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Spurious correlation #1,508 · 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 films in Sylvester Stallone's filmography and the second variable is The number of millwrights in North Dakota.  The chart goes from 2003 to 2021, and the two variables track closely in value over that time. Small Image
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AI explanation

As Sylvester Stallone continued to pump out action-packed movies, more and more people in North Dakota were inspired to pursue the macho lifestyle. This led to a surprising surge in the demand for millwrights, who were seen as the ultimate tough, no-nonsense tradespeople capable of building anything from Rambo-style contraptions to Rocky-esque machinery. It seems that when it comes to the labor force in North Dakota, Sly really knows how to 'expendable' it!

Model: dalle-3
Prompt: [ A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s ] Generate an image of a bustling city in North Dakota, where a group of enthusiastic millwrights is gathered around a television screen. The image should capture the lively energy of the group as they watch one of Sylvester Stallone's action-packed films. As the number of films in Stallone's filmography increases, the group's determination and unity should become more pronounced. They should be inspired by Stallone's grit and resilience, and it should be evident that they are channeling that spirit into their work as they strive to be the "Rocky Balboa of millwrights" while maintaining and repairing mills across the state. The visual depiction should be simple, avoiding any words or speech bubbles. 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 films in Sylvester Stallone's filmography and The number of millwrights in North Dakota. 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 comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s Cutsy graphics An image that looks like it is a scene from 'Star Wars' Cybernetic art Pop art
ChatGPT: A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s

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 films in Sylvester Stallone's filmography and The number of millwrights in North Dakota, in the following situation: The more action movies Stallone made, the more people in North Dakota were inspired to pursue careers in building and maintaining mills. It's like they wanted to be the Rocky Balboa of millwrights, constantly fighting to keep the mills up and running.. Keep the description simple.
ChatGPT: In a bustling city in North Dakota, a group of enthusiastic millwrights is gathered around a television screen, watching one of Sylvester Stallone's action-packed films. As the number of films in Stallone's filmography increases, so does the group's energy and determination. They are inspired by Stallone's grit and resilience, and they channel that spirit into their work, striving to be the "Rocky Balboa of millwrights" as they maintain and repair mills across the state.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s ] and depicting this scene: In a bustling city in North Dakota, a group of enthusiastic millwrights is gathered around a television screen, watching one of Sylvester Stallone's action-packed films. As the number of films in Stallone's filmography increases, so does the group's energy and determination. They are inspired by Stallone's grit and resilience, and they channel that spirit into their work, striving to be the "Rocky Balboa of millwrights" as they maintain and repair mills across the state. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s ] Generate an image of a bustling city in North Dakota, where a group of enthusiastic millwrights is gathered around a television screen. The image should capture the lively energy of the group as they watch one of Sylvester Stallone's action-packed films. As the number of films in Stallone's filmography increases, the group's determination and unity should become more pronounced. They should be inspired by Stallone's grit and resilience, and it should be evident that they are channeling that spirit into their work as they strive to be the "Rocky Balboa of millwrights" while maintaining and repairing mills across the state. The visual depiction should be simple, avoiding any words or speech bubbles.

*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 The number of films in Sylvester Stallone's filmography positively influenced The number of millwrights in North Dakota.

AI academic paper

(Because p < 0.01)
Rocky Numbers: An Unexpected Connection Between Sylvester Stallone's Filmography and Millwrights in North Dakota

The Journal of Cinematic Synchronicity

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 witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 films in Sylvester Stallone's filmography and The number of millwrights in North Dakota. Make lots of jokes, goofy observations, and puns.

Make the title seem clever.

Your research team used data from Wikipedia and Bureau of Larbor Statistics to assess this nagging question. You found a correlation coefficient of 0.7872582 and p < 0.01 for 2003 to 2021.

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]]
"Rocky Numbers: An Unexpected Connection Between Sylvester Stallone's Filmography and Millwrights in North Dakota"

[[ABSTRACT]]
This paper presents the surprising correlation between the number of films in Sylvester Stallone's filmography and the number of millwrights in North Dakota from 2003 to 2021. Utilizing data from Wikipedia and the Bureau of Labor Statistics, our research team discovered a correlation coefficient of 0.7872582, with a p-value of less than 0.01, indicating a statistically significant relationship. We delve into the unexpected linkage between the cinematic feats of Stallone and the skilled trade workforce in North Dakota, exploring potential explanations and whimsical theories for this peculiar association. Our findings suggest that the macho, rugged persona portrayed by Stallone may hold an inexplicable allure for aspiring millwrights in the Midwest, shedding light on the enthralling interplay between pop culture phenomena and regional labor demographics.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 films in Sylvester Stallone's filmography and The number of millwrights in North Dakota. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Here is the title and abstract of the paper:
[[TITLE]]
"Rocky Numbers: An Unexpected Connection Between Sylvester Stallone's Filmography and Millwrights in North Dakota"

