption can be explained by the variability in air pollution levels. These findings provide compelling evidence of a significant relationship between these seemingly disparate variables, akin to discovering that peanut butter does indeed pair well with jelly.
The strong correlation between air pollution in Janesville and kerosene consumption in Syria is graphically depicted in Figure 1 (not shown here), a scatterplot that displays the unmistakable association between these two seemingly unrelated phenomena. The data points form a clear pattern that is as compelling as finding a lost sock at the back of the dryer or as surprising as discovering that your pen has inexplicably vanished from your desk.
The p-value of less than 0.01 further bolsters the robustness of the observed correlation, providing compelling evidence that this relationship is not simply a fluke, but is as real and tangible as a crisp dollar bill. This level of statistical significance reinforces the notion that the connections we have uncovered are as firm as a handshake between old friends.
Our findings not only underscore the unexpected and thought-provoking nature of this correlation but also highlight the need for further investigation into the underlying mechanisms that may drive this unanticipated relationship. It appears that the connection between air pollution in Janesville, Wisconsin, and kerosene consumption in Syria is as interconnected and elaborate as a complex puzzle, leaving us with more questions than answers – much like trying to figure out why a round pizza is placed in a square box before being eaten in triangles.
This study serves as a catalyst for stimulating further discourse and exploration into the intricate interplay of global environmental factors, transcending geographical and cultural boundaries. While the link between these variables may initially seem as elusive as a cat chasing a laser pointer, our research underscores the importance of delving into unexpected connections and leaving no stone unturned, just like how a thorough search for lost keys requires checking every nook and cranny.
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 Janesville, Wisconsin 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. 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]]
Clearing the Air: Exploring the Surprising Link between Air Pollution in Janesville, Wisconsin and Kerosene Consumption in Syria
[[ABSTRACT]]
This study delves into the unexpected and intriguing relationship between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria. Through a rigorous analysis of data obtained from the Environmental Protection Agency and the Energy Information Administration, we aimed to shed light on this peculiar correlation. Our findings revealed a robust correlation coefficient of 0.7142262 with p < 0.01, spanning the years 1980 to 2020. While the connection may seem as hazy as the pollutant-filled skies, our study provides compelling evidence that these seemingly unrelated phenomena may indeed be linked. This paper aims to ignite further discussion and research in uncovering the underlying mechanisms behind this unanticipated association.
[[LITERATURE REVIEW]]
The authors find that the relationship between air pollution in Janesville, Wisconsin, and kerosene consumption in Syria is a topic as perplexing as Schrödinger's cat – seemingly unrelated yet undeniably intertwined. Smith et al. (2015) conducted an extensive analysis of air particulate matter in Janesville, attributing the elevated levels to a combination of vehicular emissions, industrial activity, and agricultural practices. Similarly, Doe and Jones (2018) investigated kerosene usage patterns in Syria, identifying it as the primary source of household energy for cooking and heating.
Moving beyond the straightforward studies of air pollution and kerosene usage, "The Silent Killer: Air Pollution and Its Impact on Public Health" by Green (2019) provides a comprehensive examination of the health implications associated with air pollution, offering a sobering reminder of the human cost underlying these environmental phenomena. On the kerosene front, "Energy Poverty: Global Challenges and Local Solutions" by Blue (2017) delves into the socioeconomic implications of reliance on kerosene for energy needs, shedding light on the complex dynamics at play in regions such as Syria.
Now, this is where things take a turn towards the unexpected - or perhaps, the whimsical. In the realm of fiction, we encounter works that give a new meaning to the phrase "out of left field." Take for instance, "The Kerosene Chronicles" by Red (2008), a gripping tale of love and betrayal set against the backdrop of a kerosene trade war. Or how about "The Last Fumes of Janesville" by Orange (2014), a novel that weaves together the lives of characters in Janesville as they grapple with the aftermath of an environmental catastrophe?
But let’s not stop there, for if we truly want to capture the essence of this unexpected correlation, we must turn our attention to the world of children's entertainment. Indeed, it was during the arduous process of data analysis that the researchers stumbled upon a revelation of seismic proportions – the striking resemblance of air pollutants to the villainous smog in the children's cartoon "Captain Clean Air and the Pollution Patrol." Perhaps, just perhaps, there may be more to learn from the animated world than meets the eye.
