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AI explanation
As air pollution increased in Sandpoint, Idaho, the demand for clean air also rose, leading people to search for "smol" air purifiers to combat the local smog, resulting in a surge of smol Google searches.Model: dalle-3
Prompt: Generate an image of a comically exaggerated scene in Sandpoint, Idaho, where the town is enveloped in a hazy smog with a hint of humor. People are depicted fervently browsing online for "smol" air purifiers amidst the smog. The town's landscape and the individuals should evoke a sense of whimsical determination to combat the local pollution. 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 Sandpoint, Idaho and Google searches for 'smol'. 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: Art nouveau a Polaroid photo Photorealism a funny image you would see on reddit Futuristic
ChatGPT: a funny image you would see on reddit
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 Sandpoint, Idaho and Google searches for 'smol', in the following situation: As air pollution increased in Sandpoint, Idaho, the demand for clean air also rose, leading people to search for "smol" air purifiers to combat the local smog, resulting in a surge of smol Google searches.. Keep the description simple.
ChatGPT: In Sandpoint, Idaho, a hazy sky filled with pollution looms over the town. Despite the smog, people are seen searching online for "smol" air purifiers, as they seek ways to improve the local air quality.
Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ a funny image you would see on reddit ] and depicting this scene: In Sandpoint, Idaho, a hazy sky filled with pollution looms over the town. Despite the smog, people are seen searching online for "smol" air purifiers, as they seek ways to improve the local air quality. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a comically exaggerated scene in Sandpoint, Idaho, where the town is enveloped in a hazy smog with a hint of humor. People are depicted fervently browsing online for "smol" air purifiers amidst the smog. The town's landscape and the individuals should evoke a sense of whimsical determination to combat the local pollution.
*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.
I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how increases in Air pollution in Sandpoint, Idaho positively influenced smol (Google searches for 'smol').\Make it sound serious until the end.
AI academic paper
A Breath of Fresh 'Smol': Investigating the Relationship Between Air Pollution in Sandpoint, Idaho and Google Searches for 'Smol' The Journal of Ecological Quirkology Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between Air pollution in Sandpoint, Idaho and Google searches for 'smol'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.
Make the title seem clever.
Your research team used data from Environmental Protection Agency and Google Trends to assess this nagging question. You found a correlation coefficient of 0.8582146 and p < 0.01 for 2004 to 2023.
Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)
[[TITLE]]
Lorem ipsum dolor sit
[[ABSTRACT]]
Lorem ipsum dolor sit
ChatGPT:
[[TITLE]]
"A Breath of Fresh 'Smol': Investigating the Relationship Between Air Pollution in Sandpoint, Idaho and Google Searches for 'Smol'"
[[ABSTRACT]]
This study delves into the seemingly whimsical connection between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for the term 'smol'. Utilizing data from the Environmental Protection Agency and Google Trends, we aimed to unravel the enigmatic relationship between these two seemingly unrelated phenomena. The statistical analysis revealed a compelling correlation coefficient of 0.8582146 and a statistically significant p-value of less than 0.01 over the period of 2004 to 2023. This discovery not only sheds light on the impact of air quality on internet search behavior but also presents an opportunity for the lighthearted exploration of environmental influences on modern language and culture. The implications of this unlikely correlation may extend far beyond the boundaries of Sandpoint, offering a glimpse into the curious interplay between environmental factors and online lexicon.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the introduction section of an academic research paper presenting the findings of the connection between Air pollution in Sandpoint, Idaho and Google searches for 'smol'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.
Here is the title and abstract of the paper:
[[TITLE]]
"A Breath of Fresh 'Smol': Investigating the Relationship Between Air Pollution in Sandpoint, Idaho and Google Searches for 'Smol'"
[[ABSTRACT]]
This study delves into the seemingly whimsical connection between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for the term 'smol'. Utilizing data from the Environmental Protection Agency and Google Trends, we aimed to unravel the enigmatic relationship between these two seemingly unrelated phenomena. The statistical analysis revealed a compelling correlation coefficient of 0.8582146 and a statistically significant p-value of less than 0.01 over the period of 2004 to 2023. This discovery not only sheds light on the impact of air quality on internet search behavior but also presents an opportunity for the lighthearted exploration of environmental influences on modern language and culture. The implications of this unlikely correlation may extend far beyond the boundaries of Sandpoint, offering a glimpse into the curious interplay between environmental factors and online lexicon.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
Introduction
Air pollution is a pervasive environmental issue that has wide-ranging effects on public health, climate change, and the natural world. In recent years, researchers have increasingly turned their attention to exploring the intricate relationships between air quality and various societal phenomena. While the majority of studies have focused on the well-established connections between air pollution and respiratory illnesses, cardiovascular diseases, or economic outcomes, few have ventured into the more unconventional realms of internet search behavior and linguistic trends.
In this study, we embark on a peculiar journey that pivots on the seemingly incongruous link between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for the term 'smol'. The term 'smol', an internet slang colloquialism denoting something small, diminutive, or endearing, has gained notable traction in online communities, particularly within the context of visual media and fan culture. Its usage has evolved to encompass a wide spectrum of implications, often associated with affection, cuteness, or admiration.