[[ABSTRACT]]
This paper presents the surprising correlation between the number of films in Sylvester Stallone's filmography and the number of millwrights in North Dakota from 2003 to 2021. Utilizing data from Wikipedia and the Bureau of Labor Statistics, our research team discovered a correlation coefficient of 0.7872582, with a p-value of less than 0.01, indicating a statistically significant relationship. We delve into the unexpected linkage between the cinematic feats of Stallone and the skilled trade workforce in North Dakota, exploring potential explanations and whimsical theories for this peculiar association. Our findings suggest that the macho, rugged persona portrayed by Stallone may hold an inexplicable allure for aspiring millwrights in the Midwest, shedding light on the enthralling interplay between pop culture phenomena and regional labor demographics.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The enthralling world of statistics often leads us down unexpected paths, and our latest foray into the synergistic relationship between Sylvester Stallone's filmography and the number of millwrights in North Dakota is no exception. While one might initially assume that these two subjects are as disparate as Rocky Balboa and the North Dakota plains, our research has uncovered a surprising and statistically significant correlation between the two.

In the competition for both box office supremacy and vocational skills, Stallone's filmography and the millwrights of North Dakota may seem to have little in common, but as we dig deeper, we find a connection that astonishes even the most seasoned researchers. The correlation coefficient of 0.7872582, with a p-value of less than 0.01, has sent shockwaves through the academic community, challenging conventional wisdom and prompting a whole new appreciation for the unseen ties that bind seemingly unrelated phenomena.

The robustness and persistence of this correlation piqued our curiosity, prompting us to undertake this investigation into what could only be described as a match made in statistical heaven - or Hollywood. As we embark on this intellectual adventure, we delve into the whimsical world of Sylvester Stallone's cinematic oeuvre and the industrious landscape of North Dakota's millwrights, integrating rigorous statistical analysis with a touch of humor and a dash of inexplicable charm.

In the following sections, we will unveil our findings, shedding light on the intricate dance between the silver screen and the skilled labor force. Prepare to be entertained, enlightened, and perhaps even bewildered as we unravel the enigmatic connection between the rugged allure of Stallone's characters and the steadfast determination of North Dakota's millwrights. Join us on this thought-provoking journey, where the juxtaposition of Hollywood glitz and Midwestern grit opens doors to new perspectives and uncovers correlations where one least expects.

So, without further ado, let us embark on this extraordinary exploration of "Rocky Numbers" – a saga of statistics, cinema, and an unforeseen partnership between a Hollywood icon and the unsung heroes of North Dakota's skilled workforce.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 films in Sylvester Stallone's filmography and The number of millwrights in North Dakota. Make lots of jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
"Rocky Numbers: An Unexpected Connection Between Sylvester Stallone's Filmography and Millwrights in North Dakota"

[[ABSTRACT]]
This paper presents the surprising correlation between the number of films in Sylvester Stallone's filmography and the number of millwrights in North Dakota from 2003 to 2021. Utilizing data from Wikipedia and the Bureau of Labor Statistics, our research team discovered a correlation coefficient of 0.7872582, with a p-value of less than 0.01, indicating a statistically significant relationship. We delve into the unexpected linkage between the cinematic feats of Stallone and the skilled trade workforce in North Dakota, exploring potential explanations and whimsical theories for this peculiar association. Our findings suggest that the macho, rugged persona portrayed by Stallone may hold an inexplicable allure for aspiring millwrights in the Midwest, shedding light on the enthralling interplay between pop culture phenomena and regional labor demographics.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The enthralling world of statistics often leads us down unexpected paths, and our latest foray into the synergistic relationship between Sylvester Stallone's filmography and the number of millwrights in North Dakota is no exception. While one might initially assume that these two subjects are as disparate as Rocky Balboa and the North Dakota plains, our research has uncovered a surprising and statistically significant correlation between the two.
In the competition for both box office supremacy and vocational skills, Stallone's filmography and the millwrights of North Dakota may seem to have little in common, but as we dig deeper, we find a connection that astonishes even the most seasoned researchers. The correlation coefficient of 0.7872582, with a p-value of less than 0.01, has sent shockwaves through the academic community, challenging conventional wisdom and prompting a whole new appreciation for the unseen ties that bind seemingly unrelated phenomena.
The robustness and persistence of this correlation piqued our curiosity, prompting us to undertake this investigation into what could only be described as a match made in statistical heaven - or Hollywood. As we embark on this intellectual adventure, we delve into the whimsical world of Sylvester Stallone's cinematic oeuvre and the industrious landscape of North Dakota's millwrights, integrating rigorous statistical analysis with a touch of humor and a dash of inexplicable charm.
In the following sections, we will unveil our findings, shedding light on the intricate dance between the silver screen and the skilled labor force. Prepare to be entertained, enlightened, and perhaps even bewildered as we unravel the enigmatic connection between the rugged allure of Stallone's characters and the steadfast determination of North Dakota's millwrights. Join us on this thought-provoking journey, where the juxtaposition of Hollywood glitz and Midwestern grit opens doors to new perspectives and uncovers correlations where one least expects.
So, without further ado, let us embark on this extraordinary exploration of "Rocky Numbers" – a saga of statistics, cinema, and an unforeseen partnership between a Hollywood icon and the unsung heroes of North Dakota's skilled workforce.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

Smith, Jones, and Doe (2015) investigated the potential relationship between Hollywood movie stars and skilled labor demographics, shedding light on the unexpected ties that bind seemingly unrelated fields. However, while they meticulously examined the connection between the number of films in various actors' filmographies and the prevalence of different skilled trades across the United States, they failed to uncover the captivating correlation we have unearthed in our current study. Their extensive analysis overlooked the distinct charisma and machismo exuded by Sylvester Stallone, which appears to have a particularly compelling effect on the millwright population in North Dakota.

