Spurious correlation #2,763 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Air pollution in Boulder and the second variable is Google searches for 'how to trap a spider'. The chart goes from 2007 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 pollution in Boulder and the second variable is Google searches for 'how to trap a spider'. The chart goes from 2007 to 2023, and the two variables track closely in value over that time.

Download png, svg

AI explanation

The crisp, clean air in Boulder made the spiders too relaxed to move, so there was no need for the internet to learn how to trap them. That or the spiders realized they had better job prospects in a less polluted area and just decided to relocate on their own.

^{Show image generation prompt} Model: dalle-3
Prompt: Prompt: Generate an image that looks like it is a scene from a Disney movie. The setting is in a hazy town filled with pollution particles. Amidst the pollution, a group of people are frantically searching "how to trap a spider" on their phones. Meanwhile, within the city, spiders seek shelter from the suffocating air indoors. The scene depicts a surge in DIY spider trapping as the spiders seek refuge from the polluted outdoors. 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 Boulder and Google searches for 'how to trap a spider'. 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: An image that looks like it is a scene from A Disney Movie Art nouveau a funny image macro A TIME magazine cover image An image that looks like it is a scene from A Disney Movie
ChatGPT: An image that looks like it is a scene from A Disney Movie

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 Boulder and Google searches for 'how to trap a spider', in the following situation: Air pollution in Boulder has caused an increase in spider populations, as the pollution particles provide a perfect habitat for their tiny lungs. With more spiders around, people in Boulder are frantically Googling "how to trap a spider" to deal with the eight-legged roommates invading their homes. The spiders, feeling suffocated by the pollution, seek refuge indoors, leading to a surge in DIY spider trapping tactics. It's a web of pollution and panic!. Keep the description simple.
ChatGPT: In Boulder, the hazy air is filled with pollution particles, creating a gloomy atmosphere. Amidst the pollution, a flurry of people are hunched over their phones, frantically searching "how to trap a spider". Meanwhile, within the city, the spider populations are flourishing, seeking shelter from the suffocating air indoors. The scene is one of air pollution creating a surge in DIY spider trapping, as the spiders seek refuge from the polluted outdoors.

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 A Disney Movie ] and depicting this scene: In Boulder, the hazy air is filled with pollution particles, creating a gloomy atmosphere. Amidst the pollution, a flurry of people are hunched over their phones, frantically searching "how to trap a spider". Meanwhile, within the city, the spider populations are flourishing, seeking shelter from the suffocating air indoors. The scene is one of air pollution creating a surge in DIY spider trapping, as the spiders seek refuge from the polluted outdoors. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image that looks like it is a scene from a Disney movie. The setting is in a hazy town filled with pollution particles. Amidst the pollution, a group of people are frantically searching "how to trap a spider" on their phones. Meanwhile, within the city, spiders seek shelter from the suffocating air indoors. The scene depicts a surge in DIY spider trapping as the spiders seek refuge from the polluted outdoors.

*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 a decrease in Air pollution in Boulder caused how to trap a spider (Google searches for 'how to trap a spider') to decrease.

AI academic paper

(Because p < 0.05)

When the Smog is Thick, Your Spider-Trap Search Trend will Stick: An Analysis of Air Pollution in Boulder and Google Searches for 'How to Trap a Spider'

The International Journal of Ecological Curiosities

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 pollution in Boulder and Google searches for 'how to trap a spider'. 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 a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
When the Smog is Thick, Your Spider-Trap Search Trend will Stick: An Analysis of Air Pollution in Boulder and Google Searches for 'How to Trap a Spider'

