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Spurious correlation #3,325 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of bridge and lock tenders in Florida and the second variable is Google searches for 'Mr. Beast'.  The chart goes from 2004 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As the number of bridge and lock tenders in Florida increased, so did the average happiness of boaters passing through. This unexpected ripple effect caused a surge in positivity among internet users, leading to a greater interest in feel-good content. Mr. Beast, known for his philanthropy and heartwarming videos, was the prime beneficiary of this statewide boost in emotional well-being. It seems that even the most obscure occupations can play a pivotal role in shaping online search trends!

Model: dalle-3
Prompt: Based on your request, here's an updated image generation prompt. Description: In a sun-drenched town in Florida, a quaint bridge stands as the focal point, connecting two parts of the town. Standing on the bridge are several bridge and lock tenders, each surrounded by a group of fascinated onlookers. The tenders are holding sets of keys and expertly navigating the locks with precision, captivating the crowd with their skillful mastery. The colorful attire of the tenders contrast against the deep blue of the bridge and the vibrant greenery surrounding the area, giving the scene a lively, cheerful atmosphere. In the background, a flurry of folks can be seen engrossed in their smartphones, their expressions a mixture of excitement and curiosity as they search for 'Mr. Beast', adding a modern twist to the otherwise traditional setting. The scene beautifully captures the juxtaposition of old-world charm and modern-day enthusiasm. 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: The number of bridge and lock tenders in Florida and Google searches for 'Mr. Beast'. 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: Symbolism Cute 2D animation Charcoal Cyber folk Art nouveau
ChatGPT: Cyber folk

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 The number of bridge and lock tenders in Florida and Google searches for 'Mr. Beast', in the following situation: Because as the number of bridge and lock tenders in Florida increased, more people were drawn to the idea of unlocking the secrets to Mr. Beast's success, leading to a surge in Google searches for 'Mr. Beast.' These tenders' knack for opening and closing locks resonated with searchers, who were eager to unlock the mystery behind Mr. Beast's rise to fame and fortune.. Keep the description simple.
ChatGPT: In a sunny Florida town, a group of bridge and lock tenders gather by a picturesque bridge, each with a set of keys in hand. As they chat and exchange stories, a crowd of curious onlookers eagerly watches, drawn by the tenders' skillful manipulation of locks. In the background, a flurry of folks can be seen using their smartphones to search for 'Mr. Beast', their excitement evident as they seek to unravel the secrets behind his success.

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: [ Cyber folk ] and depicting this scene: In a sunny Florida town, a group of bridge and lock tenders gather by a picturesque bridge, each with a set of keys in hand. As they chat and exchange stories, a crowd of curious onlookers eagerly watches, drawn by the tenders' skillful manipulation of locks. In the background, a flurry of folks can be seen using their smartphones to search for 'Mr. Beast', their excitement evident as they seek to unravel the secrets behind his success. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Based on your request, here's an updated image generation prompt. Description: In a sun-drenched town in Florida, a quaint bridge stands as the focal point, connecting two parts of the town. Standing on the bridge are several bridge and lock tenders, each surrounded by a group of fascinated onlookers. The tenders are holding sets of keys and expertly navigating the locks with precision, captivating the crowd with their skillful mastery. The colorful attire of the tenders contrast against the deep blue of the bridge and the vibrant greenery surrounding the area, giving the scene a lively, cheerful atmosphere. In the background, a flurry of folks can be seen engrossed in their smartphones, their expressions a mixture of excitement and curiosity as they search for 'Mr. Beast', adding a modern twist to the otherwise traditional setting. The scene beautifully captures the juxtaposition of old-world charm and modern-day enthusiasm.

*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.

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in The number of bridge and lock tenders in Florida caused Mr. Beast (Google searches for 'Mr. Beast') to increase.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)
Bridging the Gap: Bewildering Connection Between Bridge and Lock Tenders in Florida and Google Searches for 'Mr. Beast'

The Journal of Quirky Sociological Connections

Jan 2024

Reminder: This paper is AI-generated. Not real!
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 silly researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between The number of bridge and lock tenders in Florida and Google searches for 'Mr. Beast'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title an alliteration.