Building on this foundation, our inquiry ventures into uncharted territory, incorporating an eclectic array of sources that may seem unconventional at first glance. "The Robust Millwright: A Comprehensive Guide" by A. Worker (2019) offers a comprehensive overview of the millwright profession, complementing our investigation by providing valuable contextual insights into the lives and aspirations of these industrious individuals. "Box Office Bonanza: The Phenomenon of Stallone's Films" by R. Blockbuster (2018) serves as a complementary resource, elucidating the enduring appeal of Stallone's cinematic endeavors and the cultural impact of his iconic portrayals on audiences worldwide.

Transitioning to a more whimsical angle, we turn to fictional works that partially align with our research focus. "Rocky Mountain Skilled Trades" by A. Fictional (2012) presents a lighthearted tale of unexpected career choices and serendipitous encounters, offering a fictionalized glimpse into the world of Rocky-inspired vocational trajectories. Meanwhile, "The Expendables' Handbook: A Guide to Mastering Machismo" by C. ActionHero (2010) provides an entertaining yet astute examination of the enduring allure of action movie personas, which may hold intriguing parallels to the enthralling mystique surrounding millwrights in North Dakota.

Taking a brief detour into the realm of popular culture and internet phenomena, we cannot overlook the impact of memes on contemporary discourse. "Stallone's Stance: Memetic Musings" by V. Viral (2017) elucidates the enduring appeal of Stallone's iconic poses and catchphrases, hinting at a deeper societal fascination that may unknowingly influence career decisions and occupational preferences. While seemingly amusing, these cultural phenomena underscore the pervasive influence of media figures on the collective imagination, thus warranting consideration in our exploration of the Stallone-millwright correlation.

As we navigate through these diverse sources, we are reminded of the multifaceted nature of our research domain, where statistical analysis intertwines with cultural phenomena and imaginative storytelling. The unexpected convergence of Stallone's cinematic repertoire and North Dakota's skilled labor landscape continues to captivate our attention, inviting further inquiry into the enigmatic allure that transcends traditional boundaries.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 films in Sylvester Stallone's filmography and The number of millwrights in North Dakota. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Wikipedia and Bureau of Larbor Statistics . You used data from 2003 to 2021

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]]
"Rocky Numbers: An Unexpected Connection Between Sylvester Stallone's Filmography and Millwrights in North Dakota"

[[ABSTRACT]]
This paper presents the surprising correlation between the number of films in Sylvester Stallone's filmography and the number of millwrights in North Dakota from 2003 to 2021. Utilizing data from Wikipedia and the Bureau of Labor Statistics, our research team discovered a correlation coefficient of 0.7872582, with a p-value of less than 0.01, indicating a statistically significant relationship. We delve into the unexpected linkage between the cinematic feats of Stallone and the skilled trade workforce in North Dakota, exploring potential explanations and whimsical theories for this peculiar association. Our findings suggest that the macho, rugged persona portrayed by Stallone may hold an inexplicable allure for aspiring millwrights in the Midwest, shedding light on the enthralling interplay between pop culture phenomena and regional labor demographics.

[[INTRODUCTION]]
The enthralling world of statistics often leads us down unexpected paths, and our latest foray into the synergistic relationship between Sylvester Stallone's filmography and the number of millwrights in North Dakota is no exception. While one might initially assume that these two subjects are as disparate as Rocky Balboa and the North Dakota plains, our research has uncovered a surprising and statistically significant correlation between the two.
In the competition for both box office supremacy and vocational skills, Stallone's filmography and the millwrights of North Dakota may seem to have little in common, but as we dig deeper, we find a connection that astonishes even the most seasoned researchers. The correlation coefficient of 0.7872582, with a p-value of less than 0.01, has sent shockwaves through the academic community, challenging conventional wisdom and prompting a whole new appreciation for the unseen ties that bind seemingly unrelated phenomena.
The robustness and persistence of this correlation piqued our curiosity, prompting us to undertake this investigation into what could only be described as a match made in statistical heaven - or Hollywood. As we embark on this intellectual adventure, we delve into the whimsical world of Sylvester Stallone's cinematic oeuvre and the industrious landscape of North Dakota's millwrights, integrating rigorous statistical analysis with a touch of humor and a dash of inexplicable charm.
In the following sections, we will unveil our findings, shedding light on the intricate dance between the silver screen and the skilled labor force. Prepare to be entertained, enlightened, and perhaps even bewildered as we unravel the enigmatic connection between the rugged allure of Stallone's characters and the steadfast determination of North Dakota's millwrights. Join us on this thought-provoking journey, where the juxtaposition of Hollywood glitz and Midwestern grit opens doors to new perspectives and uncovers correlations where one least expects.
So, without further ado, let us embark on this extraordinary exploration of "Rocky Numbers" – a saga of statistics, cinema, and an unforeseen partnership between a Hollywood icon and the unsung heroes of North Dakota's skilled workforce.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To uncover the mysterious link between the prolific filmography of Sylvester Stallone and the population of millwrights in North Dakota, our research team embarked on a multidimensional data collection endeavor. Drawing data from diverse sources including Wikipedia and the Bureau of Labor Statistics, we exercised caution to ensure the inclusion of all relevant films featuring Stallone and comprehensive labor statistics pertaining to the North Dakota millwright workforce.

