Spurious correlation #1,154 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is West Nile Virus Cases and the second variable is Google searches for 'how to trap a spider'. The chart goes from 2007 to 2022, 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 West Nile Virus Cases and the second variable is Google searches for 'how to trap a spider'. The chart goes from 2007 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the West Nile Virus cases decreased, there was a correlating decrease in the mosquito population. With fewer mosquitos around to feast on, the spiders found themselves facing a food shortage. In response, they packed their bags and moved to greener (or should I say bug-ier) pastures, leading to fewer encounters with humans and thus a reduced need for spider-trapping tutorials. With the spider population seeking new hunting grounds, it seems the phrase "spider season" came to a premature end, much to the relief of arachnophobes everywhere.

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a serene backyard scene with a person sitting in front of a computer. The atmosphere should exude a sense of tranquility as fewer mosquitoes buzz around the area, leading to a reduction in the number of spiders crawling about. The person is seated comfortably, with a lower number of search results displayed on the screen for "how to trap a spider." The focus should be on the peaceful coexistence of nature and technology in the tranquil outdoor setting. 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 situation described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here is a situation: The decrease in West Nile Virus cases decreased the number of mosquitoes, which meant there were fewer spiders around the searchers to trap, resulting in a decrease in Google searches for "how to trap a spider.". Given that situation, which of the following image descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand and the tone of the explanation. Please respond with only one of the following potential descriptions: Celtic art Symbolism Woodblock painting Voxel art Data cyber art
ChatGPT: Data cyber art

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated and the explanation described. Do not reference graphs or charts; describe physical objects.
User prompt: Please describe a visual scene that depicts the following situation. Keep the description simple. The decrease in West Nile Virus cases decreased the number of mosquitoes, which meant there were fewer spiders around the searchers to trap, resulting in a decrease in Google searches for "how to trap a spider."
ChatGPT: In the backyard, there are fewer mosquitoes buzzing around. Consequently, there are also fewer spiders seen crawling around the area. A person sits in front of a computer with fewer search results for "how to trap a spider" on the screen.

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: [ Data cyber art ] and depicting this scene: In the backyard, there are fewer mosquitoes buzzing around. Consequently, there are also fewer spiders seen crawling around the area. A person sits in front of a computer with fewer search results for "how to trap a spider" on the screen. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a serene backyard scene with a person sitting in front of a computer. The atmosphere should exude a sense of tranquility as fewer mosquitoes buzz around the area, leading to a reduction in the number of spiders crawling about. The person is seated comfortably, with a lower number of search results displayed on the screen for "how to trap a spider." The focus should be on the peaceful coexistence of nature and technology in the tranquil outdoor setting.

*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 West Nile Virus Cases caused how to trap a spider (Google searches for 'how to trap a spider') to decrease.

AI academic paper

(Because p < 0.01)

Caught in the Web: Unraveling the Connection Between West Nile Virus and How to Trap a Spider Google Searches

Journal of Arachnid Ecology and Disease Control

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 West Nile Virus Cases and Google searches for 'how to trap a spider'. Make lots of 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 cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
Caught in the Web: Unraveling the Connection Between West Nile Virus and "How to Trap a Spider" Google Searches

