Spurious correlation #5,537 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air quality in Albuquerque and the second variable is Total likes of LEMMiNO YouTube videos. The chart goes from 2012 to 2023, 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 quality in Albuquerque and the second variable is Total likes of LEMMiNO YouTube videos. The chart goes from 2012 to 2023, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the air quality improved, the local population's oxygen intake increased, leading to heightened cognitive function and mood stability. This, in turn, resulted in more people feeling inclined to engage with intellectually stimulating content such as LEMMiNO's YouTube videos. In essence, cleaner air led to clearer minds, and clearer minds led to a surge in admiration for LEMMiNO's captivating video productions.

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image that recreates a scene from 'Star Wars' set in the backdrop of Albuquerque with an improved air quality. The clear blue skies reveal a contented city where people take deep breaths freely. In the foreground, a group of individuals gather around a smartphone, watching a captivating LEMMiNO YouTube video, eliciting a sense of engagement and appreciation among the viewers. 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 quality in Albuquerque and Total likes of LEMMiNO YouTube videos. 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: Pop art An image that looks like it is a scene from 'Star Wars' Woodblock painting Data cyber art Symbolism
ChatGPT: An image that looks like it is a scene from 'Star Wars'

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 quality in Albuquerque and Total likes of LEMMiNO YouTube videos, in the following situation: As the air quality improved, the local population's oxygen intake increased, leading to heightened cognitive function and mood stability. This, in turn, resulted in more people feeling inclined to engage with intellectually stimulating content such as LEMMiNO's YouTube videos. In essence, cleaner air led to clearer minds, and clearer minds led to a surge in admiration for LEMMiNO's captivating video productions. . Keep the description simple.
ChatGPT: The clear blue skies over Albuquerque reveal a city where the air quality has significantly improved. People are seen taking deep, refreshing breaths, and their relaxed expressions indicate a sense of contentment. In the foreground, a group of individuals gather around a smartphone, watching a captivating LEMMiNO YouTube video. As the video progresses, the like count steadily increases, mirroring the palpable air of engagement and appreciation among the viewers.

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: [ An image that looks like it is a scene from 'Star Wars' ] and depicting this scene: The clear blue skies over Albuquerque reveal a city where the air quality has significantly improved. People are seen taking deep, refreshing breaths, and their relaxed expressions indicate a sense of contentment. In the foreground, a group of individuals gather around a smartphone, watching a captivating LEMMiNO YouTube video. As the video progresses, the like count steadily increases, mirroring the palpable air of engagement and appreciation among the viewers. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that recreates a scene from 'Star Wars' set in the backdrop of Albuquerque with an improved air quality. The clear blue skies reveal a contented city where people take deep breaths freely. In the foreground, a group of individuals gather around a smartphone, watching a captivating LEMMiNO YouTube video, eliciting a sense of engagement and appreciation among the viewers.

*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 increases in Air quality in Albuquerque positively influenced Total likes of LEMMiNO YouTube videos.

AI academic paper

(Because p < 0.01)

A Breath of Fresh Hare: Exploring the Relationship Between Air Quality in Albuquerque and Total Likes of LEMMiNO YouTube Videos

The Journal of Unlikely Correlations

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 goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 quality in Albuquerque and Total likes of LEMMiNO YouTube videos. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name some cartoons and childrens' shows that you watched that are related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
"A Breath of Fresh Hare: Exploring the Relationship Between Air Quality in Albuquerque and Total Likes of LEMMiNO YouTube Videos"

