AI explanation
As the smog in Davenport rose, it created a competitive atmosphere among the residents. They were simply fueled to out-pollute each other, leading to an uptick in Fossil fuel use in El Salvador. It seems the dirty air in one place can really ignite a fiery drive for pollution in another!Model: dalle-3
Prompt: Generate an image that embodies the competitive and combustible nature of air pollution. In the forefront, a bustling scene of Davenport, Iowa, where thick smog veils the city and residents engage in a fierce competition to out-pollute each other. The atmosphere is tense, charged with rivalry, and the air quality visibly deteriorates. In the background, the smog from Davenport crosses continents and ignites a fiery drive for pollution in El Salvador, where the rise in fossil fuel use exacerbates the environmental impact. The juxtaposition of these scenes should visually convey the competitive and polluting dynamics between the two locations, capturing the intense and interconnected nature of air pollution. The cyber art style should emphasize a futuristic and data-driven representation of these environmental challenges. 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 Davenport, Iowa and Fossil fuel use in El Salvador. 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: Data cyber art Photorealism Whimsical illustration Low poly Oragami
ChatGPT: Data cyber art
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 Davenport, Iowa and Fossil fuel use in El Salvador, in the following situation: As the smog in Davenport rose, it created a competitive atmosphere among the residents. They were simply fueled to out-pollute each other, leading to an uptick in Fossil fuel use in El Salvador. It seems the dirty air in one place can really ignite a fiery drive for pollution in another!. Keep the description simple.
ChatGPT: In Davenport, Iowa, thick smog fills the air, creating a competitive atmosphere among the residents. They fiercely try to out-pollute each other, leading to an increase in air pollution. Meanwhile, in El Salvador, the rise in fossil fuel use is evident as the smog from Davenport seems to ignite a fiery drive for pollution in the country.
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: [ Data cyber art ] and depicting this scene: In Davenport, Iowa, thick smog fills the air, creating a competitive atmosphere among the residents. They fiercely try to out-pollute each other, leading to an increase in air pollution. Meanwhile, in El Salvador, the rise in fossil fuel use is evident as the smog from Davenport seems to ignite a fiery drive for pollution in the country. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that embodies the competitive and combustible nature of air pollution. In the forefront, a bustling scene of Davenport, Iowa, where thick smog veils the city and residents engage in a fierce competition to out-pollute each other. The atmosphere is tense, charged with rivalry, and the air quality visibly deteriorates. In the background, the smog from Davenport crosses continents and ignites a fiery drive for pollution in El Salvador, where the rise in fossil fuel use exacerbates the environmental impact. The juxtaposition of these scenes should visually convey the competitive and polluting dynamics between the two locations, capturing the intense and interconnected nature of air pollution. The cyber art style should emphasize a futuristic and data-driven representation of these environmental challenges.
*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 an increase in Air pollution in Davenport, Iowa caused Fossil fuel use in El Salvador to increase. Include one good pun.
AI academic paper
A Breath of Fossil Air: Examining the Gas-tly Link Between Air Pollution in Davenport, Iowa and Fossil Fuel Use in El Salvador The Journal of Environmental Spooktology Jan 2024 |
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 Davenport, Iowa and Fossil fuel use in El Salvador. Make lots of 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 0.8760437 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]]
"A Breath of Fossil Air: Examining the Gas-tly Link Between Air Pollution in Davenport, Iowa and Fossil Fuel Use in El Salvador"
[[ABSTRACT]]
In this study, we tackle the alarming connection between air pollution in Davenport, Iowa and fossil fuel use in El Salvador, all while trying not to "choke" on the results. Using data from the Environmental Protection Agency and Energy Information Administration, we embarked on a journey to uncover the buried treasure of correlation. Our findings revealed a significant correlation coefficient of 0.8760437 and p < 0.01 for the years 1980 to 2021, suggesting that the air pollution in Davenport might not be an isolated "gas" issue. Through this gas-tounding research, we hope to open new avenues for addressing air pollution and fossil fuel use that will leave our readers "breathless."
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 Davenport, Iowa and Fossil fuel use in El Salvador. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Here is the title and abstract of the paper:
[[TITLE]]
"A Breath of Fossil Air: Examining the Gas-tly Link Between Air Pollution in Davenport, Iowa and Fossil Fuel Use in El Salvador"
[[ABSTRACT]]
In this study, we tackle the alarming connection between air pollution in Davenport, Iowa and fossil fuel use in El Salvador, all while trying not to "choke" on the results. Using data from the Environmental Protection Agency and Energy Information Administration, we embarked on a journey to uncover the buried treasure of correlation. Our findings revealed a significant correlation coefficient of 0.8760437 and p < 0.01 for the years 1980 to 2021, suggesting that the air pollution in Davenport might not be an isolated "gas" issue. Through this gas-tounding research, we hope to open new avenues for addressing air pollution and fossil fuel use that will leave our readers "breathless."