[[ABSTRACT]]
As the saying goes, "spiders and viruses, oh my!" In this study, we set out to investigate the peculiar relationship between West Nile Virus (WNV) cases and Google searches for "how to trap a spider." Despite sounding like a tangled web of unrelated topics, we utilized data from the West Nile Support organization and Google Trends to untangle this web of curiosity. Our findings revealed a surprising correlation coefficient of 0.8024517 and statistically significant p-value of less than 0.01 from 2007 to 2022. This quirky correlation sheds light on the curious behaviors of the human mind when confronted with the threat of mosquito-borne illnesses. Our results suggest that while individuals may initially seek out methods to capture eight-legged pests, their elevated concerns may extend to other pest-related dangers, including the dreaded West Nile Virus. As we delve into the interconnectedness of seemingly unrelated search queries, it's clear that in the world of internet queries, the line between spider-catching tactics and mosquito-borne illness prevention may just be a strand of silk.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The world of research can often feel like a tangled web, full of unexpected twists and turns. Researchers comb through data, hoping to catch a glimpse of the elusive correlations and connections that lurk within. In this study, we found ourselves entangled in the peculiar relationship between West Nile Virus (WNV) cases and Google searches for "how to trap a spider." As our findings began to emerge, we couldn't help but wonder if we were caught in a web of statistical coincidence or if there was a genuine insight waiting to be unraveled.
It's a well-known fact that spiders and viruses are both skilled at spinning their webs—whether it's a delicate geometric pattern to capture prey or a complex web of molecular interactions within a host. However, their paths rarely cross in the world of scientific inquiry. Yet, as the famous arachnologist Charlotte once mused, "how puzzling all these relations are." With this sentiment in mind, we embarked on our investigation, hoping to shed light on this unexpected intersection of spider trapping and mosquito-borne disease.
Our interest in this peculiar juxtaposition was sparked by the fascinating realm of internet search patterns. The vast expanse of the web (both the digital and arachnid kinds) offers a unique lens through which to observe human behavior and the quirky, often whimsical, patterns that emerge. After all, what could be more fitting than delving into the digital domain in a quest to understand the entangled intricacies of human thought?
The aim of this paper is to illuminate the unforeseen correlation between West Nile Virus cases and the seemingly unrelated act of searching for spider-trapping techniques. In doing so, we hope to demonstrate the surprising confluences that can arise in the vast ocean of search queries and infectious diseases. Buckle up, dear readers, as we navigate through this curious journey of statistical intrigue and unexpected connections.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The captivating connection between West Nile Virus (WNV) cases and Google searches for "how to trap a spider" has sparked a flurry of scholarly inquiries into the enigmatic realms of human curiosity and digital behavior. Smith et al. (2015) delved into the intricacies of internet search patterns and their potential implications for public health surveillance. Their study, though primarily focused on flu-related queries, laid the groundwork for our own investigation into the unexpected correlation between spider-trapping inquiries and the menacing specter of WNV.

Building upon this foundation, Doe (2018) conducted a comprehensive analysis of the behavioral psychology underpinning internet search trends. Their groundbreaking work shed light on how seemingly disparate topics can intersect in the digital landscape, paving the way for our exploration of the intersection between arachnids and arboviruses. Jones (2020), in a departure from traditional epidemiological studies, highlighted the role of unconventional data sources, such as Google Trends, in uncovering novel insights into public health phenomena.

As we weave through the literature, we encounter a myriad of unexpected titles that beckon us into the world of arachnids, viruses, and the peculiar interplay of human behavior. "The Illustrated Encyclopedia of Spiders" by Smith (2019) may seem like a departure from our topic, yet its detailed depictions of arachnid species stoke our curiosity about the human fascination with spider-centric queries. On the virus front, "Emerging Infectious Diseases: A Guide to Viruses, Bacteria, and Parasites" by Doe (2016) serves as a reminder of the diverse threats lurking in the natural world, including the notorious WNV.

Venturing into the realm of fiction, we stumble upon "Spiderweb" by John Doe, a tantalizing tale of deceit, espionage, and the unsuspecting entanglements of its characters. While seemingly unrelated to our pursuit, the thread of entrapment and the unseen connections eerily mirror our quest to untangle the web of WNV and spider-trapping searches.

Social media, too, offers a fascinating foray into the public consciousness surrounding spiders and viruses. A viral tweet by @ArachnoEnthusiast declaring, "Just caught a spider in the kitchen! Now to prepare for West Nile Virus like a true daredevil," captures the essence of our investigation—how seemingly incongruous concepts can intersect in the digital domain.

Armed with this eclectic mix of literature and insights, we are poised to untangle the web of correlations and whimsical connections that underpin the nexus between WNV and "how to trap a spider" Google searches. As we proceed, let us not forget the intricate dance of fate and folly that may just lead us to unexpected revelations within this tangled web of human curiosity.

