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Spurious correlation #5,869 · 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 movies Ewan McGregor appeared in and the second variable is The number of ophthalmic medical technicians in Connecticut.  The chart goes from 2012 to 2022, and the two variables track closely in value over that time. Small Image

AI explanation

As Ewan McGregor's filmography expanded, so did the public's eye-opening admiration for him, leading to a surge in people wanting to have their eyes checked in Connecticut. It seems his captivating performances weren't just a figment of our imagination, but a real vision for the future of ophthalmic medical technicians in the state!

Model: dalle-3
Prompt: Prompt: Generate an image that captures the bustling city square in Connecticut, with a giant movie screen showing Ewan McGregor's films, and a line of ophthalmic medical technicians setting up eye-check stations amidst the gathering crowd. The scene should convey the excitement of the event and the convergence of Ewan McGregor's cinematic magic with the demand for eye care services in the state. 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 movies Ewan McGregor appeared in and The number of ophthalmic medical technicians in Connecticut. 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: Art nouveau inspired by bauhaus A Discovery magazine cover image Oragami Cutsy graphics
ChatGPT: A Discovery magazine cover image

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 movies Ewan McGregor appeared in and The number of ophthalmic medical technicians in Connecticut, in the following situation: As Ewan McGregor's filmography expanded, so did the public's eye-opening admiration for him, leading to a surge in people wanting to have their eyes checked in Connecticut. It seems his captivating performances weren't just a figment of our imagination, but a real vision for the future of ophthalmic medical technicians in the state!. Keep the description simple.
ChatGPT: In a bustling city in Connecticut, a giant movie screen is erected in the town square, showcasing a collection of Ewan McGregor's films. As people gather to watch, a line of ophthalmic medical technicians sets up eye-check stations, ready to attend to the growing crowd. The buzz of excitement fills the air as Ewan McGregor's cinematic magic coincides with the increasing demand for eye care services in 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 Discovery magazine cover image ] and depicting this scene: In a bustling city in Connecticut, a giant movie screen is erected in the town square, showcasing a collection of Ewan McGregor's films. As people gather to watch, a line of ophthalmic medical technicians sets up eye-check stations, ready to attend to the growing crowd. The buzz of excitement fills the air as Ewan McGregor's cinematic magic coincides with the increasing demand for eye care services in the state. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image that captures the bustling city square in Connecticut, with a giant movie screen showing Ewan McGregor's films, and a line of ophthalmic medical technicians setting up eye-check stations amidst the gathering crowd. The scene should convey the excitement of the event and the convergence of Ewan McGregor's cinematic magic with the demand for eye care services in the state.

*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 movies Ewan McGregor appeared in positively influenced The number of ophthalmic medical technicians in Connecticut.

AI academic paper

(Because p < 0.01)
The Eye-scape of Cinema: A Correlational Study of Ewan McGregor's Filmography and Ophthalmic Medical Technicians in Connecticut

The Journal of Irreverent Ophthalmological Studies

Jan 2024
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 movies Ewan McGregor appeared in and The number of ophthalmic medical technicians in Connecticut. 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 The Movie DB and Bureau of Larbor Statistics to assess this nagging question. You found a correlation coefficient of 0.8726826 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]]
The Eye-scape of Cinema: A Correlational Study of Ewan McGregor's Filmography and Ophthalmic Medical Technicians in Connecticut

[[ABSTRACT]]
This enthralling research paper delves into the unexpected relationship between the cinematic endeavors of Ewan McGregor and the occupational presence of ophthalmic medical technicians in the picturesque state of Connecticut. Leveraging data sources from The Movie DB and the esteemed Bureau of Labor Statistics, our research team meticulously examined the period from 2012 to 2022, yielding a striking correlation coefficient of 0.8726826 and a fervently significant p-value of less than 0.01. Our findings not only illuminate the intertwining paths of McGregor's screen appearances and the number of ophthalmic medical technicians, but also offer a glimpse into the enigmatic interplay between the world of cinema and the realm of ocular care. Amidst the metrics and calculations, this study unveils a peculiar dynamic that is both captivating and, dare we say, eye-opening.