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
Take a deep breath, dear readers, because we are about to dive into an air-raising exploration of the gas-tly link between air pollution in Davenport, Iowa and fossil fuel use in El Salvador. As we navigate the murky waters of environmental data, we hope to shed some light on the "fossil"ating relationship between these two seemingly disparate locations. Our research aims to answer the pressing question: is there a breath-taking connection between air pollution in Davenport and the fossil fuel use in El Salvador, or are we just blowing hot air?
Now, before we get too "winded," let's be clear about our approach. We are not here to simply "vent" about air pollution or to fossil-ize the discussion on fossil fuels. Instead, we are on a quest to unearth the statistical evidence that may help us understand the invisible threads that tie these two phenomena together. And believe us, the data we've collected will leave you gasping for air, or perhaps longing for a breath of fresh, fossil-free air.
Our investigation involves delving into the atmospheric soup of air quality measures, emissions data, and energy consumption statistics. We sought to sniff out any whiff of correlation or causation between air pollution in Davenport and the fossil fuel use in El Salvador, with a keen eye on staying grounded in the principles of rigorous statistical analysis. After all, we wouldn't want to cloud the issue with mere speculation or anecdotal evidence - that's not how we roll here in the world of research and number-crunching.
As we take you through our findings, brace yourselves for some "gas-ping" revelations. Our pursuit of scientific discovery has been fueled by a relentless desire to bring clarity to the complex interplay of atmospheric pollutants and energy production practices. And in the process, we just might unearth some gems of insight that will have you saying, "You've got to be smog-ging kidding me!"
So, fasten your seatbelts and get ready for a journey as turbulent as an unexpected gust of wind. Our mission is to uncover the "breeze" behind the correlation, to blow away any doubts about the significance of our results, and to leave you with a newfound appreciation for the electrifying world of environmental statistics. Let's clear the air and embark on this "gas-tounding" adventure together!
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 Davenport, Iowa and Fossil fuel use in El Salvador. Make lots of jokes, goofy observations, and puns.
Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.
Make up the lorem and ipsum part, but make it sound related to the topic at hand.
Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Perhaps you also got inspiration from some board games that are vaugely related.
Here is the title and abstract of the paper:
[[TITLE]]
"A Breath of Fossil Air: Examining the Gas-tly Link Between Air Pollution in Davenport, Iowa and Fossil Fuel Use in El Salvador"
[[ABSTRACT]]
In this study, we tackle the alarming connection between air pollution in Davenport, Iowa and fossil fuel use in El Salvador, all while trying not to "choke" on the results. Using data from the Environmental Protection Agency and Energy Information Administration, we embarked on a journey to uncover the buried treasure of correlation. Our findings revealed a significant correlation coefficient of 0.8760437 and p < 0.01 for the years 1980 to 2021, suggesting that the air pollution in Davenport might not be an isolated "gas" issue. Through this gas-tounding research, we hope to open new avenues for addressing air pollution and fossil fuel use that will leave our readers "breathless."
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Take a deep breath, dear readers, because we are about to dive into an air-raising exploration of the gas-tly link between air pollution in Davenport, Iowa and fossil fuel use in El Salvador. As we navigate the murky waters of environmental data, we hope to shed some light on the "fossil"ating relationship between these two seemingly disparate locations. Our research aims to answer the pressing question: is there a breath-taking connection between air pollution in Davenport and the fossil fuel use in El Salvador, or are we just blowing hot air?
Now, before we get too "winded," let's be clear about our approach. We are not here to simply "vent" about air pollution or to fossil-ize the discussion on fossil fuels. Instead, we are on a quest to unearth the statistical evidence that may help us understand the invisible threads that tie these two phenomena together. And believe us, the data we've collected will leave you gasping for air, or perhaps longing for a breath of fresh, fossil-free air.
Our investigation involves delving into the atmospheric soup of air quality measures, emissions data, and energy consumption statistics. We sought to sniff out any whiff of correlation or causation between air pollution in Davenport and the fossil fuel use in El Salvador, with a keen eye on staying grounded in the principles of rigorous statistical analysis. After all, we wouldn't want to cloud the issue with mere speculation or anecdotal evidence - that's not how we roll here in the world of research and number-crunching.
As we take you through our findings, brace yourselves for some "gas-ping" revelations. Our pursuit of scientific discovery has been fueled by a relentless desire to bring clarity to the complex interplay of atmospheric pollutants and energy production practices. And in the process, we just might unearth some gems of insight that will have you saying, "You've got to be smog-ging kidding me!"
So, fasten your seatbelts and get ready for a journey as turbulent as an unexpected gust of wind. Our mission is to uncover the "breeze" behind the correlation, to blow away any doubts about the significance of our results, and to leave you with a newfound appreciation for the electrifying world of environmental statistics. Let's clear the air and embark on this "gas-tounding" adventure together!
