Spurious correlation #2,081 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air pollution in Bishop, California and the second variable is Electricity generation in Jamaica. The chart goes from 1980 to 2021, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air pollution in Bishop, California and the second variable is Electricity generation in Jamaica. The chart goes from 1980 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As air pollution in Bishop, California increased, it created a demand for air purifiers. These air purifiers were manufactured in Jamaica, leading to a surge in electricity generation to power the production process. It's shocking how Bishop's pollution sparked a positive current in Jamaica's electricity industry!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of an urban cityscape at dusk, featuring towering skyscrapers and neon-lit billboards amidst the thick haze and smog. In the distance, large wind turbines can be seen atop rolling hills, their blades spinning gracefully against the sunset, alluding to Jamaica's sustainable energy source. The contrasting elements of pollution and renewable energy symbolize the dichotomy of futuristic cyberpunk settings in different parts of the world. 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 Bishop, California and Electricity generation in Jamaica. 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: Woodblock painting Woodblock painting Art nouveau Cyberpunk Voxel art
ChatGPT: Cyberpunk

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 Bishop, California and Electricity generation in Jamaica together. Keep the description simple.
ChatGPT: In Bishop, California, the air is thick with haze and smoke from nearby wildfires, causing an unhealthy air quality. Meanwhile, in Jamaica, large wind turbines spin majestically, generating clean electricity to power homes and businesses.

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: [ Cyberpunk ] and depicting this scene: In Bishop, California, the air is thick with haze and smoke from nearby wildfires, causing an unhealthy air quality. Meanwhile, in Jamaica, large wind turbines spin majestically, generating clean electricity to power homes and businesses. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of an urban cityscape at dusk, featuring towering skyscrapers and neon-lit billboards amidst the thick haze and smog. In the distance, large wind turbines can be seen atop rolling hills, their blades spinning gracefully against the sunset, alluding to Jamaica's sustainable energy source. The contrasting elements of pollution and renewable energy symbolize the dichotomy of futuristic cyberpunk settings in different parts of the world.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Air pollution in Bishop, California caused Electricity generation in Jamaica to increase. Include one good pun.

AI academic paper

(Because p < 0.01)

Smoke Signals: The Shocking Relationship Between Air Pollution in Bishop, California and Electricity Generation in Jamaica

The Journal of Environmental Connections and Contradictions

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Air pollution in Bishop, California and Electricity generation in Jamaica. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
"Smoke Signals: The Shocking Relationship Between Air Pollution in Bishop, California and Electricity Generation in Jamaica"

[[ABSTRACT]]
This study examines the surprising connection between air pollution in Bishop, California and electricity generation in Jamaica. Using data from the Environmental Protection Agency and the Energy Information Administration, we are able to uncover a correlation coefficient of 0.9143789 and a p-value of less than 0.01 for the years 1980 to 2021.

While the physical distance between Bishop and Jamaica is vast, our findings suggest an electrifying relationship between the two locations that goes beyond geographical proximity. Our research sheds light on the potential ripple effects of energy production on air quality, and raises questions about the global impact of local energy policies.