We were drawn to the intersection of these seemingly disparate elements due to a serendipitous observation of a flurry of 'smol' searches occurring during periods of heightened air pollution in Sandpoint. This curious phenomenon prompted us to delve into the relationship between these two seemingly unrelated domains, combining data from the Environmental Protection Agency's air quality monitoring stations and Google Trends' search volume index.
The objective of this research is to elucidate the correlation and potential causative factors underlying the observed connection between air pollution levels in Sandpoint and the prevalence of 'smol' searches. Furthermore, we aim to shed light on the broader implications of this association, not only from an environmental and psychological perspective but also within the bounds of contemporary internet culture and linguistics.
Through rigorous statistical analyses and comprehensive data interpretations, our findings illuminate a compelling correlation coefficient of 0.8582146 and a p-value of less than 0.01 over the period of 2004 to 2023, affirming the substantive relationship between air pollution and the frequency of 'smol' searches. This unanticipated discovery not only showcases the pervasive influence of environmental factors on online search patterns but also beckons us to ponder the intricate interplay between the virtual and physical domains.
In the subsequent sections of this paper, we present our methodology, data sources, results, and discuss the wider implications of this unorthodox correlation. Our attempt to unravel this unexpected connection not only unravels the mystery behind 'smol' queries but also accentuates the need for a multifaceted approach to understanding the influence of environmental conditions on human behavior and cultural expressions.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Sandpoint, Idaho and Google searches for 'smol'. 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 devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading the backs of shampoo bottles.
Here is the title and abstract of the paper:
[[TITLE]]
"A Breath of Fresh 'Smol': Investigating the Relationship Between Air Pollution in Sandpoint, Idaho and Google Searches for 'Smol'"
[[ABSTRACT]]
This study delves into the seemingly whimsical connection between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for the term 'smol'. Utilizing data from the Environmental Protection Agency and Google Trends, we aimed to unravel the enigmatic relationship between these two seemingly unrelated phenomena. The statistical analysis revealed a compelling correlation coefficient of 0.8582146 and a statistically significant p-value of less than 0.01 over the period of 2004 to 2023. This discovery not only sheds light on the impact of air quality on internet search behavior but also presents an opportunity for the lighthearted exploration of environmental influences on modern language and culture. The implications of this unlikely correlation may extend far beyond the boundaries of Sandpoint, offering a glimpse into the curious interplay between environmental factors and online lexicon.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Introduction
Air pollution is a pervasive environmental issue that has wide-ranging effects on public health, climate change, and the natural world. In recent years, researchers have increasingly turned their attention to exploring the intricate relationships between air quality and various societal phenomena. While the majority of studies have focused on the well-established connections between air pollution and respiratory illnesses, cardiovascular diseases, or economic outcomes, few have ventured into the more unconventional realms of internet search behavior and linguistic trends.
In this study, we embark on a peculiar journey that pivots on the seemingly incongruous link between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for the term 'smol'. The term 'smol', an internet slang colloquialism denoting something small, diminutive, or endearing, has gained notable traction in online communities, particularly within the context of visual media and fan culture. Its usage has evolved to encompass a wide spectrum of implications, often associated with affection, cuteness, or admiration.
We were drawn to the intersection of these seemingly disparate elements due to a serendipitous observation of a flurry of 'smol' searches occurring during periods of heightened air pollution in Sandpoint. This curious phenomenon prompted us to delve into the relationship between these two seemingly unrelated domains, combining data from the Environmental Protection Agency's air quality monitoring stations and Google Trends' search volume index.
The objective of this research is to elucidate the correlation and potential causative factors underlying the observed connection between air pollution levels in Sandpoint and the prevalence of 'smol' searches. Furthermore, we aim to shed light on the broader implications of this association, not only from an environmental and psychological perspective but also within the bounds of contemporary internet culture and linguistics.
Through rigorous statistical analyses and comprehensive data interpretations, our findings illuminate a compelling correlation coefficient of 0.8582146 and a p-value of less than 0.01 over the period of 2004 to 2023, affirming the substantive relationship between air pollution and the frequency of 'smol' searches. This unanticipated discovery not only showcases the pervasive influence of environmental factors on online search patterns but also beckons us to ponder the intricate interplay between the virtual and physical domains.
In the subsequent sections of this paper, we present our methodology, data sources, results, and discuss the wider implications of this unorthodox correlation. Our attempt to unravel this unexpected connection not only unravels the mystery behind 'smol' queries but also accentuates the need for a multifaceted approach to understanding the influence of environmental conditions on human behavior and cultural expressions.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
Amidst the ocean of scholarly research delving into the far-reaching impacts of air pollution, a niche yet curious field of inquiry has emerged, venturing into the unexpected territory of internet search behavior and linguistic peculiarities. Smith et al. (2015) examined the intricate relationship between air quality and online activities, shedding light on the subtle influences of environmental factors on virtual conduct. Similarly, Doe and Jones (2018) explored the impact of regional pollutants on linguistic shifts, providing an insightful framework for considering the interplay between physical surroundings and linguistic expressions.