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
Our journey into the tangled web of air pollution in Davenport, Iowa and fossil fuel use in El Salvador led us to a myriad of scholarly works that sought to unravel the mysteries of atmospheric dynamics and energy consumption patterns. Notably, Smith et al. (2015) conducted a comprehensive analysis of air quality indices in Midwestern urban centers, including Davenport, shedding light on the pervasive nature of particulate matter and ozone. However, while Smith et al. focused on local emissions, our investigation stretches beyond borders to link these emissions to the fossil fuel use in El Salvador, making our study as expansive as the horizon itself.
Doe and Jones (2018) delved into the intricate web of global energy consumption trends, providing a panoramic view of fossil fuel use across continents. Their work laid the groundwork for cross-national comparisons, allowing us to draw parallels between the consumption of fossil fuels in El Salvador and the air pollution levels in Davenport. It's like connecting the dots in a cosmic connect-the-dots puzzle, only with more fossil fuels and less stardust.
In "Dr. Seuss's Guide to Fossil Fuel Fantasies," the illustrious author takes a whimsical approach to energy production and its impact on the environment. Though the book may not be a scholarly tome, its playful commentary on humankind's voracious appetite for fossil fuels showcases the universal relevance of our research topic. After all, as Dr. Seuss so eloquently put it, "Unless someone like you cares a whole awful lot, nothing is going to get better. It's not."
Turning to fiction, "The Coal Chronicles" by J.K. Rowling paints a vivid and, at times, harrowing picture of a world powered by coal. While a work of fiction, the novel compellingly illustrates the societal dependence on fossil fuels and the consequences of unchecked pollution. It's as though Rowling's magical world of wizardry and whimsy is a metaphor for our own world, where the allure of energy production is both tantalizing and treacherous.
From the realm of board games, "Smokestacks & Ladders" provides a playful simulation of industrial growth and its environmental repercussions. The game's premise echoes the real-life trade-offs between economic development and air quality, offering players a chance to navigate the complexities of energy production and pollution management. Indeed, our research mirrors the twists and turns of this game, as we strive to climb the ladder of understanding while avoiding the pitfalls of misinformation and ambiguity.
As we reflect on these diverse sources, it becomes clear that the "air-raising" link between air pollution in Davenport and fossil fuel use in El Salvador transcends disciplinary boundaries. Whether through scholarly analysis, imaginative storytelling, or interactive simulations, the interconnectedness of these phenomena rises to the surface, much like a bubble of methane from a forgotten swamp.
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 Davenport, Iowa and Fossil fuel use in El Salvador. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
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]]
"A Breath of Fossil Air: Examining the Gas-tly Link Between Air Pollution in Davenport, Iowa and Fossil Fuel Use in El Salvador"
[[ABSTRACT]]
In this study, we tackle the alarming connection between air pollution in Davenport, Iowa and fossil fuel use in El Salvador, all while trying not to "choke" on the results. Using data from the Environmental Protection Agency and Energy Information Administration, we embarked on a journey to uncover the buried treasure of correlation. Our findings revealed a significant correlation coefficient of 0.8760437 and p < 0.01 for the years 1980 to 2021, suggesting that the air pollution in Davenport might not be an isolated "gas" issue. Through this gas-tounding research, we hope to open new avenues for addressing air pollution and fossil fuel use that will leave our readers "breathless."
[[INTRODUCTION]]
Take a deep breath, dear readers, because we are about to dive into an air-raising exploration of the gas-tly link between air pollution in Davenport, Iowa and fossil fuel use in El Salvador. As we navigate the murky waters of environmental data, we hope to shed some light on the "fossil"ating relationship between these two seemingly disparate locations. Our research aims to answer the pressing question: is there a breath-taking connection between air pollution in Davenport and the fossil fuel use in El Salvador, or are we just blowing hot air?
Now, before we get too "winded," let's be clear about our approach. We are not here to simply "vent" about air pollution or to fossil-ize the discussion on fossil fuels. Instead, we are on a quest to unearth the statistical evidence that may help us understand the invisible threads that tie these two phenomena together. And believe us, the data we've collected will leave you gasping for air, or perhaps longing for a breath of fresh, fossil-free air.
Our investigation involves delving into the atmospheric soup of air quality measures, emissions data, and energy consumption statistics. We sought to sniff out any whiff of correlation or causation between air pollution in Davenport and the fossil fuel use in El Salvador, with a keen eye on staying grounded in the principles of rigorous statistical analysis. After all, we wouldn't want to cloud the issue with mere speculation or anecdotal evidence - that's not how we roll here in the world of research and number-crunching.
As we take you through our findings, brace yourselves for some "gas-ping" revelations. Our pursuit of scientific discovery has been fueled by a relentless desire to bring clarity to the complex interplay of atmospheric pollutants and energy production practices. And in the process, we just might unearth some gems of insight that will have you saying, "You've got to be smog-ging kidding me!"
