Spurious correlation #5,694 · 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 Lumberton, North Carolina and the second variable is Solar power generated in Spain. The chart goes from 1990 to 2007, 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 Lumberton, North Carolina and the second variable is Solar power generated in Spain. The chart goes from 1990 to 2007, and the two variables track closely in value over that time.

Download png, svg

AI explanation

The increased air pollution in Lumberton, North Carolina created a unique atmospheric environment. This, in turn, led to a series of localized weather anomalies, including an unexpected surge in air currents. These air currents, while causing respiratory distress for the local inhabitants, had a serendipitous effect on the atmospheric pressure systems over the Atlantic Ocean. As a result, there was a shift in the jet stream, leading to enhanced solar radiation absorption in the Iberian Peninsula. This, combined with the continued advancements in solar technology, inexplicably boosted the solar power generated in Spain. It's a classic case of the butterfly effect, albeit with a smoggy, more like a smog-belching butterfly in this instance.

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a contrasting scene between a hazy and smog-filled city in Lumberton, North Carolina, and the sunny landscape of Spain. Show the thick pollution creating a hazy and smog-filled sky in Lumberton, with a few scattered buildings and powerful air currents twisting and spinning through the city. In contrast, depict the bright sun shining over the landscape of Spain with solar panels glinting in the sunlight, capturing the increased solar radiation and generating an abundance of solar power. The stark difference in atmosphere and energy sources should be visually striking. 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 Lumberton, North Carolina and Solar power generated in Spain. 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: Magic realism Steampunk Photorealism Voxel art a meme
ChatGPT: Photorealism

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 Lumberton, North Carolina and Solar power generated in Spain, in the following situation: The increased air pollution in Lumberton, North Carolina created a unique atmospheric environment. This, in turn, led to a series of localized weather anomalies, including an unexpected surge in air currents. These air currents, while causing respiratory distress for the local inhabitants, had a serendipitous effect on the atmospheric pressure systems over the Atlantic Ocean. As a result, there was a shift in the jet stream, leading to enhanced solar radiation absorption in the Iberian Peninsula. This, combined with the continued advancements in solar technology, inexplicably boosted the solar power generated in Spain. It's a classic case of the butterfly effect, albeit with a smoggy, more like a smog-belching butterfly in this instance.. Keep the description simple.
ChatGPT: In Lumberton, North Carolina, the air was thick with pollution, creating a hazy and smog-filled sky. Despite the gloom, powerful air currents twisted and spun through the city, causing discomfort for the locals. Meanwhile, in Spain, the sun shone brightly, casting a warm glow over the landscape. Solar panels glinted in the sunlight, capturing the increased solar radiation and generating an abundance of solar power.

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: [ Photorealism ] and depicting this scene: In Lumberton, North Carolina, the air was thick with pollution, creating a hazy and smog-filled sky. Despite the gloom, powerful air currents twisted and spun through the city, causing discomfort for the locals. Meanwhile, in Spain, the sun shone brightly, casting a warm glow over the landscape. Solar panels glinted in the sunlight, capturing the increased solar radiation and generating an abundance of solar power. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a contrasting scene between a hazy and smog-filled city in Lumberton, North Carolina, and the sunny landscape of Spain. Show the thick pollution creating a hazy and smog-filled sky in Lumberton, with a few scattered buildings and powerful air currents twisting and spinning through the city. In contrast, depict the bright sun shining over the landscape of Spain with solar panels glinting in the sunlight, capturing the increased solar radiation and generating an abundance of solar power. The stark difference in atmosphere and energy sources should be visually striking.

*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 Lumberton, North Carolina caused Solar power generated in Spain to increase.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)

Shedding Light on the Transcontinental Tango: Uncovering the Link between Lumberton's Air Pollution and Spain's Solar Power

The International Journal of Environmental Science and Solar Power Dynamics

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 Lumberton, North Carolina and Solar power generated in Spain. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Perhaps you also got inspiration from some board games that are vaugely related.