[[ABSTRACT]]
The incessant battle against airborne toxins has often overshadowed the quirky idiosyncrasies it unearths. In this study, we delved into the unorthodox relationship between air pollution in Boulder and the enigmatic phenomenon of increased Google searches for 'how to trap a spider'. Leveraging data from the Environmental Protection Agency and Google Trends, our research team employed rigorous statistical analyses to evaluate this unlikely correlation. Our findings revealed a remarkably robust correlation coefficient of 0.5891134 with a statistically significant p-value of less than 0.05, indicating a tangible link between deteriorating air quality and arachnophobic internet inquiries. This study not only sheds light on the unanticipated consequences of pollution but also uncovers the peculiar inclinations of our internet-surfing comrades. So, the next time you spot a spider in your Boulder abode, don't just blame its eight-legged presence; perhaps the smog in the air played a role in your quest to learn how to usher it out.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
Air pollution is a well-documented environmental hazard with substantial impacts on human health and well-being. From respiratory ailments to environmental degradation, the deleterious effects of smog and particulate matter have been the focus of extensive scholarly inquiry. However, amidst the fervent efforts to mitigate these adverse effects, the peculiar and unexpected connections that air pollution may have with seemingly unrelated phenomena have often been overlooked.
In this study, we venture into the whimsical realm of internet search trends to explore the curious association between air pollution in Boulder and the surge in Google searches for 'how to trap a spider'. While one might initially dismiss this correlation as a mere quirk of data, our investigation brings to light the potential interplay between environmental factors and seemingly unrelated human behaviors. The bustling digitized world of Google searches not only serves as a reflection of our collective curiosities but also unveils the perplexing and sometimes amusing connections between our daily lives and the environment around us.
The city of Boulder, nestled in the picturesque foothills of the Rocky Mountains, provides an intriguing backdrop for our inquiry. Renowned for its vibrant community and progressive environmental initiatives, Boulder also grapples with its share of air quality concerns, especially during periods of inversions and atmospheric stagnation. Against this setting, we set out to unravel the enigmatic correspondence between declining air quality and the sudden spike in spider-trapping queries on the world's most ubiquitous search engine.
Leveraging data from the Environmental Protection Agency's Air Quality System and Google Trends, our research team embarked on a rigorous quantitative analysis to disentangle this seemingly improbable association. As we unravel the intricate web of data and statistical measures, our quest is not merely to elucidate a statistical link, but to uncover the underlying mechanisms and behavioral insights that underpin this unorthodox relationship. Through this investigation, we aim to offer a nuanced perspective on the multifaceted repercussions of air pollution and delve into the inherent quirks of human response to environmental stressors.
Hence, as we embark on this scholarly expedition, let us not only seek to unravel the mysteries of statistical correlation but also embrace the serendipitous discoveries that await us. After all, in the realm of academic inquiry, uncovering unexpected connections often leads to the most intriguing and, at times, amusing revelations. So, fasten your seatbelts and brace yourselves for a journey that promises to uncover the unforeseen intersection of air pollution and arachnophobic inquisitiveness.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The investigation of seemingly incongruous phenomena often uncovers surprising connections and unexpected correlations, leading to intriguing insights. Smith et al. (2018) delved into the far-reaching impacts of air pollution, emphasizing its implications for public health and ecological sustainability. Similarly, Doe and Jones (2017) meticulously scrutinized the atmospheric dynamics of Boulder and its susceptibility to episodic deterioration in air quality, shedding light on the city's ongoing battle against airborne toxins.

Notably, the extensive body of literature on air pollution often focuses on its well-documented repercussions, encompassing a spectrum of respiratory diseases, environmental degradation, and the overarching impact on societal well-being. However, in a departure from conventional scholarly discourse, our inquiry transcends the commonly explored terrain to unravel an unusual correlation between air pollution in Boulder and the surge in Google searches for 'how to trap a spider'.

Expanding our purview beyond the academic arena, popular non-fiction works such as "The Air Pollution Crisis: Exploring Environmental Hazards" by Environmental Scientist Ipsum (2019) and "Boulder's Atmosphere: An Ongoing Saga" by Atmospheric Researcher Lorem (2020) delve into the intricate nuances of pollution dynamics and its implications for local ecosystems. These comprehensive treatises, while invaluable in elucidating the gravity of the pollution predicament, inadvertently overlook the whimsical manifestations of pollution-induced behaviors.

In a similar vein, the exercises of human curiosity in response to environmental stimuli have long been overlooked in the domain of scholarly inquiry. However, works of fiction such as "The Web of Intrigue: A Tale of Arachnophobia" by Fiction Author X (2015) and "Spiders in Smog: An Unlikely Alliance" by Novelist Y (2018) allude to the serendipitous interplay between environmental cues and peculiar human responses. Though fictional in nature, these works unknowingly presage the unexpected association that our research endeavors to unravel.

Moreover, the prevalence of internet memes, such as the "Spider Bro" and "Boulder Smog Spider Trap Challenge," serves as an additional testament to the public's engagement with the intersection of air pollution and spider-related phenomena. Seemingly irreverent at first glance, these memes offer a subtle reflection of society's intrigue with the quirky juxtapositions that emerge amidst environmental challenges.

Thus, our foray into the convergence of air pollution in Boulder and the surge in 'how to trap a spider' queries not only presents an unconventional synergy between seemingly disparate entities but also unearths the whimsical facets of human response to environmental stressors. As we navigate through the literary landscape, it becomes evident that the interplay between pollution and peculiar human inclinations transcends the boundaries of empirical investigation, unfurling a tapestry of unexpected correlations and comical juxtapositions.

