about · email me · subscribe
Spurious correlation #4,552 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Average views of Extra History YouTube videos and the second variable is The number of bellhops in Indiana.  The chart goes from 2012 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

More people watching Extra History means more interest in historical topics. This interest leads to an influx of visitors to Indiana, prompting the need for additional bellhops to cater to the growing tourism industry. Looks like Indiana is experiencing a 'bellhop' boom thanks to Extra History!

Model: dalle-3
Prompt: Generate an image that resembles a scene from 'Star Wars,' set in a bustling hotel lobby in Indiana. The scene features a group of bellhops enthusiastically welcoming a wave of tourists with their luggage. In the background, a large digital screen displays the soaring average views of Extra History YouTube videos, hinting at the surge in historical interest that is attracting visitors to Indiana. The tone should evoke both the exciting energy of a bustling hotel lobby and the futuristic world of 'Star Wars.' 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: Average views of Extra History YouTube videos and The number of bellhops in Indiana. 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: A scene from Skyrim Voxel art Celtic art An image that looks like it is a scene from 'Star Wars' Magic realism
ChatGPT: An image that looks like it is a scene from 'Star Wars'

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Average views of Extra History YouTube videos and The number of bellhops in Indiana, in the following situation: More people watching Extra History means more interest in historical topics. This interest leads to an influx of visitors to Indiana, prompting the need for additional bellhops to cater to the growing tourism industry. Looks like Indiana is experiencing a 'bellhop' boom thanks to Extra History!. Keep the description simple.
ChatGPT: In a bustling hotel lobby in Indiana, a group of bellhops enthusiastically greet a wave of tourists with their luggage. In the background, a large digital screen displays the soaring average views of Extra History YouTube videos, hinting at the surge in historical interest that is driving the influx of visitors to Indiana.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ An image that looks like it is a scene from 'Star Wars' ] and depicting this scene: In a bustling hotel lobby in Indiana, a group of bellhops enthusiastically greet a wave of tourists with their luggage. In the background, a large digital screen displays the soaring average views of Extra History YouTube videos, hinting at the surge in historical interest that is driving the influx of visitors to Indiana. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that resembles a scene from 'Star Wars,' set in a bustling hotel lobby in Indiana. The scene features a group of bellhops enthusiastically welcoming a wave of tourists with their luggage. In the background, a large digital screen displays the soaring average views of Extra History YouTube videos, hinting at the surge in historical interest that is attracting visitors to Indiana. The tone should evoke both the exciting energy of a bustling hotel lobby and the futuristic world of 'Star Wars.'

*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 increases in Average views of Extra History YouTube videos positively influenced The number of bellhops in Indiana. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)
Ringing in the Views: A Bellhop's Bellwether for Average Extra History YouTube Video Popularity in Indiana

The Journal of Quirky Quantitative Research

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 Average views of Extra History YouTube videos and The number of bellhops in Indiana. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title seem clever.

Your research team used data from YouTube and Bureau of Larbor Statistics to assess this nagging question. You found a correlation coefficient of 0.9433053 and p < 0.01 for 2012 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]]
"Ringing in the Views: A Bellhop's Bellwether for Average Extra History YouTube Video Popularity in Indiana"

[[ABSTRACT]]
This paper delves into the seemingly unrelated realms of online historical education and hospitality services, exploring the correlation between the average views of Extra History YouTube videos and the number of bellhops in the state of Indiana. Utilizing data from YouTube and the Bureau of Labor Statistics, our research team analyzed the viewing trends and employment figures from 2012 to 2022. Our findings revealed a striking correlation coefficient of 0.9433053 and a statistically significant p-value of less than 0.01, indicating a robust relationship between the two variables. This unexpected association raises intriguing questions about the cultural zeitgeist and its influence on consumer behavior and labor demand. Furthermore, it prompts contemplation on the potential motivational factors behind the viewership habits of historical enthusiasts. Our study adds a quirky twist to the intersection of digital media and the labor market, illustrating that even in the most unexpected pairings, there may be correlations that ring true.


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 Average views of Extra History YouTube videos and The number of bellhops in Indiana. 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]]
"Ringing in the Views: A Bellhop's Bellwether for Average Extra History YouTube Video Popularity in Indiana"

[[ABSTRACT]]
This paper delves into the seemingly unrelated realms of online historical education and hospitality services, exploring the correlation between the average views of Extra History YouTube videos and the number of bellhops in the state of Indiana. Utilizing data from YouTube and the Bureau of Labor Statistics, our research team analyzed the viewing trends and employment figures from 2012 to 2022. Our findings revealed a striking correlation coefficient of 0.9433053 and a statistically significant p-value of less than 0.01, indicating a robust relationship between the two variables. This unexpected association raises intriguing questions about the cultural zeitgeist and its influence on consumer behavior and labor demand. Furthermore, it prompts contemplation on the potential motivational factors behind the viewership habits of historical enthusiasts. Our study adds a quirky twist to the intersection of digital media and the labor market, illustrating that even in the most unexpected pairings, there may be correlations that ring true.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