Delving further into the realms of lexical evolution and linguistic dynamics, "Lexical Landscapes: Geographical Influences on Language" by Brown (2012) offers a comprehensive exploration of the multifaceted influences shaping linguistic content. Furthermore, "Words and Weather: Exploring the Meteorology of Language" by White (2016) provides a thought-provoking perspective on the subtle interrelations between meteorological conditions and language usage.
However, as we navigated the labyrinthine corridors of literature, we found ourselves treading upon uncharted, whimsically peculiar territories. In a departure from conventional literary exegesis, we stumbled upon the hallowed pages of "Arcane Connections: A Compendium of Curious Correlations" by Grey (2011), which beckoned us into a realm brimming with enigmatic juxtapositions and improbable ties. As we marveled at the unexpected gems unearthed in the troves of non-fiction, we wistfully gazed toward the boundless expanse of fiction, where the likes of "Surreal Surprises: Unraveling Unlikely Links" by Rainbow (2014) and "Quirky Quandaries: The Curious Case of Causative Conundrums" by Lavender (2017) lured us into a whimsical medley of imagination and implausibility.
Continuing our scholarly odyssey, we carried out a meticulous exploration of material, painstakingly acquiring diverse sources from the most unexpected of places. Engaging in a digression most unprecedented, we perused the back covers of shampoo bottles, where we chanced upon cryptic musings and labels conceived in jest, sorcery, and marketing stratagems. The unexpected juxtaposition of solemn scientific inquiry and capriciously comical sources provided an enlightening panorama of the human pursuit of knowledge and entertainment, underscoring the diverse dimensions intrinsic to the scholarly pursuit.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Sandpoint, Idaho and Google searches for 'smol'. 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 Google Trends . You used data from 2004 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 'Smol': Investigating the Relationship Between Air Pollution in Sandpoint, Idaho and Google Searches for 'Smol'"
[[ABSTRACT]]
This study delves into the seemingly whimsical connection between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for the term 'smol'. Utilizing data from the Environmental Protection Agency and Google Trends, we aimed to unravel the enigmatic relationship between these two seemingly unrelated phenomena. The statistical analysis revealed a compelling correlation coefficient of 0.8582146 and a statistically significant p-value of less than 0.01 over the period of 2004 to 2023. This discovery not only sheds light on the impact of air quality on internet search behavior but also presents an opportunity for the lighthearted exploration of environmental influences on modern language and culture. The implications of this unlikely correlation may extend far beyond the boundaries of Sandpoint, offering a glimpse into the curious interplay between environmental factors and online lexicon.
[[INTRODUCTION]]
Introduction
Air pollution is a pervasive environmental issue that has wide-ranging effects on public health, climate change, and the natural world. In recent years, researchers have increasingly turned their attention to exploring the intricate relationships between air quality and various societal phenomena. While the majority of studies have focused on the well-established connections between air pollution and respiratory illnesses, cardiovascular diseases, or economic outcomes, few have ventured into the more unconventional realms of internet search behavior and linguistic trends.
In this study, we embark on a peculiar journey that pivots on the seemingly incongruous link between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for the term 'smol'. The term 'smol', an internet slang colloquialism denoting something small, diminutive, or endearing, has gained notable traction in online communities, particularly within the context of visual media and fan culture. Its usage has evolved to encompass a wide spectrum of implications, often associated with affection, cuteness, or admiration.
We were drawn to the intersection of these seemingly disparate elements due to a serendipitous observation of a flurry of 'smol' searches occurring during periods of heightened air pollution in Sandpoint. This curious phenomenon prompted us to delve into the relationship between these two seemingly unrelated domains, combining data from the Environmental Protection Agency's air quality monitoring stations and Google Trends' search volume index.
The objective of this research is to elucidate the correlation and potential causative factors underlying the observed connection between air pollution levels in Sandpoint and the prevalence of 'smol' searches. Furthermore, we aim to shed light on the broader implications of this association, not only from an environmental and psychological perspective but also within the bounds of contemporary internet culture and linguistics.
Through rigorous statistical analyses and comprehensive data interpretations, our findings illuminate a compelling correlation coefficient of 0.8582146 and a p-value of less than 0.01 over the period of 2004 to 2023, affirming the substantive relationship between air pollution and the frequency of 'smol' searches. This unanticipated discovery not only showcases the pervasive influence of environmental factors on online search patterns but also beckons us to ponder the intricate interplay between the virtual and physical domains.
In the subsequent sections of this paper, we present our methodology, data sources, results, and discuss the wider implications of this unorthodox correlation. Our attempt to unravel this unexpected connection not only unravels the mystery behind 'smol' queries but also accentuates the need for a multifaceted approach to understanding the influence of environmental conditions on human behavior and cultural expressions.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
Data Collection:
The data utilized in this study were obtained from a variety of sources, with a particular emphasis on the Environmental Protection Agency's air quality monitoring stations and Google Trends. The Environmental Protection Agency provided comprehensive air quality data in Sandpoint, Idaho, spanning from 2004 to 2023. The data encompassed a plethora of pollutants, including particulate matter, ozone, carbon monoxide, sulfur dioxide, and nitrogen dioxide, showcasing the rich tapestry of air pollution in the region. Meanwhile, Google Trends supplied invaluable information on the relative search volume for the term 'smol' within geographic and temporal parameters corresponding to our air quality dataset.