Here is the title and abstract of the paper:
[[TITLE]]
"Shedding Light on the Transcontinental Tango: Uncovering the Link between Lumberton's Air Pollution and Spain's Solar Power"

[[ABSTRACT]]
This study investigates the peculiar relationship between air pollution in Lumberton, North Carolina, and the solar power generated in Spain, utilizing data from the Environmental Protection Agency and the Energy Information Administration for the years 1990 to 2007. Our findings revealed a remarkably high correlation coefficient of 0.8207828 (p < 0.01), suggesting a robust association between the two seemingly disparate phenomena. Despite the considerable physical distance separating these locations, there appears to be an intriguing dance of influence, teasing the boundaries of traditional environmental and energy paradigms. Delving deeper into this enigmatic connection, we've pondered whether it's a case of "dirty secrets shedding light" or a cosmic joke orchestrated by atmospheric whims. As we illuminate this unlikely correlation, we invite readers to glimpse the world through an unexpected lens, where Lumberton's smog and Spain's solar rays engage in a captivating duet across the continents.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The interplay between air pollution and solar power has long been a topic of interest in the realm of environmental and energy research. While the traditional view may relegate these two phenomena to distinct and unrelated spheres, our study aims to peel back the layers of this intricate interaction, revealing a surprising and robust connection between the air pollution in Lumberton, North Carolina, and the solar power generated in Spain.
The juxtaposition of these seemingly disparate locations raises both eyebrows and questions, as the confluence of Lumberton's industrial emissions and Spain's sun-kissed solar potential offers a compelling intellectual puzzle. The intersection of environmental degradation and renewable energy production may seem akin to a paradoxical ballet, where the darkened skies of one locale waltz with the radiant sunbeams of another.
As we set out to examine this enigmatic correlation, we were mindful of the potential for spurious relationships and confounding factors. Nevertheless, our findings revealed a strikingly high correlation coefficient, sparking our curiosity and prompting us to delve further into this unexpected tango across continents. The dance of data and the harmonious convergence of empirical evidence beckon us to explore the profound implications of this connection, inviting us to question whether the universe is orchestrating a cosmic joke with atmospheric whims as its wry conductor.
Thus, with a blend of scholarly rigor and a touch of whimsy, we embark on a journey to uncover the underlying mechanisms and implications of this transcontinental pas de deux between Lumberton's air pollution and Spain's solar power, inviting readers to partake in the intellectual ballroom built on empirical evidence and playful imagination.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The relationship between air pollution and solar power is a topic that has received considerable attention in the environmental and energy research arena. Smith (2015) conducted a comprehensive analysis of air pollution levels in various U.S. cities, while Doe (2012) explored the dynamics of solar power generation in Europe. Jones (2018) investigated the effects of atmospheric conditions on renewable energy sources. These studies provided valuable insights into the individual aspects of air pollution and solar power generation.

Expanding beyond the immediate domain of environmental and energy research, several non-fiction works have also shed light on related themes. In "The Sixth Extinction" by Elizabeth Kolbert, the author discusses the impact of human activities on the planet's ecosystems, including the role of air pollution. Similarly, "The Sun Also Rises" by Ernest Hemingway, though a work of fiction, offers a metaphorical exploration of the interplay between environmental degradation and the transcendent power of the sun. Against this backdrop, the board game "Terraforming Mars" encapsulates the intricate balance between pollution and renewable energy, albeit in a speculative and playful setting.

Venturing further into the realm of fiction, the works of J.R.R. Tolkien, particularly "The Lord of the Rings," present a mythical portrayal of the forces of nature, hinting at a deeper connection between environmental phenomena and the cosmic order. In a surprising twist, the game "Solar Flare" introduces a playful rendition of solar power dynamics, weaving elements of strategy and whimsy into the narrative of renewable energy.

As the authors progress in unraveling the connection between Lumberton's air pollution and Spain's solar power, these diverse influences serve as a backdrop for engaging with the multifaceted dimensions of this intriguing correlation. Indeed, the intersection of empirical research and imaginative exploration invites a deeper understanding of the cosmic dance between seemingly incongruous environmental phenomena, where the serious and the whimsical converge in unexpected harmony.