In the world of academic research, correlations often lead us on an unexpected journey, much like a historian stumbling upon a hidden cache of archival documents or a bellhop discovering an overlooked suitcase in the lobby. Such serendipitous findings can leave us pondering the idiosyncrasies of human behavior and the enigmatic dance of statistical variables. In this spirit of delightful discovery, our research team embarked on a peculiar quest to unravel the mystical connection between the average views of Extra History YouTube videos and the number of bellhops in the land of cornfields and Hoosier hospitality – Indiana.

As researchers often do, we found ourselves in uncharted territory, seemingly lost in a maze of digital algorithms and labor market data, questioning whether we were threading the needle of enlightenment or merely chasing shadows in the statistical twilight. The task at hand was to decipher whether the popularity of online historical content and the bustling activity of bellhops in Indiana were distant bedfellows or secret admirers intertwined in an enigmatic tango of significance.

Our foray into this uncharted terrain was not without its moments of levity and amusement, much like a historian stumbling upon an amusing anecdote buried in the annals of antiquity. The quest to uncover the pearls of wisdom hidden beneath the digital waves and labor desks led to many a raised eyebrow and chuckle amongst our cohort of researchers, as we traversed the realm of data anomalies and unexpected statistical bedfellows.

The findings that emerged from our analysis raised more than a few eyebrows and sparked lively conversations at our research roundtable, evoking theories as diverse as the interpretations of historical texts. With a correlation coefficient of 0.9433053 and a p-value that danced its way to statistical significance, our study reveals a relationship between the online historical enthusiasts and the bellhops of Indiana that is as intriguing as a cryptic message etched in the marble corridors of ancient palaces.

In this paper, we invite you to join us in exploring this captivating correlation, a conundrum wrapped in a mystery, waiting to be unraveled. Our journey through the labyrinth of numbers and digital footprints unveils a tale that, much like history itself, is full of unexpected twists and turns. So, prepare to embark on a scholarly adventure that merges the realms of digital storytelling and guest services, and brace yourself for a few surprises along the way.


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 Average views of Extra History YouTube videos and The number of bellhops in Indiana. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading the backs of shampoo bottles.

Here is the title and abstract of the paper:
[[TITLE]]
"Ringing in the Views: A Bellhop's Bellwether for Average Extra History YouTube Video Popularity in Indiana"

[[ABSTRACT]]
This paper delves into the seemingly unrelated realms of online historical education and hospitality services, exploring the correlation between the average views of Extra History YouTube videos and the number of bellhops in the state of Indiana. Utilizing data from YouTube and the Bureau of Labor Statistics, our research team analyzed the viewing trends and employment figures from 2012 to 2022. Our findings revealed a striking correlation coefficient of 0.9433053 and a statistically significant p-value of less than 0.01, indicating a robust relationship between the two variables. This unexpected association raises intriguing questions about the cultural zeitgeist and its influence on consumer behavior and labor demand. Furthermore, it prompts contemplation on the potential motivational factors behind the viewership habits of historical enthusiasts. Our study adds a quirky twist to the intersection of digital media and the labor market, illustrating that even in the most unexpected pairings, there may be correlations that ring true.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the world of academic research, correlations often lead us on an unexpected journey, much like a historian stumbling upon a hidden cache of archival documents or a bellhop discovering an overlooked suitcase in the lobby. Such serendipitous findings can leave us pondering the idiosyncrasies of human behavior and the enigmatic dance of statistical variables. In this spirit of delightful discovery, our research team embarked on a peculiar quest to unravel the mystical connection between the average views of Extra History YouTube videos and the number of bellhops in the land of cornfields and Hoosier hospitality – Indiana.
As researchers often do, we found ourselves in uncharted territory, seemingly lost in a maze of digital algorithms and labor market data, questioning whether we were threading the needle of enlightenment or merely chasing shadows in the statistical twilight. The task at hand was to decipher whether the popularity of online historical content and the bustling activity of bellhops in Indiana were distant bedfellows or secret admirers intertwined in an enigmatic tango of significance.
Our foray into this uncharted terrain was not without its moments of levity and amusement, much like a historian stumbling upon an amusing anecdote buried in the annals of antiquity. The quest to uncover the pearls of wisdom hidden beneath the digital waves and labor desks led to many a raised eyebrow and chuckle amongst our cohort of researchers, as we traversed the realm of data anomalies and unexpected statistical bedfellows.
The findings that emerged from our analysis raised more than a few eyebrows and sparked lively conversations at our research roundtable, evoking theories as diverse as the interpretations of historical texts. With a correlation coefficient of 0.9433053 and a p-value that danced its way to statistical significance, our study reveals a relationship between the online historical enthusiasts and the bellhops of Indiana that is as intriguing as a cryptic message etched in the marble corridors of ancient palaces.
In this paper, we invite you to join us in exploring this captivating correlation, a conundrum wrapped in a mystery, waiting to be unraveled. Our journey through the labyrinth of numbers and digital footprints unveils a tale that, much like history itself, is full of unexpected twists and turns. So, prepare to embark on a scholarly adventure that merges the realms of digital storytelling and guest services, and brace yourself for a few surprises along the way.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The relationship between online content consumption and labor market dynamics has been a subject of scholarly inquiry in recent years. Smith et al. (2018) examined the impact of digital media viewership on employment patterns, highlighting the potential influence of online trends on labor demand. Similarly, Doe and Jones (2020) explored the intersection of cultural interests and occupational trends, shedding light on the intricate connections between popular culture and workforce dynamics.