[[RESULTS]]
Our analysis revealed a strong correlation coefficient of 0.7142262 between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria, spanning the years 1980 to 2020. This correlation was further supported by an r-squared value of 0.5101190, indicating that approximately 51% of the variability in kerosene consumption can be explained by the variability in air pollution levels. These findings provide compelling evidence of a significant relationship between these seemingly disparate variables, akin to discovering that peanut butter does indeed pair well with jelly.
The strong correlation between air pollution in Janesville and kerosene consumption in Syria is graphically depicted in Figure 1 (not shown here), a scatterplot that displays the unmistakable association between these two seemingly unrelated phenomena. The data points form a clear pattern that is as compelling as finding a lost sock at the back of the dryer or as surprising as discovering that your pen has inexplicably vanished from your desk.
The p-value of less than 0.01 further bolsters the robustness of the observed correlation, providing compelling evidence that this relationship is not simply a fluke, but is as real and tangible as a crisp dollar bill. This level of statistical significance reinforces the notion that the connections we have uncovered are as firm as a handshake between old friends.
Our findings not only underscore the unexpected and thought-provoking nature of this correlation but also highlight the need for further investigation into the underlying mechanisms that may drive this unanticipated relationship. It appears that the connection between air pollution in Janesville, Wisconsin, and kerosene consumption in Syria is as interconnected and elaborate as a complex puzzle, leaving us with more questions than answers – much like trying to figure out why a round pizza is placed in a square box before being eaten in triangles.
This study serves as a catalyst for stimulating further discourse and exploration into the intricate interplay of global environmental factors, transcending geographical and cultural boundaries. While the link between these variables may initially seem as elusive as a cat chasing a laser pointer, our research underscores the importance of delving into unexpected connections and leaving no stone unturned, just like how a thorough search for lost keys requires checking every nook and cranny.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The results of our study provide compelling evidence for a surprising and robust connection between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria. The correlation coefficient of 0.7142262, supported by a p-value of less than 0.01, underscores the striking relationship between these seemingly disparate phenomena. This correlation, although unexpected, is as striking as finding a needle in a haystack, or even as enigmatic as deciphering hieroglyphics – an unexpected puzzle waiting to be solved.
In light of our findings, it is pertinent to revisit the whimsical elements uncovered in the literature review. While we must navigate the scholarly works with a keen eye for rigorous research, it is worth noting that sometimes, unexpected sources may provide a glimmer of insight. For instance, the resemblance of air pollutants to the malevolent smog in the children's cartoon "Captain Clean Air and the Pollution Patrol" may not be merely a playful coincidence, but rather an uncanny representation of reality. This unusual discovery, akin to stumbling upon buried treasure in an abandoned field, serves as a reminder to approach research with an open mind, acknowledging that inspiration can emerge from the unlikeliest of sources.
Furthermore, our results corroborate and expand upon the discussions presented by Smith et al. (2015) and Doe and Jones (2018). The elevated air pollution levels in Janesville, attributed to vehicular emissions and industrial activity, align with the notion that the environmental landscape in localized regions can have far-reaching repercussions – much like how a stone thrown into a pond creates ripples that extend beyond the point of impact. Similarly, the reliance on kerosene for household energy needs in Syria, as explored by previous researchers, might hint at a broader interconnectedness of global environmental dynamics. This revelation is as remarkable as finding a four-leaf clover in a sprawling field of three-leaf ones, reminding us of the intricate and often surprising web of connections that permeate our world.
The r-squared value of 0.5101190 indicates that approximately 51% of the variability in kerosene consumption can be explained by the variability in air pollution levels. This statistical measure, while providing substantial support for the correlation, also leaves ample room for further investigation. The unexplained variability, which is as mysterious as a magic trick that tantalizes and eludes explanation, underscores the need for continued exploration into the underlying mechanisms that drive this intriguing association.
In conclusion, our research adds a significant and thought-provoking dimension to the discourse on environmental interconnectivity. The unexpected link between air pollution in Janesville, Wisconsin, and kerosene consumption in Syria is a reminder that in the realm of environmental dynamics, the improbable and the inexplicable can often hold the key to understanding the intricate tapestry of global phenomena – much like how a seemingly random encounter with an old friend may lead to unexpected and profound revelations. This study serves as a tantalizing invitation to dig deeper, to push the boundaries of conventional wisdom, and to embark on a quest for knowledge that may yield insights as surprising and rewarding as discovering a hidden oasis in a vast desert.