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 pollution in Boulder and Google searches for 'how to trap a spider'. 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 2007 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]]
When the Smog is Thick, Your Spider-Trap Search Trend will Stick: An Analysis of Air Pollution in Boulder and Google Searches for 'How to Trap a Spider'

[[ABSTRACT]]
The incessant battle against airborne toxins has often overshadowed the quirky idiosyncrasies it unearths. In this study, we delved into the unorthodox relationship between air pollution in Boulder and the enigmatic phenomenon of increased Google searches for 'how to trap a spider'. Leveraging data from the Environmental Protection Agency and Google Trends, our research team employed rigorous statistical analyses to evaluate this unlikely correlation. Our findings revealed a remarkably robust correlation coefficient of 0.5891134 with a statistically significant p-value of less than 0.05, indicating a tangible link between deteriorating air quality and arachnophobic internet inquiries. This study not only sheds light on the unanticipated consequences of pollution but also uncovers the peculiar inclinations of our internet-surfing comrades. So, the next time you spot a spider in your Boulder abode, don't just blame its eight-legged presence; perhaps the smog in the air played a role in your quest to learn how to usher it out.

[[INTRODUCTION]]
INTRODUCTION
Air pollution is a well-documented environmental hazard with substantial impacts on human health and well-being. From respiratory ailments to environmental degradation, the deleterious effects of smog and particulate matter have been the focus of extensive scholarly inquiry. However, amidst the fervent efforts to mitigate these adverse effects, the peculiar and unexpected connections that air pollution may have with seemingly unrelated phenomena have often been overlooked.
In this study, we venture into the whimsical realm of internet search trends to explore the curious association between air pollution in Boulder and the surge in Google searches for 'how to trap a spider'. While one might initially dismiss this correlation as a mere quirk of data, our investigation brings to light the potential interplay between environmental factors and seemingly unrelated human behaviors. The bustling digitized world of Google searches not only serves as a reflection of our collective curiosities but also unveils the perplexing and sometimes amusing connections between our daily lives and the environment around us.
The city of Boulder, nestled in the picturesque foothills of the Rocky Mountains, provides an intriguing backdrop for our inquiry. Renowned for its vibrant community and progressive environmental initiatives, Boulder also grapples with its share of air quality concerns, especially during periods of inversions and atmospheric stagnation. Against this setting, we set out to unravel the enigmatic correspondence between declining air quality and the sudden spike in spider-trapping queries on the world's most ubiquitous search engine.
Leveraging data from the Environmental Protection Agency's Air Quality System and Google Trends, our research team embarked on a rigorous quantitative analysis to disentangle this seemingly improbable association. As we unravel the intricate web of data and statistical measures, our quest is not merely to elucidate a statistical link, but to uncover the underlying mechanisms and behavioral insights that underpin this unorthodox relationship. Through this investigation, we aim to offer a nuanced perspective on the multifaceted repercussions of air pollution and delve into the inherent quirks of human response to environmental stressors.
Hence, as we embark on this scholarly expedition, let us not only seek to unravel the mysteries of statistical correlation but also embrace the serendipitous discoveries that await us. After all, in the realm of academic inquiry, uncovering unexpected connections often leads to the most intriguing and, at times, amusing revelations. So, fasten your seatbelts and brace yourselves for a journey that promises to uncover the unforeseen intersection of air pollution and arachnophobic inquisitiveness.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

**[[METHODOLOGY]]**

**Data Collection**

To unlock the mysteries hidden within the virtual labyrinth of data, our research team utilized a combination of solemn analytics and lighthearted skepticism. We collated air quality data from the Environmental Protection Agency's Air Quality System, sifting through years of atmospheric nuances with the diligence of a curious arachnid perusing the World Wide Web. We focused our attention on Boulder, Colorado, a locale nestled within the embrace of nature's grandeur, yet not immune to the tendrils of atmospheric contaminants.

**Environmental Data Analysis**

Armed with an abacus of modern statistical tools, we prised away the layers of complexity enveloping air pollution data. Our quantitative examination encompassed ambient concentrations of pollutants including ozone, particulate matter, nitrogen dioxide, sulfur dioxide, and carbon monoxide. Through convolution integrals and meteorological adjustments, we aimed to distill the essence of Boulder's atmospheric composition, much like a discerning oenophile parsing the complex bouquet of a fine wine.

**Spider-Trap Search Trends**

Venturing into the ephemeral realm of internet queries, we navigated through the digital tapestry woven by Google Trends. With the precision of an artisan crafting delicate lace, we uncovered the temporal patterns of 'how to trap a spider' searches. The deluge of queries, exhibiting undulating peaks and valleys akin to the spine-tingling dance of a lurking arachnid, was meticulously archived and scrutinized for its subtle correlations with the chronicles of polluted air.

**Statistical Analysis**

Employing the venerable tools of correlation analysis and regression modeling, we set out to gauge the dance of numbers as they intertwined like the errant strands of a spider's web. The Pearson correlation coefficient and its pertinacious ally, the p-value, stood vigil as we probed the interplay between air pollution and spider-trapping inquiries. The statistical significance of our findings, akin to the fabled yet elusive Black Widow, concealed itself within the intricate patterns of data, awaiting our methodical scrutiny.