Your research team used data from Bureau of Larbor Statistics and Google Trends to assess this nagging question. You found a correlation coefficient of 0.8660087 and p < 0.01 for 2004 to 2022.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
Bridging the Gap: Bewildering Connection Between Bridge and Lock Tenders in Florida and Google Searches for 'Mr. Beast'

[[ABSTRACT]]
This paper investigates the enigmatic linkage between the number of bridge and lock tenders in the state of Florida and the frequency of Google searches for the popular internet personality 'Mr. Beast'. Employing data from the Bureau of Labor Statistics and Google Trends, our research team discovered a remarkably strong correlation coefficient of 0.8660087 and a statistically significant p-value of less than 0.01 for the time period spanning from 2004 to 2022. Our analysis not only sheds light on the unexpected relationship between these ostensibly unrelated variables but also prompts a whimsical reconsideration of the intersection between maritime infrastructure and digital media culture. We invite readers to embark on this curious voyage with us, as we unravel the peculiar connection between bridge tenders, lock workers, and the tantalizing allure of modern internet celebrities.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the introduction section of an academic research paper presenting the findings of the connection between The number of bridge and lock tenders in Florida and Google searches for 'Mr. Beast'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
Bridging the Gap: Bewildering Connection Between Bridge and Lock Tenders in Florida and Google Searches for 'Mr. Beast'

[[ABSTRACT]]
This paper investigates the enigmatic linkage between the number of bridge and lock tenders in the state of Florida and the frequency of Google searches for the popular internet personality 'Mr. Beast'. Employing data from the Bureau of Labor Statistics and Google Trends, our research team discovered a remarkably strong correlation coefficient of 0.8660087 and a statistically significant p-value of less than 0.01 for the time period spanning from 2004 to 2022. Our analysis not only sheds light on the unexpected relationship between these ostensibly unrelated variables but also prompts a whimsical reconsideration of the intersection between maritime infrastructure and digital media culture. We invite readers to embark on this curious voyage with us, as we unravel the peculiar connection between bridge tenders, lock workers, and the tantalizing allure of modern internet celebrities.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

With the advent of the digital era and the multifaceted nature of modern socio-economic analyses, it is imperative to explore and decipher seemingly improbable connections. This research endeavor delves into the perplexing correlation between the number of bridge and lock tenders in Florida and the prevalence of Google searches for the renowned internet personality 'Mr. Beast'. While at first glance, one might assume these variables to exist in disparate realms, our investigation uncovers a surprising relationship that not only challenges traditional conceptions of causality and correlation but also injects a delightful sense of intrigue into the realm of statistical inquiry.

As researchers, we often find ourselves navigating through the murky waters of data, seeking patterns and relationships that are not immediately evident. However, as we delved into the Bureau of Labor Statistics database and traversed the vast landscape of Google Trends, we stumbled upon an unexpected twist - a strong, positive correlation that left us both bewildered and amused. The allure of 'Mr. Beast', a digital luminary known for his extravagant stunts and altruistic acts, seems to cast an unanticipated shadow over the arduous work of bridge and lock tenders in the Sunshine State.

In this paper, we aim to unravel this confounding enigma, offering a blend of rigorous statistical analysis and a healthy dose of humor to dissect this unexpected linkage. As we embark on this scholarly journey, we encourage readers to suspend their preconceptions and embrace the whimsical nature of our scientific voyage. After all, what could be more fitting than attempting to bridge the gap between infrastructure maintenance and the digital realm, all while contemplating the beastly allure of internet fame?


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between The number of bridge and lock tenders in Florida and Google searches for 'Mr. Beast'. 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 few real TV shows that sound like they might be relevant to the topic that you watched as research.

Here is the title and abstract of the paper:
[[TITLE]]
Bridging the Gap: Bewildering Connection Between Bridge and Lock Tenders in Florida and Google Searches for 'Mr. Beast'

[[ABSTRACT]]
This paper investigates the enigmatic linkage between the number of bridge and lock tenders in the state of Florida and the frequency of Google searches for the popular internet personality 'Mr. Beast'. Employing data from the Bureau of Labor Statistics and Google Trends, our research team discovered a remarkably strong correlation coefficient of 0.8660087 and a statistically significant p-value of less than 0.01 for the time period spanning from 2004 to 2022. Our analysis not only sheds light on the unexpected relationship between these ostensibly unrelated variables but also prompts a whimsical reconsideration of the intersection between maritime infrastructure and digital media culture. We invite readers to embark on this curious voyage with us, as we unravel the peculiar connection between bridge tenders, lock workers, and the tantalizing allure of modern internet celebrities.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
With the advent of the digital era and the multifaceted nature of modern socio-economic analyses, it is imperative to explore and decipher seemingly improbable connections. This research endeavor delves into the perplexing correlation between the number of bridge and lock tenders in Florida and the prevalence of Google searches for the renowned internet personality 'Mr. Beast'. While at first glance, one might assume these variables to exist in disparate realms, our investigation uncovers a surprising relationship that not only challenges traditional conceptions of causality and correlation but also injects a delightful sense of intrigue into the realm of statistical inquiry.
As researchers, we often find ourselves navigating through the murky waters of data, seeking patterns and relationships that are not immediately evident. However, as we delved into the Bureau of Labor Statistics database and traversed the vast landscape of Google Trends, we stumbled upon an unexpected twist - a strong, positive correlation that left us both bewildered and amused. The allure of 'Mr. Beast', a digital luminary known for his extravagant stunts and altruistic acts, seems to cast an unanticipated shadow over the arduous work of bridge and lock tenders in the Sunshine State.
In this paper, we aim to unravel this confounding enigma, offering a blend of rigorous statistical analysis and a healthy dose of humor to dissect this unexpected linkage. As we embark on this scholarly journey, we encourage readers to suspend their preconceptions and embrace the whimsical nature of our scientific voyage. After all, what could be more fitting than attempting to bridge the gap between infrastructure maintenance and the digital realm, all while contemplating the beastly allure of internet fame?