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 movies Ewan McGregor appeared in and The number of ophthalmic medical technicians in Connecticut. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Here is the title and abstract of the paper:
[[TITLE]]
The Eye-scape of Cinema: A Correlational Study of Ewan McGregor's Filmography and Ophthalmic Medical Technicians in Connecticut

[[ABSTRACT]]
This enthralling research paper delves into the unexpected relationship between the cinematic endeavors of Ewan McGregor and the occupational presence of ophthalmic medical technicians in the picturesque state of Connecticut. Leveraging data sources from The Movie DB and the esteemed Bureau of Labor Statistics, our research team meticulously examined the period from 2012 to 2022, yielding a striking correlation coefficient of 0.8726826 and a fervently significant p-value of less than 0.01. Our findings not only illuminate the intertwining paths of McGregor's screen appearances and the number of ophthalmic medical technicians, but also offer a glimpse into the enigmatic interplay between the world of cinema and the realm of ocular care. Amidst the metrics and calculations, this study unveils a peculiar dynamic that is both captivating and, dare we say, eye-opening.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

In the labyrinth of statistical analysis, it is a rare delight to stumble upon a correlation that seems to defy the bounds of conventional reasoning. The adage "seeing is believing" takes on a whimsical twist as we embark on a journey through the celluloid universe of Ewan McGregor and the professional landscape of ophthalmic medical technicians in the idyllic state of Connecticut.

The intersection of the silver screen and the meticulous world of ocular care may at first appear as distant as the depths of space explored by McGregor's character in "The Phantom Menace." However, as astute researchers, we have harnessed the power of quantitative analysis to unearth a connection that is as mystifying as the bends and twists of a Christopher Nolan plotline.

While the mundanity of daily life would have us believe that McGregor's roles in "Moulin Rouge!" and "Trainspotting" are galaxies away from the meticulous work of ophthalmic medical technicians, our investigation has unearthed a correlation that demands more than just a cursory glance. The allure of the silver screen and the intricacies of ocular care seem to be entwined in a dance of statistical significance, harmonizing in a manner that would make even the most avant-garde filmmaker green with envy.

In the following sections, we will navigate through the intricacies of our data collection, statistical methods, and the revelatory findings that have left our research team both astounded and amused. As we delve into the heart of this enigmatic correlation, prepare yourselves for a journey that promises not only empirical rigor, but also a dash of the unexpected—much like stumbling upon a unicorn in a field of standard deviations.


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 movies Ewan McGregor appeared in and The number of ophthalmic medical technicians in Connecticut. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
The Eye-scape of Cinema: A Correlational Study of Ewan McGregor's Filmography and Ophthalmic Medical Technicians in Connecticut

[[ABSTRACT]]
This enthralling research paper delves into the unexpected relationship between the cinematic endeavors of Ewan McGregor and the occupational presence of ophthalmic medical technicians in the picturesque state of Connecticut. Leveraging data sources from The Movie DB and the esteemed Bureau of Labor Statistics, our research team meticulously examined the period from 2012 to 2022, yielding a striking correlation coefficient of 0.8726826 and a fervently significant p-value of less than 0.01. Our findings not only illuminate the intertwining paths of McGregor's screen appearances and the number of ophthalmic medical technicians, but also offer a glimpse into the enigmatic interplay between the world of cinema and the realm of ocular care. Amidst the metrics and calculations, this study unveils a peculiar dynamic that is both captivating and, dare we say, eye-opening.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the labyrinth of statistical analysis, it is a rare delight to stumble upon a correlation that seems to defy the bounds of conventional reasoning. The adage "seeing is believing" takes on a whimsical twist as we embark on a journey through the celluloid universe of Ewan McGregor and the professional landscape of ophthalmic medical technicians in the idyllic state of Connecticut.
The intersection of the silver screen and the meticulous world of ocular care may at first appear as distant as the depths of space explored by McGregor's character in "The Phantom Menace." However, as astute researchers, we have harnessed the power of quantitative analysis to unearth a connection that is as mystifying as the bends and twists of a Christopher Nolan plotline.
While the mundanity of daily life would have us believe that McGregor's roles in "Moulin Rouge!" and "Trainspotting" are galaxies away from the meticulous work of ophthalmic medical technicians, our investigation has unearthed a correlation that demands more than just a cursory glance. The allure of the silver screen and the intricacies of ocular care seem to be entwined in a dance of statistical significance, harmonizing in a manner that would make even the most avant-garde filmmaker green with envy.
In the following sections, we will navigate through the intricacies of our data collection, statistical methods, and the revelatory findings that have left our research team both astounded and amused. As we delve into the heart of this enigmatic correlation, prepare yourselves for a journey that promises not only empirical rigor, but also a dash of the unexpected—much like stumbling upon a unicorn in a field of standard deviations.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The enigmatic relationship between the cinematic exploits of Ewan McGregor and the occupational presence of ophthalmic medical technicians in Connecticut has gripped the imagination of researchers and cinephiles alike. As we embark on this scholarly voyage, it is imperative to acknowledge the existing literature that has set the stage for unraveling this peculiar connection.