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 West Nile Virus Cases and Google searches for 'how to trap a spider'. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from West Nile Support and Google Trends . You used data from 2007 to 2022

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]]
Caught in the Web: Unraveling the Connection Between West Nile Virus and "How to Trap a Spider" Google Searches

[[ABSTRACT]]
As the saying goes, "spiders and viruses, oh my!" In this study, we set out to investigate the peculiar relationship between West Nile Virus (WNV) cases and Google searches for "how to trap a spider." Despite sounding like a tangled web of unrelated topics, we utilized data from the West Nile Support organization and Google Trends to untangle this web of curiosity. Our findings revealed a surprising correlation coefficient of 0.8024517 and statistically significant p-value of less than 0.01 from 2007 to 2022. This quirky correlation sheds light on the curious behaviors of the human mind when confronted with the threat of mosquito-borne illnesses. Our results suggest that while individuals may initially seek out methods to capture eight-legged pests, their elevated concerns may extend to other pest-related dangers, including the dreaded West Nile Virus. As we delve into the interconnectedness of seemingly unrelated search queries, it's clear that in the world of internet queries, the line between spider-catching tactics and mosquito-borne illness prevention may just be a strand of silk.

[[INTRODUCTION]]
The world of research can often feel like a tangled web, full of unexpected twists and turns. Researchers comb through data, hoping to catch a glimpse of the elusive correlations and connections that lurk within. In this study, we found ourselves entangled in the peculiar relationship between West Nile Virus (WNV) cases and Google searches for "how to trap a spider." As our findings began to emerge, we couldn't help but wonder if we were caught in a web of statistical coincidence or if there was a genuine insight waiting to be unraveled.
It's a well-known fact that spiders and viruses are both skilled at spinning their webs—whether it's a delicate geometric pattern to capture prey or a complex web of molecular interactions within a host. However, their paths rarely cross in the world of scientific inquiry. Yet, as the famous arachnologist Charlotte once mused, "how puzzling all these relations are." With this sentiment in mind, we embarked on our investigation, hoping to shed light on this unexpected intersection of spider trapping and mosquito-borne disease.
Our interest in this peculiar juxtaposition was sparked by the fascinating realm of internet search patterns. The vast expanse of the web (both the digital and arachnid kinds) offers a unique lens through which to observe human behavior and the quirky, often whimsical, patterns that emerge. After all, what could be more fitting than delving into the digital domain in a quest to understand the entangled intricacies of human thought?
The aim of this paper is to illuminate the unforeseen correlation between West Nile Virus cases and the seemingly unrelated act of searching for spider-trapping techniques. In doing so, we hope to demonstrate the surprising confluences that can arise in the vast ocean of search queries and infectious diseases. Buckle up, dear readers, as we navigate through this curious journey of statistical intrigue and unexpected connections.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To untangle the sticky threads linking West Nile Virus (WNV) cases and Google searches for "how to trap a spider," we embarked on a journey that was part statistically rigorous and part arachnologically amusing. Our research team set out to capture the essence of this peculiar relationship by utilizing data from both the virtual domain of Google Trends and the real-world expertise of the West Nile Support organization. As we embarked on our rather peculiar quest, we encountered a few twists and turns that would make even the most seasoned statistical theorist squirm in their seat.

First and foremost, we delved into the realm of Google Trends, casting our digital net far and wide to capture the ebb and flow of searches related to spider-trapping methods from 2007 to 2022. We marveled at the vast array of search queries, from "how to trap a spider with household items" to "spider-catching contraptions of the modern era." It was a veritable web of search data, and we spared no effort in untangling the gossamer threads of curious internet users seeking to conquer their arachnoid adversaries.

Simultaneously, we relied on the impactful insights provided by the West Nile Support organization, where we gathered data on reported WNV cases across the same temporal span. As we navigated through their database, we couldn't help but appreciate the intricate nature of disease tracking, all the while pondering the parallel complexities involved in the art of spider trapping. It was a true meeting of minds, where the world of epidemiology intertwined with the expertise of spider enthusiasts in a truly unusual union.

To measure the correlation between these seemingly disparate phenomena, we employed the stalwart Pearson correlation coefficient, rendering our data into a tidy statistical web. We then spun our metaphorical statistical web, drawing from the depths of our knowledge in data analysis to calculate p-values and extract meaningful insights from the intertwined data sets. Our statistical endeavors were not for the faint of heart, straddling the line between traditional epidemiological analysis and the arachnologically unconventional.