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 Lumberton, North Carolina and Solar power generated in Spain. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and Energy Information Administration . You used data from 1990 to 2007

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]]
"Shedding Light on the Transcontinental Tango: Uncovering the Link between Lumberton's Air Pollution and Spain's Solar Power"

[[ABSTRACT]]
This study investigates the peculiar relationship between air pollution in Lumberton, North Carolina, and the solar power generated in Spain, utilizing data from the Environmental Protection Agency and the Energy Information Administration for the years 1990 to 2007. Our findings revealed a remarkably high correlation coefficient of 0.8207828 (p < 0.01), suggesting a robust association between the two seemingly disparate phenomena. Despite the considerable physical distance separating these locations, there appears to be an intriguing dance of influence, teasing the boundaries of traditional environmental and energy paradigms. Delving deeper into this enigmatic connection, we've pondered whether it's a case of "dirty secrets shedding light" or a cosmic joke orchestrated by atmospheric whims. As we illuminate this unlikely correlation, we invite readers to glimpse the world through an unexpected lens, where Lumberton's smog and Spain's solar rays engage in a captivating duet across the continents.

[[INTRODUCTION]]
The interplay between air pollution and solar power has long been a topic of interest in the realm of environmental and energy research. While the traditional view may relegate these two phenomena to distinct and unrelated spheres, our study aims to peel back the layers of this intricate interaction, revealing a surprising and robust connection between the air pollution in Lumberton, North Carolina, and the solar power generated in Spain.
The juxtaposition of these seemingly disparate locations raises both eyebrows and questions, as the confluence of Lumberton's industrial emissions and Spain's sun-kissed solar potential offers a compelling intellectual puzzle. The intersection of environmental degradation and renewable energy production may seem akin to a paradoxical ballet, where the darkened skies of one locale waltz with the radiant sunbeams of another.
As we set out to examine this enigmatic correlation, we were mindful of the potential for spurious relationships and confounding factors. Nevertheless, our findings revealed a strikingly high correlation coefficient, sparking our curiosity and prompting us to delve further into this unexpected tango across continents. The dance of data and the harmonious convergence of empirical evidence beckon us to explore the profound implications of this connection, inviting us to question whether the universe is orchestrating a cosmic joke with atmospheric whims as its wry conductor.
Thus, with a blend of scholarly rigor and a touch of whimsy, we embark on a journey to uncover the underlying mechanisms and implications of this transcontinental pas de deux between Lumberton's air pollution and Spain's solar power, inviting readers to partake in the intellectual ballroom built on empirical evidence and playful imagination.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

Data Collection:
The data utilized in this study was sourced from a variety of datasets, with the primary sources being the Environmental Protection Agency (EPA) and the Energy Information Administration (EIA). The period of analysis spanned from 1990 to 2007, allowing for a comprehensive examination of trends and patterns in air pollution levels in Lumberton, North Carolina, and solar power generation in Spain. The selection of these specific timeframes was based on considerations of data availability and compatibility, striving to capture the essence of the relationship between these divergent yet curiously entwined variables.

Air Pollution Assessment:
The assessment of air pollution in Lumberton, North Carolina, harnessed a range of pollutant measures, including particulate matter, nitrogen dioxide, sulfur dioxide, and ozone concentrations. These metrics were obtained from a diffusion of monitoring stations within the designated area, leveraging a mosaic of observational inputs to construct a comprehensive depiction of the region's atmospheric quality. The integration of this multipronged approach aimed to present a nuanced representation of Lumberton's pollutant landscape, while also acknowledging the complex interplay of anthropogenic and natural factors shaping air quality dynamics.

Solar Power Data Analysis:
In contrast, the analysis of solar power generation in Spain delved into the realm of meteorological and energy production records, encompassing solar irradiance, photovoltaic capacity installations, and electricity output from solar resources. The fusion of these diverse datasets furnished a panoramic view of the solar energy landscape in Spain, capturing the ebbs and flows of photonic prowess across the nation's sun-dappled terrain. By interfacing meteorological observations with energy generation statistics, our study sought to unveil the intricate relationship between natural radiance and technological harnessing, shedding light on Spain's solar energy crescendo.

Statistical Correlation Examination:
The computational backbone of this study involved the calculation of correlation coefficients between air pollution levels in Lumberton and solar power generation in Spain, employing the venerable Pearson correlation analysis as our compass in this statistical odyssey. The resulting coefficients not only unveiled the degree of association between these seemingly disparate variables but also instigated ruminations on the underlying mechanisms orchestrating their interconnectedness. Through the manipulation of these statistical levers, we endeavored to narrate the silent dialogue of pollution and solar radiance, translating their clandestine exchanges into numerical parables of connection and divergence.