Moving beyond the realm of traditional academic studies, non-fiction works such as "Data Analysis for Dummies" and "YouTube Marketing Secrets Unveiled" have offered insights into the analytics of digital platforms and the influencing factors behind viewer engagement. On the fictional front, novels like "The Bellhop's Diaries" and "The Chronicles of YouTube: Tales of Digital Discovery" present imaginative narratives that, albeit fictional, offer glimpses into the peculiar intersections of historical fascination and the service industry.

Venturing into unconventional sources, the researchers also draw inspiration from the unlikeliest of places, including the back covers of shampoo bottles found in hotel bathrooms. While seemingly unrelated to the core themes of this investigation, these sources served as a whimsical reminder of the unexpected connections that can arise in the most peculiar of circumstances.

As the exploration into the relationship between average views of Extra History YouTube videos and the number of bellhops in Indiana unfolds, it is evident that the academic pursuit has taken on a lighthearted and unexpected demeanor. The journey to unravel this peculiar correlation has transcended traditional scholarly pursuits and embraced the whimsical nature of uncovering hidden associations in the digital and labor landscapes.


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 Average views of Extra History YouTube videos and The number of bellhops in Indiana. 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 YouTube and Bureau of Larbor Statistics . You used data from 2012 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]]
"Ringing in the Views: A Bellhop's Bellwether for Average Extra History YouTube Video Popularity in Indiana"

[[ABSTRACT]]
This paper delves into the seemingly unrelated realms of online historical education and hospitality services, exploring the correlation between the average views of Extra History YouTube videos and the number of bellhops in the state of Indiana. Utilizing data from YouTube and the Bureau of Labor Statistics, our research team analyzed the viewing trends and employment figures from 2012 to 2022. Our findings revealed a striking correlation coefficient of 0.9433053 and a statistically significant p-value of less than 0.01, indicating a robust relationship between the two variables. This unexpected association raises intriguing questions about the cultural zeitgeist and its influence on consumer behavior and labor demand. Furthermore, it prompts contemplation on the potential motivational factors behind the viewership habits of historical enthusiasts. Our study adds a quirky twist to the intersection of digital media and the labor market, illustrating that even in the most unexpected pairings, there may be correlations that ring true.

[[INTRODUCTION]]
In the world of academic research, correlations often lead us on an unexpected journey, much like a historian stumbling upon a hidden cache of archival documents or a bellhop discovering an overlooked suitcase in the lobby. Such serendipitous findings can leave us pondering the idiosyncrasies of human behavior and the enigmatic dance of statistical variables. In this spirit of delightful discovery, our research team embarked on a peculiar quest to unravel the mystical connection between the average views of Extra History YouTube videos and the number of bellhops in the land of cornfields and Hoosier hospitality – Indiana.
As researchers often do, we found ourselves in uncharted territory, seemingly lost in a maze of digital algorithms and labor market data, questioning whether we were threading the needle of enlightenment or merely chasing shadows in the statistical twilight. The task at hand was to decipher whether the popularity of online historical content and the bustling activity of bellhops in Indiana were distant bedfellows or secret admirers intertwined in an enigmatic tango of significance.
Our foray into this uncharted terrain was not without its moments of levity and amusement, much like a historian stumbling upon an amusing anecdote buried in the annals of antiquity. The quest to uncover the pearls of wisdom hidden beneath the digital waves and labor desks led to many a raised eyebrow and chuckle amongst our cohort of researchers, as we traversed the realm of data anomalies and unexpected statistical bedfellows.
The findings that emerged from our analysis raised more than a few eyebrows and sparked lively conversations at our research roundtable, evoking theories as diverse as the interpretations of historical texts. With a correlation coefficient of 0.9433053 and a p-value that danced its way to statistical significance, our study reveals a relationship between the online historical enthusiasts and the bellhops of Indiana that is as intriguing as a cryptic message etched in the marble corridors of ancient palaces.
In this paper, we invite you to join us in exploring this captivating correlation, a conundrum wrapped in a mystery, waiting to be unraveled. Our journey through the labyrinth of numbers and digital footprints unveils a tale that, much like history itself, is full of unexpected twists and turns. So, prepare to embark on a scholarly adventure that merges the realms of digital storytelling and guest services, and brace yourself for a few surprises along the way.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To commence our peculiar journey into the world of statistical inquiry and offbeat correlations, our research team first undertook the daunting task of assembling and mining a treasure trove of data from the digital archives and labor landscapes. We scoured the expansive expanse of YouTube's historical edutainment hub, homing in on the esteemed productions of the "Extra History" series. Video views were meticulously tabulated and derived from a decade-long span, encompassing the years 2012 through 2022. Like nimble-fingered historians deciphering ancient manuscripts, we meticulously documented the ebb and flow of online viewership, navigating through the annals of internet lore with unwavering determination and the occasional snack break.