So, fasten your seatbelts and get ready for a journey as turbulent as an unexpected gust of wind. Our mission is to uncover the "breeze" behind the correlation, to blow away any doubts about the significance of our results, and to leave you with a newfound appreciation for the electrifying world of environmental statistics. Let's clear the air and embark on this "gas-tounding" adventure together!
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
To kick off our research endeavor, we gathered an assortment of data from the Environmental Protection Agency and the Energy Information Administration, sourced from the years 1980 to 2021. Our approach to data collection was as meticulous as a detective on the trail of a sneaky suspect, ensuring that no statistical stone was left unturned. Of course, we didn't want to leave any room for statistical entropy to sneak in and "pollute" our results!
Upon securing our treasure trove of data, we embarked on a wild statistical safari, utilizing a sophisticated combination of regression analysis, time series modeling, and multivariate techniques to untangle the web of relationships between air pollution in Davenport, Iowa, and fossil fuel use in El Salvador. Just like intrepid explorers in the jungle, we hacked through the statistical underbrush, dodging potential lurking outliers and quirky autocorrelation patterns along the way.
In our pursuit of statistical truth, we subjected our data to rigorous scrutiny, employing techniques that would make even the most seasoned mathematician raise an eyebrow in admiration. Our statistical toolbox included Pearson's correlation coefficient, structural equation modeling, and perhaps a sprinkle of Bayesian inference for good measure. We also threw in a bit of bootstrapping to ensure that our conclusions were robust enough to withstand the gusts of skepticism that might blow our way.
However, our journey through the statistical rainforest did not stop there. We employed time series analysis to examine the temporal dynamics of air pollution and fossil fuel use, akin to deciphering the rhythmic beats of an ecological symphony. To top it off, we cast a careful eye over the potential confounding variables that could have snuck in, determined to keep our statistical landscape as pristine as a freshly scrubbed laboratory bench.
In summary, our scientific escapade through the maze of data involved a blend of traditional statistical analyses, cutting-edge modeling techniques, and a dash of creativity to tackle the unique challenges posed by the connection between air pollution in Davenport and fossil fuel use in El Salvador. It was a wild ride, but one that has led us to the gas-pening revelations we are about to unveil.
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 Davenport, Iowa and Fossil fuel use in El Salvador. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
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 0.8760437, r-squared of 0.7674526, 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]]
"A Breath of Fossil Air: Examining the Gas-tly Link Between Air Pollution in Davenport, Iowa and Fossil Fuel Use in El Salvador"
[[ABSTRACT]]
In this study, we tackle the alarming connection between air pollution in Davenport, Iowa and fossil fuel use in El Salvador, all while trying not to "choke" on the results. Using data from the Environmental Protection Agency and Energy Information Administration, we embarked on a journey to uncover the buried treasure of correlation. Our findings revealed a significant correlation coefficient of 0.8760437 and p < 0.01 for the years 1980 to 2021, suggesting that the air pollution in Davenport might not be an isolated "gas" issue. Through this gas-tounding research, we hope to open new avenues for addressing air pollution and fossil fuel use that will leave our readers "breathless."
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
Take a deep breath, dear readers, because we are about to dive into an air-raising exploration of the gas-tly link between air pollution in Davenport, Iowa and fossil fuel use in El Salvador. As we navigate the murky waters of environmental data, we hope to shed some light on the "fossil"ating relationship between these two seemingly disparate locations. Our research aims to answer the pressing question: is there a breath-taking connection between air pollution in Davenport and the fossil fuel use in El Salvador, or are we just blowing hot air?
Now, before we get too "winded," let's be clear about our approach. We are not here to simply "vent" about air pollution or to fossil-ize the discussion on fossil fuels. Instead, we are on a quest to unearth the statistical evidence that may help us understand the invisible threads that tie these two phenomena together. And believe us, the data we've collected will leave you gasping for air, or perhaps longing for a breath of fresh, fossil-free air.
Our investigation involves delving into the atmospheric soup of air quality measures, emissions data, and energy consumption statistics. We sought to sniff out any whiff of correlation or causation between air pollution in Davenport and the fossil fuel use in El Salvador, with a keen eye on staying grounded in the principles of rigorous statistical analysis. After all, we wouldn't want to cloud the issue with mere speculation or anecdotal evidence - that's not how we roll here in the world of research and number-crunching.
As we take you through our findings, brace yourselves for some "gas-ping" revelations. Our pursuit of scientific discovery has been fueled by a relentless desire to bring clarity to the complex interplay of atmospheric pollutants and energy production practices. And in the process, we just might unearth some gems of insight that will have you saying, "You've got to be smog-ging kidding me!"
So, fasten your seatbelts and get ready for a journey as turbulent as an unexpected gust of wind. Our mission is to uncover the "breeze" behind the correlation, to blow away any doubts about the significance of our results, and to leave you with a newfound appreciation for the electrifying world of environmental statistics. Let's clear the air and embark on this "gas-tounding" adventure together!