Smith et al. (2015) laid a formidable foundation by examining the societal impact of leading actors on the workforce demographics of various states. While their focus was not specifically on ophthalmic medical technicians or the thespian virtuosity of Mr. McGregor, their work provided crucial insight into the subtle ripples that actors can create in the labor pool. However, as captivating as Smith et al.'s work may be, it does not delve into the nuanced interplay of ocular care and McGregor's on-screen endeavors.

In a similar vein, Doe (2018) explored the econometric entanglement of Hollywood stardom and its repercussions on specialized medical professions. While their analysis touched on optometry as a whole, the intricate dynamics underlying ophthalmic medical technicians were left unexplored. It is within this lacuna of research that our current investigation shines a probing light, weaving together the tapestry of McGregor's filmography with the occupational fabric of Connecticut's ocular health sector.

As our foray transitions from the sobering depths of empirical inquiry to the whimsical meanderings of literature and popular culture, it is imperative to note the indirect influences that may permeate the interplay between film and eye care. The works of Gladwell (2000) and Pink (2009) offer insights into the cognitive impact of visual stimuli and storytelling, hinting at the potential sway that cinematic experiences may exert on the public's perception of ocular health and its allied professions. The allure of McGregor's performances, akin to the captivating narratives found in bestselling fiction such as "The Great Gatsby" and "Eyes of a Stranger," may further bolster this subtle influence on societal attitudes toward ocular care.

Folkloric as it may seem, the advent of internet memes has also left its digital footprint in this discourse. The "McGregor Blinking in Confusion" meme, a popular online jest derived from the actor's bewilderment in a particular interview, resonates with the very essence of our inquiry. In its own lighthearted manner, this meme underscores the unexpected—much like the correlation we are probing—that is often embedded in our daily encounters, both on and off the silver screen.

As we navigate the intricate terrain of literature and culture, it becomes evident that the interweaving of McGregor's filmic presence and the professional landscape of ophthalmic medical technicians in Connecticut transcends the realm of sheer statistical analysis. This fusion of entertainment and ocular care paints a canvas that is not only statistically compelling, but eternally infused with the whimsy of the cinematic 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 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 movies Ewan McGregor appeared in and The number of ophthalmic medical technicians in Connecticut. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from The Movie DB 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]]
The Eye-scape of Cinema: A Correlational Study of Ewan McGregor's Filmography and Ophthalmic Medical Technicians in Connecticut

[[ABSTRACT]]
This enthralling research paper delves into the unexpected relationship between the cinematic endeavors of Ewan McGregor and the occupational presence of ophthalmic medical technicians in the picturesque state of Connecticut. Leveraging data sources from The Movie DB and the esteemed Bureau of Labor Statistics, our research team meticulously examined the period from 2012 to 2022, yielding a striking correlation coefficient of 0.8726826 and a fervently significant p-value of less than 0.01. Our findings not only illuminate the intertwining paths of McGregor's screen appearances and the number of ophthalmic medical technicians, but also offer a glimpse into the enigmatic interplay between the world of cinema and the realm of ocular care. Amidst the metrics and calculations, this study unveils a peculiar dynamic that is both captivating and, dare we say, eye-opening.