Simultaneously, our intrepid researchers delved into the Bureau of Labor Statistics, wielding our statistical compass to navigate through the labyrinthine corridors of employment data. Zeroing in on the domain of hospitality and guest services, particularly the valiant guardians of luggage and purveyors of concierge wisdom—the bellhops—we meticulously extracted employment figures from the heartland of America: Indiana. This endeavor involved analyzing employment data for bellhops, baggage porters, and concierges, recognizing the unsung heroes of the hotel lobby with a tip of our metaphorical research hats.

With data in hand, we ventured into the statistical wilderness, brandishing the sword of software and the shield of significance testing. Employing sophisticated statistical software, we summoned the power of correlation analysis to discern the hidden ties binding these seemingly disparate variables. Like alchemists of digital data, we combined the elixirs of views and bellhops, subjecting them to the mystical art of Pearson's correlation coefficient to unveil the mystical union of these enigmatic statistical bedfellows.

The results were nothing short of revelatory, unveiling a correlation coefficient of 0.9433053—akin to a historical artifact emitting a faint but discernible signal through the ages. Statistical significance shimmered like a long-lost treasure, with a p-value of less than 0.01, signifying a relationship that echoed through the annals of significance testing.

In summary, our methodology wove a tapestry of digital analytics and labor market exploration, united by the common thread of curiosity and a thirst for unconventional insights. With a dash of humor and scholarly intrigue, we embarked on this unorthodox escapade into the labyrinth of data, and our findings left us not only with correlations but with a newfound appreciation for the unexpected quirks of statistical inquiry.


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 Average views of Extra History YouTube videos and The number of bellhops in Indiana. 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 YouTube and Bureau of Larbor Statistics .

For the time period 2012 to 2022, you found a correlation 0.9433053, r-squared of 0.8898249, 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]]
"Ringing in the Views: A Bellhop's Bellwether for Average Extra History YouTube Video Popularity in Indiana"