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The results of our study revealed a striking correlation between air pollution in Davenport, Iowa and fossil fuel use in El Salvador, leaving us "gasping" for breath at the significance of this finding. Our analysis yielded a correlation coefficient of 0.8760437, with an r-squared value of 0.7674526 and a p-value of less than 0.01. It's safe to say that these results are statistically significant and not just a bunch of hot air!
Fig. 1 displays a scatterplot that visually captures the strong correlation between these two variables. The data points are so closely clustered together that it's almost as if they're trying to carpool through the realms of statistical significance. Needless to say, the relationship between air pollution in Davenport and fossil fuel use in El Salvador is more than just a fleeting "whiff" of a connection.
Our statistical analysis leaves little room for doubt, as the p-value being less than 0.01 indicates that the likelihood of observing such a strong association by pure chance is about as rare as finding a unicorn in a field of fossilized fuel sources. The correlation coefficient of 0.8760437 speaks volumes about the intertwined nature of these two variables, akin to a never-ending game of environmental "tag."
These findings not only demonstrate the depth of the connection between air pollution in Davenport and fossil fuel use in El Salvador but also underscore the urgent need for collaborative efforts to address this issue. It's time to clear the air and take decisive steps towards reducing the impact of air pollution, so that we all can breathe a little easier.
In conclusion, our research has unearthed a gas-tounding correlation between these seemingly unrelated variables, providing compelling evidence that air pollution in Davenport, Iowa is closely linked to fossil fuel use in El Salvador. Our hope is that this revelation will fuel initiatives to tackle air pollution and promote cleaner, greener energy practices, leaving a breath of fresh air for generations to come.
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 Davenport, Iowa and Fossil fuel use in El Salvador. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
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]]
"A Breath of Fossil Air: Examining the Gas-tly Link Between Air Pollution in Davenport, Iowa and Fossil Fuel Use in El Salvador"
[[ABSTRACT]]
In this study, we tackle the alarming connection between air pollution in Davenport, Iowa and fossil fuel use in El Salvador, all while trying not to "choke" on the results. Using data from the Environmental Protection Agency and Energy Information Administration, we embarked on a journey to uncover the buried treasure of correlation. Our findings revealed a significant correlation coefficient of 0.8760437 and p < 0.01 for the years 1980 to 2021, suggesting that the air pollution in Davenport might not be an isolated "gas" issue. Through this gas-tounding research, we hope to open new avenues for addressing air pollution and fossil fuel use that will leave our readers "breathless."
[[LITERATURE REVIEW]]
Our journey into the tangled web of air pollution in Davenport, Iowa and fossil fuel use in El Salvador led us to a myriad of scholarly works that sought to unravel the mysteries of atmospheric dynamics and energy consumption patterns. Notably, Smith et al. (2015) conducted a comprehensive analysis of air quality indices in Midwestern urban centers, including Davenport, shedding light on the pervasive nature of particulate matter and ozone. However, while Smith et al. focused on local emissions, our investigation stretches beyond borders to link these emissions to the fossil fuel use in El Salvador, making our study as expansive as the horizon itself.
Doe and Jones (2018) delved into the intricate web of global energy consumption trends, providing a panoramic view of fossil fuel use across continents. Their work laid the groundwork for cross-national comparisons, allowing us to draw parallels between the consumption of fossil fuels in El Salvador and the air pollution levels in Davenport. It's like connecting the dots in a cosmic connect-the-dots puzzle, only with more fossil fuels and less stardust.
In "Dr. Seuss's Guide to Fossil Fuel Fantasies," the illustrious author takes a whimsical approach to energy production and its impact on the environment. Though the book may not be a scholarly tome, its playful commentary on humankind's voracious appetite for fossil fuels showcases the universal relevance of our research topic. After all, as Dr. Seuss so eloquently put it, "Unless someone like you cares a whole awful lot, nothing is going to get better. It's not."
Turning to fiction, "The Coal Chronicles" by J.K. Rowling paints a vivid and, at times, harrowing picture of a world powered by coal. While a work of fiction, the novel compellingly illustrates the societal dependence on fossil fuels and the consequences of unchecked pollution. It's as though Rowling's magical world of wizardry and whimsy is a metaphor for our own world, where the allure of energy production is both tantalizing and treacherous.
From the realm of board games, "Smokestacks & Ladders" provides a playful simulation of industrial growth and its environmental repercussions. The game's premise echoes the real-life trade-offs between economic development and air quality, offering players a chance to navigate the complexities of energy production and pollution management. Indeed, our research mirrors the twists and turns of this game, as we strive to climb the ladder of understanding while avoiding the pitfalls of misinformation and ambiguity.
As we reflect on these diverse sources, it becomes clear that the "air-raising" link between air pollution in Davenport and fossil fuel use in El Salvador transcends disciplinary boundaries. Whether through scholarly analysis, imaginative storytelling, or interactive simulations, the interconnectedness of these phenomena rises to the surface, much like a bubble of methane from a forgotten swamp.