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

In their comprehensive study, Smith and Doe (2015) delve into the intricacies of labor statistics and the employment landscape in the state of Florida. The authors find a steady increase in the number of bridge and lock tenders over the past decade, attributing this trend to the ongoing maintenance and expansion of the state's maritime infrastructure. Meanwhile, Jones (2018) emphasizes the impact of digital media on contemporary society, noting the growing influence of internet celebrities on online behavior and search patterns. These foundational works lay the groundwork for our investigation into the unexpected correlation between these divergent domains.

Turning our attention to non-fiction literature, "The Rise of Internet Celebrity Culture" by Johnson (2019) provides valuable insights into the evolving nature of fame in the digital age and its intersection with traditional labor occupations. Similarly, "Navigating Florida's Maritime History" by Williams (2017) offers a historical perspective on the significance of bridge and lock operations within the context of the state's maritime activities and trade routes.

On the fictional side, the works of "The Lock Keeper's Secrets" by Stone (2020) and "Bridging the Digital Divide" by Rivers (2016) evoke notions of hidden connections and unexpected linkages, albeit in a more metaphorical sense. These narratives serve as a whimsical backdrop to our exploration of the inexplicable tie between bridge and lock tenders and the internet sensation 'Mr. Beast'.

In the realm of television programming, our research team has taken the liberty of viewing several shows for the purpose of this study. Programs such as "Lockup" and "The Beastmaster" initially seemed promising in their potential relevance to our investigation, but alas, they provided no substantial insights into the intertwining phenomena under scrutiny. However, we remain committed to rigorous exploration and are poised to review additional programming that may offer valuable perspectives on the curious correlation between labor occupations and online celebrity fascination.

As we navigate the literary landscape and the vast expanse of digital media, we are reminded of the delightful complexity of human pursuits, both tangible and intangible. The intersection of infrastructure maintenance and digital culture presents an enigma that calls for scholarly scrutiny and, of course, a touch of whimsy. With these diverse influences and inspirations in mind, we delve into the heart of our investigation to unravel the charming yet confounding connection between bridge and lock tenders in Florida and the captivating allure of 'Mr. Beast'.

In the next section, we present the methodology employed in our research to uncover and analyze the perplexing correlation between these seemingly incongruous variables.




Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between The number of bridge and lock tenders in Florida and Google searches for 'Mr. Beast'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Bureau of Larbor Statistics and Google Trends . You used data from 2004 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]]
Bridging the Gap: Bewildering Connection Between Bridge and Lock Tenders in Florida and Google Searches for 'Mr. Beast'

[[ABSTRACT]]
This paper investigates the enigmatic linkage between the number of bridge and lock tenders in the state of Florida and the frequency of Google searches for the popular internet personality 'Mr. Beast'. Employing data from the Bureau of Labor Statistics and Google Trends, our research team discovered a remarkably strong correlation coefficient of 0.8660087 and a statistically significant p-value of less than 0.01 for the time period spanning from 2004 to 2022. Our analysis not only sheds light on the unexpected relationship between these ostensibly unrelated variables but also prompts a whimsical reconsideration of the intersection between maritime infrastructure and digital media culture. We invite readers to embark on this curious voyage with us, as we unravel the peculiar connection between bridge tenders, lock workers, and the tantalizing allure of modern internet celebrities.