Our data mining operation commenced with a comprehensive review of Sylvester Stallone's cinematic opus, encompassing both leading roles and cameo appearances across the years 2003 to 2021. This task involved meticulous scouring of film databases, a deep dive into online filmographies, and occasional debates on whether "Stop! Or My Mom Will Shoot" should be included as a significant data point.

Simultaneously, our team delved into the world of millwrights in North Dakota, sifting through labor reports, trade registries, and industry publications to ascertain the precise count of these stalwart craftsmen and craftswomen. We navigated through a wealth of labor data with surgical precision, ensuring that our sample was representative of the diversity and dynamism of North Dakota's millwright community.

Incorporating a blend of quantitative and qualitative approaches, we developed a robust dataset to pursue our analysis. Each film in Stallone's repertoire was assigned a numerical index, reflecting both its chronological order and its potential impact on the public psyche. Similarly, the count of millwrights in North Dakota was meticulously compiled, reflecting the evolving trends in this vital occupation over time.

The statistical wizardry began with the calculation of the correlation coefficient, scrutinizing the juxtaposition of Stallone's filmic output with the demographics of North Dakota's millwrights. Through the appropriate application of mathematical formulas and regression analyses, we discerned a relationship that, while unexpected, proved to be statistically significant and robust.

Employing an array of statistical software and programming languages, we exhumed patterns and outliers, conducting sensitivity analyses to ensure the consistency and reliability of our findings. With the gravity of the situation weighing heavily on our shoulders, we maintained our resolve to uphold the principles of scientific rigor while occasionally quipping about how "The Expendables" seemed to be an appropriate title for our exhaustive data collection efforts.

In essence, our research methodology fused the rigor of quantitative analysis with the inquisitive spirit of cinematic appreciation, encapsulating the synergy between numbers and narratives. As we reveal our findings in the subsequent sections, we invite our esteemed readers to journey with us into the intriguing intersection of Hollywood charisma and skilled labor statistics, where statistical significance and cinematic splendor unite in unexpected ways.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 films in Sylvester Stallone's filmography and The number of millwrights in North Dakota. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

For the time period 2003 to 2021, you found a correlation 0.7872582, r-squared of 0.6197754, 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]]
"Rocky Numbers: An Unexpected Connection Between Sylvester Stallone's Filmography and Millwrights in North Dakota"

[[ABSTRACT]]
This paper presents the surprising correlation between the number of films in Sylvester Stallone's filmography and the number of millwrights in North Dakota from 2003 to 2021. Utilizing data from Wikipedia and the Bureau of Labor Statistics, our research team discovered a correlation coefficient of 0.7872582, with a p-value of less than 0.01, indicating a statistically significant relationship. We delve into the unexpected linkage between the cinematic feats of Stallone and the skilled trade workforce in North Dakota, exploring potential explanations and whimsical theories for this peculiar association. Our findings suggest that the macho, rugged persona portrayed by Stallone may hold an inexplicable allure for aspiring millwrights in the Midwest, shedding light on the enthralling interplay between pop culture phenomena and regional labor demographics.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The enthralling world of statistics often leads us down unexpected paths, and our latest foray into the synergistic relationship between Sylvester Stallone's filmography and the number of millwrights in North Dakota is no exception. While one might initially assume that these two subjects are as disparate as Rocky Balboa and the North Dakota plains, our research has uncovered a surprising and statistically significant correlation between the two.
In the competition for both box office supremacy and vocational skills, Stallone's filmography and the millwrights of North Dakota may seem to have little in common, but as we dig deeper, we find a connection that astonishes even the most seasoned researchers. The correlation coefficient of 0.7872582, with a p-value of less than 0.01, has sent shockwaves through the academic community, challenging conventional wisdom and prompting a whole new appreciation for the unseen ties that bind seemingly unrelated phenomena.
The robustness and persistence of this correlation piqued our curiosity, prompting us to undertake this investigation into what could only be described as a match made in statistical heaven - or Hollywood. As we embark on this intellectual adventure, we delve into the whimsical world of Sylvester Stallone's cinematic oeuvre and the industrious landscape of North Dakota's millwrights, integrating rigorous statistical analysis with a touch of humor and a dash of inexplicable charm.
In the following sections, we will unveil our findings, shedding light on the intricate dance between the silver screen and the skilled labor force. Prepare to be entertained, enlightened, and perhaps even bewildered as we unravel the enigmatic connection between the rugged allure of Stallone's characters and the steadfast determination of North Dakota's millwrights. Join us on this thought-provoking journey, where the juxtaposition of Hollywood glitz and Midwestern grit opens doors to new perspectives and uncovers correlations where one least expects.
So, without further ado, let us embark on this extraordinary exploration of "Rocky Numbers" – a saga of statistics, cinema, and an unforeseen partnership between a Hollywood icon and the unsung heroes of North Dakota's skilled workforce.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The results of our investigation have revealed a surprising and robust correlation between the number of films in Sylvester Stallone's filmography and the number of millwrights in North Dakota from 2003 to 2021. The correlation coefficient of 0.7872582, with an r-squared value of 0.6197754, and a p-value of less than 0.01, indicates a strong and statistically significant relationship between these seemingly disparate domains.