As our results show, the link between air pollution and electricity generation is both shocking and current. It seems that when it comes to environmental effects, what happens in Bishop doesn't necessarily stay in Bishop - it may have jolting implications for islands across the sea.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The study of environmental factors and their interconnectedness has electrified the scientific community in recent years, prompting electrifying research to shed light on the shocking relationships that exist. In this context, our research delves into the unexpected and striking connection between air pollution in Bishop, California and electricity generation in Jamaica. One might say that the sparks of curiosity ignited our interest in this peculiar correlation.
As the smoke clears and the data comes to light, we find ourselves facing a rather electrifying revelation. The correlation coefficient of 0.9143789 and the statistically significant p-value indicate a strong and surprising relationship between the level of air pollution in Bishop and the electricity generation in Jamaica. This connection, much like a bolt of lightning, has struck us with both amazement and curiosity.
The seemingly vast physical distance between these two locations only adds to the shock factor of our findings. It appears that the impact of electricity generation stretches further than the eye can see, reaching across continents and oceans. One might even say that the implications of our research have crossed borders in an electrifying manner.
It is our hope that this research not only illuminates the surprising relationship between air pollution and electricity generation but also generates a charged discussion within the scientific community. The findings may serve as a powerful catalyst for further exploration into the complex web of environmental interconnectedness. After all, the currents of scientific discovery often lead to electrifying breakthroughs that can light the way for future research endeavors.
In the words of Benjamin Franklin, "Energy and persistence conquer all things." As we embark on this journey of scientific inquiry, let us remain energized and persistent in uncovering the hidden connections that electrify our understanding of the world around us.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Several studies have addressed the relationship between air pollution and electricity generation, highlighting the complex and often surprising interplay between these two seemingly disparate phenomena. Smith et al. (2015) discovered a positive correlation between particulate matter levels and electricity consumption in urban areas, indicating a potential link between energy usage and air quality. Similarly, Doe and Jones (2018) found that sulfur dioxide emissions from power plants were associated with increased respiratory illnesses in nearby communities, underscoring the far-reaching impact of electricity generation on public health.

Turning to more comprehensive analyses, "Electricity and the Environment" by Johnson (2013) provides a detailed exploration of the environmental implications of various energy sources, shedding light on the interconnected nature of power production and ecological well-being. In a related vein, "Pollution and Power: The Hidden Costs of Electricity Generation" by Thompson (2017) offers a critical examination of the environmental toll of different electricity generation methods, exposing the shocking ramifications of our energy consumption habits.

In the realm of fiction, "Electricity in the Mist" by Sparks (2005) presents a whimsical tale of a mystical generator that affects the air quality of a small town, mirroring the uncanny union between air pollution in Bishop and electricity generation in Jamaica. Similarly, "Shocking Sparks" by Swift (2012) weaves a captivating narrative of a lightning-powered energy plant and its unforeseen impact on a distant island, offering an allegorical glimpse into the unexpected interconnectedness of environmental factors.

In a more unconventional twist, social media posts from environmental advocates and energy enthusiasts have inadvertently illuminated the fascinating relationship between air pollution and electricity generation. One user on an energy forum quipped, "The link between Bishop’s air pollution and Jamaica’s electricity seems positively electrifying – a real voltage of connection!" Such informal discourse serves as a reminder of the widespread intrigue surrounding this unconventional correlation, sparking interest and curiosity among online communities.

In conclusion, the literature surrounding the coupling of air pollution in Bishop, California and electricity generation in Jamaica showcases the multifaceted nature of their association. While the initial exploration of this relationship may seem bewildering, it is clear that further investigation is warranted to fully fathom the electrifying dynamics at play.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Air pollution in Bishop, California and Electricity generation in Jamaica. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
"Smoke Signals: The Shocking Relationship Between Air Pollution in Bishop, California and Electricity Generation in Jamaica"

[[ABSTRACT]]
This study examines the surprising connection between air pollution in Bishop, California and electricity generation in Jamaica. Using data from the Environmental Protection Agency and the Energy Information Administration, we are able to uncover a correlation coefficient of 0.9143789 and a p-value of less than 0.01 for the years 1980 to 2021.

While the physical distance between Bishop and Jamaica is vast, our findings suggest an electrifying relationship between the two locations that goes beyond geographical proximity. Our research sheds light on the potential ripple effects of energy production on air quality, and raises questions about the global impact of local energy policies.

As our results show, the link between air pollution and electricity generation is both shocking and current. It seems that when it comes to environmental effects, what happens in Bishop doesn't necessarily stay in Bishop - it may have jolting implications for islands across the sea.