[[RESULTS]]
The results of our study revealed a striking correlation between air pollution in Davenport, Iowa and fossil fuel use in El Salvador, leaving us "gasping" for breath at the significance of this finding. Our analysis yielded a correlation coefficient of 0.8760437, with an r-squared value of 0.7674526 and a p-value of less than 0.01. It's safe to say that these results are statistically significant and not just a bunch of hot air!
Fig. 1 displays a scatterplot that visually captures the strong correlation between these two variables. The data points are so closely clustered together that it's almost as if they're trying to carpool through the realms of statistical significance. Needless to say, the relationship between air pollution in Davenport and fossil fuel use in El Salvador is more than just a fleeting "whiff" of a connection.
Our statistical analysis leaves little room for doubt, as the p-value being less than 0.01 indicates that the likelihood of observing such a strong association by pure chance is about as rare as finding a unicorn in a field of fossilized fuel sources. The correlation coefficient of 0.8760437 speaks volumes about the intertwined nature of these two variables, akin to a never-ending game of environmental "tag."
These findings not only demonstrate the depth of the connection between air pollution in Davenport and fossil fuel use in El Salvador but also underscore the urgent need for collaborative efforts to address this issue. It's time to clear the air and take decisive steps towards reducing the impact of air pollution, so that we all can breathe a little easier.
In conclusion, our research has unearthed a gas-tounding correlation between these seemingly unrelated variables, providing compelling evidence that air pollution in Davenport, Iowa is closely linked to fossil fuel use in El Salvador. Our hope is that this revelation will fuel initiatives to tackle air pollution and promote cleaner, greener energy practices, leaving a breath of fresh air for generations to come.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The results of our study leave us not just holding our breath, but also pondering the implications of the gas-tly link between air pollution in Davenport, Iowa and fossil fuel use in El Salvador. Our findings support the prior research conducted by Smith et al. (2015) and Doe and Jones (2018), albeit with a twist of statistical serendipity. Smith’s study on air quality indices in Midwestern urban centers provided a critical backdrop for understanding the localized impact of air pollution, much like setting the stage for a climactic act in a play. Our research stretches that stage across borders, revealing an international drama of emissions and consumption worthy of its own Netflix series.
Meanwhile, we must not discount the whimsical contributions to our literature review. Dr. Seuss’s poignant words cast a shadow on the gravity of our collective environmental responsibility, reminding us that unless we care a whole awful lot, nothing is going to get better - a sentiment that aligns with the urgency echoed in our research. J.K. Rowling’s enchanting tale of coal-powered societies serves as a haunting reminder that our dependence on fossil fuels may lead to a narrative of consequences that we cannot simply wave away with a magic wand. And who could forget "Smokestacks & Ladders," a playful reminder that navigating the complexities of energy production and pollution management can be akin to trying to win in a game with endlessly shifting rules and hurdles.
Returning to the more serious side of things, our results echo the broader narrative of interconnectedness between environmental and energy phenomena. The striking correlation coefficient of 0.8760437 suggests that the relationship between air pollution in Davenport and fossil fuel use in El Salvador is as robust as the gravitational pull of a black hole. The p-value of less than 0.01 speaks volumes about the statistical significance of our findings, leaving little room for doubt that this connection is more than just a fluke in the data.
Our study has ventured into uncharted territory, illustrating the domino effect of energy consumption patterns on air quality, much like a game of Jenga where every move has consequences. It is imperative that we leverage these findings to steer the course toward cleaner, more sustainable energy practices, ensuring that our planet breathes a collective sigh of relief.
In the words of Albert Einstein, "The world as we have created it is a process of our thinking. It cannot be changed without changing our thinking." Our research has provided empirical evidence that calls for a change in thinking when it comes to managing air pollution and fossil fuel use. The implications of this study are as far-reaching as the tendrils of smoke from a factory chimney, and it is our responsibility to harness this knowledge to pave the way for a future where the air is not just cleaner, but also a gas-tly reminder of our commitment to a healthier planet.
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 Davenport, Iowa and Fossil fuel use in El Salvador. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
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]]
"A Breath of Fossil Air: Examining the Gas-tly Link Between Air Pollution in Davenport, Iowa and Fossil Fuel Use in El Salvador"
[[ABSTRACT]]
In this study, we tackle the alarming connection between air pollution in Davenport, Iowa and fossil fuel use in El Salvador, all while trying not to "choke" on the results. Using data from the Environmental Protection Agency and Energy Information Administration, we embarked on a journey to uncover the buried treasure of correlation. Our findings revealed a significant correlation coefficient of 0.8760437 and p < 0.01 for the years 1980 to 2021, suggesting that the air pollution in Davenport might not be an isolated "gas" issue. Through this gas-tounding research, we hope to open new avenues for addressing air pollution and fossil fuel use that will leave our readers "breathless."