[[ABSTRACT]]
In this study, we delved into the often-overlooked and undoubtedly fascinating correlation between the air quality in Albuquerque and the total likes accumulated by LEMMiNO's thought-provoking YouTube videos. Utilizing data from the Environmental Protection Agency and the eclectic world of YouTube analytics, we employed rigorous statistical analysis to uncover a surprising coefficient of correlation, with a striking 0.8594484 and p < 0.01, spanning the years 2012 to 2023. Our findings not only shed light on the interconnected web of environmental and social influences but also underscore the whimsical and whimsy of seemingly unrelated phenomena. Our results hold vast potential not only for environmental policy but also for the discerning connoisseur of statistical curiosities and delightful intellectual diversions.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The pursuit of knowledge often leads us down unexpected and unconventional paths, where the seemingly disparate realms of air quality in urban environments and the engrossing allure of YouTube content converge in an analytical pas de deux. It is amidst this intellectual dance that we explore the curious relationship between the air quality index in Albuquerque, New Mexico, and the total likes garnered by LEMMiNO's captivating YouTube videos.
The proverbial air hangs thick with anticipation as we embark on this whimsical foray into the world of statistical analysis, where the tangibility of air particles collides with the intangible digital affirmations of online content. As we leap into this scholarly tango, we are poised to unearth correlations that may be as elusive as a well-disguised Easter egg in a field of statistical significance!
In the pages that follow, we navigate the twists and turns of data analysis, treading the fine line between causation and correlation, all the while maintaining a sense of humor sharper than Occam's razor. As we dissect the intricacies of air quality parameters and YouTube engagement metrics, we do not merely crunch numbers; we embrace the rhythmic pulse of data with the enthusiasm of a salsa dancer at a statistics convention.
Our exploration doesn't stop at the threshold of academic curiosity – it delves into the intersection of environmental health and digital discourse, bringing to the fore a confluence of seemingly unrelated forces that may rival the serendipitous discovery of penicillin in a petri dish.
We invite the reader to join us in this academic waltz, where the gaily colored petals of data bloom and sway with the statistical breeze, yielding insights that are as delightful as the unexpected punchline of a well-crafted joke – and perhaps just as illuminating. Shall we, then, waltz our way through the realm of environmental data and social media metrics, with a sense of whimsy akin to a YouTube vlogger's narrative flourish? Let us dare to shed light on the improbable and unearth the unexpected correlations that may hide in the statistical underbrush, all in the pursuit of knowledge and the occasional chuckle.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The relationship between environmental factors and social media engagement has long intrigued researchers across various disciplines. Smith et al. (2015) examined the impact of air quality on social media behavior, noting intriguing patterns in user activity during periods of heightened air pollution. According to their findings, there seems to be a discernible shift in online engagement, with users displaying either increased electronic social interactions as a form of escapism or a decrease in online activity due to environmental concerns. The implications of these findings extend beyond the scope of mere internet behavior, offering a window into the interplay between environmental stimuli and virtual engagements.

Doe and Jones (2017) delved deeper into the perceptual disparities stemming from environmental quality and their influence on public sentiment. Their analysis revealed a connection between individuals’ evaluations of their immediate surroundings and their online content preferences, challenging conventional wisdom and providing a robust foundation for further investigation into the nuanced interactions between environmental perceptions and digital behavior.

Turning to non-fiction literature, "The Air We Breathe" by Anjali Malhotra discusses the profound impact of air quality on human health and society, inviting readers to contemplate the far-reaching ramifications of environmental pollutants. Chetan Bhagat's "Half Girlfriend" subtly intertwines the narrative with atmospheric descriptions, indirectly alluding to the atmospheric conditions that may parallel the online insights of the LEMMiNO YouTube channel. While fictional in nature, these works offer compelling insights into the societal implications of environmental conditions.

As we venture into the realm of fiction, "Fahrenheit 451" by Ray Bradbury presents a dystopian vision where the quality of the air is indicative of a society's moral decay, urging us to ponder the implications of polluted atmospheres beyond their physical health effects. Moreover, the adventures of the Berenstain Bears in "The Berenstain Bears Learn About Strangers" shed a curious light on environmental stewardship, offering a whimsical yet surprisingly insightful perspective on the multifaceted connections between environmental consciousness and social dynamics.

Cartoons and children's shows, such as "Captain Planet and the Planeteers" and "The Magic School Bus," have long sought to instill environmental awareness in younger audiences, juxtaposing the complexities of air quality with the vibrancy of animated storytelling. Although lighthearted, these creative works underscore the importance of engaging with environmental topics across diverse media, resonating with our efforts to unravel the correlations between air quality in Albuquerque and the online resonance of LEMMiNO's captivating content.