In tracking the rise and fall of WNV cases and spider-trapping queries, we sought to weave a narrative that would reveal the hidden threads connecting these seemingly incongruous entities. Embarking on this statistical escapade, we chuckled at the thought of spiders employing their own "web analytics" and wondered if the mosquitoes harboring West Nile Virus were secretly organizing their own search engine optimization campaigns. It was a curious blend of scientific inquiry and whimsical amusement, as we waded into the depths of inquisitive human behavior and the intricate dance between infectious diseases and innate fears of the arachnid kind.

In sum, our methodology entailed casting a wide digital net, tapping into the obscure corners of human internet behavior, and employing the tenets of statistical analysis to tease out the threads connecting West Nile Virus cases and the pursuit of spider-trapping knowledge. The journey was as amusing as it was enlightening, and we emerged with our statistical tools firmly in hand, ready to untangle the curious web of correlation that had captivated our scientific curiosity.

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 West Nile Virus Cases and Google searches for 'how to trap a spider'. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Caught in the Web: Unraveling the Connection Between West Nile Virus and "How to Trap a Spider" Google Searches

[[ABSTRACT]]
As the saying goes, "spiders and viruses, oh my!" In this study, we set out to investigate the peculiar relationship between West Nile Virus (WNV) cases and Google searches for "how to trap a spider." Despite sounding like a tangled web of unrelated topics, we utilized data from the West Nile Support organization and Google Trends to untangle this web of curiosity. Our findings revealed a surprising correlation coefficient of 0.8024517 and statistically significant p-value of less than 0.01 from 2007 to 2022. This quirky correlation sheds light on the curious behaviors of the human mind when confronted with the threat of mosquito-borne illnesses. Our results suggest that while individuals may initially seek out methods to capture eight-legged pests, their elevated concerns may extend to other pest-related dangers, including the dreaded West Nile Virus. As we delve into the interconnectedness of seemingly unrelated search queries, it's clear that in the world of internet queries, the line between spider-catching tactics and mosquito-borne illness prevention may just be a strand of silk.

[[LITERATURE REVIEW]]
The captivating connection between West Nile Virus (WNV) cases and Google searches for "how to trap a spider" has sparked a flurry of scholarly inquiries into the enigmatic realms of human curiosity and digital behavior. Smith et al. (2015) delved into the intricacies of internet search patterns and their potential implications for public health surveillance. Their study, though primarily focused on flu-related queries, laid the groundwork for our own investigation into the unexpected correlation between spider-trapping inquiries and the menacing specter of WNV.
Building upon this foundation, Doe (2018) conducted a comprehensive analysis of the behavioral psychology underpinning internet search trends. Their groundbreaking work shed light on how seemingly disparate topics can intersect in the digital landscape, paving the way for our exploration of the intersection between arachnids and arboviruses. Jones (2020), in a departure from traditional epidemiological studies, highlighted the role of unconventional data sources, such as Google Trends, in uncovering novel insights into public health phenomena.
As we weave through the literature, we encounter a myriad of unexpected titles that beckon us into the world of arachnids, viruses, and the peculiar interplay of human behavior. "The Illustrated Encyclopedia of Spiders" by Smith (2019) may seem like a departure from our topic, yet its detailed depictions of arachnid species stoke our curiosity about the human fascination with spider-centric queries. On the virus front, "Emerging Infectious Diseases: A Guide to Viruses, Bacteria, and Parasites" by Doe (2016) serves as a reminder of the diverse threats lurking in the natural world, including the notorious WNV.
Venturing into the realm of fiction, we stumble upon "Spiderweb" by John Doe, a tantalizing tale of deceit, espionage, and the unsuspecting entanglements of its characters. While seemingly unrelated to our pursuit, the thread of entrapment and the unseen connections eerily mirror our quest to untangle the web of WNV and spider-trapping searches.
Social media, too, offers a fascinating foray into the public consciousness surrounding spiders and viruses. A viral tweet by @ArachnoEnthusiast declaring, "Just caught a spider in the kitchen! Now to prepare for West Nile Virus like a true daredevil," captures the essence of our investigation—how seemingly incongruous concepts can intersect in the digital domain.
Armed with this eclectic mix of literature and insights, we are poised to untangle the web of correlations and whimsical connections that underpin the nexus between WNV and "how to trap a spider" Google searches. As we proceed, let us not forget the intricate dance of fate and folly that may just lead us to unexpected revelations within this tangled web of human curiosity.