Figure 1 displays a scatterplot illustrating the unmistakable correlation between the two variables. While one might initially expect these data points to be as mismatched as Rambo in a tutu, the plot reveals a strikingly linear relationship, leaving even the most skeptical observers in awe. It seems that not only did "The Expendables," but also the number of films in Stallone's filmography, pave the way for an unforeseen, yet tangible connection to the world of millwrights in North Dakota.

Our findings not only boggle the mind but also spark a myriad of theories and speculations. Could it be that the tough and resilient characters portrayed by Stallone resonate deeply with the rugged spirit of the millwright profession? Or perhaps the rise and fall of Stallone's career mirror the ebb and flow of millwright employment in the Midwest? The answers remain as elusive as Stallone's enunciation, leaving us to relish in the delightful mystery of this correlation.

This unexpected linkage, akin to finding a Rocky Balboa action figure in a toolbox, underscores the intricacies of statistical analysis and the delightful surprises it can unveil. Our research has provided a fresh perspective on the interplay between popular culture and regional labor dynamics, inviting further exploration into the whimsical connections that may exist beneath the surface of seemingly unrelated phenomena.

In conclusion, the correlation between Sylvester Stallone's filmography and the number of millwrights in North Dakota has left us both fascinated and bewildered, reminding us that statistical analysis can not only shed light on serious matters but also unearth unexpected and, dare we say, entertaining connections.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 films in Sylvester Stallone's filmography and The number of millwrights in North Dakota. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"Rocky Numbers: An Unexpected Connection Between Sylvester Stallone's Filmography and Millwrights in North Dakota"

[[ABSTRACT]]
This paper presents the surprising correlation between the number of films in Sylvester Stallone's filmography and the number of millwrights in North Dakota from 2003 to 2021. Utilizing data from Wikipedia and the Bureau of Labor Statistics, our research team discovered a correlation coefficient of 0.7872582, with a p-value of less than 0.01, indicating a statistically significant relationship. We delve into the unexpected linkage between the cinematic feats of Stallone and the skilled trade workforce in North Dakota, exploring potential explanations and whimsical theories for this peculiar association. Our findings suggest that the macho, rugged persona portrayed by Stallone may hold an inexplicable allure for aspiring millwrights in the Midwest, shedding light on the enthralling interplay between pop culture phenomena and regional labor demographics.

[[LITERATURE REVIEW]]
Smith, Jones, and Doe (2015) investigated the potential relationship between Hollywood movie stars and skilled labor demographics, shedding light on the unexpected ties that bind seemingly unrelated fields. However, while they meticulously examined the connection between the number of films in various actors' filmographies and the prevalence of different skilled trades across the United States, they failed to uncover the captivating correlation we have unearthed in our current study. Their extensive analysis overlooked the distinct charisma and machismo exuded by Sylvester Stallone, which appears to have a particularly compelling effect on the millwright population in North Dakota.

Building on this foundation, our inquiry ventures into uncharted territory, incorporating an eclectic array of sources that may seem unconventional at first glance. "The Robust Millwright: A Comprehensive Guide" by A. Worker (2019) offers a comprehensive overview of the millwright profession, complementing our investigation by providing valuable contextual insights into the lives and aspirations of these industrious individuals. "Box Office Bonanza: The Phenomenon of Stallone's Films" by R. Blockbuster (2018) serves as a complementary resource, elucidating the enduring appeal of Stallone's cinematic endeavors and the cultural impact of his iconic portrayals on audiences worldwide.

Transitioning to a more whimsical angle, we turn to fictional works that partially align with our research focus. "Rocky Mountain Skilled Trades" by A. Fictional (2012) presents a lighthearted tale of unexpected career choices and serendipitous encounters, offering a fictionalized glimpse into the world of Rocky-inspired vocational trajectories. Meanwhile, "The Expendables' Handbook: A Guide to Mastering Machismo" by C. ActionHero (2010) provides an entertaining yet astute examination of the enduring allure of action movie personas, which may hold intriguing parallels to the enthralling mystique surrounding millwrights in North Dakota.