In the next section, we delve into the methods employed to disentangle the intricate web of air quality measurements and YouTube acclaim in our quest for revelatory findings and, dare we say, a breath of fresh insights.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 quality in Albuquerque and Total likes of LEMMiNO YouTube videos. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Environmental Protection Agency and YouTube . You used data from 2012 to 2023

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"A Breath of Fresh Hare: Exploring the Relationship Between Air Quality in Albuquerque and Total Likes of LEMMiNO YouTube Videos"

[[ABSTRACT]]
In this study, we delved into the often-overlooked and undoubtedly fascinating correlation between the air quality in Albuquerque and the total likes accumulated by LEMMiNO's thought-provoking YouTube videos. Utilizing data from the Environmental Protection Agency and the eclectic world of YouTube analytics, we employed rigorous statistical analysis to uncover a surprising coefficient of correlation, with a striking 0.8594484 and p < 0.01, spanning the years 2012 to 2023. Our findings not only shed light on the interconnected web of environmental and social influences but also underscore the whimsical and whimsy of seemingly unrelated phenomena. Our results hold vast potential not only for environmental policy but also for the discerning connoisseur of statistical curiosities and delightful intellectual diversions.

[[INTRODUCTION]]
The pursuit of knowledge often leads us down unexpected and unconventional paths, where the seemingly disparate realms of air quality in urban environments and the engrossing allure of YouTube content converge in an analytical pas de deux. It is amidst this intellectual dance that we explore the curious relationship between the air quality index in Albuquerque, New Mexico, and the total likes garnered by LEMMiNO's captivating YouTube videos.
The proverbial air hangs thick with anticipation as we embark on this whimsical foray into the world of statistical analysis, where the tangibility of air particles collides with the intangible digital affirmations of online content. As we leap into this scholarly tango, we are poised to unearth correlations that may be as elusive as a well-disguised Easter egg in a field of statistical significance!
In the pages that follow, we navigate the twists and turns of data analysis, treading the fine line between causation and correlation, all the while maintaining a sense of humor sharper than Occam's razor. As we dissect the intricacies of air quality parameters and YouTube engagement metrics, we do not merely crunch numbers; we embrace the rhythmic pulse of data with the enthusiasm of a salsa dancer at a statistics convention.
Our exploration doesn't stop at the threshold of academic curiosity – it delves into the intersection of environmental health and digital discourse, bringing to the fore a confluence of seemingly unrelated forces that may rival the serendipitous discovery of penicillin in a petri dish.
We invite the reader to join us in this academic waltz, where the gaily colored petals of data bloom and sway with the statistical breeze, yielding insights that are as delightful as the unexpected punchline of a well-crafted joke – and perhaps just as illuminating. Shall we, then, waltz our way through the realm of environmental data and social media metrics, with a sense of whimsy akin to a YouTube vlogger's narrative flourish? Let us dare to shed light on the improbable and unearth the unexpected correlations that may hide in the statistical underbrush, all in the pursuit of knowledge and the occasional chuckle.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To untangle the enigmatic web of correlation between air quality in Albuquerque and the total likes of LEMMiNO's YouTube videos, we employed a multifaceted and, dare I say, multi-sensory approach to data collection and analysis. Our methodology, much like a well-crafted soufflé, required a delicate balance of precision and pizzazz, designed to capture the essence of both environmental indicators and digital engagement.

The primary source of air quality data was derived from the Environmental Protection Agency (EPA), offering a veritable buffet of environmental parameters that could rival the array of delectable toppings at an ice cream parlor. From particulate matter to ozone levels, we scrutinized these atmospheric constituents with the stern scrutiny of a no-nonsense librarian examining overdue books – except, in this case, the "books" were air particles, and the library was the great expanse of the New Mexican sky.

Furthermore, in the realm of YouTube engagement metrics, we delved into the captivating world of LEMMiNO's content, where the total likes served as a barometer of digital acclaim and admiration akin to a standing ovation in a grand theater. With the diligence of a skilled botanist cataloging rare blooms, we meticulously collected and analyzed the numerical expressions of approval bestowed upon LEMMiNO's intellectually stimulating videos.

Having amassed this cornucopia of data, we proceeded to deploy a comprehensive statistical arsenal, featuring the stalwart tools of correlation analysis, regression modeling, and time series examination. We navigated the treacherous landscape of statistical inference with the finesse of a tightrope walker in a statistical circus, treading the line between significance and spurious correlations with the caution of a cat tiptoeing through a field of statistical minefields.