Spatial-Temporal Convergence Mapping:
Additionally, the spatial-temporal convergence of air pollution and solar power was visualized through geographic information systems (GIS) mapping, articulating the geographic symmetry and dissonance between the two geographically separated phenomena. This cartographic exposition teased out the patterns and anomalies inherent in the transatlantic dance of environmental degradation and renewable luster, encapsulating the quirks and harmonies of this cosmopolitan coupling through a visual tableau of subtleties and contrasts.

Residual Analysis and Sensitivity Testing:
To mitigate the influence of residual confounding and to fortify the robustness of our findings, sensitivity analyses and residual diagnostics were marshaled, elucidating the fidelity of the identified relationship and gauging its susceptibility to perturbations. These analyses served as sentinels guarding against the encroachment of spurious associations, ensuring that the presented conclusions stood impervious to the caprices of lurking variables and idiosyncrasies.

Ethical Considerations:
Throughout the execution of this research, ethical considerations and data integrity were upheld with unwavering dedication, acknowledging the importance of responsible data utilization and the sanctity of scientific inquiry. The dissemination of findings prioritized transparency and veracity, cultivating an environment of scholarly integrity and collegial discourse.

Limitations:
It is prudent to acknowledge the limitations inherent in this study, including the constraints of data availability, temporal granularity, and the requisite reliance on proxy measures for certain variables. While strides were made to navigate these limitations with prudence and pragmatism, their shadow continues to linger, emphasizing the bounded nature of our analytical expanse.

In summary, the methodological orchestration deployed in this study emblematizes the fusion of empirical precision and spirited inquiry, culminating in a symphony of data and analysis. As we proceed to unveil the findings born of this methodological symposium, we invite readers to partake in the unraveling of the unexpected alliance between Lumberton's atmospheric exhalations and Spain's solar serenades.

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 Lumberton, North Carolina and Solar power generated in Spain. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
"Shedding Light on the Transcontinental Tango: Uncovering the Link between Lumberton's Air Pollution and Spain's Solar Power"

[[ABSTRACT]]
This study investigates the peculiar relationship between air pollution in Lumberton, North Carolina, and the solar power generated in Spain, utilizing data from the Environmental Protection Agency and the Energy Information Administration for the years 1990 to 2007. Our findings revealed a remarkably high correlation coefficient of 0.8207828 (p < 0.01), suggesting a robust association between the two seemingly disparate phenomena. Despite the considerable physical distance separating these locations, there appears to be an intriguing dance of influence, teasing the boundaries of traditional environmental and energy paradigms. Delving deeper into this enigmatic connection, we've pondered whether it's a case of "dirty secrets shedding light" or a cosmic joke orchestrated by atmospheric whims. As we illuminate this unlikely correlation, we invite readers to glimpse the world through an unexpected lens, where Lumberton's smog and Spain's solar rays engage in a captivating duet across the continents.

[[LITERATURE REVIEW]]
The relationship between air pollution and solar power is a topic that has received considerable attention in the environmental and energy research arena. Smith (2015) conducted a comprehensive analysis of air pollution levels in various U.S. cities, while Doe (2012) explored the dynamics of solar power generation in Europe. Jones (2018) investigated the effects of atmospheric conditions on renewable energy sources. These studies provided valuable insights into the individual aspects of air pollution and solar power generation.
Expanding beyond the immediate domain of environmental and energy research, several non-fiction works have also shed light on related themes. In "The Sixth Extinction" by Elizabeth Kolbert, the author discusses the impact of human activities on the planet's ecosystems, including the role of air pollution. Similarly, "The Sun Also Rises" by Ernest Hemingway, though a work of fiction, offers a metaphorical exploration of the interplay between environmental degradation and the transcendent power of the sun. Against this backdrop, the board game "Terraforming Mars" encapsulates the intricate balance between pollution and renewable energy, albeit in a speculative and playful setting.
Venturing further into the realm of fiction, the works of J.R.R. Tolkien, particularly "The Lord of the Rings," present a mythical portrayal of the forces of nature, hinting at a deeper connection between environmental phenomena and the cosmic order. In a surprising twist, the game "Solar Flare" introduces a playful rendition of solar power dynamics, weaving elements of strategy and whimsy into the narrative of renewable energy.
As the authors progress in unraveling the connection between Lumberton's air pollution and Spain's solar power, these diverse influences serve as a backdrop for engaging with the multifaceted dimensions of this intriguing correlation. Indeed, the intersection of empirical research and imaginative exploration invites a deeper understanding of the cosmic dance between seemingly incongruous environmental phenomena, where the serious and the whimsical converge in unexpected harmony.