*Temporal Scope*

Our chronological odyssey spanned from the year 2007 to 2023, encompassing an era marked by digital transformation and the unwavering persistence of volatile atmospheric constituents. This expansive temporal purview allowed us to capture the undulating rhythms of air pollution and the ebb and flow of arachnophobic musings, entwining the annals of both human curiosity and environmental turbulence.

Upon successfully wielding this fusion of data, statistical fortitude, and a touch of whimsy, we set the stage for a revealing exposé of an unassuming yet captivating correlation.

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 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 Boulder and Google searches for 'how to trap a spider'. 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 2007 to 2023, you found a correlation 0.5891134, r-squared of 0.3470546, and p < 0.05.

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]]
When the Smog is Thick, Your Spider-Trap Search Trend will Stick: An Analysis of Air Pollution in Boulder and Google Searches for 'How to Trap a Spider'

[[ABSTRACT]]
The incessant battle against airborne toxins has often overshadowed the quirky idiosyncrasies it unearths. In this study, we delved into the unorthodox relationship between air pollution in Boulder and the enigmatic phenomenon of increased Google searches for 'how to trap a spider'. Leveraging data from the Environmental Protection Agency and Google Trends, our research team employed rigorous statistical analyses to evaluate this unlikely correlation. Our findings revealed a remarkably robust correlation coefficient of 0.5891134 with a statistically significant p-value of less than 0.05, indicating a tangible link between deteriorating air quality and arachnophobic internet inquiries. This study not only sheds light on the unanticipated consequences of pollution but also uncovers the peculiar inclinations of our internet-surfing comrades. So, the next time you spot a spider in your Boulder abode, don't just blame its eight-legged presence; perhaps the smog in the air played a role in your quest to learn how to usher it out.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
INTRODUCTION
Air pollution is a well-documented environmental hazard with substantial impacts on human health and well-being. From respiratory ailments to environmental degradation, the deleterious effects of smog and particulate matter have been the focus of extensive scholarly inquiry. However, amidst the fervent efforts to mitigate these adverse effects, the peculiar and unexpected connections that air pollution may have with seemingly unrelated phenomena have often been overlooked.
In this study, we venture into the whimsical realm of internet search trends to explore the curious association between air pollution in Boulder and the surge in Google searches for 'how to trap a spider'. While one might initially dismiss this correlation as a mere quirk of data, our investigation brings to light the potential interplay between environmental factors and seemingly unrelated human behaviors. The bustling digitized world of Google searches not only serves as a reflection of our collective curiosities but also unveils the perplexing and sometimes amusing connections between our daily lives and the environment around us.
The city of Boulder, nestled in the picturesque foothills of the Rocky Mountains, provides an intriguing backdrop for our inquiry. Renowned for its vibrant community and progressive environmental initiatives, Boulder also grapples with its share of air quality concerns, especially during periods of inversions and atmospheric stagnation. Against this setting, we set out to unravel the enigmatic correspondence between declining air quality and the sudden spike in spider-trapping queries on the world's most ubiquitous search engine.
Leveraging data from the Environmental Protection Agency's Air Quality System and Google Trends, our research team embarked on a rigorous quantitative analysis to disentangle this seemingly improbable association. As we unravel the intricate web of data and statistical measures, our quest is not merely to elucidate a statistical link, but to uncover the underlying mechanisms and behavioral insights that underpin this unorthodox relationship. Through this investigation, we aim to offer a nuanced perspective on the multifaceted repercussions of air pollution and delve into the inherent quirks of human response to environmental stressors.
Hence, as we embark on this scholarly expedition, let us not only seek to unravel the mysteries of statistical correlation but also embrace the serendipitous discoveries that await us. After all, in the realm of academic inquiry, uncovering unexpected connections often leads to the most intriguing and, at times, amusing revelations. So, fasten your seatbelts and brace yourselves for a journey that promises to uncover the unforeseen intersection of air pollution and arachnophobic inquisitiveness.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The statistical analysis of the data unearthed a notable correlation between air pollution in Boulder and the frequency of Google searches for 'how to trap a spider'. Over the period from 2007 to 2023, our research team found a correlation coefficient of 0.5891134, indicating a moderately strong relationship between these seemingly disparate variables. The coefficient of determination (r-squared) of 0.3470546 suggests that approximately 34.71% of the variability in spider-trapping queries can be explained by changes in air pollution levels. Furthermore, the p-value of less than 0.05 attests to the statistical significance of this relationship, providing compelling evidence for the link between air quality and arachnophobic online behavior.

The scatterplot depicted in Figure 1 illustrates the robust correlation, affirming the upward trend in 'how to trap a spider' searches as air pollution escalates. The data points congregate along a discernible trajectory, mirroring the ascent of spider-related queries amidst the haze of elevated pollution levels. It's almost as if the influx of smog acts as a silent prompt, nudging denizens of Boulder to seek refuge from not only the noxious air but also the perturbing presence of eight-legged visitors.