Development of the Smol Index:
To refine our analysis and capture the nuanced fluctuations in 'smol' searches, we developed the Smol Index, a proprietary aggregation of 'smol' search frequency. This index was meticulously curated to account for seasonal variations, internet usage patterns, and the ebb and flow of online vernacular. Through a series of convoluted algorithms and arcane incantations – or, in more scholarly terms, a sophisticated time-series analysis and data normalization procedure – we produced a robust representation of 'smol' queries over the study period.
Statistical Analysis:
The methodological backbone of this research rested on a blend of statistical techniques aimed at uncovering the elusive relationship between air pollution and 'smol' searches. Utilizing correlation analyses, time series modeling, and complex regression methodologies, we traversed the labyrinthine pathways of data analysis in pursuit of enlightenment. The statistical rigour applied in this study accounts for the myriad confounders and spurious correlations that often lurk in the depths of statistical landscapes, ensuring the veracity and reliability of our findings.
Ethical Considerations:
Throughout the course of this study, we remained steadfast in our commitment to data ethics and integrity. The data sources were rigorously vetted to ensure their authenticity and relevance, and all analyses were conducted with the utmost respect for privacy and confidentiality. Furthermore, we strove to maintain the spirit of scientific inquiry and intellectual curiosity, all while embracing the occasional whimsy and levity offered by our peculiar research subject.
In sum, the methodology employed in this investigation was underpinned by a blend of robust data collection, innovative index development, and rigorous statistical analyses, all expertly laced with a dash of scholarly eccentricity and humor. This methodological odyssey paved the way for a detailed examination of the mysterious nexus between air pollution in Sandpoint and the ever-curious quest for 'smol' on the digital frontier.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the results section of an academic research paper presenting the findings of the connection between Air pollution in Sandpoint, Idaho and Google searches for 'smol'. 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 Google Trends .
For the time period 2004 to 2023, you found a correlation 0.8582146, r-squared of 0.7365323, and p < 0.01.
One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.
Here is the title and abstract of the paper:
[[TITLE]]
"A Breath of Fresh 'Smol': Investigating the Relationship Between Air Pollution in Sandpoint, Idaho and Google Searches for 'Smol'"
[[ABSTRACT]]
This study delves into the seemingly whimsical connection between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for the term 'smol'. Utilizing data from the Environmental Protection Agency and Google Trends, we aimed to unravel the enigmatic relationship between these two seemingly unrelated phenomena. The statistical analysis revealed a compelling correlation coefficient of 0.8582146 and a statistically significant p-value of less than 0.01 over the period of 2004 to 2023. This discovery not only sheds light on the impact of air quality on internet search behavior but also presents an opportunity for the lighthearted exploration of environmental influences on modern language and culture. The implications of this unlikely correlation may extend far beyond the boundaries of Sandpoint, offering a glimpse into the curious interplay between environmental factors and online lexicon.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
Introduction
Air pollution is a pervasive environmental issue that has wide-ranging effects on public health, climate change, and the natural world. In recent years, researchers have increasingly turned their attention to exploring the intricate relationships between air quality and various societal phenomena. While the majority of studies have focused on the well-established connections between air pollution and respiratory illnesses, cardiovascular diseases, or economic outcomes, few have ventured into the more unconventional realms of internet search behavior and linguistic trends.
In this study, we embark on a peculiar journey that pivots on the seemingly incongruous link between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for the term 'smol'. The term 'smol', an internet slang colloquialism denoting something small, diminutive, or endearing, has gained notable traction in online communities, particularly within the context of visual media and fan culture. Its usage has evolved to encompass a wide spectrum of implications, often associated with affection, cuteness, or admiration.
We were drawn to the intersection of these seemingly disparate elements due to a serendipitous observation of a flurry of 'smol' searches occurring during periods of heightened air pollution in Sandpoint. This curious phenomenon prompted us to delve into the relationship between these two seemingly unrelated domains, combining data from the Environmental Protection Agency's air quality monitoring stations and Google Trends' search volume index.
The objective of this research is to elucidate the correlation and potential causative factors underlying the observed connection between air pollution levels in Sandpoint and the prevalence of 'smol' searches. Furthermore, we aim to shed light on the broader implications of this association, not only from an environmental and psychological perspective but also within the bounds of contemporary internet culture and linguistics.
Through rigorous statistical analyses and comprehensive data interpretations, our findings illuminate a compelling correlation coefficient of 0.8582146 and a p-value of less than 0.01 over the period of 2004 to 2023, affirming the substantive relationship between air pollution and the frequency of 'smol' searches. This unanticipated discovery not only showcases the pervasive influence of environmental factors on online search patterns but also beckons us to ponder the intricate interplay between the virtual and physical domains.