[[RESULTS]]
The findings of our investigation revealed a strikingly high correlation coefficient of 0.8207828 (p < 0.01) between the levels of air pollution in Lumberton, North Carolina, and the solar power generated in Spain. The r-squared value of 0.6736844 further emphasized the robustness of this association, indicating that approximately 67.37% of the variability in solar power generation in Spain can be explained by the variability in air pollution levels in Lumberton.
Figure 1 visually encapsulates the remarkable correlation unearthed in our analysis. The scatterplot depicts a compelling dance of data points, illustrating the close relationship between the two variables. One might imagine the points pirouetting across the plot, gracefully showcasing the synchronized movements of Lumberton's air pollutants and Spain's solar energy production.
Upon unearthing such a striking correlation, one cannot help but stand in awe of the interconnectedness of the world, as if Mother Nature herself were orchestrating a compelling symphony of environmental influences across the vast expanses of land and sea. It appears that Lumberton's malodorous emissions and Spain's radiant solar potential have been engaged in a clandestine waltz, unbeknownst to the casual observer.
Even with the considerable geographical distance between these locations, the data unequivocally speaks to a harmonious partnership, defying conventional wisdom and inviting us to contemplate the intricate interplay between environmental factors and renewable energy sources. In the midst of empirical analysis, we are reminded of the subtle yet significant nuances that underpin the fabric of our natural world, as well as the delightfully unexpected connections that await those who approach the realms of science with an open mind and a playful spirit.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of our study have illuminated a striking and unexpected link between the air pollution levels in Lumberton, North Carolina, and the solar power generated in Spain. The robust correlation coefficient of 0.8207828 (p < 0.01), as well as the r-squared value of 0.6736844, provide compelling evidence for the interdependence of these seemingly disparate environmental and energy phenomena.

The results of our investigation echo the insights gleaned from prior research, reflecting the intricate dynamics that underlie the relationship between air pollution and solar power. This peculiar connection, which might appear far-fetched at first glance, finds resonance in the work of Smith (2015), who meticulously analyzed air pollution levels in diverse U.S. cities, and in Doe's (2012) exploration of solar power generation dynamics in Europe. Additionally, Jones (2018) delved into the effects of atmospheric conditions on renewable energy sources, offering valuable context for interpreting our findings.

Paying homage to the whimsical musings alluded to in our literature review, it is indeed tempting to visualize the data points in our scatterplot as dancers in a grand performance, with Lumberton's air pollutants and Spain's solar energy production engaged in an intricate and synchronized duet across the plot. The playful influences of non-fiction and fictional works, such as Hemingway's "The Sun Also Rises" and Tolkien's mythic portrayal of nature's forces in "The Lord of the Rings," serve as a whimsical lens through which we can ponder the unexpected alliance between Lumberton's atmospheric burdens and Spain's radiant solar potential.

The observed association between these disparate environmental and energy variables bears testament to the enigmatic dance of influence that we sought to unravel. This correlation challenges conventional wisdom and invites contemplation of the interconnectedness of our natural world, providing a thought-provoking juxtaposition of Lumberton's atmospheric woes and Spain's solar prowess. As we consider these findings, we are poised to contribute to a broader dialogue that transcends disciplinary boundaries and embraces the poetic resonance of environmental and energy interplay.

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 Lumberton, North Carolina and Solar power generated in Spain. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Shedding Light on the Transcontinental Tango: Uncovering the Link between Lumberton's Air Pollution and Spain's Solar Power"

[[ABSTRACT]]
This study investigates the peculiar relationship between air pollution in Lumberton, North Carolina, and the solar power generated in Spain, utilizing data from the Environmental Protection Agency and the Energy Information Administration for the years 1990 to 2007. Our findings revealed a remarkably high correlation coefficient of 0.8207828 (p < 0.01), suggesting a robust association between the two seemingly disparate phenomena. Despite the considerable physical distance separating these locations, there appears to be an intriguing dance of influence, teasing the boundaries of traditional environmental and energy paradigms. Delving deeper into this enigmatic connection, we've pondered whether it's a case of "dirty secrets shedding light" or a cosmic joke orchestrated by atmospheric whims. As we illuminate this unlikely correlation, we invite readers to glimpse the world through an unexpected lens, where Lumberton's smog and Spain's solar rays engage in a captivating duet across the continents.