[[ABSTRACT]]
This paper delves into the seemingly unrelated realms of online historical education and hospitality services, exploring the correlation between the average views of Extra History YouTube videos and the number of bellhops in the state of Indiana. Utilizing data from YouTube and the Bureau of Labor Statistics, our research team analyzed the viewing trends and employment figures from 2012 to 2022. Our findings revealed a striking correlation coefficient of 0.9433053 and a statistically significant p-value of less than 0.01, indicating a robust relationship between the two variables. This unexpected association raises intriguing questions about the cultural zeitgeist and its influence on consumer behavior and labor demand. Furthermore, it prompts contemplation on the potential motivational factors behind the viewership habits of historical enthusiasts. Our study adds a quirky twist to the intersection of digital media and the labor market, illustrating that even in the most unexpected pairings, there may be correlations that ring true.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
In the world of academic research, correlations often lead us on an unexpected journey, much like a historian stumbling upon a hidden cache of archival documents or a bellhop discovering an overlooked suitcase in the lobby. Such serendipitous findings can leave us pondering the idiosyncrasies of human behavior and the enigmatic dance of statistical variables. In this spirit of delightful discovery, our research team embarked on a peculiar quest to unravel the mystical connection between the average views of Extra History YouTube videos and the number of bellhops in the land of cornfields and Hoosier hospitality – Indiana.
As researchers often do, we found ourselves in uncharted territory, seemingly lost in a maze of digital algorithms and labor market data, questioning whether we were threading the needle of enlightenment or merely chasing shadows in the statistical twilight. The task at hand was to decipher whether the popularity of online historical content and the bustling activity of bellhops in Indiana were distant bedfellows or secret admirers intertwined in an enigmatic tango of significance.
Our foray into this uncharted terrain was not without its moments of levity and amusement, much like a historian stumbling upon an amusing anecdote buried in the annals of antiquity. The quest to uncover the pearls of wisdom hidden beneath the digital waves and labor desks led to many a raised eyebrow and chuckle amongst our cohort of researchers, as we traversed the realm of data anomalies and unexpected statistical bedfellows.
The findings that emerged from our analysis raised more than a few eyebrows and sparked lively conversations at our research roundtable, evoking theories as diverse as the interpretations of historical texts. With a correlation coefficient of 0.9433053 and a p-value that danced its way to statistical significance, our study reveals a relationship between the online historical enthusiasts and the bellhops of Indiana that is as intriguing as a cryptic message etched in the marble corridors of ancient palaces.
In this paper, we invite you to join us in exploring this captivating correlation, a conundrum wrapped in a mystery, waiting to be unraveled. Our journey through the labyrinth of numbers and digital footprints unveils a tale that, much like history itself, is full of unexpected twists and turns. So, prepare to embark on a scholarly adventure that merges the realms of digital storytelling and guest services, and brace yourself for a few surprises along the way.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The analysis of the data yielded a correlation coefficient of 0.9433053 between the average views of Extra History YouTube videos and the number of bellhops in Indiana, from 2012 to 2022. This value indicates a strong positive linear relationship between these seemingly disparate variables. The r-squared value of 0.8898249 further corroborates this association, suggesting that approximately 88.98% of the variability in the views of Extra History YouTube videos can be explained by the number of bellhops in Indiana. The p-value of less than 0.01 provides robust evidence for the statistical significance of this correlation, reinforcing the notion that this result is not merely a statistical fluke but a real and intriguing phenomenon.

The scatterplot (Fig. 1) visually demonstrates the compelling correlation between the average views of Extra History YouTube videos and the number of bellhops in Indiana, highlighting the strong positive trend. The data points appear to form a pattern that is as captivating as the plot of a historical drama, underscoring the noteworthy relationship between these unexpected bedfellows of online historical education and hospitality services.

These findings have unearthed a fascinating connection that piques the curiosity of researchers and practitioners alike. The implications of this correlation transcend the realms of mere statistical analysis and delve into the cultural and behavioral intricacies of historical enthusiasts and labor market dynamics. It seems that, like the cryptic clues hidden within historical artifacts, the interplay between digital media consumption and employment trends unveils a narrative that is as engaging as it is enigmatic.

In conclusion, this study not only sheds light on the unexpected correlation between the average views of Extra History YouTube videos and the number of bellhops in Indiana but also beckons researchers to explore the labyrinthine landscape of data and the quirky coincidences that it may reveal. It serves as a reminder that even in the most incongruous pairings, correlations may indeed lurk, waiting to be teased out and scrutinized, much like the intricate threads of historical analysis. As the bellhops of Indiana continue their diligent service and history enthusiasts indulge in the digital retelling of bygone eras, our study invites further investigation into the whimsical world of unlikely correlations and unforeseen connections.


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 Average views of Extra History YouTube videos and The number of bellhops in Indiana. 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]]
"Ringing in the Views: A Bellhop's Bellwether for Average Extra History YouTube Video Popularity in Indiana"

[[ABSTRACT]]
This paper delves into the seemingly unrelated realms of online historical education and hospitality services, exploring the correlation between the average views of Extra History YouTube videos and the number of bellhops in the state of Indiana. Utilizing data from YouTube and the Bureau of Labor Statistics, our research team analyzed the viewing trends and employment figures from 2012 to 2022. Our findings revealed a striking correlation coefficient of 0.9433053 and a statistically significant p-value of less than 0.01, indicating a robust relationship between the two variables. This unexpected association raises intriguing questions about the cultural zeitgeist and its influence on consumer behavior and labor demand. Furthermore, it prompts contemplation on the potential motivational factors behind the viewership habits of historical enthusiasts. Our study adds a quirky twist to the intersection of digital media and the labor market, illustrating that even in the most unexpected pairings, there may be correlations that ring true.