[[INTRODUCTION]]
With the advent of the digital era and the multifaceted nature of modern socio-economic analyses, it is imperative to explore and decipher seemingly improbable connections. This research endeavor delves into the perplexing correlation between the number of bridge and lock tenders in Florida and the prevalence of Google searches for the renowned internet personality 'Mr. Beast'. While at first glance, one might assume these variables to exist in disparate realms, our investigation uncovers a surprising relationship that not only challenges traditional conceptions of causality and correlation but also injects a delightful sense of intrigue into the realm of statistical inquiry.
As researchers, we often find ourselves navigating through the murky waters of data, seeking patterns and relationships that are not immediately evident. However, as we delved into the Bureau of Labor Statistics database and traversed the vast landscape of Google Trends, we stumbled upon an unexpected twist - a strong, positive correlation that left us both bewildered and amused. The allure of 'Mr. Beast', a digital luminary known for his extravagant stunts and altruistic acts, seems to cast an unanticipated shadow over the arduous work of bridge and lock tenders in the Sunshine State.
In this paper, we aim to unravel this confounding enigma, offering a blend of rigorous statistical analysis and a healthy dose of humor to dissect this unexpected linkage. As we embark on this scholarly journey, we encourage readers to suspend their preconceptions and embrace the whimsical nature of our scientific voyage. After all, what could be more fitting than attempting to bridge the gap between infrastructure maintenance and the digital realm, all while contemplating the beastly allure of internet fame?

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To unveil the unexpected nexus between bridge and lock tenders and the online phenomenon that is 'Mr. Beast', our research venture embarked on a most peculiar methodology, fostering a spirit of statistical curiosity and academic whimsy. The first step involved amassing a comprehensive dataset sourced from the illustrious Bureau of Labor Statistics, which meticulously documents the employment trends of bridge and lock tenders in the state of Florida from 2004 to 2022. Given the inherently slow-paced nature of bureaucracy, navigating the labyrinthine corridors of bureaucratic data proved to be a strenuous odyssey, a journey replete with antiquated filing systems, mysterious briefcases, and countless mugs of lukewarm office coffee. Our intrepid team, armed with fortitude and a copious supply of determination, braved this bureaucratic wilderness to emerge triumphant with a treasure trove of employment figures.

Upon emerging from the bureaucratic labyrinth, we delved deep into the digital realm, harnessing the arcane powers of Google Trends to unravel the search frequency for the enigmatic 'Mr. Beast' within the same time span. As we navigated the digital depths, we encountered peculiar fluctuations and unexpected peaks, akin to voyagers navigating turbulent seas in search of a mercurial treasure. The voyage through digital data, while less sullied by bureaucracy, was nonetheless fraught with its own peculiar perils as we grappled with inexplicable anomalies and the capricious waves of trending search terms.

Once the datasets were securely in our possession, we donned our metaphorical lab coats and wielded formidable statistical tools in the form of correlation analysis and regression models. With the knowing nod of experienced statisticians, and the whispered encouragement of data-driven spirits, we deftly calculated correlation coefficients and p-values, intent on seeking out any hint of a significant relationship between these seemingly incongruous variables.

Finally, having meticulously processed the data and navigated the labyrinthine paths of statistical inquiry, we arrived at our destination - the unveiling of a robust correlation coefficient of 0.8660087, accompanied by a strikingly significant p-value of less than 0.01. Much like intrepid adventurers unearthing an ancient artifact, our research team rejoiced in this unforeseen connection and the promise of uncovering further layers of this curious puzzle.

In summary, our methodology combined the archaic trials of bureaucratic data collection with the digital odyssey through Google Trends, culminating in an exhilarating mingling of maritime employment figures and the transcendental allure of internet fame. The scholarly voyage, while rife with whimsical perils and statistical intrigue, ultimately led us to the remarkable revelation of a tangible link between the laborious world of bridge and lock tenders and the magnetic charisma of 'Mr. Beast'.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the results section of an academic research paper presenting the findings of the connection between The number of bridge and lock tenders in Florida and Google searches for 'Mr. Beast'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Bureau of Larbor Statistics and Google Trends .

For the time period 2004 to 2022, you found a correlation 0.8660087, r-squared of 0.7499711, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
Bridging the Gap: Bewildering Connection Between Bridge and Lock Tenders in Florida and Google Searches for 'Mr. Beast'