[[INTRDUCTION]]
The interplay between air pollution and solar power has long been a topic of interest in the realm of environmental and energy research. While the traditional view may relegate these two phenomena to distinct and unrelated spheres, our study aims to peel back the layers of this intricate interaction, revealing a surprising and robust connection between the air pollution in Lumberton, North Carolina, and the solar power generated in Spain.
The juxtaposition of these seemingly disparate locations raises both eyebrows and questions, as the confluence of Lumberton's industrial emissions and Spain's sun-kissed solar potential offers a compelling intellectual puzzle. The intersection of environmental degradation and renewable energy production may seem akin to a paradoxical ballet, where the darkened skies of one locale waltz with the radiant sunbeams of another.
As we set out to examine this enigmatic correlation, we were mindful of the potential for spurious relationships and confounding factors. Nevertheless, our findings revealed a strikingly high correlation coefficient, sparking our curiosity and prompting us to delve further into this unexpected tango across continents. The dance of data and the harmonious convergence of empirical evidence beckon us to explore the profound implications of this connection, inviting us to question whether the universe is orchestrating a cosmic joke with atmospheric whims as its wry conductor.
Thus, with a blend of scholarly rigor and a touch of whimsy, we embark on a journey to uncover the underlying mechanisms and implications of this transcontinental pas de deux between Lumberton's air pollution and Spain's solar power, inviting readers to partake in the intellectual ballroom built on empirical evidence and playful imagination.

[[RESULTS]]
The findings of our investigation revealed a strikingly high correlation coefficient of 0.8207828 (p < 0.01) between the levels of air pollution in Lumberton, North Carolina, and the solar power generated in Spain. The r-squared value of 0.6736844 further emphasized the robustness of this association, indicating that approximately 67.37% of the variability in solar power generation in Spain can be explained by the variability in air pollution levels in Lumberton.
Figure 1 visually encapsulates the remarkable correlation unearthed in our analysis. The scatterplot depicts a compelling dance of data points, illustrating the close relationship between the two variables. One might imagine the points pirouetting across the plot, gracefully showcasing the synchronized movements of Lumberton's air pollutants and Spain's solar energy production.
Upon unearthing such a striking correlation, one cannot help but stand in awe of the interconnectedness of the world, as if Mother Nature herself were orchestrating a compelling symphony of environmental influences across the vast expanses of land and sea. It appears that Lumberton's malodorous emissions and Spain's radiant solar potential have been engaged in a clandestine waltz, unbeknownst to the casual observer.
Even with the considerable geographical distance between these locations, the data unequivocally speaks to a harmonious partnership, defying conventional wisdom and inviting us to contemplate the intricate interplay between environmental factors and renewable energy sources. In the midst of empirical analysis, we are reminded of the subtle yet significant nuances that underpin the fabric of our natural world, as well as the delightfully unexpected connections that await those who approach the realms of science with an open mind and a playful spirit.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has uncovered a compelling and statistically robust association between the air pollution levels in Lumberton, North Carolina, and the solar power generated in Spain. The remarkably high correlation coefficient, r-squared value, and visually captivating scatterplot collectively attest to the unlikely yet undeniable dance of influence between these seemingly disparate phenomena. This transcontinental tango challenges conventional environmental and energy paradigms, prompting us to ponder whether it's a case of "dirty secrets shedding light" or an orchestration of cosmic humor by atmospheric whims.

The implications of this unexpected correlation raise both eyebrows and questions, teasing the boundaries of traditional scientific understanding. The wry smile of empirical evidence beckons us to ponder the interplay between Lumberton's industrial emissions and Spain's sun-kissed solar potential, offering a unique perspective that transcends the limitations of conventional wisdom. It appears that, amidst the haze of Lumberton's pollutants and the brilliance of Spain's solar rays, a captivating duet unfolds across continents, inviting us to consider the intertwined fate of seemingly unrelated environmental and energy dynamics.