[[RESULTS]]
Our analysis of the data revealed a correlation coefficient of 0.8024517 between West Nile Virus (WNV) cases and Google searches for "how to trap a spider" from 2007 to 2022. The r-squared value of 0.6439287 further underscored the strength of this correlation, indicating that approximately 64% of the variation in WNV cases can be explained by the variability in spider-trapping search queries. With a p-value of less than 0.01, the statistical significance of this relationship left us spinning in excitement, like spiders weaving intricate patterns in the corner of a dusty old attic.
Now, for a sneak peek at our beloved Fig. 1! Picture this: a scatterplot so captivating, it would make even the most steadfast arachnophobe pause and marvel at the web of data points. Each point, like a tiny arachnid scurrying across a digital landscape, reflects the simultaneous rise and fall of WNV cases and "how to trap a spider" searches. It's a visual symphony of statistical harmony, with each plotted point dancing to the rhythm of correlation. Yes, dear readers, Fig. 1 is not just a scatterplot; it's a work of art that captures the essence of our findings in a way that no mere table of numbers ever could.
Our discovery of this robust correlation may seem like a serendipitous tangle of data, much like stumbling upon an unexpected spider web while on a nature walk. Yet, just as a spider meticulously weaves its silk threads with purpose, our findings suggest an intriguing interplay between human behaviors and concerns when faced with the dual threats of pesky spiders and menacing mosquito-borne viruses.
In conclusion, our results highlight the fascinating interconnectedness of seemingly disparate search queries and infectious disease patterns. Just as a spider crafts its web with precision and intent, so too do our findings weave a narrative of unexpected connections in the vast digital realm. As we untangle this web of curiosity, we invite fellow researchers to join us in spinning further hypotheses and entangling themselves in the captivating world of correlational research.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The connection between West Nile Virus (WNV) cases and Google searches for "how to trap a spider" has ensnared our intellectual curiosity, much like a spider capturing its unsuspecting prey. Our findings not only support the prior research delving into the peculiar interplay of seemingly unrelated topics but also offer a delightful twist in the intricate dance of human behavior and digital exploration.

Harking back to the scholarly pursuits that initially piqued our interest, our robust correlation coefficient and statistically significant p-value lend credence to the work of Smith et al. (2015) and Doe (2018) regarding the unexpected intersections in internet search patterns and public health surveillance. Just as a spider deftly navigates its web, our results navigate the labyrinthine landscape of digital inquiries, revealing the interconnectedness of human concern for pests and potential health threats.

As we traverse the arachnoid avenues of statistical analysis, it becomes evident that our findings are not merely a curious web of data but a gossamer thread linking human curiosity, pest management, and disease prevention. The correlation coefficient of 0.8024517 serves as a sturdy strand in this intricate web, showcasing the surprising entanglement of spider-related queries and the menace of WNV.

In the tradition of spinning a good yarn, our study adds an unexpected twist to the web of scientific inquiry, ensnaring readers not only in the gossamer strands of statistical analysis but also in the whimsical dance of human behavior and digital exploration. As we lay bare the captivating correlation between seemingly incongruous topics, it is clear that the world of statistical research is not devoid of humor and unexpected discoveries.

In the tangled web of public health and digital curiosity, our research contributes a unique perspective, much like a spider navigating the nooks and crannies of an old attic. Just as a spider deftly constructs its web, we have woven together a narrative that captures the essence of human curiosity and the unexpected intersections within the digital domain. As we delve deeper into the entwined realms of statistics and human behavior, let us not forget the whimsical surprises that await us in the unexpected corners of scientific exploration.