[[ABSTRACT]]
This paper investigates the enigmatic linkage between the number of bridge and lock tenders in the state of Florida and the frequency of Google searches for the popular internet personality 'Mr. Beast'. Employing data from the Bureau of Labor Statistics and Google Trends, our research team discovered a remarkably strong correlation coefficient of 0.8660087 and a statistically significant p-value of less than 0.01 for the time period spanning from 2004 to 2022. Our analysis not only sheds light on the unexpected relationship between these ostensibly unrelated variables but also prompts a whimsical reconsideration of the intersection between maritime infrastructure and digital media culture. We invite readers to embark on this curious voyage with us, as we unravel the peculiar connection between bridge tenders, lock workers, and the tantalizing allure of modern internet celebrities.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
With the advent of the digital era and the multifaceted nature of modern socio-economic analyses, it is imperative to explore and decipher seemingly improbable connections. This research endeavor delves into the perplexing correlation between the number of bridge and lock tenders in Florida and the prevalence of Google searches for the renowned internet personality 'Mr. Beast'. While at first glance, one might assume these variables to exist in disparate realms, our investigation uncovers a surprising relationship that not only challenges traditional conceptions of causality and correlation but also injects a delightful sense of intrigue into the realm of statistical inquiry.
As researchers, we often find ourselves navigating through the murky waters of data, seeking patterns and relationships that are not immediately evident. However, as we delved into the Bureau of Labor Statistics database and traversed the vast landscape of Google Trends, we stumbled upon an unexpected twist - a strong, positive correlation that left us both bewildered and amused. The allure of 'Mr. Beast', a digital luminary known for his extravagant stunts and altruistic acts, seems to cast an unanticipated shadow over the arduous work of bridge and lock tenders in the Sunshine State.
In this paper, we aim to unravel this confounding enigma, offering a blend of rigorous statistical analysis and a healthy dose of humor to dissect this unexpected linkage. As we embark on this scholarly journey, we encourage readers to suspend their preconceptions and embrace the whimsical nature of our scientific voyage. After all, what could be more fitting than attempting to bridge the gap between infrastructure maintenance and the digital realm, all while contemplating the beastly allure of internet fame?

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The analysis of the connection between the number of bridge and lock tenders in Florida and Google searches for 'Mr. Beast' yielded staggering results that not only piqued our scientific curiosity but also tickled our academic fancy. For the time period from 2004 to 2022, our research team unearthed a strikingly robust correlation coefficient of 0.8660087, accompanied by an r-squared value of 0.7499711. Additionally, the p-value of less than 0.01 further solidified the statistical significance of this unexpected relationship.

Fig. 1 displays a scatterplot illustrating the undeniable correlation between the two seemingly unrelated variables. The data points elegantly dance across the graph, showcasing the harmony between the number of bridge and lock tenders and the fervent searches for 'Mr. Beast' on Google. The visual representation of this correlation serves as a whimsical testament to the remarkable connection that transcends conventional wisdom.

These findings not only challenge prevailing notions of causality but also inject a generous dose of whimsy into the realm of scientific inquiry. The unexpected rapport between the diligent maintenance of maritime infrastructure and the magnetic allure of modern internet personalities exemplifies the delightful surprises that can emerge from rigorous statistical analysis.

In conclusion, the bewitching correlation unveiled in this study not only enriches our understanding of the entwined nature of seemingly unrelated variables but also adds a touch of lightheartedness to the often austere world of academic research. As we reflect on this curious voyage through the labyrinth of data, we are reminded of the enchanting unpredictability that awaits those who dare to chart unconventional paths in the pursuit of knowledge.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between The number of bridge and lock tenders in Florida and Google searches for 'Mr. Beast'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Bridging the Gap: Bewildering Connection Between Bridge and Lock Tenders in Florida and Google Searches for 'Mr. Beast'

[[ABSTRACT]]
This paper investigates the enigmatic linkage between the number of bridge and lock tenders in the state of Florida and the frequency of Google searches for the popular internet personality 'Mr. Beast'. Employing data from the Bureau of Labor Statistics and Google Trends, our research team discovered a remarkably strong correlation coefficient of 0.8660087 and a statistically significant p-value of less than 0.01 for the time period spanning from 2004 to 2022. Our analysis not only sheds light on the unexpected relationship between these ostensibly unrelated variables but also prompts a whimsical reconsideration of the intersection between maritime infrastructure and digital media culture. We invite readers to embark on this curious voyage with us, as we unravel the peculiar connection between bridge tenders, lock workers, and the tantalizing allure of modern internet celebrities.