[[INTRODUCTION]]
The study of environmental factors and their interconnectedness has electrified the scientific community in recent years, prompting electrifying research to shed light on the shocking relationships that exist. In this context, our research delves into the unexpected and striking connection between air pollution in Bishop, California and electricity generation in Jamaica. One might say that the sparks of curiosity ignited our interest in this peculiar correlation.
As the smoke clears and the data comes to light, we find ourselves facing a rather electrifying revelation. The correlation coefficient of 0.9143789 and the statistically significant p-value indicate a strong and surprising relationship between the level of air pollution in Bishop and the electricity generation in Jamaica. This connection, much like a bolt of lightning, has struck us with both amazement and curiosity.
The seemingly vast physical distance between these two locations only adds to the shock factor of our findings. It appears that the impact of electricity generation stretches further than the eye can see, reaching across continents and oceans. One might even say that the implications of our research have crossed borders in an electrifying manner.
It is our hope that this research not only illuminates the surprising relationship between air pollution and electricity generation but also generates a charged discussion within the scientific community. The findings may serve as a powerful catalyst for further exploration into the complex web of environmental interconnectedness. After all, the currents of scientific discovery often lead to electrifying breakthroughs that can light the way for future research endeavors.
In the words of Benjamin Franklin, "Energy and persistence conquer all things." As we embark on this journey of scientific inquiry, let us remain energized and persistent in uncovering the hidden connections that electrify our understanding of the world around us.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To unravel the electrifying connection between air pollution in Bishop, California, and electricity generation in Jamaica, a methodological approach as rigorous as a thunderstorm was employed. The data utilized in this study was collected from the Environmental Protection Agency and the Energy Information Administration, spanning the years 1980 to 2021. The first step involved gathering data with the diligence of a lightning rod, ensuring that no statistical bolt of energy was left unaccounted for.

To analyze the data, the researchers wielded statistical tools with the precision of a seasoned electrician. The correlation coefficient and p-value were calculated using techniques reminiscent of Benjamin Franklin's famous kite experiment, but with fewer risk factors and, of course, more modern technology.

The statistical analysis was augmented with a method known as the "Voltage-Discharge Technique", where various variables were metaphorically zapped with pulses of statistical electricity to measure their relative influence on the main relationship. It should be noted that no researchers were harmed in the implementation of this technique, despite a few shocking revelations along the way.

The data was also subjected to a "Current-Flow Analysis", which involved tracing the flow of statistical energy through the dataset to identify any potential power surges or fluctuations. This technique provided insights into the dynamic interactions between air pollution in Bishop and electricity generation in Jamaica, illuminating the complex dance of environmental factors with the subtle brilliance of a well-executed light show.

Furthermore, a "Wattage-Weighted Regression Model" was employed to quantify the impact of various factors on the observed relationship, shedding light on the relative contributions of different variables in a manner akin to measuring the relative power consumption of different appliances in a household.

Finally, the computational analysis was conducted using state-of-the-art software, which was as essential to the study as transformers are to electrical distribution. The rigorous application of statistical methodologies, combined with a dash of scientific humor, allowed the researchers to shine a light on the surprising connection between air pollution in Bishop, California, and electricity generation in Jamaica.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Air pollution in Bishop, California and Electricity generation in Jamaica. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
"Smoke Signals: The Shocking Relationship Between Air Pollution in Bishop, California and Electricity Generation in Jamaica"

[[ABSTRACT]]
This study examines the surprising connection between air pollution in Bishop, California and electricity generation in Jamaica. Using data from the Environmental Protection Agency and the Energy Information Administration, we are able to uncover a correlation coefficient of 0.9143789 and a p-value of less than 0.01 for the years 1980 to 2021.

While the physical distance between Bishop and Jamaica is vast, our findings suggest an electrifying relationship between the two locations that goes beyond geographical proximity. Our research sheds light on the potential ripple effects of energy production on air quality, and raises questions about the global impact of local energy policies.

As our results show, the link between air pollution and electricity generation is both shocking and current. It seems that when it comes to environmental effects, what happens in Bishop doesn't necessarily stay in Bishop - it may have jolting implications for islands across the sea.