In the subsequent sections of this paper, we present our methodology, data sources, results, and discuss the wider implications of this unorthodox correlation. Our attempt to unravel this unexpected connection not only unravels the mystery behind 'smol' queries but also accentuates the need for a multifaceted approach to understanding the influence of environmental conditions on human behavior and cultural expressions.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The correlation analysis revealed a strong positive relationship between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for the term 'smol'. The correlation coefficient of 0.8582146 indicated a robust association between these two seemingly incongruous variables. Additionally, the coefficient of determination (r-squared) of 0.7365323 suggests that approximately 73.7% of the variability in 'smol' searches can be explained by variations in air pollution levels. The statistical significance was further bolstered by a p-value of less than 0.01, underscoring the reliability of the observed relationship.
Figure 1 depicts the scatterplot illustrating the striking correlation between air pollution levels and 'smol' searches, further exemplifying the unexpected kinship between environmental factors and online linguistic phenomena.
The robustness of the correlation coefficient signifies a consistently compelling association, substantiating the plausibility of a meaningful influence of air quality on modern language usage. This discovery not only provides a fascinating glimpse into the interplay of environmental cues and linguistic evolution but also prompts contemplation on the often whimsical and unanticipated ways in which human behavior is influenced by external factors.
The implications of this unorthodox correlation extend beyond the realms of environmental science and linguistics, offering a captivating window into the intricate dynamics between physical surroundings and virtual expressions. This unlikely linkage between air pollution and 'smol' searches accentuates the need for a holistic understanding of the nuanced interconnections between environmental conditions and cultural phenomena, urging a reevaluation of traditional boundaries in interdisciplinary research.
In summary, our findings illuminate a substantial and statistically significant relationship between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for 'smol'. This revelatory connection not only enriches our comprehension of the interwoven influence of environmental factors and online language patterns but also injects an element of levity and intrigue into the discourse surrounding air quality and societal behavior.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Sandpoint, Idaho and Google searches for 'smol'. 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]]
"A Breath of Fresh 'Smol': Investigating the Relationship Between Air Pollution in Sandpoint, Idaho and Google Searches for 'Smol'"
[[ABSTRACT]]
This study delves into the seemingly whimsical connection between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for the term 'smol'. Utilizing data from the Environmental Protection Agency and Google Trends, we aimed to unravel the enigmatic relationship between these two seemingly unrelated phenomena. The statistical analysis revealed a compelling correlation coefficient of 0.8582146 and a statistically significant p-value of less than 0.01 over the period of 2004 to 2023. This discovery not only sheds light on the impact of air quality on internet search behavior but also presents an opportunity for the lighthearted exploration of environmental influences on modern language and culture. The implications of this unlikely correlation may extend far beyond the boundaries of Sandpoint, offering a glimpse into the curious interplay between environmental factors and online lexicon.
[[LITERATURE REVIEW]]
Amidst the ocean of scholarly research delving into the far-reaching impacts of air pollution, a niche yet curious field of inquiry has emerged, venturing into the unexpected territory of internet search behavior and linguistic peculiarities. Smith et al. (2015) examined the intricate relationship between air quality and online activities, shedding light on the subtle influences of environmental factors on virtual conduct. Similarly, Doe and Jones (2018) explored the impact of regional pollutants on linguistic shifts, providing an insightful framework for considering the interplay between physical surroundings and linguistic expressions.
Delving further into the realms of lexical evolution and linguistic dynamics, "Lexical Landscapes: Geographical Influences on Language" by Brown (2012) offers a comprehensive exploration of the multifaceted influences shaping linguistic content. Furthermore, "Words and Weather: Exploring the Meteorology of Language" by White (2016) provides a thought-provoking perspective on the subtle interrelations between meteorological conditions and language usage.
However, as we navigated the labyrinthine corridors of literature, we found ourselves treading upon uncharted, whimsically peculiar territories. In a departure from conventional literary exegesis, we stumbled upon the hallowed pages of "Arcane Connections: A Compendium of Curious Correlations" by Grey (2011), which beckoned us into a realm brimming with enigmatic juxtapositions and improbable ties. As we marveled at the unexpected gems unearthed in the troves of non-fiction, we wistfully gazed toward the boundless expanse of fiction, where the likes of "Surreal Surprises: Unraveling Unlikely Links" by Rainbow (2014) and "Quirky Quandaries: The Curious Case of Causative Conundrums" by Lavender (2017) lured us into a whimsical medley of imagination and implausibility.
Continuing our scholarly odyssey, we carried out a meticulous exploration of material, painstakingly acquiring diverse sources from the most unexpected of places. Engaging in a digression most unprecedented, we perused the back covers of shampoo bottles, where we chanced upon cryptic musings and labels conceived in jest, sorcery, and marketing stratagems. The unexpected juxtaposition of solemn scientific inquiry and capriciously comical sources provided an enlightening panorama of the human pursuit of knowledge and entertainment, underscoring the diverse dimensions intrinsic to the scholarly pursuit.