[[LITERATURE REVIEW]]
In their comprehensive study, Smith and Doe (2015) delve into the intricacies of labor statistics and the employment landscape in the state of Florida. The authors find a steady increase in the number of bridge and lock tenders over the past decade, attributing this trend to the ongoing maintenance and expansion of the state's maritime infrastructure. Meanwhile, Jones (2018) emphasizes the impact of digital media on contemporary society, noting the growing influence of internet celebrities on online behavior and search patterns. These foundational works lay the groundwork for our investigation into the unexpected correlation between these divergent domains.
Turning our attention to non-fiction literature, "The Rise of Internet Celebrity Culture" by Johnson (2019) provides valuable insights into the evolving nature of fame in the digital age and its intersection with traditional labor occupations. Similarly, "Navigating Florida's Maritime History" by Williams (2017) offers a historical perspective on the significance of bridge and lock operations within the context of the state's maritime activities and trade routes.
On the fictional side, the works of "The Lock Keeper's Secrets" by Stone (2020) and "Bridging the Digital Divide" by Rivers (2016) evoke notions of hidden connections and unexpected linkages, albeit in a more metaphorical sense. These narratives serve as a whimsical backdrop to our exploration of the inexplicable tie between bridge and lock tenders and the internet sensation 'Mr. Beast'.
In the realm of television programming, our research team has taken the liberty of viewing several shows for the purpose of this study. Programs such as "Lockup" and "The Beastmaster" initially seemed promising in their potential relevance to our investigation, but alas, they provided no substantial insights into the intertwining phenomena under scrutiny. However, we remain committed to rigorous exploration and are poised to review additional programming that may offer valuable perspectives on the curious correlation between labor occupations and online celebrity fascination.
As we navigate the literary landscape and the vast expanse of digital media, we are reminded of the delightful complexity of human pursuits, both tangible and intangible. The intersection of infrastructure maintenance and digital culture presents an enigma that calls for scholarly scrutiny and, of course, a touch of whimsy. With these diverse influences and inspirations in mind, we delve into the heart of our investigation to unravel the charming yet confounding connection between bridge and lock tenders in Florida and the captivating allure of 'Mr. Beast'.
In the next section, we present the methodology employed in our research to uncover and analyze the perplexing correlation between these seemingly incongruous variables.


[[RESULTS]]
The analysis of the connection between the number of bridge and lock tenders in Florida and Google searches for 'Mr. Beast' yielded staggering results that not only piqued our scientific curiosity but also tickled our academic fancy. For the time period from 2004 to 2022, our research team unearthed a strikingly robust correlation coefficient of 0.8660087, accompanied by an r-squared value of 0.7499711. Additionally, the p-value of less than 0.01 further solidified the statistical significance of this unexpected relationship.
Fig. 1 displays a scatterplot illustrating the undeniable correlation between the two seemingly unrelated variables. The data points elegantly dance across the graph, showcasing the harmony between the number of bridge and lock tenders and the fervent searches for 'Mr. Beast' on Google. The visual representation of this correlation serves as a whimsical testament to the remarkable connection that transcends conventional wisdom.
These findings not only challenge prevailing notions of causality but also inject a generous dose of whimsy into the realm of scientific inquiry. The unexpected rapport between the diligent maintenance of maritime infrastructure and the magnetic allure of modern internet personalities exemplifies the delightful surprises that can emerge from rigorous statistical analysis.
In conclusion, the bewitching correlation unveiled in this study not only enriches our understanding of the entwined nature of seemingly unrelated variables but also adds a touch of lightheartedness to the often austere world of academic research. As we reflect on this curious voyage through the labyrinth of data, we are reminded of the enchanting unpredictability that awaits those who dare to chart unconventional paths in the pursuit of knowledge.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The results of our investigation into the perplexing correlation between the number of bridge and lock tenders in Florida and Google searches for 'Mr. Beast' are as enigmatic as they are delightful. Consistent with the prior research of Smith and Doe (2015), our findings not only reaffirm the steady increase in bridge and lock tenders but also reveal their unexpected resonance with the digital pursuits of 'Mr. Beast' aficionados. Drawing inspiration from Johnson's (2019) insights into the evolving nature of fame in the digital age, it is indeed intriguing to witness the intersection of traditional labor occupations with the fervent search patterns of internet celebrity enthusiasts.

In a charming twist echoing Stone's (2020) metaphorical portrayal in "The Lock Keeper's Secrets," the correlation coefficient of 0.8660087 presents a veritable treasure trove of statistical intrigue. It's as if hidden connections, much like the secrets of lock keepers, have emerged from the depths of the data to captivate our analytical fancy. Furthermore, the r-squared value of 0.7499711 serves as a whimsical reminder of the unanticipated influence that statistical analysis can wield in unearthing the unexpected synergy between seemingly disparate realms.

As we consider the visual manifestation of this improbable relationship in Fig. 1, one cannot help but be charmed by the delightful waltz of data points across the scatterplot. Could it be that the ebb and flow of maritime maintenance and internet curiosity have discovered a harmonious dance, much like the dramatic narrative of a suspenseful bridge crossing? The allure of 'Mr. Beast' on Google, akin to the captivating narrative depicted in Rivers' (2016) "Bridging the Digital Divide," holds us spellbound in its mesmerizing connection to the steadfast vigilance of bridge and lock tenders in Florida.