Our analysis spanned the years 2012 to 2023, encompassing a temporal canvas as expansive and beguiling as a symphony composed by the winds of change themselves. This temporal scope allowed us to capture an expansive vista of environmental fluctuations and digital trends, akin to savoring the evolving hues of a sunset over the New Mexican horizon while observing the ebb and flow of YouTube admiration.

It is crucial to acknowledge the limitations of our study, including potential confounding variables such as changes in social media trends and the ever-shifting algorithms governing digital content visibility. Nonetheless, armed with robust statistical methodologies and a penchant for scholarly adventure, we forged ahead into the intricate labyrinth of data analysis, determined to uncover the hidden gems of correlation between air quality and YouTube engagement – a quest as exhilarating as searching for the pot of gold at the end of a statistical rainbow.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 quality in Albuquerque and Total likes of LEMMiNO YouTube videos. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"A Breath of Fresh Hare: Exploring the Relationship Between Air Quality in Albuquerque and Total Likes of LEMMiNO YouTube Videos"

[[ABSTRACT]]
In this study, we delved into the often-overlooked and undoubtedly fascinating correlation between the air quality in Albuquerque and the total likes accumulated by LEMMiNO's thought-provoking YouTube videos. Utilizing data from the Environmental Protection Agency and the eclectic world of YouTube analytics, we employed rigorous statistical analysis to uncover a surprising coefficient of correlation, with a striking 0.8594484 and p < 0.01, spanning the years 2012 to 2023. Our findings not only shed light on the interconnected web of environmental and social influences but also underscore the whimsical and whimsy of seemingly unrelated phenomena. Our results hold vast potential not only for environmental policy but also for the discerning connoisseur of statistical curiosities and delightful intellectual diversions.

[[LITERATURE REVIEW]]
The relationship between environmental factors and social media engagement has long intrigued researchers across various disciplines. Smith et al. (2015) examined the impact of air quality on social media behavior, noting intriguing patterns in user activity during periods of heightened air pollution. According to their findings, there seems to be a discernible shift in online engagement, with users displaying either increased electronic social interactions as a form of escapism or a decrease in online activity due to environmental concerns. The implications of these findings extend beyond the scope of mere internet behavior, offering a window into the interplay between environmental stimuli and virtual engagements.
Doe and Jones (2017) delved deeper into the perceptual disparities stemming from environmental quality and their influence on public sentiment. Their analysis revealed a connection between individuals’ evaluations of their immediate surroundings and their online content preferences, challenging conventional wisdom and providing a robust foundation for further investigation into the nuanced interactions between environmental perceptions and digital behavior.
Turning to non-fiction literature, "The Air We Breathe" by Anjali Malhotra discusses the profound impact of air quality on human health and society, inviting readers to contemplate the far-reaching ramifications of environmental pollutants. Chetan Bhagat's "Half Girlfriend" subtly intertwines the narrative with atmospheric descriptions, indirectly alluding to the atmospheric conditions that may parallel the online insights of the LEMMiNO YouTube channel. While fictional in nature, these works offer compelling insights into the societal implications of environmental conditions.
As we venture into the realm of fiction, "Fahrenheit 451" by Ray Bradbury presents a dystopian vision where the quality of the air is indicative of a society's moral decay, urging us to ponder the implications of polluted atmospheres beyond their physical health effects. Moreover, the adventures of the Berenstain Bears in "The Berenstain Bears Learn About Strangers" shed a curious light on environmental stewardship, offering a whimsical yet surprisingly insightful perspective on the multifaceted connections between environmental consciousness and social dynamics.
Cartoons and children's shows, such as "Captain Planet and the Planeteers" and "The Magic School Bus," have long sought to instill environmental awareness in younger audiences, juxtaposing the complexities of air quality with the vibrancy of animated storytelling. Although lighthearted, these creative works underscore the importance of engaging with environmental topics across diverse media, resonating with our efforts to unravel the correlations between air quality in Albuquerque and the online resonance of LEMMiNO's captivating content.
In the next section, we delve into the methods employed to disentangle the intricate web of air quality measurements and YouTube acclaim in our quest for revelatory findings and, dare we say, a breath of fresh insights.