The unexpected affinity between environmental pollutants and spider-trapping inquiries unravels a curious dimension of human response to air quality fluctuations. While the initial premise of our investigation may have elicited bemusement, the empirical findings affirm the legitimacy of this unorthodox association. From a whimsical standpoint, one might ponder if the spiders themselves, emboldened by the murky atmosphere, instigate a virtual uproar as residents scramble to devise ingenious trapping strategies.

This study, while unearthing an unconventional linkage, serves as a potent reminder of the intricate tapestry that interweaves human behavior and environmental dynamics. The implications of this research extend beyond the confines of academic novelty, offering insight into the idiosyncrasies of human responses to environmental stressors. The next time you find yourself furrowing your brow at a preposterously specific Google search trend, remember that within the labyrinthine corridors of internet data, peculiar connections await their revelation.

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 pollution in Boulder and Google searches for 'how to trap a spider'. 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]]
When the Smog is Thick, Your Spider-Trap Search Trend will Stick: An Analysis of Air Pollution in Boulder and Google Searches for 'How to Trap a Spider'

[[ABSTRACT]]
The incessant battle against airborne toxins has often overshadowed the quirky idiosyncrasies it unearths. In this study, we delved into the unorthodox relationship between air pollution in Boulder and the enigmatic phenomenon of increased Google searches for 'how to trap a spider'. Leveraging data from the Environmental Protection Agency and Google Trends, our research team employed rigorous statistical analyses to evaluate this unlikely correlation. Our findings revealed a remarkably robust correlation coefficient of 0.5891134 with a statistically significant p-value of less than 0.05, indicating a tangible link between deteriorating air quality and arachnophobic internet inquiries. This study not only sheds light on the unanticipated consequences of pollution but also uncovers the peculiar inclinations of our internet-surfing comrades. So, the next time you spot a spider in your Boulder abode, don't just blame its eight-legged presence; perhaps the smog in the air played a role in your quest to learn how to usher it out.

[[LITERATURE REVIEW]]
The investigation of seemingly incongruous phenomena often uncovers surprising connections and unexpected correlations, leading to intriguing insights. Smith et al. (2018) delved into the far-reaching impacts of air pollution, emphasizing its implications for public health and ecological sustainability. Similarly, Doe and Jones (2017) meticulously scrutinized the atmospheric dynamics of Boulder and its susceptibility to episodic deterioration in air quality, shedding light on the city's ongoing battle against airborne toxins.
Notably, the extensive body of literature on air pollution often focuses on its well-documented repercussions, encompassing a spectrum of respiratory diseases, environmental degradation, and the overarching impact on societal well-being. However, in a departure from conventional scholarly discourse, our inquiry transcends the commonly explored terrain to unravel an unusual correlation between air pollution in Boulder and the surge in Google searches for 'how to trap a spider'.
Expanding our purview beyond the academic arena, popular non-fiction works such as "The Air Pollution Crisis: Exploring Environmental Hazards" by Environmental Scientist Ipsum (2019) and "Boulder's Atmosphere: An Ongoing Saga" by Atmospheric Researcher Lorem (2020) delve into the intricate nuances of pollution dynamics and its implications for local ecosystems. These comprehensive treatises, while invaluable in elucidating the gravity of the pollution predicament, inadvertently overlook the whimsical manifestations of pollution-induced behaviors.
In a similar vein, the exercises of human curiosity in response to environmental stimuli have long been overlooked in the domain of scholarly inquiry. However, works of fiction such as "The Web of Intrigue: A Tale of Arachnophobia" by Fiction Author X (2015) and "Spiders in Smog: An Unlikely Alliance" by Novelist Y (2018) allude to the serendipitous interplay between environmental cues and peculiar human responses. Though fictional in nature, these works unknowingly presage the unexpected association that our research endeavors to unravel.
Moreover, the prevalence of internet memes, such as the "Spider Bro" and "Boulder Smog Spider Trap Challenge," serves as an additional testament to the public's engagement with the intersection of air pollution and spider-related phenomena. Seemingly irreverent at first glance, these memes offer a subtle reflection of society's intrigue with the quirky juxtapositions that emerge amidst environmental challenges.
Thus, our foray into the convergence of air pollution in Boulder and the surge in 'how to trap a spider' queries not only presents an unconventional synergy between seemingly disparate entities but also unearths the whimsical facets of human response to environmental stressors. As we navigate through the literary landscape, it becomes evident that the interplay between pollution and peculiar human inclinations transcends the boundaries of empirical investigation, unfurling a tapestry of unexpected correlations and comical juxtapositions.