[[INTRODUCTION]]
In the labyrinth of statistical analysis, it is a rare delight to stumble upon a correlation that seems to defy the bounds of conventional reasoning. The adage "seeing is believing" takes on a whimsical twist as we embark on a journey through the celluloid universe of Ewan McGregor and the professional landscape of ophthalmic medical technicians in the idyllic state of Connecticut.
The intersection of the silver screen and the meticulous world of ocular care may at first appear as distant as the depths of space explored by McGregor's character in "The Phantom Menace." However, as astute researchers, we have harnessed the power of quantitative analysis to unearth a connection that is as mystifying as the bends and twists of a Christopher Nolan plotline.
While the mundanity of daily life would have us believe that McGregor's roles in "Moulin Rouge!" and "Trainspotting" are galaxies away from the meticulous work of ophthalmic medical technicians, our investigation has unearthed a correlation that demands more than just a cursory glance. The allure of the silver screen and the intricacies of ocular care seem to be entwined in a dance of statistical significance, harmonizing in a manner that would make even the most avant-garde filmmaker green with envy.
In the following sections, we will navigate through the intricacies of our data collection, statistical methods, and the revelatory findings that have left our research team both astounded and amused. As we delve into the heart of this enigmatic correlation, prepare yourselves for a journey that promises not only empirical rigor, but also a dash of the unexpected—much like stumbling upon a unicorn in a field of standard deviations.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

Data Collection:

The painstaking process of data collection commenced with a thorough scouring of The Movie DB, a virtual cornucopia of cinematic information, to ascertain the number of movies graced by the esteemed presence of Ewan McGregor. Our diligent data extraction extended from the hallowed year of 2012 to the intriguing year of 2022, encompassing the entirety of McGregor's cinematic exploits during this temporal span. This involved delving into the minutiae of his filmography, from the blockbuster epics to the obscure indie gems that glittered amidst the cinematic firmament.

Simultaneously, our gallant research team ventured into the digital realms of the Bureau of Labor Statistics, drawing forth the esoteric figures pertaining to the ophthalmic medical technicians populating the verdant expanse of Connecticut. The occupational data, spanning the same temporal epochs as McGregor's cinematic odyssey, unveiled the nuanced ebb and flow of the ophthalmic workforce within the resilient confines of the Constitution State.

Data Analysis:

With the nuggets of data gathered from their cybernautical expeditions, our intrepid researchers embarked on a tumultuous odyssey through the gales of statistical analysis. Embracing the stalwart methods of correlation analysis, we unveiled the remarkable interplay between McGregor's on-screen escapades and the occupational tapestry of ophthalmic medical technicians in Connecticut.

Statistical Methods:

The humble Pearson correlation coefficient emerged as our stalwart companion in this tumultuous journey of statistical exploration, revealing a commendable correlation coefficient of 0.8726826. This beguiling metric served as a harbinger of the entwined destinies of McGregor's celluloid voyage and the professional endeavors of ophthalmic medical technicians in Connecticut.

In addition, the application of regression analysis allowed for a nuanced dissection of the causal relationship between the number of movies featuring McGregor and the count of ophthalmic medical technicians within the picturesque confines of Connecticut. The results of this regression analysis yielded coefficients that shimmered with the effervescence of statistical relevance, solidifying the enchanting connection that had eluded the gaze of the empirical tradition for eons.

Conclusion:

In this methodological expedition through the labyrinthine landscapes of correlation analysis and regression modeling, our intrepid research team ventured beyond the conventional bounds of statistical inquiry to unravel the enigmatic relationship between McGregor's cinematic exploits and the occupational presence of ophthalmic medical technicians in Connecticut. The statistical methods employed served as the compass that guided us through this enthralling exploration, leaving us not only enraptured by the empirical finesse but also imbued with a newfound appreciation for the unexpected symphonies that resonate within the confluence of cinema and healthcare.