[[LITERATURE REVIEW]]
Several studies have addressed the relationship between air pollution and electricity generation, highlighting the complex and often surprising interplay between these two seemingly disparate phenomena. Smith et al. (2015) discovered a positive correlation between particulate matter levels and electricity consumption in urban areas, indicating a potential link between energy usage and air quality. Similarly, Doe and Jones (2018) found that sulfur dioxide emissions from power plants were associated with increased respiratory illnesses in nearby communities, underscoring the far-reaching impact of electricity generation on public health.
Turning to more comprehensive analyses, "Electricity and the Environment" by Johnson (2013) provides a detailed exploration of the environmental implications of various energy sources, shedding light on the interconnected nature of power production and ecological well-being. In a related vein, "Pollution and Power: The Hidden Costs of Electricity Generation" by Thompson (2017) offers a critical examination of the environmental toll of different electricity generation methods, exposing the shocking ramifications of our energy consumption habits.
In the realm of fiction, "Electricity in the Mist" by Sparks (2005) presents a whimsical tale of a mystical generator that affects the air quality of a small town, mirroring the uncanny union between air pollution in Bishop and electricity generation in Jamaica. Similarly, "Shocking Sparks" by Swift (2012) weaves a captivating narrative of a lightning-powered energy plant and its unforeseen impact on a distant island, offering an allegorical glimpse into the unexpected interconnectedness of environmental factors.
In a more unconventional twist, social media posts from environmental advocates and energy enthusiasts have inadvertently illuminated the fascinating relationship between air pollution and electricity generation. One user on an energy forum quipped, "The link between Bishop’s air pollution and Jamaica’s electricity seems positively electrifying – a real voltage of connection!" Such informal discourse serves as a reminder of the widespread intrigue surrounding this unconventional correlation, sparking interest and curiosity among online communities.
In conclusion, the literature surrounding the coupling of air pollution in Bishop, California and electricity generation in Jamaica showcases the multifaceted nature of their association. While the initial exploration of this relationship may seem bewildering, it is clear that further investigation is warranted to fully fathom the electrifying dynamics at play.

[[RESULTS]]
The statistical analysis of the data revealed a striking correlation coefficient of 0.9143789 between air pollution in Bishop, California and electricity generation in Jamaica for the period spanning 1980 to 2021. This finding suggests a shockingly strong relationship between these seemingly unrelated variables, as if they were positively charged magnets inexplicably drawn together.
Furthermore, the r-squared value of 0.8360888 indicates that approximately 83.61% of the variation in air pollution levels in Bishop can be explained by the variance in electricity generation in Jamaica. One could say that this relationship is as clear as the ionized air after a thunderstorm and leaves little room for doubt about its significance.
The p-value of less than 0.01 provides compelling evidence to reject the null hypothesis, indicating that the observed relationship is highly unlikely to have occurred by chance. This level of statistical significance is as rare and valuable as a lightning in a bottle – or in this case, a statistical model.
In Fig. 1, the scatterplot graphically depicts this electrifying relationship, showing a tightly clustered pattern of data points that resemble a constellation of stars in the night sky. Much like how stars are connected in constellations, these variables appear to be cosmically linked in their impact on each other, painting a picture that is truly out of this world.
In conclusion, our findings reveal a shocking and current connection between air pollution in Bishop, California and electricity generation in Jamaica, suggesting that the effects of energy production transcend geographic boundaries in a truly electrifying manner. These results shed light on the interwoven nature of environmental and energy systems, sparking new questions and discussions within the scientific community. As scientists, we must stay grounded in our pursuit of knowledge while continuing to chase the electrifying mysteries that power our understanding of the world.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of this study confirm and expand upon prior research, highlighting the electrifying relationship between air pollution in Bishop, California and electricity generation in Jamaica. The remarkably high correlation coefficient of 0.9143789 supports the work of Smith et al. (2015) and Doe and Jones (2018), who hinted at the potential link between energy consumption and air quality. One might say the strength of this relationship is as shocking as grabbing an electrified fence – it's bound to leave an impression!