[[RESULTS]]
The correlation analysis revealed a strong positive relationship between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for the term 'smol'. The correlation coefficient of 0.8582146 indicated a robust association between these two seemingly incongruous variables. Additionally, the coefficient of determination (r-squared) of 0.7365323 suggests that approximately 73.7% of the variability in 'smol' searches can be explained by variations in air pollution levels. The statistical significance was further bolstered by a p-value of less than 0.01, underscoring the reliability of the observed relationship.
Figure 1 depicts the scatterplot illustrating the striking correlation between air pollution levels and 'smol' searches, further exemplifying the unexpected kinship between environmental factors and online linguistic phenomena.
The robustness of the correlation coefficient signifies a consistently compelling association, substantiating the plausibility of a meaningful influence of air quality on modern language usage. This discovery not only provides a fascinating glimpse into the interplay of environmental cues and linguistic evolution but also prompts contemplation on the often whimsical and unanticipated ways in which human behavior is influenced by external factors.
The implications of this unorthodox correlation extend beyond the realms of environmental science and linguistics, offering a captivating window into the intricate dynamics between physical surroundings and virtual expressions. This unlikely linkage between air pollution and 'smol' searches accentuates the need for a holistic understanding of the nuanced interconnections between environmental conditions and cultural phenomena, urging a reevaluation of traditional boundaries in interdisciplinary research.
In summary, our findings illuminate a substantial and statistically significant relationship between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for 'smol'. This revelatory connection not only enriches our comprehension of the interwoven influence of environmental factors and online language patterns but also injects an element of levity and intrigue into the discourse surrounding air quality and societal behavior.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The findings of this study not only substantiate prior research into the impact of environmental factors on online activities but also introduce a whimsical twist in our understanding of linguistic peculiarities. Building upon the foundations laid by Smith et al. (2015) and Doe and Jones (2018), our study reveals a robust association between air pollution levels and Google searches for 'smol', thus reinforcing the notion that environmental influences extend beyond tangible outcomes to permeate the virtual sphere of internet search behavior.
Moreover, as we harken back to the peculiarities unearthed in our literature review, the unexpected linkage between air pollution and 'smol' searches resonates with the spirit of "Arcane Connections: A Compendium of Curious Correlations" by Grey (2011). Though initially regarded as whimsical, the lighthearted insights presented in Grey's work now bear a striking resemblance to the substantive correlation unveiled in the context of our study, underscoring the implications of embracing unorthodox perspectives in scholarly inquiry.
In a parallel vein, our present investigation bridges the divide between the realms of physical surroundings and linguistic expressions, echoing the sentiment expressed in "Lexical Landscapes: Geographical Influences on Language" by Brown (2012). The unexpected relationship between air quality and 'smol' searches suggests the profound impact of geographical and environmental factors on virtual lexicon, thereby augmenting our appreciation of the multifaceted influences shaping modern language usage.
As we delve deeper into the implications of our findings, it becomes apparent that the robust correlation coefficient and statistically significant p-value underscore the legitimacy of the observed relationship. The striking correlation elucidates the unanticipated interplay between external environmental stimuli and online language patterns, enlivening the discourse surrounding the subtleties of societal behavior.
Our study embodies the essence of scholarly exploration by unearthing unexpected connections amidst the labyrinthine corridors of research. It prompts contemplation on the capriciously comical facets of academic pursuit, mirroring the juxtaposition of solemn scientific inquiry with the jestful musings found on the back covers of shampoo bottles, as highlighted in our literature review. This study thus serves as a testament to the multifaceted dimensions intrinsic to the pursuit of knowledge, all while injecting an element of levity and intrigue into the discourse surrounding air quality and societal behavior.
In conclusion, the findings of this study not only contribute to the burgeoning field of environmental influences on virtual conduct but also offer a delightful glimpse into the surprising interplay between air pollution in Sandpoint, Idaho, and Google searches for 'smol', underscoring the inexplicable whimsy that often permeates the scholarly pursuit.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.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 Sandpoint, Idaho and Google searches for 'smol'. 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]]
"A Breath of Fresh 'Smol': Investigating the Relationship Between Air Pollution in Sandpoint, Idaho and Google Searches for 'Smol'"
[[ABSTRACT]]
This study delves into the seemingly whimsical connection between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for the term 'smol'. Utilizing data from the Environmental Protection Agency and Google Trends, we aimed to unravel the enigmatic relationship between these two seemingly unrelated phenomena. The statistical analysis revealed a compelling correlation coefficient of 0.8582146 and a statistically significant p-value of less than 0.01 over the period of 2004 to 2023. This discovery not only sheds light on the impact of air quality on internet search behavior but also presents an opportunity for the lighthearted exploration of environmental influences on modern language and culture. The implications of this unlikely correlation may extend far beyond the boundaries of Sandpoint, offering a glimpse into the curious interplay between environmental factors and online lexicon.
[[INTRDUCTION]]
Introduction
Air pollution is a pervasive environmental issue that has wide-ranging effects on public health, climate change, and the natural world. In recent years, researchers have increasingly turned their attention to exploring the intricate relationships between air quality and various societal phenomena. While the majority of studies have focused on the well-established connections between air pollution and respiratory illnesses, cardiovascular diseases, or economic outcomes, few have ventured into the more unconventional realms of internet search behavior and linguistic trends.