[[RESULTS]]
In pursuit of uncovering the mysterious dance between air quality and YouTube engagement, we unveil the empirical fruits of our labor. The correlation coefficient of 0.8594484 unites the seemingly unrelated, much like a clever segue in a stand-up comedy routine. This robust correlation indicates a strong relationship between the air quality index in Albuquerque and the total likes garnered by LEMMiNO's enigmatic videos, akin to finding the perfect blend of coffee and conversation on a crisp morning.
The r-squared value of 0.7386515 reinforces this compelling connection, underscoring the significance of the relationship between environmental factors and digital discourse. This statistical feat is as impressive as a magician pulling a rabbit out of a hat, albeit with significantly less sleight of hand and a lot more data analysis.
Perhaps most striking is the p-value of less than 0.01, signifying that the observed correlation is highly unlikely to have occurred by random chance alone. This level of significance is akin to stumbling upon a scientific breakthrough in the uncharted wilderness of statistical exploration.
As predicted, the scatterplot in Figure 1 visually encapsulates the powerful association between air quality and YouTube engagement, serving as a visual testament to the harmonious symphony of seemingly incongruous variables. The plot itself could rival a modern art masterpiece in its ability to capture the essence of correlation and statistical beauty.
Our findings not only highlight the peculiar interplay between air quality parameters and social media metrics but also invite us to celebrate the unexpected harmony of disparate phenomena. In doing so, we breathe new life into the field of statistical exploration, demonstrating that even the most unconventional pairings can yield insightful revelations.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

Upon unraveling the enigmatic correlation between air quality in Albuquerque and the total likes of LEMMiNO YouTube videos, we find ourselves presented with a tapestry of statistical marvels and whimsical insights. Our findings not only confirm but also elevate the earlier work of Smith et al. (2015) and Doe and Jones (2017), who, much like alchemists of yore, laid the groundwork for this intriguing quest. Our results align with the observed patterns of user behavior amidst environmental fluctuations, akin to deciphering the cryptic messages of a treasure map – in this case, the treasure being the elusive connection between atmospheric conditions and online engagements.

The robust correlation coefficient of 0.8594484 serves as a shining beacon, illuminating the symbiotic relationship between air quality and the digital applause reserved for LEMMiNO's intellectual offerings. This numerical embrace is as heartwarming as reuniting with a long-lost friend, with the added bonus of satisfying our thirst for statistical significance. The r-squared value of 0.7386515 further cements the strength of this connection, reminiscent of a sturdy bridge spanning the chasm between environmental influences and virtual interactions, providing a reliable path for future researchers to traverse.

Ah, the p-value of less than 0.01 – a prized gem in the treasure trove of statistical significance! The likelihood of stumbling upon such a substantial correlation by chance alone is akin to discovering a unicorn in your backyard – highly improbable, but undeniably magical. Our scatterplot, serving as a visual testament to this captivating liaison, is a veritable work of art, rivaling the compelling narratives of "Fahrenheit 451" and the animated endeavors of "Captain Planet and the Planeteers" in its ability to encapsulate the interplay of seemingly divergent elements.

In essence, our findings not only affirm the earlier hints of environmental stimuli shaping digital realms but also invite a delightful dance of appreciation for the unexpected connections within our tangled web of existence. As we gaze upon the horizon of statistical exploration, we are compelled to celebrate the harmonious orchestration of the seemingly unrelated, for in the realm of research, as in life, the most unconventional pairings often yield the most captivating revelations. With our findings, we breathe a breath of fresh insights into the field, much like a gentle zephyr on a balmy summer evening, offering both intellectual sustenance and a touch of whimsy to our scholarly pursuits.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 quality in Albuquerque and Total likes of LEMMiNO YouTube videos. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"A Breath of Fresh Hare: Exploring the Relationship Between Air Quality in Albuquerque and Total Likes of LEMMiNO YouTube Videos"

[[ABSTRACT]]
In this study, we delved into the often-overlooked and undoubtedly fascinating correlation between the air quality in Albuquerque and the total likes accumulated by LEMMiNO's thought-provoking YouTube videos. Utilizing data from the Environmental Protection Agency and the eclectic world of YouTube analytics, we employed rigorous statistical analysis to uncover a surprising coefficient of correlation, with a striking 0.8594484 and p < 0.01, spanning the years 2012 to 2023. Our findings not only shed light on the interconnected web of environmental and social influences but also underscore the whimsical and whimsy of seemingly unrelated phenomena. Our results hold vast potential not only for environmental policy but also for the discerning connoisseur of statistical curiosities and delightful intellectual diversions.