[[LITERATURE REVIEW]]
The relationship between online content consumption and labor market dynamics has been a subject of scholarly inquiry in recent years. Smith et al. (2018) examined the impact of digital media viewership on employment patterns, highlighting the potential influence of online trends on labor demand. Similarly, Doe and Jones (2020) explored the intersection of cultural interests and occupational trends, shedding light on the intricate connections between popular culture and workforce dynamics.
Moving beyond the realm of traditional academic studies, non-fiction works such as "Data Analysis for Dummies" and "YouTube Marketing Secrets Unveiled" have offered insights into the analytics of digital platforms and the influencing factors behind viewer engagement. On the fictional front, novels like "The Bellhop's Diaries" and "The Chronicles of YouTube: Tales of Digital Discovery" present imaginative narratives that, albeit fictional, offer glimpses into the peculiar intersections of historical fascination and the service industry.
Venturing into unconventional sources, the researchers also draw inspiration from the unlikeliest of places, including the back covers of shampoo bottles found in hotel bathrooms. While seemingly unrelated to the core themes of this investigation, these sources served as a whimsical reminder of the unexpected connections that can arise in the most peculiar of circumstances.
As the exploration into the relationship between average views of Extra History YouTube videos and the number of bellhops in Indiana unfolds, it is evident that the academic pursuit has taken on a lighthearted and unexpected demeanor. The journey to unravel this peculiar correlation has transcended traditional scholarly pursuits and embraced the whimsical nature of uncovering hidden associations in the digital and labor landscapes.

[[RESULTS]]
The analysis of the data yielded a correlation coefficient of 0.9433053 between the average views of Extra History YouTube videos and the number of bellhops in Indiana, from 2012 to 2022. This value indicates a strong positive linear relationship between these seemingly disparate variables. The r-squared value of 0.8898249 further corroborates this association, suggesting that approximately 88.98% of the variability in the views of Extra History YouTube videos can be explained by the number of bellhops in Indiana. The p-value of less than 0.01 provides robust evidence for the statistical significance of this correlation, reinforcing the notion that this result is not merely a statistical fluke but a real and intriguing phenomenon.
The scatterplot (Fig. 1) visually demonstrates the compelling correlation between the average views of Extra History YouTube videos and the number of bellhops in Indiana, highlighting the strong positive trend. The data points appear to form a pattern that is as captivating as the plot of a historical drama, underscoring the noteworthy relationship between these unexpected bedfellows of online historical education and hospitality services.
These findings have unearthed a fascinating connection that piques the curiosity of researchers and practitioners alike. The implications of this correlation transcend the realms of mere statistical analysis and delve into the cultural and behavioral intricacies of historical enthusiasts and labor market dynamics. It seems that, like the cryptic clues hidden within historical artifacts, the interplay between digital media consumption and employment trends unveils a narrative that is as engaging as it is enigmatic.
In conclusion, this study not only sheds light on the unexpected correlation between the average views of Extra History YouTube videos and the number of bellhops in Indiana but also beckons researchers to explore the labyrinthine landscape of data and the quirky coincidences that it may reveal. It serves as a reminder that even in the most incongruous pairings, correlations may indeed lurk, waiting to be teased out and scrutinized, much like the intricate threads of historical analysis. As the bellhops of Indiana continue their diligent service and history enthusiasts indulge in the digital retelling of bygone eras, our study invites further investigation into the whimsical world of unlikely correlations and unforeseen connections.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The results of our study have brought to light a correlation that seems as improbable as the discovery of a bellhop's memoirs in a dusty library. The robust relationship between the average views of Extra History YouTube videos and the number of bellhops in Indiana not only affirms previous scholarly inquiries into digital media consumption and labor demand but also adds a delightful twist to the narrative of statistical analysis.

Taking a cue from the unorthodox but insightful "Data Analysis for Dummies," our approach to uncovering the correlation between historical viewership and bellhop employment has proven to be anything but amateurish. The statistically significant p-value, akin to a resounding bell toll, rings true in its affirmation of the tangible link between these seemingly unrelated variables.

One could almost imagine this unexpected correlation as a plot twist in a tale of cultural and occupational intrigue. Much like the unconventional narratives in "The Bellhop's Diaries," our findings illustrate a narrative that transcends the boundaries of traditional research and ventures into the realms of whimsy and wonder. The scatterplot, akin to a visual masterpiece, portrays a story as compelling as the accounts found in "The Chronicles of YouTube: Tales of Digital Discovery."

In light of these findings, it becomes clear that the hunch derived from the back covers of hotel shampoo bottles may have been more than just a lighthearted whim. The whimsical nature of these seemingly disparate elements aligns with our results, emphasizing the playful yet substantive character of our investigation.

Our study invites further exploration into the myriad peculiar connections that await discovery in the labyrinthine landscape of data analysis. As we forge ahead in this whimsical world of statistical delving, it is apparent that even the most unexpected correlations can unfold into narratives as captivating as the annals of history itself. Our findings not only advance our understanding of the unexpected bedfellows of online historical education and hospitality services but also underscore the humorous and enigmatic dimensions of academic inquiry.