In this study, we embark on a peculiar journey that pivots on the seemingly incongruous link between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for the term 'smol'. The term 'smol', an internet slang colloquialism denoting something small, diminutive, or endearing, has gained notable traction in online communities, particularly within the context of visual media and fan culture. Its usage has evolved to encompass a wide spectrum of implications, often associated with affection, cuteness, or admiration.
We were drawn to the intersection of these seemingly disparate elements due to a serendipitous observation of a flurry of 'smol' searches occurring during periods of heightened air pollution in Sandpoint. This curious phenomenon prompted us to delve into the relationship between these two seemingly unrelated domains, combining data from the Environmental Protection Agency's air quality monitoring stations and Google Trends' search volume index.
The objective of this research is to elucidate the correlation and potential causative factors underlying the observed connection between air pollution levels in Sandpoint and the prevalence of 'smol' searches. Furthermore, we aim to shed light on the broader implications of this association, not only from an environmental and psychological perspective but also within the bounds of contemporary internet culture and linguistics.
Through rigorous statistical analyses and comprehensive data interpretations, our findings illuminate a compelling correlation coefficient of 0.8582146 and a p-value of less than 0.01 over the period of 2004 to 2023, affirming the substantive relationship between air pollution and the frequency of 'smol' searches. This unanticipated discovery not only showcases the pervasive influence of environmental factors on online search patterns but also beckons us to ponder the intricate interplay between the virtual and physical domains.
In the subsequent sections of this paper, we present our methodology, data sources, results, and discuss the wider implications of this unorthodox correlation. Our attempt to unravel this unexpected connection not only unravels the mystery behind 'smol' queries but also accentuates the need for a multifaceted approach to understanding the influence of environmental conditions on human behavior and cultural expressions.
[[RESULTS]]
The correlation analysis revealed a strong positive relationship between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for the term 'smol'. The correlation coefficient of 0.8582146 indicated a robust association between these two seemingly incongruous variables. Additionally, the coefficient of determination (r-squared) of 0.7365323 suggests that approximately 73.7% of the variability in 'smol' searches can be explained by variations in air pollution levels. The statistical significance was further bolstered by a p-value of less than 0.01, underscoring the reliability of the observed relationship.
Figure 1 depicts the scatterplot illustrating the striking correlation between air pollution levels and 'smol' searches, further exemplifying the unexpected kinship between environmental factors and online linguistic phenomena.
The robustness of the correlation coefficient signifies a consistently compelling association, substantiating the plausibility of a meaningful influence of air quality on modern language usage. This discovery not only provides a fascinating glimpse into the interplay of environmental cues and linguistic evolution but also prompts contemplation on the often whimsical and unanticipated ways in which human behavior is influenced by external factors.
The implications of this unorthodox correlation extend beyond the realms of environmental science and linguistics, offering a captivating window into the intricate dynamics between physical surroundings and virtual expressions. This unlikely linkage between air pollution and 'smol' searches accentuates the need for a holistic understanding of the nuanced interconnections between environmental conditions and cultural phenomena, urging a reevaluation of traditional boundaries in interdisciplinary research.
In summary, our findings illuminate a substantial and statistically significant relationship between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for 'smol'. This revelatory connection not only enriches our comprehension of the interwoven influence of environmental factors and online language patterns but also injects an element of levity and intrigue into the discourse surrounding air quality and societal behavior.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our investigation has shed light on the underlying relationship between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for the term 'smol'. The robust correlation coefficient of 0.8582146 and the statistically significant p-value of less than 0.01 over the period of 2004 to 2023 underscore the substantive connection between these seemingly disparate variables. The compelling nature of this association not only underscores the pervasive impact of environmental conditions on online search behavior but also offers a whimsical insight into the interplay between air quality and linguistic trends.
The study's findings not only emphasize the need for a comprehensive understanding of the multifaceted influences of environmental factors on human behavior but also present a peculiar avenue for the exploration of contemporary internet culture and language dynamics. The implications of this unanticipated correlation extend beyond the boundaries of traditional disciplinary confines, sparking contemplation on the intricate interrelations between physical environments and virtual expressions.
However, it is important to acknowledge the limitations of this study, including the focus on a specific geographic location and a singular internet search term. Renewed investigations encompassing broader geographic regions and diverse online vernacular may provide further depth to our understanding of the complex interdependencies between environmental conditions and linguistic evolution. Furthermore, considering the dynamic nature of internet language trends, continuous monitoring and analysis are crucial to capture the evolving nuances in online lexicon.
In light of the compelling findings and the broader implications unearthed in this odyssey of unexpected correlation, it is our contention that further research in this peculiar realm may not yield substantive advancements. Instead, the revelation of the connection between air pollution in Sandpoint, Idaho, and 'smol' searches serves as a poignant reminder of the whimsical intricacies woven into our daily existence, urging us to embrace the serendipitous and oftentimes inexplicable facets of the world around us.
In light of these insights, we assert that no further research is essential in this domain, as the charm of unpredictability is an integral part of the fabric of our scientific and societal exploration.