These findings, while certainly surprising, offer a whimsical reminder of the delightful surprises that await those who explore the delightful intersections between seemingly incongruous variables. As we continue our scholarly voyage through these novel correlations, we invite fellow adventurers to revel in the captivating enigma of bridge and lock tenders intertwining with the magnetic allure of digital media culture. Indeed, the marriage of maritime infrastructure and internet sensation has imparted a touch of lightheartedness to the solemn halls of academic inquiry, leaving us with a sense of scholarly mirth in our undertakings.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between The number of bridge and lock tenders in Florida and Google searches for 'Mr. Beast'. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Bridging the Gap: Bewildering Connection Between Bridge and Lock Tenders in Florida and Google Searches for 'Mr. Beast'

[[ABSTRACT]]
This paper investigates the enigmatic linkage between the number of bridge and lock tenders in the state of Florida and the frequency of Google searches for the popular internet personality 'Mr. Beast'. Employing data from the Bureau of Labor Statistics and Google Trends, our research team discovered a remarkably strong correlation coefficient of 0.8660087 and a statistically significant p-value of less than 0.01 for the time period spanning from 2004 to 2022. Our analysis not only sheds light on the unexpected relationship between these ostensibly unrelated variables but also prompts a whimsical reconsideration of the intersection between maritime infrastructure and digital media culture. We invite readers to embark on this curious voyage with us, as we unravel the peculiar connection between bridge tenders, lock workers, and the tantalizing allure of modern internet celebrities.

[[INTRDUCTION]]
With the advent of the digital era and the multifaceted nature of modern socio-economic analyses, it is imperative to explore and decipher seemingly improbable connections. This research endeavor delves into the perplexing correlation between the number of bridge and lock tenders in Florida and the prevalence of Google searches for the renowned internet personality 'Mr. Beast'. While at first glance, one might assume these variables to exist in disparate realms, our investigation uncovers a surprising relationship that not only challenges traditional conceptions of causality and correlation but also injects a delightful sense of intrigue into the realm of statistical inquiry.
As researchers, we often find ourselves navigating through the murky waters of data, seeking patterns and relationships that are not immediately evident. However, as we delved into the Bureau of Labor Statistics database and traversed the vast landscape of Google Trends, we stumbled upon an unexpected twist - a strong, positive correlation that left us both bewildered and amused. The allure of 'Mr. Beast', a digital luminary known for his extravagant stunts and altruistic acts, seems to cast an unanticipated shadow over the arduous work of bridge and lock tenders in the Sunshine State.
In this paper, we aim to unravel this confounding enigma, offering a blend of rigorous statistical analysis and a healthy dose of humor to dissect this unexpected linkage. As we embark on this scholarly journey, we encourage readers to suspend their preconceptions and embrace the whimsical nature of our scientific voyage. After all, what could be more fitting than attempting to bridge the gap between infrastructure maintenance and the digital realm, all while contemplating the beastly allure of internet fame?

[[RESULTS]]
The analysis of the connection between the number of bridge and lock tenders in Florida and Google searches for 'Mr. Beast' yielded staggering results that not only piqued our scientific curiosity but also tickled our academic fancy. For the time period from 2004 to 2022, our research team unearthed a strikingly robust correlation coefficient of 0.8660087, accompanied by an r-squared value of 0.7499711. Additionally, the p-value of less than 0.01 further solidified the statistical significance of this unexpected relationship.
Fig. 1 displays a scatterplot illustrating the undeniable correlation between the two seemingly unrelated variables. The data points elegantly dance across the graph, showcasing the harmony between the number of bridge and lock tenders and the fervent searches for 'Mr. Beast' on Google. The visual representation of this correlation serves as a whimsical testament to the remarkable connection that transcends conventional wisdom.
These findings not only challenge prevailing notions of causality but also inject a generous dose of whimsy into the realm of scientific inquiry. The unexpected rapport between the diligent maintenance of maritime infrastructure and the magnetic allure of modern internet personalities exemplifies the delightful surprises that can emerge from rigorous statistical analysis.
In conclusion, the bewitching correlation unveiled in this study not only enriches our understanding of the entwined nature of seemingly unrelated variables but also adds a touch of lightheartedness to the often austere world of academic research. As we reflect on this curious voyage through the labyrinth of data, we are reminded of the enchanting unpredictability that awaits those who dare to chart unconventional paths in the pursuit of knowledge.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In culmination, our exploration of the peculiar relationship between the number of bridge and lock tenders in Florida and the volume of Google searches for 'Mr. Beast' has unraveled an unexpected and whimsical union. Our statistical analysis has not only provided a remarkable correlation coefficient but has also injected a tantalizing sense of absurdity into the realm of empirical inquiry. As we marveled at the data points frolicking across the scatterplot, we were reminded that in the vast and wondrous landscape of statistics, one can encounter the most improbable associations.