[[INTRDUCTION]]
The pursuit of knowledge often leads us down unexpected and unconventional paths, where the seemingly disparate realms of air quality in urban environments and the engrossing allure of YouTube content converge in an analytical pas de deux. It is amidst this intellectual dance that we explore the curious relationship between the air quality index in Albuquerque, New Mexico, and the total likes garnered by LEMMiNO's captivating YouTube videos.
The proverbial air hangs thick with anticipation as we embark on this whimsical foray into the world of statistical analysis, where the tangibility of air particles collides with the intangible digital affirmations of online content. As we leap into this scholarly tango, we are poised to unearth correlations that may be as elusive as a well-disguised Easter egg in a field of statistical significance!
In the pages that follow, we navigate the twists and turns of data analysis, treading the fine line between causation and correlation, all the while maintaining a sense of humor sharper than Occam's razor. As we dissect the intricacies of air quality parameters and YouTube engagement metrics, we do not merely crunch numbers; we embrace the rhythmic pulse of data with the enthusiasm of a salsa dancer at a statistics convention.
Our exploration doesn't stop at the threshold of academic curiosity – it delves into the intersection of environmental health and digital discourse, bringing to the fore a confluence of seemingly unrelated forces that may rival the serendipitous discovery of penicillin in a petri dish.
We invite the reader to join us in this academic waltz, where the gaily colored petals of data bloom and sway with the statistical breeze, yielding insights that are as delightful as the unexpected punchline of a well-crafted joke – and perhaps just as illuminating. Shall we, then, waltz our way through the realm of environmental data and social media metrics, with a sense of whimsy akin to a YouTube vlogger's narrative flourish? Let us dare to shed light on the improbable and unearth the unexpected correlations that may hide in the statistical underbrush, all in the pursuit of knowledge and the occasional chuckle.

[[RESULTS]]
In pursuit of uncovering the mysterious dance between air quality and YouTube engagement, we unveil the empirical fruits of our labor. The correlation coefficient of 0.8594484 unites the seemingly unrelated, much like a clever segue in a stand-up comedy routine. This robust correlation indicates a strong relationship between the air quality index in Albuquerque and the total likes garnered by LEMMiNO's enigmatic videos, akin to finding the perfect blend of coffee and conversation on a crisp morning.
The r-squared value of 0.7386515 reinforces this compelling connection, underscoring the significance of the relationship between environmental factors and digital discourse. This statistical feat is as impressive as a magician pulling a rabbit out of a hat, albeit with significantly less sleight of hand and a lot more data analysis.
Perhaps most striking is the p-value of less than 0.01, signifying that the observed correlation is highly unlikely to have occurred by random chance alone. This level of significance is akin to stumbling upon a scientific breakthrough in the uncharted wilderness of statistical exploration.
As predicted, the scatterplot in Figure 1 visually encapsulates the powerful association between air quality and YouTube engagement, serving as a visual testament to the harmonious symphony of seemingly incongruous variables. The plot itself could rival a modern art masterpiece in its ability to capture the essence of correlation and statistical beauty.
Our findings not only highlight the peculiar interplay between air quality parameters and social media metrics but also invite us to celebrate the unexpected harmony of disparate phenomena. In doing so, we breathe new life into the field of statistical exploration, demonstrating that even the most unconventional pairings can yield insightful revelations.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

The unveiling of the robust correlation between the air quality in Albuquerque and the total likes of LEMMiNO's YouTube videos has shed light on the whimsical interplay of seemingly unrelated phenomena. This novel connection, with statistical significance rivaling the excitement of a surprise party at a math convention, underscores the intricate dance between environmental factors and digital discourse.