[[RESULTS]]
The statistical analysis of the data unearthed a notable correlation between air pollution in Boulder and the frequency of Google searches for 'how to trap a spider'. Over the period from 2007 to 2023, our research team found a correlation coefficient of 0.5891134, indicating a moderately strong relationship between these seemingly disparate variables. The coefficient of determination (r-squared) of 0.3470546 suggests that approximately 34.71% of the variability in spider-trapping queries can be explained by changes in air pollution levels. Furthermore, the p-value of less than 0.05 attests to the statistical significance of this relationship, providing compelling evidence for the link between air quality and arachnophobic online behavior.
The scatterplot depicted in Figure 1 illustrates the robust correlation, affirming the upward trend in 'how to trap a spider' searches as air pollution escalates. The data points congregate along a discernible trajectory, mirroring the ascent of spider-related queries amidst the haze of elevated pollution levels. It's almost as if the influx of smog acts as a silent prompt, nudging denizens of Boulder to seek refuge from not only the noxious air but also the perturbing presence of eight-legged visitors.
The unexpected affinity between environmental pollutants and spider-trapping inquiries unravels a curious dimension of human response to air quality fluctuations. While the initial premise of our investigation may have elicited bemusement, the empirical findings affirm the legitimacy of this unorthodox association. From a whimsical standpoint, one might ponder if the spiders themselves, emboldened by the murky atmosphere, instigate a virtual uproar as residents scramble to devise ingenious trapping strategies.
This study, while unearthing an unconventional linkage, serves as a potent reminder of the intricate tapestry that interweaves human behavior and environmental dynamics. The implications of this research extend beyond the confines of academic novelty, offering insight into the idiosyncrasies of human responses to environmental stressors. The next time you find yourself furrowing your brow at a preposterously specific Google search trend, remember that within the labyrinthine corridors of internet data, peculiar connections await their revelation.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of our investigation reveal a compelling correlation between air pollution in Boulder and the surge in Google searches for 'how to trap a spider'. Our results align with prior research by Smith et al. (2018) and Doe and Jones (2017), which emphasized the multifaceted implications of air pollution, albeit not in the context of spider-trapping inquiries. Although the quirky manifestations of pollution-induced behaviors have often been downplayed, our study underscores the validity of these peculiar interconnections and validates the relevance of seemingly offbeat phenomena in understanding environmental dynamics.

It is noteworthy that our results not only corroborate the presence of a statistically significant relationship between air quality and arachnophobic internet inquiries but also shed light on the unexpected nuances of human behavior in response to environmental stressors. This substantiates the premise put forth in works of fiction such as "The Web of Intrigue: A Tale of Arachnophobia" and "Spiders in Smog: An Unlikely Alliance," which incidentally foresaw the unlikely association our research endeavors to unravel.

The robust correlation coefficient between air pollution and spider-trapping searches underscores a tangible link, hinting at a potential psychological response to deteriorating air quality. While it may seem far-fetched, the empirical evidence lends credence to the prospect that the unsettling presence of spiders may be exacerbated by the haze of environmental pollutants, provoking a surge in information-seeking behavior regarding spider entrapment techniques. One might even jest that the spiders, emboldened by the smog, are orchestrating a virtual uproar, compelling denizens of Boulder to devise elaborate strategies for their capture.

The unanticipated alliance between pollution and peculiar human inclinations furthers our understanding of the intricate interplay between environmental cues and idiosyncratic responses. It also resonates with the popular internet memes, such as the "Spider Bro" and "Boulder Smog Spider Trap Challenge," offering a quirky reflection of society's engagement with the unexpected correlations that emerge amidst environmental challenges.

In conclusion, our research warns against the perils of underestimating the whimsical manifestations of pollution-induced behaviors and emphasizes the relevance of considering seemingly incongruous phenomena in the discourse on environmental dynamics. As we delve deeper into the convoluted web of environmental interconnections, we unravel an enigmatic tapestry of peculiar correlations and comical juxtapositions, affirming that even in the hazy fog of pollution, unexpected connections await their revelation.

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 pollution in Boulder and Google searches for 'how to trap a spider'. 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]]
When the Smog is Thick, Your Spider-Trap Search Trend will Stick: An Analysis of Air Pollution in Boulder and Google Searches for 'How to Trap a Spider'

[[ABSTRACT]]
The incessant battle against airborne toxins has often overshadowed the quirky idiosyncrasies it unearths. In this study, we delved into the unorthodox relationship between air pollution in Boulder and the enigmatic phenomenon of increased Google searches for 'how to trap a spider'. Leveraging data from the Environmental Protection Agency and Google Trends, our research team employed rigorous statistical analyses to evaluate this unlikely correlation. Our findings revealed a remarkably robust correlation coefficient of 0.5891134 with a statistically significant p-value of less than 0.05, indicating a tangible link between deteriorating air quality and arachnophobic internet inquiries. This study not only sheds light on the unanticipated consequences of pollution but also uncovers the peculiar inclinations of our internet-surfing comrades. So, the next time you spot a spider in your Boulder abode, don't just blame its eight-legged presence; perhaps the smog in the air played a role in your quest to learn how to usher it out.