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 Average views of Extra History YouTube videos and The number of bellhops in Indiana. 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]]
"Ringing in the Views: A Bellhop's Bellwether for Average Extra History YouTube Video Popularity in Indiana"

[[ABSTRACT]]
This paper delves into the seemingly unrelated realms of online historical education and hospitality services, exploring the correlation between the average views of Extra History YouTube videos and the number of bellhops in the state of Indiana. Utilizing data from YouTube and the Bureau of Labor Statistics, our research team analyzed the viewing trends and employment figures from 2012 to 2022. Our findings revealed a striking correlation coefficient of 0.9433053 and a statistically significant p-value of less than 0.01, indicating a robust relationship between the two variables. This unexpected association raises intriguing questions about the cultural zeitgeist and its influence on consumer behavior and labor demand. Furthermore, it prompts contemplation on the potential motivational factors behind the viewership habits of historical enthusiasts. Our study adds a quirky twist to the intersection of digital media and the labor market, illustrating that even in the most unexpected pairings, there may be correlations that ring true.

[[INTRDUCTION]]
In the world of academic research, correlations often lead us on an unexpected journey, much like a historian stumbling upon a hidden cache of archival documents or a bellhop discovering an overlooked suitcase in the lobby. Such serendipitous findings can leave us pondering the idiosyncrasies of human behavior and the enigmatic dance of statistical variables. In this spirit of delightful discovery, our research team embarked on a peculiar quest to unravel the mystical connection between the average views of Extra History YouTube videos and the number of bellhops in the land of cornfields and Hoosier hospitality – Indiana.
As researchers often do, we found ourselves in uncharted territory, seemingly lost in a maze of digital algorithms and labor market data, questioning whether we were threading the needle of enlightenment or merely chasing shadows in the statistical twilight. The task at hand was to decipher whether the popularity of online historical content and the bustling activity of bellhops in Indiana were distant bedfellows or secret admirers intertwined in an enigmatic tango of significance.
Our foray into this uncharted terrain was not without its moments of levity and amusement, much like a historian stumbling upon an amusing anecdote buried in the annals of antiquity. The quest to uncover the pearls of wisdom hidden beneath the digital waves and labor desks led to many a raised eyebrow and chuckle amongst our cohort of researchers, as we traversed the realm of data anomalies and unexpected statistical bedfellows.
The findings that emerged from our analysis raised more than a few eyebrows and sparked lively conversations at our research roundtable, evoking theories as diverse as the interpretations of historical texts. With a correlation coefficient of 0.9433053 and a p-value that danced its way to statistical significance, our study reveals a relationship between the online historical enthusiasts and the bellhops of Indiana that is as intriguing as a cryptic message etched in the marble corridors of ancient palaces.
In this paper, we invite you to join us in exploring this captivating correlation, a conundrum wrapped in a mystery, waiting to be unraveled. Our journey through the labyrinth of numbers and digital footprints unveils a tale that, much like history itself, is full of unexpected twists and turns. So, prepare to embark on a scholarly adventure that merges the realms of digital storytelling and guest services, and brace yourself for a few surprises along the way.

[[RESULTS]]
The analysis of the data yielded a correlation coefficient of 0.9433053 between the average views of Extra History YouTube videos and the number of bellhops in Indiana, from 2012 to 2022. This value indicates a strong positive linear relationship between these seemingly disparate variables. The r-squared value of 0.8898249 further corroborates this association, suggesting that approximately 88.98% of the variability in the views of Extra History YouTube videos can be explained by the number of bellhops in Indiana. The p-value of less than 0.01 provides robust evidence for the statistical significance of this correlation, reinforcing the notion that this result is not merely a statistical fluke but a real and intriguing phenomenon.
The scatterplot (Fig. 1) visually demonstrates the compelling correlation between the average views of Extra History YouTube videos and the number of bellhops in Indiana, highlighting the strong positive trend. The data points appear to form a pattern that is as captivating as the plot of a historical drama, underscoring the noteworthy relationship between these unexpected bedfellows of online historical education and hospitality services.
These findings have unearthed a fascinating connection that piques the curiosity of researchers and practitioners alike. The implications of this correlation transcend the realms of mere statistical analysis and delve into the cultural and behavioral intricacies of historical enthusiasts and labor market dynamics. It seems that, like the cryptic clues hidden within historical artifacts, the interplay between digital media consumption and employment trends unveils a narrative that is as engaging as it is enigmatic.
In conclusion, this study not only sheds light on the unexpected correlation between the average views of Extra History YouTube videos and the number of bellhops in Indiana but also beckons researchers to explore the labyrinthine landscape of data and the quirky coincidences that it may reveal. It serves as a reminder that even in the most incongruous pairings, correlations may indeed lurk, waiting to be teased out and scrutinized, much like the intricate threads of historical analysis. As the bellhops of Indiana continue their diligent service and history enthusiasts indulge in the digital retelling of bygone eras, our study invites further investigation into the whimsical world of unlikely correlations and unforeseen connections.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In this research, we have illuminated the unexpected connection between the popularity of digital historical content and the bustling world of bellhops in Indiana. Our findings have not only uncloaked a striking correlation but have also raised more eyebrows than an over-caffeinated historian at a cryptic crossword competition. The robust relationship between these variables is as undeniable as the intrigue of an unsolved historical mystery, affirming the peculiar interconnectedness between online engagement with history and the labor force devoted to guest services.