Ultimately, our findings challenge us to view the world through an unexpected lens, one that transcends disciplinary boundaries and embraces the delightful complexities of nature's choreography. As we bid adieu to this transcontinental pas de deux, we assert that no further research is needed in this area, for the fusion of rigorous analysis and subtle whimsy has shed ample light on this unforeseen relationship.

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 Shedding Light on the Transcontinental Tango: Uncovering the Link between Lumberton's Air Pollution and Spain's Solar Power. Respond only with the name of a fictional academic journal.

ChatGPT:

The International Journal of Environmental Science and Solar Power Dynamics

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 Shedding Light on the Transcontinental Tango: Uncovering the Link between Lumberton's Air Pollution and Spain's Solar Power. Respond only with the name of a fictional organization.

ChatGPT:

Sustainable Energy Research Institute

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 Shedding Light on the Transcontinental Tango: Uncovering the Link between Lumberton's Air Pollution and Spain's Solar Power with an abstract of This study investigates the peculiar relationship between air pollution in Lumberton, North Carolina, and the solar power generated in Spain, utilizing data from the Environmental Protection Agency and the Energy Information Administration for the years 1990 to 2007. Our findings revealed a remarkably high correlation coefficient of 0.8207828 (p < 0.01), suggesting a robust association between the two seemingly disparate phenomena. Despite the considerable physical distance separating these locations, there appears to be an intriguing dance of influence, teasing the boundaries of traditional environmental and energy paradigms. Delving deeper into this enigmatic connection, we've pondered whether it's a case of "dirty secrets shedding light" or a cosmic joke orchestrated by atmospheric whims. As we illuminate this unlikely correlation, we invite readers to glimpse the world through an unexpected lens, where Lumberton's smog and Spain's solar rays engage in a captivating duet across the continents.

ChatGPT:

Lumberton air pollution, Spain solar power, transcontinental environmental influence, correlation coefficient, environmental data analysis, solar power generation, air quality in Lumberton, solar energy trends, transatlantic environmental connection, atmospheric influence on solar power

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

Solar power generated in Spain
Detailed data title: Total solar power generated in Spain in billion kWh
Source: Energy Information Administration
See what else correlates with Solar power generated in Spain

Correlation r = 0.8207828 (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 = 0.6736844 (Coefficient of determination)
This means 67.4% of the change in the one variable (i.e., Solar power generated in Spain) is predictable based on the change in the other (i.e., Air pollution in Lumberton, North Carolina) over the 18 years from 1990 through 2007.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 3.0E-5.^Show 0.0000299856739339618240000000
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 0.82 in 0.003% of random cases. Said differently, if you correlated 33,349 random variables^Note You don't actually need 33 thousand variables to find a correlation like this one. 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.

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 17 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 17 because we have two variables measured over a period of 18 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.

[ 0.57, 0.93 ] 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.

	1990	1991	1992	1993	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007
Air pollution in Lumberton, North Carolina (Bad air quality days)	0	0	0	0	0	0	0	0	0	0	0	0	0.00833333	0	0.00833333	0	0	0.0168067
Solar power generated in Spain (Billion kWh)	0.006	0.007	0.008	0.009	0.01	0.015	0.012	0.013	0.015	0.017	0.018	0.024	0.03	0.041	0.056	0.041	0.119	0.508

Why this works

Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^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([0,0,0,0,0,0,0,0,0,0,0,0,0.00833333,0,0.00833333,0,0,0.0168067,])
array_2 = np.array([0.006,0.007,0.008,0.009,0.01,0.015,0.012,0.013,0.015,0.017,0.018,0.024,0.03,0.041,0.056,0.041,0.119,0.508,])
array_1_name = "Air pollution in Lumberton, North Carolina"
array_2_name = "Solar power generated in Spain"

# 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 Lumberton, North Carolina
Line chart for only Solar power generated in Spain
AI-generated correlation image
The spurious research paper: Shedding Light on the Transcontinental Tango: Uncovering the Link between Lumberton's Air Pollution and Spain's Solar Power

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Correlation ID: 5694 · Black Variable ID: 21621 · Red Variable ID: 23996


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