The r-squared value of 0.8360888 suggests that approximately 83.61% of the variation in air pollution levels in Bishop can be attributed to the variance in electricity generation in Jamaica, akin to the predictability of a well-constructed circuit. This finding echoes the work of Johnson (2013) and Thompson (2017), who illuminated the profound impact of energy production on ecological well-being, demonstrating that the connection between these variables is as reliable as Ohm's law.

The p-value of less than 0.01 provides robust evidence against the null hypothesis, underscoring the unlikelihood of this relationship occurring by chance. This level of statistical significance is as rare and valuable as a lightning in a bottle – or in this case, a statistical model. One might say it's as statistically significant as a bolt of lightning in a storm!

The scatterplot, resembling a constellation of data points, visually represents the tightly clustered pattern that reflects the close relationship between air pollution in Bishop and electricity generation in Jamaica. The resemblance to a constellation speaks to the cosmic link between these variables, much like the interconnectedness of stars in the night sky – it's as if these variables were cosmically destined to be linked, much like a magnetic attraction.

In conclusion, the results of this study provide electrifying evidence of the connection between air pollution in Bishop, California and electricity generation in Jamaica. These findings underscore the surprising and far-reaching impact of energy production on air quality and raise questions about the global implications of local energy policies. One might say these results are as electrifying as a lightning storm, shedding light on the interconnected nature of environmental and energy systems. As researchers, it is important to stay current with discussions surrounding these unexpected relationships and continue to generate sparks of insight in our pursuit of understanding the world.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Air pollution in Bishop, California and Electricity generation in Jamaica. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
"Smoke Signals: The Shocking Relationship Between Air Pollution in Bishop, California and Electricity Generation in Jamaica"

[[ABSTRACT]]
This study examines the surprising connection between air pollution in Bishop, California and electricity generation in Jamaica. Using data from the Environmental Protection Agency and the Energy Information Administration, we are able to uncover a correlation coefficient of 0.9143789 and a p-value of less than 0.01 for the years 1980 to 2021.

While the physical distance between Bishop and Jamaica is vast, our findings suggest an electrifying relationship between the two locations that goes beyond geographical proximity. Our research sheds light on the potential ripple effects of energy production on air quality, and raises questions about the global impact of local energy policies.

As our results show, the link between air pollution and electricity generation is both shocking and current. It seems that when it comes to environmental effects, what happens in Bishop doesn't necessarily stay in Bishop - it may have jolting implications for islands across the sea.

[[INTRDUCTION]]
The study of environmental factors and their interconnectedness has electrified the scientific community in recent years, prompting electrifying research to shed light on the shocking relationships that exist. In this context, our research delves into the unexpected and striking connection between air pollution in Bishop, California and electricity generation in Jamaica. One might say that the sparks of curiosity ignited our interest in this peculiar correlation.
As the smoke clears and the data comes to light, we find ourselves facing a rather electrifying revelation. The correlation coefficient of 0.9143789 and the statistically significant p-value indicate a strong and surprising relationship between the level of air pollution in Bishop and the electricity generation in Jamaica. This connection, much like a bolt of lightning, has struck us with both amazement and curiosity.
The seemingly vast physical distance between these two locations only adds to the shock factor of our findings. It appears that the impact of electricity generation stretches further than the eye can see, reaching across continents and oceans. One might even say that the implications of our research have crossed borders in an electrifying manner.
It is our hope that this research not only illuminates the surprising relationship between air pollution and electricity generation but also generates a charged discussion within the scientific community. The findings may serve as a powerful catalyst for further exploration into the complex web of environmental interconnectedness. After all, the currents of scientific discovery often lead to electrifying breakthroughs that can light the way for future research endeavors.
In the words of Benjamin Franklin, "Energy and persistence conquer all things." As we embark on this journey of scientific inquiry, let us remain energized and persistent in uncovering the hidden connections that electrify our understanding of the world around us.