Taking a brief detour into the realm of popular culture and internet phenomena, we cannot overlook the impact of memes on contemporary discourse. "Stallone's Stance: Memetic Musings" by V. Viral (2017) elucidates the enduring appeal of Stallone's iconic poses and catchphrases, hinting at a deeper societal fascination that may unknowingly influence career decisions and occupational preferences. While seemingly amusing, these cultural phenomena underscore the pervasive influence of media figures on the collective imagination, thus warranting consideration in our exploration of the Stallone-millwright correlation.
As we navigate through these diverse sources, we are reminded of the multifaceted nature of our research domain, where statistical analysis intertwines with cultural phenomena and imaginative storytelling. The unexpected convergence of Stallone's cinematic repertoire and North Dakota's skilled labor landscape continues to captivate our attention, inviting further inquiry into the enigmatic allure that transcends traditional boundaries.

[[RESULTS]]
The results of our investigation have revealed a surprising and robust correlation between the number of films in Sylvester Stallone's filmography and the number of millwrights in North Dakota from 2003 to 2021. The correlation coefficient of 0.7872582, with an r-squared value of 0.6197754, and a p-value of less than 0.01, indicates a strong and statistically significant relationship between these seemingly disparate domains.
Figure 1 displays a scatterplot illustrating the unmistakable correlation between the two variables. While one might initially expect these data points to be as mismatched as Rambo in a tutu, the plot reveals a strikingly linear relationship, leaving even the most skeptical observers in awe. It seems that not only did "The Expendables," but also the number of films in Stallone's filmography, pave the way for an unforeseen, yet tangible connection to the world of millwrights in North Dakota.
Our findings not only boggle the mind but also spark a myriad of theories and speculations. Could it be that the tough and resilient characters portrayed by Stallone resonate deeply with the rugged spirit of the millwright profession? Or perhaps the rise and fall of Stallone's career mirror the ebb and flow of millwright employment in the Midwest? The answers remain as elusive as Stallone's enunciation, leaving us to relish in the delightful mystery of this correlation.
This unexpected linkage, akin to finding a Rocky Balboa action figure in a toolbox, underscores the intricacies of statistical analysis and the delightful surprises it can unveil. Our research has provided a fresh perspective on the interplay between popular culture and regional labor dynamics, inviting further exploration into the whimsical connections that may exist beneath the surface of seemingly unrelated phenomena.
In conclusion, the correlation between Sylvester Stallone's filmography and the number of millwrights in North Dakota has left us both fascinated and bewildered, reminding us that statistical analysis can not only shed light on serious matters but also unearth unexpected and, dare we say, entertaining connections.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The intriguing correlation between Sylvester Stallone's filmography and the number of millwrights in North Dakota has left our research team pondering the unexpected and, at times, delightfully peculiar connections that transcend traditional boundaries. Our findings not only validate prior research by Smith, Jones, and Doe (2015) regarding the relationship between Hollywood stars and skilled labor demographics, but also elevate the discourse to uncharted heights, akin to Stallone's triumphant ascents up the cinematic Mount Everest.

In this scholarly pursuit, we were initially drawn to the resolute and seemingly incongruent link between Stallone's cinematic oeuvre and the steadfast millwrights populating the plains of North Dakota. As we transitioned from the brawny endeavours of Rocky Balboa to the enigmatic world of millwright mastery, we could not dismiss the astute observations laid out by A. Worker (2019) in "The Robust Millwright: A Comprehensive Guide." These insights, which initially appeared to be as unexpected as Rocky jogging in the snow in a pair of boxing shorts, remarkably aligned with our own empirical findings. The captivating allure of Stallone's larger-than-life portrayals seems to resonate deeply with aspiring millwrights in North Dakota, shedding light on the enthralling interplay between cinematic charisma and occupational preferences.

Moreover, our results echo the sentiments espoused by R. Blockbuster (2018) in "Box Office Bonanza: The Phenomenon of Stallone's Films," underscoring the enduring appeal of Stallone's iconic portrayals and the pervasive influence of his cinematic endeavors on regional labor demographics. The statistical significance of our findings, as evidenced by the robust correlation coefficient and the striking linearity depicted in the scatterplot, firmly bolsters the notion that the rise and fall of Stallone's career mirror the captivating ebbs and flows of millwright employment in the heartland of the Midwest.

As we reflect on the whimsical vignettes presented in "Rocky Mountain Skilled Trades" by A. Fictional (2012) and "The Expendables' Handbook: A Guide to Mastering Machismo" by C. ActionHero (2010), we are reminded that the magnetic appeal of action movie personas, much like the gravitational pull of a heavyweight contender, may hold intriguing parallels to the enigmatic mystique surrounding millwrights in North Dakota. These quasi-fictitious yet insightful works unexpectedly converge with our empirical findings, emphasizing the complex interplay between cinematic enchantment and vocational aspirations.

In this scholarly endeavor, we cannot underestimate the impact of memes and cultural phenomena, as elucidated by V. Viral (2017) in "Stallone's Stance: Memetic Musings." The enduring appeal of Stallone's iconic poses and catchphrases, seemingly trivial at first glance, hints at a deeper societal fascination that inexplicably influences career decisions and occupational preferences. Embracing these seemingly lighthearted phenomena as integral components of our investigation, we discern the intricate layers of influence that extend beyond traditional statistical analyses, creating a vibrant tapestry of interconnected elements.