As we wrap up our expedition through the statistical wilderness, we are reminded that correlations, much like historical narratives, often weave a tale filled with surprises and unexpected twists. The scatterplot (Fig. 1) revealed a pattern as captivating as a plot twist in historical drama, underscoring the enchanting bond between online historical education and the labor market. As researchers continue their scholarly escapades, we urge them to heed the wondrous and weird signals that emerge from unexpected pairings of variables, much like a diligent bellhop attending to cryptic messages left by guests.

In the spirit of academic curiosity and amusement, we decree that no further research is urgently needed in this domain, as our study has unmasked a correlation as clear as a Renaissance portrait. Let us bask in the delight of this quirky discovery, knowing that even in the world of statistics, there is room for the unexpected and the amusing. As the bellhops of Indiana continue to attend to the needs of travelers, and history enthusiasts venture into the digital realm of bygone eras, we bid adieu to this peculiar correlation, knowing that the scientific intricacies of this delightful oddity will continue to ring true in the annals of research.


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 Ringing in the Views: A Bellhop's Bellwether for Average Extra History YouTube Video Popularity in Indiana. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Quirky Quantitative Research


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 Ringing in the Views: A Bellhop's Bellwether for Average Extra History YouTube Video Popularity in Indiana. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Quirky Data Analysis and Research 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 Ringing in the Views: A Bellhop's Bellwether for Average Extra History YouTube Video Popularity in Indiana with an abstract of This paper delves into the seemingly unrelated realms of online historical education and hospitality services, exploring the correlation between the average views of Extra History YouTube videos and the number of bellhops in the state of Indiana. Utilizing data from YouTube and the Bureau of Labor Statistics, our research team analyzed the viewing trends and employment figures from 2012 to 2022. Our findings revealed a striking correlation coefficient of 0.9433053 and a statistically significant p-value of less than 0.01, indicating a robust relationship between the two variables. This unexpected association raises intriguing questions about the cultural zeitgeist and its influence on consumer behavior and labor demand. Furthermore, it prompts contemplation on the potential motivational factors behind the viewership habits of historical enthusiasts. Our study adds a quirky twist to the intersection of digital media and the labor market, illustrating that even in the most unexpected pairings, there may be correlations that ring true.

ChatGPT:

"Extra History YouTube videos, popularity, Indiana, bellhops, average views, historical education, hospitality services, correlation coefficient, Bureau of Labor Statistics, viewing trends, employment figures, cultural zeitgeist, consumer behavior, labor demand, motivational factors, digital media, labor market, quirky correlations"

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



Random correlation

Discover a new correlation

View all correlations

View all research papers

Report an error


Data details

Average views of Extra History YouTube videos
Detailed data title: Average views of Extra History YouTube videos.
Source: YouTube
Additional Info: Current total views of videos released that year.

See what else correlates with Average views of Extra History YouTube videos

The number of bellhops in Indiana
Detailed data title: BLS estimate of baggage porters and bellhops in Indiana
Source: Bureau of Larbor Statistics
See what else correlates with The number of bellhops in Indiana

Correlation r = 0.9433053 (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 = 0.8898249 (Coefficient of determination)
This means 89% of the change in the one variable (i.e., The number of bellhops in Indiana) is predictable based on the change in the other (i.e., Average views of Extra History YouTube videos) over the 11 years from 2012 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.3E-5. 0.0000132654585305544300000000
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 0.94 in 0.0013% of random cases. Said differently, if you correlated 75,384 random variables You don't actually need 75 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 10 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 10 because we have two variables measured over a period of 11 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.

[ 0.79, 0.99 ] 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.
20122013201420152016201720182019202020212022
Average views of Extra History YouTube videos (Average views)51997267380953510187188810007301381640813838559940384507332483358355
The number of bellhops in Indiana (Laborers)230260270510580680420390250140110




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.




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([519972,673809,535101,871888,1000730,1381640,813838,559940,384507,332483,358355,])
array_2 = np.array([230,260,270,510,580,680,420,390,250,140,110,])
array_1_name = "Average views of Extra History YouTube videos"
array_2_name = "The number of bellhops in Indiana"

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

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



Reuseable content

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

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

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

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

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

Download images for these variables:


View another random correlation

How fun was this correlation?

Kudos for rating!


Correlation ID: 4552 · Black Variable ID: 25775 · Red Variable ID: 7734
about · subscribe · emailme@tylervigen.com · twitter

CC BY 4.0