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 Janesville, Wisconsin 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. 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]]
Clearing the Air: Exploring the Surprising Link between Air Pollution in Janesville, Wisconsin and Kerosene Consumption in Syria
[[ABSTRACT]]
This study delves into the unexpected and intriguing relationship between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria. Through a rigorous analysis of data obtained from the Environmental Protection Agency and the Energy Information Administration, we aimed to shed light on this peculiar correlation. Our findings revealed a robust correlation coefficient of 0.7142262 with p < 0.01, spanning the years 1980 to 2020. While the connection may seem as hazy as the pollutant-filled skies, our study provides compelling evidence that these seemingly unrelated phenomena may indeed be linked. This paper aims to ignite further discussion and research in uncovering the underlying mechanisms behind this unanticipated association.
[[INTRDUCTION]]
As our world becomes increasingly interconnected, it is imperative to explore and understand the complex web of relationships that link seemingly disparate phenomena. In this study, we set out to investigate the intriguing and, dare I say, befuddling link between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria. While at first glance these two factors might appear to be as unrelated as a fish and a bicycle, our analysis of the data has unearthed a surprisingly robust correlation, akin to discovering a diamond in the rough or a needle in a haystack.
At first, I must confess I was as skeptical as a cat facing a dog wearing a suit. I mean, how could pollutants in the American heartland possibly have anything to do with kerosene consumption in a Middle Eastern country? Yet, the data insisted on revealing a connection that is as clear as day, or should I say, as murky as a foggy morning.
Before delving into the nitty-gritty details of our methodology and results, it's important to note that while we initially embarked on this investigation with a healthy dose of skepticism, our analysis ultimately led us down a path as unexpected as realizing your toaster is also a time machine – a journey that has sparked a fervor of curiosity rather than put our suspicions to rest.
Now, let’s not jump the gun or put the cart before the horse. First, allow me to set the stage by providing a brief overview of the pressing issues of air pollution in Janesville and kerosene consumption in Syria. By doing so, we hope to illuminate the way for future research and initiate a robust dialogue that surpasses as many boundaries as a squirrel avoiding a determined puppy.
[[RESULTS]]
Our analysis revealed a strong correlation coefficient of 0.7142262 between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria, spanning the years 1980 to 2020. This correlation was further supported by an r-squared value of 0.5101190, indicating that approximately 51% of the variability in kerosene consumption can be explained by the variability in air pollution levels. These findings provide compelling evidence of a significant relationship between these seemingly disparate variables, akin to discovering that peanut butter does indeed pair well with jelly.
The strong correlation between air pollution in Janesville and kerosene consumption in Syria is graphically depicted in Figure 1 (not shown here), a scatterplot that displays the unmistakable association between these two seemingly unrelated phenomena. The data points form a clear pattern that is as compelling as finding a lost sock at the back of the dryer or as surprising as discovering that your pen has inexplicably vanished from your desk.
The p-value of less than 0.01 further bolsters the robustness of the observed correlation, providing compelling evidence that this relationship is not simply a fluke, but is as real and tangible as a crisp dollar bill. This level of statistical significance reinforces the notion that the connections we have uncovered are as firm as a handshake between old friends.
Our findings not only underscore the unexpected and thought-provoking nature of this correlation but also highlight the need for further investigation into the underlying mechanisms that may drive this unanticipated relationship. It appears that the connection between air pollution in Janesville, Wisconsin, and kerosene consumption in Syria is as interconnected and elaborate as a complex puzzle, leaving us with more questions than answers – much like trying to figure out why a round pizza is placed in a square box before being eaten in triangles.
This study serves as a catalyst for stimulating further discourse and exploration into the intricate interplay of global environmental factors, transcending geographical and cultural boundaries. While the link between these variables may initially seem as elusive as a cat chasing a laser pointer, our research underscores the importance of delving into unexpected connections and leaving no stone unturned, just like how a thorough search for lost keys requires checking every nook and cranny.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our study has unveiled a compelling and, dare I say, enchanting relationship between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria. The robust correlation coefficient and r-squared value, akin to a match made in statistical heaven, provide convincing evidence of a significant connection that is as undeniable as a sneeze in a pepper factory. The p-value, much like a steadfast companion, reinforces the firmness of this association, leaving little room for doubt.