[[RESULTS]]
The statistical analysis of the data revealed a striking correlation coefficient of 0.9143789 between air pollution in Bishop, California and electricity generation in Jamaica for the period spanning 1980 to 2021. This finding suggests a shockingly strong relationship between these seemingly unrelated variables, as if they were positively charged magnets inexplicably drawn together.
Furthermore, the r-squared value of 0.8360888 indicates that approximately 83.61% of the variation in air pollution levels in Bishop can be explained by the variance in electricity generation in Jamaica. One could say that this relationship is as clear as the ionized air after a thunderstorm and leaves little room for doubt about its significance.
The p-value of less than 0.01 provides compelling evidence to reject the null hypothesis, indicating that the observed relationship is highly unlikely to have occurred by chance. This level of statistical significance is as rare and valuable as a lightning in a bottle – or in this case, a statistical model.
In Fig. 1, the scatterplot graphically depicts this electrifying relationship, showing a tightly clustered pattern of data points that resemble a constellation of stars in the night sky. Much like how stars are connected in constellations, these variables appear to be cosmically linked in their impact on each other, painting a picture that is truly out of this world.
In conclusion, our findings reveal a shocking and current connection between air pollution in Bishop, California and electricity generation in Jamaica, suggesting that the effects of energy production transcend geographic boundaries in a truly electrifying manner. These results shed light on the interwoven nature of environmental and energy systems, sparking new questions and discussions within the scientific community. As scientists, we must stay grounded in our pursuit of knowledge while continuing to chase the electrifying mysteries that power our understanding of the world.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has provided illuminating insights into the electrifying relationship between air pollution in Bishop, California and electricity generation in Jamaica. The shocking correlation coefficient of 0.9143789 and the statistically significant p-value of less than 0.01 have sparked a lively buzz in the scientific community, much like a high-voltage power line.

Our findings suggest that the impact of electricity generation in Jamaica has a shocking effect on air pollution levels in Bishop, California, almost as if it were an electric current traveling through interconnected circuits. It seems that what happens in the land of reggae music doesn't necessarily stay there - it has a shockingly far-reaching impact.

The strong correlation coefficient and r-squared value indicate that this relationship is as clear as a cloudless day, leaving little room for doubt that the two variables are positively charged in their connection. It's almost as if air pollution and electricity generation are caught in an electrifying dance, moving in sync like a well-choreographed tango.

Moreover, the statistically significant p-value is as rare and valuable as a bolt of lightning, providing compelling evidence that this connection is highly unlikely to have occurred by chance. It's like discovering a powerful, once-in-a-lifetime electrical storm in the data, leaving us both astonished and energized.

In light of these findings, it seems that no more research is needed in this area; we've certainly sparked enough interest for now. However, we encourage future studies to continue exploring the electrifying web of environmental interconnectedness, as the currents of scientific discovery often lead to unexpected and enlightening breakthroughs. After all, as scientists, we must stay grounded in our pursuit of knowledge while continuing to chase the electrifying mysteries that power our understanding of the world.

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 Smoke Signals: The Shocking Relationship Between Air Pollution in Bishop, California and Electricity Generation in Jamaica. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Environmental Connections and Contradictions

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 Smoke Signals: The Shocking Relationship Between Air Pollution in Bishop, California and Electricity Generation in Jamaica. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Atmospheric Collaboration and Global Energy Research

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Smoke Signals: The Shocking Relationship Between Air Pollution in Bishop, California and Electricity Generation in Jamaica with an abstract of This study examines the surprising connection between air pollution in Bishop, California and electricity generation in Jamaica. Using data from the Environmental Protection Agency and the Energy Information Administration, we are able to uncover a correlation coefficient of 0.9143789 and a p-value of less than 0.01 for the years 1980 to 2021.
While the physical distance between Bishop and Jamaica is vast, our findings suggest an electrifying relationship between the two locations that goes beyond geographical proximity. Our research sheds light on the potential ripple effects of energy production on air quality, and raises questions about the global impact of local energy policies.
As our results show, the link between air pollution and electricity generation is both shocking and current. It seems that when it comes to environmental effects, what happens in Bishop doesn't necessarily stay in Bishop - it may have jolting implications for islands across the sea.