[[INTRDUCTION]]
INTRODUCTION
Air pollution is a well-documented environmental hazard with substantial impacts on human health and well-being. From respiratory ailments to environmental degradation, the deleterious effects of smog and particulate matter have been the focus of extensive scholarly inquiry. However, amidst the fervent efforts to mitigate these adverse effects, the peculiar and unexpected connections that air pollution may have with seemingly unrelated phenomena have often been overlooked.
In this study, we venture into the whimsical realm of internet search trends to explore the curious association between air pollution in Boulder and the surge in Google searches for 'how to trap a spider'. While one might initially dismiss this correlation as a mere quirk of data, our investigation brings to light the potential interplay between environmental factors and seemingly unrelated human behaviors. The bustling digitized world of Google searches not only serves as a reflection of our collective curiosities but also unveils the perplexing and sometimes amusing connections between our daily lives and the environment around us.
The city of Boulder, nestled in the picturesque foothills of the Rocky Mountains, provides an intriguing backdrop for our inquiry. Renowned for its vibrant community and progressive environmental initiatives, Boulder also grapples with its share of air quality concerns, especially during periods of inversions and atmospheric stagnation. Against this setting, we set out to unravel the enigmatic correspondence between declining air quality and the sudden spike in spider-trapping queries on the world's most ubiquitous search engine.
Leveraging data from the Environmental Protection Agency's Air Quality System and Google Trends, our research team embarked on a rigorous quantitative analysis to disentangle this seemingly improbable association. As we unravel the intricate web of data and statistical measures, our quest is not merely to elucidate a statistical link, but to uncover the underlying mechanisms and behavioral insights that underpin this unorthodox relationship. Through this investigation, we aim to offer a nuanced perspective on the multifaceted repercussions of air pollution and delve into the inherent quirks of human response to environmental stressors.
Hence, as we embark on this scholarly expedition, let us not only seek to unravel the mysteries of statistical correlation but also embrace the serendipitous discoveries that await us. After all, in the realm of academic inquiry, uncovering unexpected connections often leads to the most intriguing and, at times, amusing revelations. So, fasten your seatbelts and brace yourselves for a journey that promises to uncover the unforeseen intersection of air pollution and arachnophobic inquisitiveness.

[[RESULTS]]
The statistical analysis of the data unearthed a notable correlation between air pollution in Boulder and the frequency of Google searches for 'how to trap a spider'. Over the period from 2007 to 2023, our research team found a correlation coefficient of 0.5891134, indicating a moderately strong relationship between these seemingly disparate variables. The coefficient of determination (r-squared) of 0.3470546 suggests that approximately 34.71% of the variability in spider-trapping queries can be explained by changes in air pollution levels. Furthermore, the p-value of less than 0.05 attests to the statistical significance of this relationship, providing compelling evidence for the link between air quality and arachnophobic online behavior.
The scatterplot depicted in Figure 1 illustrates the robust correlation, affirming the upward trend in 'how to trap a spider' searches as air pollution escalates. The data points congregate along a discernible trajectory, mirroring the ascent of spider-related queries amidst the haze of elevated pollution levels. It's almost as if the influx of smog acts as a silent prompt, nudging denizens of Boulder to seek refuge from not only the noxious air but also the perturbing presence of eight-legged visitors.
The unexpected affinity between environmental pollutants and spider-trapping inquiries unravels a curious dimension of human response to air quality fluctuations. While the initial premise of our investigation may have elicited bemusement, the empirical findings affirm the legitimacy of this unorthodox association. From a whimsical standpoint, one might ponder if the spiders themselves, emboldened by the murky atmosphere, instigate a virtual uproar as residents scramble to devise ingenious trapping strategies.
This study, while unearthing an unconventional linkage, serves as a potent reminder of the intricate tapestry that interweaves human behavior and environmental dynamics. The implications of this research extend beyond the confines of academic novelty, offering insight into the idiosyncrasies of human responses to environmental stressors. The next time you find yourself furrowing your brow at a preposterously specific Google search trend, remember that within the labyrinthine corridors of internet data, peculiar connections await their revelation.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study elucidates the unanticipated nexus between air pollution in Boulder and the surge in Google searches for 'how to trap a spider'. While it may seem like an unlikely pair, our robust statistical analysis has revealed a tangible correlation, throwing a web of intrigue over the unsuspecting realm of internet search trends. The correlation coefficient of 0.5891134 and the statistically significant p-value of less than 0.05 underscore the legitimacy of this peculiar association, prompting us to ponder if the spiders themselves have enlisted the smog as their impish accomplice.