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 movies Ewan McGregor appeared in and The number of ophthalmic medical technicians in Connecticut. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

For the time period 2012 to 2022, you found a correlation 0.8726826, r-squared of 0.7615749, 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]]
The Eye-scape of Cinema: A Correlational Study of Ewan McGregor's Filmography and Ophthalmic Medical Technicians in Connecticut

[[ABSTRACT]]
This enthralling research paper delves into the unexpected relationship between the cinematic endeavors of Ewan McGregor and the occupational presence of ophthalmic medical technicians in the picturesque state of Connecticut. Leveraging data sources from The Movie DB and the esteemed Bureau of Labor Statistics, our research team meticulously examined the period from 2012 to 2022, yielding a striking correlation coefficient of 0.8726826 and a fervently significant p-value of less than 0.01. Our findings not only illuminate the intertwining paths of McGregor's screen appearances and the number of ophthalmic medical technicians, but also offer a glimpse into the enigmatic interplay between the world of cinema and the realm of ocular care. Amidst the metrics and calculations, this study unveils a peculiar dynamic that is both captivating and, dare we say, eye-opening.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
In the labyrinth of statistical analysis, it is a rare delight to stumble upon a correlation that seems to defy the bounds of conventional reasoning. The adage "seeing is believing" takes on a whimsical twist as we embark on a journey through the celluloid universe of Ewan McGregor and the professional landscape of ophthalmic medical technicians in the idyllic state of Connecticut.
The intersection of the silver screen and the meticulous world of ocular care may at first appear as distant as the depths of space explored by McGregor's character in "The Phantom Menace." However, as astute researchers, we have harnessed the power of quantitative analysis to unearth a connection that is as mystifying as the bends and twists of a Christopher Nolan plotline.
While the mundanity of daily life would have us believe that McGregor's roles in "Moulin Rouge!" and "Trainspotting" are galaxies away from the meticulous work of ophthalmic medical technicians, our investigation has unearthed a correlation that demands more than just a cursory glance. The allure of the silver screen and the intricacies of ocular care seem to be entwined in a dance of statistical significance, harmonizing in a manner that would make even the most avant-garde filmmaker green with envy.
In the following sections, we will navigate through the intricacies of our data collection, statistical methods, and the revelatory findings that have left our research team both astounded and amused. As we delve into the heart of this enigmatic correlation, prepare yourselves for a journey that promises not only empirical rigor, but also a dash of the unexpected—much like stumbling upon a unicorn in a field of standard deviations.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The results of our investigation into the relationship between the number of movies featuring the charismatic Ewan McGregor and the count of ophthalmic medical technicians in the bucolic landscape of Connecticut are as intriguing as they are illuminating. The correlation coefficient of 0.8726826 underscores a strong positive relationship between these seemingly disparate variables. This statistical camaraderie is further validated by an r-squared value of 0.7615749, emphasizing the robustness of the association. Notably, the p-value of less than 0.01 showcases the resounding significance of our findings, reaffirming the magnetic interplay between McGregor's cinematic presence and the professional cadre of ophthalmic medical technicians.

Our sole figure (Fig. 1) offers a visual encapsulation of this compelling correlation. In this scatterplot, the upward trajectory of Ewan McGregor's filmography aligns harmoniously with the ascent in the number of ophthalmic medical technicians in Connecticut, akin to a well-choreographed dance sequence in one of McGregor's cinematic ventures. The enchanting synergy between these two domains is palpable, resonating with a resonance that is as captivating as McGregor's celebrated performances on the silver screen.

In summary, our results not only substantiate the unexpected bond between McGregor's cinematic endeavors and the occupational landscape of ophthalmic medical technicians in Connecticut but also spark further contemplation on the nuanced interplay between the world of cinema and the sphere of ocular care. This fortuitous union of realms has left our research team in rapt awe, attesting to the serendipitous discoveries that await amidst the tapestry of statistical analysis.


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 movies Ewan McGregor appeared in and The number of ophthalmic medical technicians in Connecticut. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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]]
The Eye-scape of Cinema: A Correlational Study of Ewan McGregor's Filmography and Ophthalmic Medical Technicians in Connecticut

[[ABSTRACT]]
This enthralling research paper delves into the unexpected relationship between the cinematic endeavors of Ewan McGregor and the occupational presence of ophthalmic medical technicians in the picturesque state of Connecticut. Leveraging data sources from The Movie DB and the esteemed Bureau of Labor Statistics, our research team meticulously examined the period from 2012 to 2022, yielding a striking correlation coefficient of 0.8726826 and a fervently significant p-value of less than 0.01. Our findings not only illuminate the intertwining paths of McGregor's screen appearances and the number of ophthalmic medical technicians, but also offer a glimpse into the enigmatic interplay between the world of cinema and the realm of ocular care. Amidst the metrics and calculations, this study unveils a peculiar dynamic that is both captivating and, dare we say, eye-opening.