ChatGPT:

air pollution, electricity generation, correlation coefficient, p-value, Environmental Protection Agency, Energy Information Administration, ripple effects, energy production, air quality, global impact, local energy policies, environmental effects

*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 Bishop, California
Detailed data title: Percentage of days with air quality at 'unhealthy for sensitive groups' or worse in Bishop, CA
Source: Environmental Protection Agency
See what else correlates with Air pollution in Bishop, California

Electricity generation in Jamaica
Detailed data title: Total electricity generation in Jamaica in billion kWh
Source: Energy Information Administration
See what else correlates with Electricity generation in Jamaica

Correlation r = 0.9143789 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r² = 0.8360888 (Coefficient of determination)
This means 83.6% of the change in the one variable (i.e., Electricity generation in Jamaica) is predictable based on the change in the other (i.e., Air pollution in Bishop, California) over the 42 years from 1980 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.7E-17.^Show 0.0000000000000000267447294629
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.91 in 2.7E-15% of random cases. Said differently, if you correlated 37,390,544,607,571,712 random variables^Note You don't actually need 37 quadrillion 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, ^Note 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.

[ 0.85, 0.95 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

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

	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 Bishop, California (Bad air quality days)	1.14286	1.0101	0	0	0	0	0	0	0	0	0	1.51515	1.92837	6.0274	16.2088	7.39726	10.929	9.0411	14.2466	15.8904	16.1202	19.726	21.9178	18.0822	16.3934	19.1781	18.0822	13.4247	9.56284	6.0274	8.49315	12.6027	7.9235	5.75342	4.10959	5.75342	6.28415	6.84932	10.137	3.28767	15.0273	11.7808
Electricity generation in Jamaica (Billion kWh)	1.731	1.746	1.804	2.025	1.926	1.655	1.709	1.891	1.905	2.122	2.414	2.048	2.165	3.592	4.523	5.488	5.688	5.893	6.103	6.225	6.22172	6.26434	6.52446	6.72512	6.7951	6.98896	7.0381	5.603	3.995	4.053	3.97172	4.0149	3.92762	3.92436	3.89984	3.90172	4.13046	4.11098	4.16985	4.24199	4.07334	4.34592

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."

# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([1.14286,1.0101,0,0,0,0,0,0,0,0,0,1.51515,1.92837,6.0274,16.2088,7.39726,10.929,9.0411,14.2466,15.8904,16.1202,19.726,21.9178,18.0822,16.3934,19.1781,18.0822,13.4247,9.56284,6.0274,8.49315,12.6027,7.9235,5.75342,4.10959,5.75342,6.28415,6.84932,10.137,3.28767,15.0273,11.7808,])
array_2 = np.array([1.731,1.746,1.804,2.025,1.926,1.655,1.709,1.891,1.905,2.122,2.414,2.048,2.165,3.592,4.523,5.488,5.688,5.893,6.103,6.225,6.22172,6.26434,6.52446,6.72512,6.7951,6.98896,7.0381,5.603,3.995,4.053,3.97172,4.0149,3.92762,3.92436,3.89984,3.90172,4.13046,4.11098,4.16985,4.24199,4.07334,4.34592,])
array_1_name = "Air pollution in Bishop, California"
array_2_name = "Electricity generation in Jamaica"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Air pollution in Bishop, California
Line chart for only Electricity generation in Jamaica
AI-generated correlation image
The spurious research paper: Smoke Signals: The Shocking Relationship Between Air Pollution in Bishop, California and Electricity Generation in Jamaica

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Correlation ID: 2081 · Black Variable ID: 20361 · Red Variable ID: 23752


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