As we reflect on the whimsical interplay between environmental pollutants and arachnophobic inquiries, this inquiry reminds us that amidst the dense fog of scientific rigor, unexpected revelations often weave a narrative of their own. Whether it's the spiders seeking solace from the murky skies or the denizens of Boulder fervently drafting escape strategies, our findings beckon us to contemplate the enigmatic dance between nature's quirks and human response.

Therefore, with a wink to serendipity and a nod to the uncharted frontiers of scientific inquiry, we assert that the tale of air pollution and 'how to trap a spider' queries has been unraveled with finesse. No further research is needed on this baffling yet amusing correlation, lest we risk entangling ourselves in a web of quixotic conundrums.

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 When the Smog is Thick, Your Spider-Trap Search Trend will Stick: An Analysis of Air Pollution in Boulder and Google Searches for 'How to Trap a Spider'. Respond only with the name of a fictional academic journal.

ChatGPT:

The International Journal of Ecological Curiosities

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 When the Smog is Thick, Your Spider-Trap Search Trend will Stick: An Analysis of Air Pollution in Boulder and Google Searches for 'How to Trap a Spider'. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Environmental Neuro-Entomology Research (SENER)

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 When the Smog is Thick, Your Spider-Trap Search Trend will Stick: An Analysis of Air Pollution in Boulder and Google Searches for 'How to Trap a Spider' with an abstract of The incessant battle against airborne toxins has often overshadowed the quirky idiosyncrasies it unearths. In this study, we delved into the unorthodox relationship between air pollution in Boulder and the enigmatic phenomenon of increased Google searches for 'how to trap a spider'. Leveraging data from the Environmental Protection Agency and Google Trends, our research team employed rigorous statistical analyses to evaluate this unlikely correlation. Our findings revealed a remarkably robust correlation coefficient of 0.5891134 with a statistically significant p-value of less than 0.05, indicating a tangible link between deteriorating air quality and arachnophobic internet inquiries. This study not only sheds light on the unanticipated consequences of pollution but also uncovers the peculiar inclinations of our internet-surfing comrades. So, the next time you spot a spider in your Boulder abode, don't just blame its eight-legged presence; perhaps the smog in the air played a role in your quest to learn how to usher it out.

ChatGPT:

Air pollution, Boulder air quality, Google searches, Spider trap searches, Airborne toxins, Environmental Protection Agency data, Air pollution research, Statistical analysis, Google Trends, Correlation coefficient, P-value, Internet search behavior

*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.

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Data details

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

Google searches for 'how to trap a spider'
Detailed data title: Relative volume of Google searches for 'how to trap a spider' (Worldwide, without quotes)
Source: Google Trends
Additional Info: ^{See full details} Relative search volume (not absolute numbers)

See what else correlates with Google searches for 'how to trap a spider'

Correlation r = 0.5891134 (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 = 0.3470546 (Coefficient of determination)
This means 34.7% of the change in the one variable (i.e., Google searches for 'how to trap a spider') is predictable based on the change in the other (i.e., Air pollution in Boulder) over the 17 years from 2007 through 2023.

p < 0.05, which statistically significant(Null hypothesis significance test)
The p-value is 0.013.^Show 0.0128329598794020470000000000
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 0.59 in 1.3% of random cases. Said differently, if you correlated 78 random variables^Note Which I absolutely did.
with the same 16 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 16 because we have two variables measured over a period of 17 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.

[ 0.15, 0.83 ] 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.

	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022	2023
Air pollution in Boulder (Bad air quality days)	6.0274	4.37158	2.73973	3.28767	4.38356	9.7493	4.44444	1.38889	1.91781	0	3.08123	8.01105	1.36986	5.7377	9.58904	1.91781	2.00803
Google searches for 'how to trap a spider' (Rel. search volume)	12.9167	5.66667	4.41667	4	5.16667	12.9167	8.25	5.5	6.66667	4.16667	5.75	7.16667	5.66667	6.75	5.83333	6.25	5.33333

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
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([6.0274,4.37158,2.73973,3.28767,4.38356,9.7493,4.44444,1.38889,1.91781,0,3.08123,8.01105,1.36986,5.7377,9.58904,1.91781,2.00803,])
array_2 = np.array([12.9167,5.66667,4.41667,4,5.16667,12.9167,8.25,5.5,6.66667,4.16667,5.75,7.16667,5.66667,6.75,5.83333,6.25,5.33333,])
array_1_name = "Air pollution in Boulder"
array_2_name = "Google searches for 'how to trap a spider'"

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

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

Reuseable content

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

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

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

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

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

Download images for these variables:

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

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

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Air pollution in Boulder
Line chart for only Google searches for 'how to trap a spider'
AI-generated correlation image
The spurious research paper: When the Smog is Thick, Your Spider-Trap Search Trend will Stick: An Analysis of Air Pollution in Boulder and Google Searches for 'How to Trap a Spider'

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Correlation ID: 2763 · Black Variable ID: 20381 · Red Variable ID: 1448


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