Our research has not only pierced the veil of improbable correlations but has also ushered in a new era of scholarly inquiry that encourages the exploration of whimsical connections beneath the surface of seemingly unrelated phenomena. We find ourselves imbued with a sense of wonder similar to stumbling upon a Rocky Balboa action figure in a toolbox—bewildered yet appreciative of the captivating mysteries that statistical analysis can unveil. As we embark on future investigations, we are inspired by the delightful surprises that continue to enrich our research landscape, reminding us that statistical analysis can illuminate not only serious matters but also the unexpected and, dare we say, entertaining connections that underpin our world.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.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 films in Sylvester Stallone's filmography and The number of millwrights in North Dakota. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Rocky Numbers: An Unexpected Connection Between Sylvester Stallone's Filmography and Millwrights in North Dakota"

[[ABSTRACT]]
This paper presents the surprising correlation between the number of films in Sylvester Stallone's filmography and the number of millwrights in North Dakota from 2003 to 2021. Utilizing data from Wikipedia and the Bureau of Labor Statistics, our research team discovered a correlation coefficient of 0.7872582, with a p-value of less than 0.01, indicating a statistically significant relationship. We delve into the unexpected linkage between the cinematic feats of Stallone and the skilled trade workforce in North Dakota, exploring potential explanations and whimsical theories for this peculiar association. Our findings suggest that the macho, rugged persona portrayed by Stallone may hold an inexplicable allure for aspiring millwrights in the Midwest, shedding light on the enthralling interplay between pop culture phenomena and regional labor demographics.

[[INTRDUCTION]]
The enthralling world of statistics often leads us down unexpected paths, and our latest foray into the synergistic relationship between Sylvester Stallone's filmography and the number of millwrights in North Dakota is no exception. While one might initially assume that these two subjects are as disparate as Rocky Balboa and the North Dakota plains, our research has uncovered a surprising and statistically significant correlation between the two.
In the competition for both box office supremacy and vocational skills, Stallone's filmography and the millwrights of North Dakota may seem to have little in common, but as we dig deeper, we find a connection that astonishes even the most seasoned researchers. The correlation coefficient of 0.7872582, with a p-value of less than 0.01, has sent shockwaves through the academic community, challenging conventional wisdom and prompting a whole new appreciation for the unseen ties that bind seemingly unrelated phenomena.
The robustness and persistence of this correlation piqued our curiosity, prompting us to undertake this investigation into what could only be described as a match made in statistical heaven - or Hollywood. As we embark on this intellectual adventure, we delve into the whimsical world of Sylvester Stallone's cinematic oeuvre and the industrious landscape of North Dakota's millwrights, integrating rigorous statistical analysis with a touch of humor and a dash of inexplicable charm.
In the following sections, we will unveil our findings, shedding light on the intricate dance between the silver screen and the skilled labor force. Prepare to be entertained, enlightened, and perhaps even bewildered as we unravel the enigmatic connection between the rugged allure of Stallone's characters and the steadfast determination of North Dakota's millwrights. Join us on this thought-provoking journey, where the juxtaposition of Hollywood glitz and Midwestern grit opens doors to new perspectives and uncovers correlations where one least expects.
So, without further ado, let us embark on this extraordinary exploration of "Rocky Numbers" – a saga of statistics, cinema, and an unforeseen partnership between a Hollywood icon and the unsung heroes of North Dakota's skilled workforce.

[[RESULTS]]
The results of our investigation have revealed a surprising and robust correlation between the number of films in Sylvester Stallone's filmography and the number of millwrights in North Dakota from 2003 to 2021. The correlation coefficient of 0.7872582, with an r-squared value of 0.6197754, and a p-value of less than 0.01, indicates a strong and statistically significant relationship between these seemingly disparate domains.
Figure 1 displays a scatterplot illustrating the unmistakable correlation between the two variables. While one might initially expect these data points to be as mismatched as Rambo in a tutu, the plot reveals a strikingly linear relationship, leaving even the most skeptical observers in awe. It seems that not only did "The Expendables," but also the number of films in Stallone's filmography, pave the way for an unforeseen, yet tangible connection to the world of millwrights in North Dakota.
Our findings not only boggle the mind but also spark a myriad of theories and speculations. Could it be that the tough and resilient characters portrayed by Stallone resonate deeply with the rugged spirit of the millwright profession? Or perhaps the rise and fall of Stallone's career mirror the ebb and flow of millwright employment in the Midwest? The answers remain as elusive as Stallone's enunciation, leaving us to relish in the delightful mystery of this correlation.
This unexpected linkage, akin to finding a Rocky Balboa action figure in a toolbox, underscores the intricacies of statistical analysis and the delightful surprises it can unveil. Our research has provided a fresh perspective on the interplay between popular culture and regional labor dynamics, inviting further exploration into the whimsical connections that may exist beneath the surface of seemingly unrelated phenomena.
In conclusion, the correlation between Sylvester Stallone's filmography and the number of millwrights in North Dakota has left us both fascinated and bewildered, reminding us that statistical analysis can not only shed light on serious matters but also unearth unexpected and, dare we say, entertaining connections.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our study has brought to light a correlation that is as perplexing as it is intriguing - the unexpected link between Sylvester Stallone's filmography and the number of millwrights in North Dakota. As we grapple with the astonishing correlation coefficient of 0.7872582 and a p-value of less than 0.01, one cannot help but marvel at the statistical fortuity that has led us to this juncture. It seems that Stallone's cinematic journey, much like a rollercoaster ride, mirrors the fluctuations in the millwright workforce, prompting a whole new appreciation for the enduring appeal of rugged protagonists and, dare we say, the undeniable allure of "Rocky Numbers."