Our results, akin to stumbling upon a scientific breakthrough in the uncharted wilderness of statistical exploration, not only offer valuable insights for environmental policy but also serve as a delightful intellectual diversion for the discerning connoisseur of statistical curiosities. The whimsical tango of data analysis has left us with findings that are as delightful as the unexpected punchline of a well-crafted joke – and perhaps just as illuminating.

In light of these compelling findings, we assert that further research in this arena would be akin to attempting to quantify the weight of a shadow or measure the length of a piece of string. In simpler terms, no further research is needed in this area. It's time to hang up our statistical hats and revel in the delightful, if unexpected, harmony of air quality and YouTube likes.

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited A Breath of Fresh Hare: Exploring the Relationship Between Air Quality in Albuquerque and Total Likes of LEMMiNO YouTube Videos. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Unlikely Correlations

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited A Breath of Fresh Hare: Exploring the Relationship Between Air Quality in Albuquerque and Total Likes of LEMMiNO YouTube Videos. Respond only with the name of a fictional organization.

ChatGPT:

The Society for the Advancement of Zany Research (SAZR)

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled A Breath of Fresh Hare: Exploring the Relationship Between Air Quality in Albuquerque and Total Likes of LEMMiNO YouTube Videos with an abstract of In this study, we delved into the often-overlooked and undoubtedly fascinating correlation between the air quality in Albuquerque and the total likes accumulated by LEMMiNO's thought-provoking YouTube videos. Utilizing data from the Environmental Protection Agency and the eclectic world of YouTube analytics, we employed rigorous statistical analysis to uncover a surprising coefficient of correlation, with a striking 0.8594484 and p < 0.01, spanning the years 2012 to 2023. Our findings not only shed light on the interconnected web of environmental and social influences but also underscore the whimsical and whimsy of seemingly unrelated phenomena. Our results hold vast potential not only for environmental policy but also for the discerning connoisseur of statistical curiosities and delightful intellectual diversions.

ChatGPT:

air quality Albuquerque, LEMMiNO YouTube, YouTube analytics, environmental influences, statistical analysis, correlation coefficient, environmental policy, social influences, whimsical phenomena, statistical curiosities

*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 quality in Albuquerque
Detailed data title: Percentage of days with good air quality in Albuquerque, NM
Source: Environmental Protection Agency
See what else correlates with Air quality in Albuquerque

Total likes of LEMMiNO YouTube videos
Detailed data title: Total likes of LEMMiNO YouTube videos.
Source: YouTube
See what else correlates with Total likes of LEMMiNO YouTube videos

Correlation r = 0.8594484 (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 = 0.7386515 (Coefficient of determination)
This means 73.9% of the change in the one variable (i.e., Total likes of LEMMiNO YouTube videos) is predictable based on the change in the other (i.e., Air quality in Albuquerque) over the 12 years from 2012 through 2023.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00034.^Show 0.0003395351739490731600000000
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 0.86 in 0.034% of random cases. Said differently, if you correlated 2,945 random variables^Note Which I absolutely did.
with the same 11 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 11 because we have two variables measured over a period of 12 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.

[ 0.56, 0.96 ] 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.

	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022	2023
Air quality in Albuquerque (Good air quality)	27.3224	38.9041	52.3288	55.0685	50.5464	45.2055	41.3699	44.1096	35.7924	23.5616	28.2192	23.6264
Total likes of LEMMiNO YouTube videos (Total likes)	115428	555877	2204980	2235840	1683820	1104080	1654540	1440560	1023450	963087	217315	419849

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.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

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([27.3224,38.9041,52.3288,55.0685,50.5464,45.2055,41.3699,44.1096,35.7924,23.5616,28.2192,23.6264,])
array_2 = np.array([115428,555877,2204980,2235840,1683820,1104080,1654540,1440560,1023450,963087,217315,419849,])
array_1_name = "Air quality in Albuquerque"
array_2_name = "Total likes of LEMMiNO YouTube videos"

# 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 quality in Albuquerque
Line chart for only Total likes of LEMMiNO YouTube videos
AI-generated correlation image
The spurious research paper: A Breath of Fresh Hare: Exploring the Relationship Between Air Quality in Albuquerque and Total Likes of LEMMiNO YouTube Videos

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Correlation ID: 5537 · Black Variable ID: 20247 · Red Variable ID: 25601


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