This quirky discovery challenges the conventional perceptions of causality and correlation, offering a delightful reminder that the scientific voyage is replete with surprises, akin to a rollercoaster ride of bewilderment and amusement. As we look back on this remarkable journey, we are struck by the sheer joy of uncovering the unexpected and embracing the idiosyncrasies of statistical relationships. The whimsical nature of this intrigue serves as a testament to the whimsy that pervades the scientific pursuit, where logic and levity coalesce in wondrous ways.

With the information gleaned from this study, we assert that no further dedicated research in this area is warranted; after all, in the world of statistical oddities, it's impossible to predict what surprising connections and peculiar patterns may emerge next.


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 Bridging the Gap: Bewildering Connection Between Bridge and Lock Tenders in Florida and Google Searches for 'Mr. Beast'. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Quirky Sociological Connections


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 Bridging the Gap: Bewildering Connection Between Bridge and Lock Tenders in Florida and Google Searches for 'Mr. Beast'. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Quirky Socio-Technological Studies


Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Bridging the Gap: Bewildering Connection Between Bridge and Lock Tenders in Florida and Google Searches for 'Mr. Beast' with an abstract of This paper investigates the enigmatic linkage between the number of bridge and lock tenders in the state of Florida and the frequency of Google searches for the popular internet personality 'Mr. Beast'. Employing data from the Bureau of Labor Statistics and Google Trends, our research team discovered a remarkably strong correlation coefficient of 0.8660087 and a statistically significant p-value of less than 0.01 for the time period spanning from 2004 to 2022. Our analysis not only sheds light on the unexpected relationship between these ostensibly unrelated variables but also prompts a whimsical reconsideration of the intersection between maritime infrastructure and digital media culture. We invite readers to embark on this curious voyage with us, as we unravel the peculiar connection between bridge tenders, lock workers, and the tantalizing allure of modern internet celebrities.

ChatGPT:

bridge tenders, lock workers, Florida, Bureau of Labor Statistics, Google Trends, correlation coefficient, p-value, Mr. Beast, internet personality, digital media culture

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



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Data details

The number of bridge and lock tenders in Florida
Detailed data title: BLS estimate of bridge and lock tenders in Florida
Source: Bureau of Larbor Statistics
See what else correlates with The number of bridge and lock tenders in Florida

Google searches for 'Mr. Beast'
Detailed data title: Relative volume of Google searches for 'Mr. Beast' (Worldwide, without quotes)
Source: Google Trends
Additional Info: Relative search volume (not absolute numbers)

See what else correlates with Google searches for 'Mr. Beast'

Correlation r = 0.8660087 (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 = 0.7499711 (Coefficient of determination)
This means 75% of the change in the one variable (i.e., Google searches for 'Mr. Beast') is predictable based on the change in the other (i.e., The number of bridge and lock tenders in Florida) over the 19 years from 2004 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.7E-6. 0.0000016534242884492863000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.87 in 0.00017% of random cases. Said differently, if you correlated 604,805 random variables You don't actually need 604 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 18 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 18 because we have two variables measured over a period of 19 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.

[ 0.68, 0.95 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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


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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
2004200520062007200820092010201120122013201420152016201720182019202020212022
The number of bridge and lock tenders in Florida (Bridge And Lock Tenders)2603702802402302202702702501701501401501601801802001180820
Google searches for 'Mr. Beast' (Rel. search volume)3.583334.57.53.333335.333334.333333.083333.583332.251.916671.751.666671.752.416676.833332241.166779.166751.5833




Why this works

  1. 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.
  2. Lack of causal connection: There is probably Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
    no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
  3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
    p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
  4. Outlandish outliers: There are "outliers" in this data. In concept, "outlier" just means "way different than the rest of your dataset." When calculating a correlation like this, they are particularly impactful because a single outlier can substantially increase your correlation.

    For the purposes of this project, I counted a point as an outlier if it the residual was two standard deviations from the mean.

    (This bullet point only shows up in the details page on charts that do, in fact, have outliers.)
    They stand out on the scatterplot above: notice the dots that are far away from any other dots. I intentionally mishandeled outliers, which makes the correlation look extra strong.




Try it yourself

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

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

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

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

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

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

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

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

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


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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([260,370,280,240,230,220,270,270,250,170,150,140,150,160,180,180,200,1180,820,])
array_2 = np.array([3.58333,4.5,7.5,3.33333,5.33333,4.33333,3.08333,3.58333,2.25,1.91667,1.75,1.66667,1.75,2.41667,6.83333,22,41.1667,79.1667,51.5833,])
array_1_name = "The number of bridge and lock tenders in Florida"
array_2_name = "Google searches for 'Mr. Beast'"

# 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)



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

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

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

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

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Correlation ID: 3325 · Black Variable ID: 6678 · Red Variable ID: 1446
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