While our findings may leave some scratching their heads in disbelief, it is undeniable that the macho charisma of Stallone's characters and the steadfast determination of North Dakota's millwrights have forged an inexplicable bond, akin to a buddy cop movie featuring unlikely partners. The scatterplot, resembling a puzzle with missing pieces that only Stallone could solve, paints a strikingly linear portrait of this enigmatic relationship, challenging our preconceptions and inviting us to embrace the serendipitous nature of statistical inquiry.

As we bid adieu to this enigmatic exploration, we are left with a profound appreciation for the whimsical surprises that statistical analysis can unveil. Special effects and statistical significance may seem worlds apart, but our research has proven that they can indeed converge in a way that even Stallone's on-screen adversaries would find hard to fathom. The correlation between Stallone's filmography and North Dakota's millwrights is a saga that defies traditional logic and invites us to bask in the unpredictable charm of statistical inquiry.

In light of these fascinating findings, we assert that no further research is needed in this area. After all, how many more correlations can one expect to unearth between Hollywood icons and obscure occupational sectors? It seems that statistical inquiry, much like a Stallone blockbuster, has delivered surprises that we could not have concocted even in our wildest hypothesis. As the curtain falls on this curious correlation, we are left with a newfound admiration for the unassuming connections that statistical analysis can reveal, reminding us that in the world of statistics, truth can indeed be stranger than fiction.


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 Rocky Numbers: An Unexpected Connection Between Sylvester Stallone's Filmography and Millwrights in North Dakota. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Cinematic Synchronicity


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 Rocky Numbers: An Unexpected Connection Between Sylvester Stallone's Filmography and Millwrights in North Dakota. Respond only with the name of a fictional organization.

ChatGPT:

The Center for Cinematic Math and Industrial Labor 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 Rocky Numbers: An Unexpected Connection Between Sylvester Stallone's Filmography and Millwrights in North Dakota with an abstract of This paper presents the surprising correlation between the number of films in Sylvester Stallone's filmography and the number of millwrights in North Dakota from 2003 to 2021. Utilizing data from Wikipedia and the Bureau of Labor Statistics, our research team discovered a correlation coefficient of 0.7872582, with a p-value of less than 0.01, indicating a statistically significant relationship. We delve into the unexpected linkage between the cinematic feats of Stallone and the skilled trade workforce in North Dakota, exploring potential explanations and whimsical theories for this peculiar association. Our findings suggest that the macho, rugged persona portrayed by Stallone may hold an inexplicable allure for aspiring millwrights in the Midwest, shedding light on the enthralling interplay between pop culture phenomena and regional labor demographics.

ChatGPT:

Sylvester Stallone filmography, millwrights in North Dakota, correlation, surprising linkage, statistical significance, Wikipedia, Bureau of Labor Statistics, correlation coefficient, p-value, skilled trade workforce, macho persona, Midwest labor demographics

*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 films in Sylvester Stallone's filmography
Detailed data title: Number of films in Sylvester Stallone's filmography
Source: Wikipedia
See what else correlates with The number of films in Sylvester Stallone's filmography

The number of millwrights in North Dakota
Detailed data title: BLS estimate of millwrights in North Dakota
Source: Bureau of Larbor Statistics
See what else correlates with The number of millwrights in North Dakota

Correlation r = 0.7872582 (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 = 0.6197754 (Coefficient of determination)
This means 62% of the change in the one variable (i.e., The number of millwrights in North Dakota) is predictable based on the change in the other (i.e., The number of films in Sylvester Stallone's filmography) over the 19 years from 2003 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 6.3E-5. 0.0000633032927637311200000000
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 0.79 in 0.0063% of random cases. Said differently, if you correlated 15,797 random variables Which I absolutely did.
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.

[ 0.52, 0.91 ] 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.
2003200420052006200720082009201020112012201320142015201620172018201920202021
The number of films in Sylvester Stallone's filmography (Films)3001011112321123502
The number of millwrights in North Dakota (Millwrights)3101308010090130130130150260260250170150290370260160170




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([3,0,0,1,0,1,1,1,1,2,3,2,1,1,2,3,5,0,2,])
array_2 = np.array([310,130,80,100,90,130,130,130,150,260,260,250,170,150,290,370,260,160,170,])
array_1_name = "The number of films in Sylvester Stallone's filmography"
array_2_name = "The number of millwrights in North Dakota"

# 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 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: 1508 · Black Variable ID: 508 · Red Variable ID: 12707
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