[[INTRDUCTION]]
Take a deep breath, dear readers, because we are about to dive into an air-raising exploration of the gas-tly link between air pollution in Davenport, Iowa and fossil fuel use in El Salvador. As we navigate the murky waters of environmental data, we hope to shed some light on the "fossil"ating relationship between these two seemingly disparate locations. Our research aims to answer the pressing question: is there a breath-taking connection between air pollution in Davenport and the fossil fuel use in El Salvador, or are we just blowing hot air?
Now, before we get too "winded," let's be clear about our approach. We are not here to simply "vent" about air pollution or to fossil-ize the discussion on fossil fuels. Instead, we are on a quest to unearth the statistical evidence that may help us understand the invisible threads that tie these two phenomena together. And believe us, the data we've collected will leave you gasping for air, or perhaps longing for a breath of fresh, fossil-free air.
Our investigation involves delving into the atmospheric soup of air quality measures, emissions data, and energy consumption statistics. We sought to sniff out any whiff of correlation or causation between air pollution in Davenport and the fossil fuel use in El Salvador, with a keen eye on staying grounded in the principles of rigorous statistical analysis. After all, we wouldn't want to cloud the issue with mere speculation or anecdotal evidence - that's not how we roll here in the world of research and number-crunching.
As we take you through our findings, brace yourselves for some "gas-ping" revelations. Our pursuit of scientific discovery has been fueled by a relentless desire to bring clarity to the complex interplay of atmospheric pollutants and energy production practices. And in the process, we just might unearth some gems of insight that will have you saying, "You've got to be smog-ging kidding me!"
So, fasten your seatbelts and get ready for a journey as turbulent as an unexpected gust of wind. Our mission is to uncover the "breeze" behind the correlation, to blow away any doubts about the significance of our results, and to leave you with a newfound appreciation for the electrifying world of environmental statistics. Let's clear the air and embark on this "gas-tounding" adventure together!
[[RESULTS]]
The results of our study revealed a striking correlation between air pollution in Davenport, Iowa and fossil fuel use in El Salvador, leaving us "gasping" for breath at the significance of this finding. Our analysis yielded a correlation coefficient of 0.8760437, with an r-squared value of 0.7674526 and a p-value of less than 0.01. It's safe to say that these results are statistically significant and not just a bunch of hot air!
Fig. 1 displays a scatterplot that visually captures the strong correlation between these two variables. The data points are so closely clustered together that it's almost as if they're trying to carpool through the realms of statistical significance. Needless to say, the relationship between air pollution in Davenport and fossil fuel use in El Salvador is more than just a fleeting "whiff" of a connection.
Our statistical analysis leaves little room for doubt, as the p-value being less than 0.01 indicates that the likelihood of observing such a strong association by pure chance is about as rare as finding a unicorn in a field of fossilized fuel sources. The correlation coefficient of 0.8760437 speaks volumes about the intertwined nature of these two variables, akin to a never-ending game of environmental "tag."
These findings not only demonstrate the depth of the connection between air pollution in Davenport and fossil fuel use in El Salvador but also underscore the urgent need for collaborative efforts to address this issue. It's time to clear the air and take decisive steps towards reducing the impact of air pollution, so that we all can breathe a little easier.
In conclusion, our research has unearthed a gas-tounding correlation between these seemingly unrelated variables, providing compelling evidence that air pollution in Davenport, Iowa is closely linked to fossil fuel use in El Salvador. Our hope is that this revelation will fuel initiatives to tackle air pollution and promote cleaner, greener energy practices, leaving a breath of fresh air for generations to come.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
As we wrap up this gas-tastic adventure through the world of environmental statistics, it's clear that our findings have left us "breathless" and gasping for air - pun intended! The correlation coefficient of 0.8760437 and the p-value of less than 0.01 have blown away any doubts about the significant link between air pollution in Davenport and fossil fuel use in El Salvador. It's a correlation so strong that it's like trying to separate two atoms in a covalent bond - nearly impossible!
Our journey has been anything but a walk in the park; it's been more like a hike through a dense fog of statistical analysis and atmospheric data. But fear not, for we have emerged on the other side with a newfound appreciation for the interconnectedness of seemingly disparate phenomena. It's like watching two unlikely friends bond over a mutual love for statistical significance - a heartwarming sight indeed!
Now, before we bid adieu to this research, let's clear the air on one thing: the evidence speaks for itself. The correlation between air pollution in Davenport and fossil fuel use in El Salvador is as clear as a cloudless sky on a crisp autumn day. So, as we take our final breaths of fossil air in this discussion, we assert that no more research is needed in this area. It's time to take the findings and "fan the flames" of change, steering towards cleaner, greener pastures for our planet.
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 A Breath of Fossil Air: Examining the Gas-tly Link Between Air Pollution in Davenport, Iowa and Fossil Fuel Use in El Salvador. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Environmental Spooktology
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 A Breath of Fossil Air: Examining the Gas-tly Link Between Air Pollution in Davenport, Iowa and Fossil Fuel Use in El Salvador. Respond only with the name of a fictional organization.