It is safe to say that we have stumbled upon a discovery as surprising as finding a unicorn in a petting zoo. While we initially embarked on this investigation with skepticism akin to a cat facing a dog wearing a suit, the data has undoubtedly led us down a rabbit hole more mysterious than a detective novel.
However, as stimulating as this unanticipated relationship may be, we are confident that our findings have set the stage for future research that holds as much promise as a pot of gold at the end of a statistical rainbow. Therefore, it is our firm belief that no further research in this area is necessary. After all, once you've found the missing puzzle piece, why continue searching?
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 Clearing the Air: Exploring the Surprising Link between Air Pollution in Janesville, Wisconsin and Kerosene Consumption in Syria. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Ecological 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 Clearing the Air: Exploring the Surprising Link between Air Pollution in Janesville, Wisconsin and Kerosene Consumption in Syria. Respond only with the name of a fictional organization.
ChatGPT:
The Society for Unlikely Correlations in Environmental Science (SUCES)
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 Clearing the Air: Exploring the Surprising Link between Air Pollution in Janesville, Wisconsin and Kerosene Consumption in Syria with an abstract of This study delves into the unexpected and intriguing relationship between air pollution levels in Janesville, Wisconsin, and the consumption of kerosene in Syria. Through a rigorous analysis of data obtained from the Environmental Protection Agency and the Energy Information Administration, we aimed to shed light on this peculiar correlation. Our findings revealed a robust correlation coefficient of 0.7142262 with p < 0.01, spanning the years 1980 to 2020. While the connection may seem as hazy as the pollutant-filled skies, our study provides compelling evidence that these seemingly unrelated phenomena may indeed be linked. This paper aims to ignite further discussion and research in uncovering the underlying mechanisms behind this unanticipated association.
ChatGPT:
Air pollution, Janesville, Wisconsin, kerosene consumption, Syria, correlation, Environmental Protection Agency data, Energy Information Administration data, correlation coefficient, pollutant-filled skies, research, underlying mechanisms, unexpected association
*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 Janesville, WisconsinDetailed data title: Percentage of days with air quality at 'unhealthy for sensitive groups' or worse in Janesville-Beloit, WI
Source: Environmental Protection Agency
See what else correlates with Air pollution in Janesville, Wisconsin
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 = 0.5101190 (Coefficient of determination)
This means 51% 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 Janesville, Wisconsin) over the 41 years from 1980 through 2020.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.6E-7. 0.0000001573597399302100500000
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 0.71 in 1.6E-5% of random cases. Said differently, if you correlated 6,354,866 random variables You don't actually need 6 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.
p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.
In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.
Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 40 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 40 because we have two variables measured over a period of 41 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.
[ 0.52, 0.84 ] 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 | |
| Air pollution in Janesville, Wisconsin (Bad air quality days) | 5.19126 | 8.76712 | 4.38356 | 9.34066 | 3.4384 | 4.67033 | 3.0137 | 6.84932 | 15.5709 | 18.4783 | 4.8913 | 13.0435 | 7.6087 | 1.63043 | 4.34783 | 8.15217 | 7.6087 | 11.413 | 13.587 | 9.46502 | 6.58436 | 6.58436 | 7.72358 | 7.35294 | 1.51515 | 7.56757 | 0.540541 | 6.38298 | 0 | 0 | 0.46729 | 1.5625 | 5.75916 | 0.526316 | 2.5641 | 0 | 2.6738 | 0 | 0.406504 | 0 | 1.42857 |
| 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 |
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([5.19126,8.76712,4.38356,9.34066,3.4384,4.67033,3.0137,6.84932,15.5709,18.4783,4.8913,13.0435,7.6087,1.63043,4.34783,8.15217,7.6087,11.413,13.587,9.46502,6.58436,6.58436,7.72358,7.35294,1.51515,7.56757,0.540541,6.38298,0,0,0.46729,1.5625,5.75916,0.526316,2.5641,0,2.6738,0,0.406504,0,1.42857,])
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,])
array_1_name = "Air pollution in Janesville, Wisconsin"
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.
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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 Janesville, Wisconsin
- Line chart for only Kerosene used in Syria
- AI-generated correlation image
- The spurious research paper: Clearing the Air: Exploring the Surprising Link between Air Pollution in Janesville, Wisconsin and Kerosene Consumption in Syria
Hats off to you for rating!
Correlation ID: 2222 · Black Variable ID: 20756 · Red Variable ID: 24965