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 West Nile Virus Cases and Google searches for 'how to trap a spider'. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Caught in the Web: Unraveling the Connection Between West Nile Virus and "How to Trap a Spider" Google Searches

[[ABSTRACT]]
As the saying goes, "spiders and viruses, oh my!" In this study, we set out to investigate the peculiar relationship between West Nile Virus (WNV) cases and Google searches for "how to trap a spider." Despite sounding like a tangled web of unrelated topics, we utilized data from the West Nile Support organization and Google Trends to untangle this web of curiosity. Our findings revealed a surprising correlation coefficient of 0.8024517 and statistically significant p-value of less than 0.01 from 2007 to 2022. This quirky correlation sheds light on the curious behaviors of the human mind when confronted with the threat of mosquito-borne illnesses. Our results suggest that while individuals may initially seek out methods to capture eight-legged pests, their elevated concerns may extend to other pest-related dangers, including the dreaded West Nile Virus. As we delve into the interconnectedness of seemingly unrelated search queries, it's clear that in the world of internet queries, the line between spider-catching tactics and mosquito-borne illness prevention may just be a strand of silk.

[[INTRDUCTION]]
The world of research can often feel like a tangled web, full of unexpected twists and turns. Researchers comb through data, hoping to catch a glimpse of the elusive correlations and connections that lurk within. In this study, we found ourselves entangled in the peculiar relationship between West Nile Virus (WNV) cases and Google searches for "how to trap a spider." As our findings began to emerge, we couldn't help but wonder if we were caught in a web of statistical coincidence or if there was a genuine insight waiting to be unraveled.
It's a well-known fact that spiders and viruses are both skilled at spinning their webs—whether it's a delicate geometric pattern to capture prey or a complex web of molecular interactions within a host. However, their paths rarely cross in the world of scientific inquiry. Yet, as the famous arachnologist Charlotte once mused, "how puzzling all these relations are." With this sentiment in mind, we embarked on our investigation, hoping to shed light on this unexpected intersection of spider trapping and mosquito-borne disease.
Our interest in this peculiar juxtaposition was sparked by the fascinating realm of internet search patterns. The vast expanse of the web (both the digital and arachnid kinds) offers a unique lens through which to observe human behavior and the quirky, often whimsical, patterns that emerge. After all, what could be more fitting than delving into the digital domain in a quest to understand the entangled intricacies of human thought?
The aim of this paper is to illuminate the unforeseen correlation between West Nile Virus cases and the seemingly unrelated act of searching for spider-trapping techniques. In doing so, we hope to demonstrate the surprising confluences that can arise in the vast ocean of search queries and infectious diseases. Buckle up, dear readers, as we navigate through this curious journey of statistical intrigue and unexpected connections.

[[RESULTS]]
Our analysis of the data revealed a correlation coefficient of 0.8024517 between West Nile Virus (WNV) cases and Google searches for "how to trap a spider" from 2007 to 2022. The r-squared value of 0.6439287 further underscored the strength of this correlation, indicating that approximately 64% of the variation in WNV cases can be explained by the variability in spider-trapping search queries. With a p-value of less than 0.01, the statistical significance of this relationship left us spinning in excitement, like spiders weaving intricate patterns in the corner of a dusty old attic.
Now, for a sneak peek at our beloved Fig. 1! Picture this: a scatterplot so captivating, it would make even the most steadfast arachnophobe pause and marvel at the web of data points. Each point, like a tiny arachnid scurrying across a digital landscape, reflects the simultaneous rise and fall of WNV cases and "how to trap a spider" searches. It's a visual symphony of statistical harmony, with each plotted point dancing to the rhythm of correlation. Yes, dear readers, Fig. 1 is not just a scatterplot; it's a work of art that captures the essence of our findings in a way that no mere table of numbers ever could.
Our discovery of this robust correlation may seem like a serendipitous tangle of data, much like stumbling upon an unexpected spider web while on a nature walk. Yet, just as a spider meticulously weaves its silk threads with purpose, our findings suggest an intriguing interplay between human behaviors and concerns when faced with the dual threats of pesky spiders and menacing mosquito-borne viruses.
In conclusion, our results highlight the fascinating interconnectedness of seemingly disparate search queries and infectious disease patterns. Just as a spider crafts its web with precision and intent, so too do our findings weave a narrative of unexpected connections in the vast digital realm. As we untangle this web of curiosity, we invite fellow researchers to join us in spinning further hypotheses and entangling themselves in the captivating world of correlational research.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, it seems we've stumbled into a research web more tangled than Miss Muffet's worst nightmare! Our findings unveil a curious correlation between West Nile Virus (WNV) cases and the Google quest for "how to trap a spider," spinning an unexpected yarn of interconnectedness. Who knew that the search for eight-legged eviction strategies could be entwined with concerns about mosquito-borne maladies? It's as if our data points were doing the funky spider dance, weaving a colorful narrative of statistical harmony.