ChatGPT:
The Institute for Global Air Quality Research and Analysis
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 A Breath of Fossil Air: Examining the Gas-tly Link Between Air Pollution in Davenport, Iowa and Fossil Fuel Use in El Salvador with an abstract of In this study, we tackle the alarming connection between air pollution in Davenport, Iowa and fossil fuel use in El Salvador, all while trying not to "choke" on the results. Using data from the Environmental Protection Agency and Energy Information Administration, we embarked on a journey to uncover the buried treasure of correlation. Our findings revealed a significant correlation coefficient of 0.8760437 and p < 0.01 for the years 1980 to 2021, suggesting that the air pollution in Davenport might not be an isolated "gas" issue. Through this gas-tounding research, we hope to open new avenues for addressing air pollution and fossil fuel use that will leave our readers "breathless.
ChatGPT:
air pollution, Davenport Iowa, fossil fuel use, El Salvador, correlation coefficient, Environmental Protection Agency, Energy Information Administration, addressing air pollution
*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 Davenport, IowaDetailed data title: Percentage of days with moderate or worse air quality in Davenport-Moline-Rock Island, IA-IL
Source: Environmental Protection Agency
See what else correlates with Air pollution in Davenport, Iowa
Fossil fuel use in El Salvador
Detailed data title: Total fossil fuel use in El Salvador in billion kWh
Source: Energy Information Administration
See what else correlates with Fossil fuel use in El Salvador
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 = 0.7674526 (Coefficient of determination)
This means 76.7% of the change in the one variable (i.e., Fossil fuel use in El Salvador) is predictable based on the change in the other (i.e., Air pollution in Davenport, Iowa) over the 42 years from 1980 through 2021.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 3.04E-14. 0.0000000000000303960441931645
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 0.88 in 3.04E-12% of random cases. Said differently, if you correlated 32,899,017,834,198 random variables You don't actually need 32 trillion 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.
[ 0.78, 0.93 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.
This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!
All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.
Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
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 Davenport, Iowa (Bad air quality days) | 29.0411 | 20 | 14.5205 | 29.1209 | 18.8525 | 23.0137 | 20 | 24.1096 | 34.4262 | 23.8356 | 12.0548 | 21.9178 | 15.3005 | 13.1507 | 22.7397 | 25.4795 | 42.0765 | 45.7534 | 31.2329 | 51.2329 | 61.4754 | 58.9041 | 55.8904 | 53.4247 | 47.8142 | 66.3014 | 59.4521 | 69.863 | 55.7377 | 53.4247 | 62.4658 | 65.2055 | 61.7486 | 63.2877 | 67.3973 | 69.863 | 64.4809 | 53.4247 | 52.8767 | 40.5479 | 37.4317 | 43.8356 |
Fossil fuel use in El Salvador (Billion kWh) | 0.094 | 0.128 | 0.094 | 0.132 | 0.099 | 0.165 | 0.119 | 0.359 | 0.277 | 0.194 | 0.159 | 0.648 | 0.633 | 0.857 | 1.232 | 1.358 | 1.02 | 1.604 | 1.688 | 1.319 | 1.757 | 1.653 | 1.83 | 1.747 | 1.9036 | 1.9094 | 2.358 | 2.463 | 2.262 | 2.592 | 2.092 | 2.255 | 2.48 | 2.481 | 2.508 | 2.526 | 2.505 | 1.39934 | 1.19997 | 1.75595 | 0.977059 | 1.03959 |
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([29.0411,20,14.5205,29.1209,18.8525,23.0137,20,24.1096,34.4262,23.8356,12.0548,21.9178,15.3005,13.1507,22.7397,25.4795,42.0765,45.7534,31.2329,51.2329,61.4754,58.9041,55.8904,53.4247,47.8142,66.3014,59.4521,69.863,55.7377,53.4247,62.4658,65.2055,61.7486,63.2877,67.3973,69.863,64.4809,53.4247,52.8767,40.5479,37.4317,43.8356,])
array_2 = np.array([0.094,0.128,0.094,0.132,0.099,0.165,0.119,0.359,0.277,0.194,0.159,0.648,0.633,0.857,1.232,1.358,1.02,1.604,1.688,1.319,1.757,1.653,1.83,1.747,1.9036,1.9094,2.358,2.463,2.262,2.592,2.092,2.255,2.48,2.481,2.508,2.526,2.505,1.39934,1.19997,1.75595,0.977059,1.03959,])
array_1_name = "Air pollution in Davenport, Iowa"
array_2_name = "Fossil fuel use in El Salvador"
# 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 Davenport, Iowa
- Line chart for only Fossil fuel use in El Salvador
- AI-generated correlation image
- The spurious research paper: A Breath of Fossil Air: Examining the Gas-tly Link Between Air Pollution in Davenport, Iowa and Fossil Fuel Use in El Salvador
Bravo! Your evaluation rocks!
Correlation ID: 4959 · Black Variable ID: 20520 · Red Variable ID: 23646