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 'Smol': Investigating the Relationship Between Air Pollution in Sandpoint, Idaho and Google Searches for 'Smol'. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Ecological Quirkology
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 'Smol': Investigating the Relationship Between Air Pollution in Sandpoint, Idaho and Google Searches for 'Smol'. Respond only with the name of a fictional organization.
ChatGPT:
The Center for Environmental Health and Internet Culture Studies
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 'Smol': Investigating the Relationship Between Air Pollution in Sandpoint, Idaho and Google Searches for 'Smol' with an abstract of This study delves into the seemingly whimsical connection between air pollution levels in Sandpoint, Idaho, and the frequency of Google searches for the term 'smol'. Utilizing data from the Environmental Protection Agency and Google Trends, we aimed to unravel the enigmatic relationship between these two seemingly unrelated phenomena. The statistical analysis revealed a compelling correlation coefficient of 0.8582146 and a statistically significant p-value of less than 0.01 over the period of 2004 to 2023. This discovery not only sheds light on the impact of air quality on internet search behavior but also presents an opportunity for the lighthearted exploration of environmental influences on modern language and culture. The implications of this unlikely correlation may extend far beyond the boundaries of Sandpoint, offering a glimpse into the curious interplay between environmental factors and online lexicon.
ChatGPT:
air pollution, Sandpoint Idaho, Google searches, 'smol', correlation coefficient, statistical analysis, Environmental Protection Agency, Google Trends, air quality, internet search behavior, modern language, culture, environmental factors, online lexicon
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
Discover a new correlation
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Data details
Air pollution in Sandpoint, IdahoDetailed data title: Percentage of days with moderate or worse air quality in Sandpoint, ID
Source: Environmental Protection Agency
See what else correlates with Air pollution in Sandpoint, Idaho
Google searches for 'smol'
Detailed data title: Relative volume of Google searches for 'smol' (Worldwide, without quotes)
Source: Google Trends
Additional Info: Relative search volume (not absolute numbers)
See what else correlates with Google searches for 'smol'
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 = 0.7365323 (Coefficient of determination)
This means 73.7% of the change in the one variable (i.e., Google searches for 'smol') is predictable based on the change in the other (i.e., Air pollution in Sandpoint, Idaho) over the 20 years from 2004 through 2023.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.3E-6. 0.0000012994121377771935000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.
But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.
Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.86 in 0.00013% of random cases. Said differently, if you correlated 769,579 random variables You don't actually need 769 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.
p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.
In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.
Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 19 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 19 because we have two variables measured over a period of 20 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.
[ 0.67, 0.94 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.
This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!
All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.
Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | |
Air pollution in Sandpoint, Idaho (Bad air quality days) | 0.0144928 | 0.0353982 | 0.00569801 | 0 | 0.00277778 | 0.011236 | 0.00623053 | 0 | 0 | 0.00732601 | 0.00623053 | 0.134247 | 0.079235 | 0.207182 | 0.151515 | 0.134247 | 0.109589 | 0.167582 | 0.192308 | 0.0446927 |
Google searches for 'smol' (Rel. search volume) | 12.25 | 13.5 | 10.6667 | 12.1667 | 13.0833 | 18.5 | 19.5 | 20.3333 | 21.3333 | 26.5 | 32.0833 | 46 | 74.8333 | 85.1667 | 86.3333 | 84.25 | 89.0833 | 83.1667 | 75.4167 | 74 |
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
Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied. - Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple
Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
Try it yourself
You can calculate the values on this page on your own! Try running the Python code to see the calculation results. Step 1: Download and install Python on your computer.Step 2: Open a plaintext editor like Notepad and paste the code below into it.
Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"
Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.
Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.
Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.
Step 7: Run the Python script by typing "python calculate_correlation.py"
If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:
"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."
# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats
# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):
# Calculate Pearson correlation coefficient and p-value
correlation, p_value = stats.pearsonr(array1, array2)
# Calculate R-squared as the square of the correlation coefficient
r_squared = correlation**2
return correlation, r_squared, p_value
# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([0.0144928,0.0353982,0.00569801,0,0.00277778,0.011236,0.00623053,0,0,0.00732601,0.00623053,0.134247,0.079235,0.207182,0.151515,0.134247,0.109589,0.167582,0.192308,0.0446927,])
array_2 = np.array([12.25,13.5,10.6667,12.1667,13.0833,18.5,19.5,20.3333,21.3333,26.5,32.0833,46,74.8333,85.1667,86.3333,84.25,89.0833,83.1667,75.4167,74,])
array_1_name = "Air pollution in Sandpoint, Idaho"
array_2_name = "Google searches for 'smol'"
# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)
# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)
Reuseable content
You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.
For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."
When spoken, my last name is pronounced "vegan," like I don't eat meat.
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
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 Sandpoint, Idaho
- Line chart for only Google searches for 'smol'
- AI-generated correlation image
- The spurious research paper: A Breath of Fresh 'Smol': Investigating the Relationship Between Air Pollution in Sandpoint, Idaho and Google Searches for 'Smol'
Kudos for rating!
Correlation ID: 5741 · Black Variable ID: 22120 · Red Variable ID: 1370