Like a spider carefully crafting its web, our research has meticulously unraveled a tale of unexpected connections. Weaving through the digital landscape, our findings emphasize the whimsical nature of human inquiry and the surprising overlaps that emerge from seemingly unrelated search queries. This correlation, with a statistical significance that would make even the most stoic arachnophobe pause, highlights the intricate web of human thought and behavior in the face of intertwined threats.

Our journey may have felt like stumbling upon a spider web in a dark attic, but we've emerged with a trove of insight into the surprising correlations that lurk within the digital domain. It's as though we've been caught in a statistical spider's web, and we're absolutely delighted about it!

Now, like any good researcher, we must assert that no further research is needed in this area. We have sufficiently untangled this web of statistical curiosity, leaving fellow scholars with a bounty of insights to ponder.

So, to all the wandering academics out there, remember: when it comes to the perplexing world of tangled research webs, sometimes the unexpected connections are the ones that ultimately spin the most captivating tales. And with that, we bid adieu to our spider-catching statistical adventure, until the next tangled web beckons!

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 Caught in the Web: Unraveling the Connection Between West Nile Virus and How to Trap a Spider Google Searches. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Arachnid Ecology and Disease Control

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 Caught in the Web: Unraveling the Connection Between West Nile Virus and How to Trap a Spider Google Searches. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Arachnid-Borne Disease Research

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Caught in the Web: Unraveling the Connection Between West Nile Virus and How to Trap a Spider Google Searches with an abstract of As the saying goes, "spiders and viruses, oh my!" In this study, we set out to investigate the peculiar relationship between West Nile Virus (WNV) cases and Google searches for "how to trap a spider." Despite sounding like a tangled web of unrelated topics, we utilized data from the West Nile Support organization and Google Trends to untangle this web of curiosity. Our findings revealed a surprising correlation coefficient of 0.8024517 and statistically significant p-value of less than 0.01 from 2007 to 2022. This quirky correlation sheds light on the curious behaviors of the human mind when confronted with the threat of mosquito-borne illnesses. Our results suggest that while individuals may initially seek out methods to capture eight-legged pests, their elevated concerns may extend to other pest-related dangers, including the dreaded West Nile Virus. As we delve into the interconnectedness of seemingly unrelated search queries, it's clear that in the world of internet queries, the line between spider-catching tactics and mosquito-borne illness prevention may just be a strand of silk.

ChatGPT:

West Nile Virus, trap a spider, Google searches, correlation, West Nile Support organization, Google Trends, mosquito-borne illnesses, spider-catching tactics, pest-related dangers, internet queries, interconnectedness

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

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Data details

West Nile Virus Cases
Source: West Nile Support
See what else correlates with West Nile Virus Cases

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 = 0.8024517 (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 = 0.6439287 (Coefficient of determination)
This means 64.4% 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., West Nile Virus Cases) over the 16 years from 2007 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00018.^Show 0.0001834232046404660300000000
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 0.8 in 0.018% of random cases. Said differently, if you correlated 5,452 random variables^Note Which I absolutely did.
with the same 15 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 15 because we have two variables measured over a period of 16 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.

[ 0.51, 0.93 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

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

	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
West Nile Virus Cases (West Nile Cases)	3630	1356	720	1021	712	5674	2469	2205	2175	2149	2097	2647	971	731	2911	1126
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

Why this works

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

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([3630,1356,720,1021,712,5674,2469,2205,2175,2149,2097,2647,971,731,2911,1126,])
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,])
array_1_name = "West Nile Virus Cases"
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 West Nile Virus Cases
Line chart for only Google searches for 'how to trap a spider'
The spurious research paper: Caught in the Web: Unraveling the Connection Between West Nile Virus and How to Trap a Spider Google Searches

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Correlation ID: 1154 · Black Variable ID: 197 · Red Variable ID: 1448


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