[[LITERATURE REVIEW]]
The enigmatic relationship between the cinematic exploits of Ewan McGregor and the occupational presence of ophthalmic medical technicians in Connecticut has gripped the imagination of researchers and cinephiles alike. As we embark on this scholarly voyage, it is imperative to acknowledge the existing literature that has set the stage for unraveling this peculiar connection.
Smith et al. (2015) laid a formidable foundation by examining the societal impact of leading actors on the workforce demographics of various states. While their focus was not specifically on ophthalmic medical technicians or the thespian virtuosity of Mr. McGregor, their work provided crucial insight into the subtle ripples that actors can create in the labor pool. However, as captivating as Smith et al.'s work may be, it does not delve into the nuanced interplay of ocular care and McGregor's on-screen endeavors.
In a similar vein, Doe (2018) explored the econometric entanglement of Hollywood stardom and its repercussions on specialized medical professions. While their analysis touched on optometry as a whole, the intricate dynamics underlying ophthalmic medical technicians were left unexplored. It is within this lacuna of research that our current investigation shines a probing light, weaving together the tapestry of McGregor's filmography with the occupational fabric of Connecticut's ocular health sector.
As our foray transitions from the sobering depths of empirical inquiry to the whimsical meanderings of literature and popular culture, it is imperative to note the indirect influences that may permeate the interplay between film and eye care. The works of Gladwell (2000) and Pink (2009) offer insights into the cognitive impact of visual stimuli and storytelling, hinting at the potential sway that cinematic experiences may exert on the public's perception of ocular health and its allied professions. The allure of McGregor's performances, akin to the captivating narratives found in bestselling fiction such as "The Great Gatsby" and "Eyes of a Stranger," may further bolster this subtle influence on societal attitudes toward ocular care.
Folkloric as it may seem, the advent of internet memes has also left its digital footprint in this discourse. The "McGregor Blinking in Confusion" meme, a popular online jest derived from the actor's bewilderment in a particular interview, resonates with the very essence of our inquiry. In its own lighthearted manner, this meme underscores the unexpected—much like the correlation we are probing—that is often embedded in our daily encounters, both on and off the silver screen.
As we navigate the intricate terrain of literature and culture, it becomes evident that the interweaving of McGregor's filmic presence and the professional landscape of ophthalmic medical technicians in Connecticut transcends the realm of sheer statistical analysis. This fusion of entertainment and ocular care paints a canvas that is not only statistically compelling, but eternally infused with the whimsy of the cinematic world.

[[RESULTS]]
The results of our investigation into the relationship between the number of movies featuring the charismatic Ewan McGregor and the count of ophthalmic medical technicians in the bucolic landscape of Connecticut are as intriguing as they are illuminating. The correlation coefficient of 0.8726826 underscores a strong positive relationship between these seemingly disparate variables. This statistical camaraderie is further validated by an r-squared value of 0.7615749, emphasizing the robustness of the association. Notably, the p-value of less than 0.01 showcases the resounding significance of our findings, reaffirming the magnetic interplay between McGregor's cinematic presence and the professional cadre of ophthalmic medical technicians.
Our sole figure (Fig. 1) offers a visual encapsulation of this compelling correlation. In this scatterplot, the upward trajectory of Ewan McGregor's filmography aligns harmoniously with the ascent in the number of ophthalmic medical technicians in Connecticut, akin to a well-choreographed dance sequence in one of McGregor's cinematic ventures. The enchanting synergy between these two domains is palpable, resonating with a resonance that is as captivating as McGregor's celebrated performances on the silver screen.
In summary, our results not only substantiate the unexpected bond between McGregor's cinematic endeavors and the occupational landscape of ophthalmic medical technicians in Connecticut but also spark further contemplation on the nuanced interplay between the world of cinema and the sphere of ocular care. This fortuitous union of realms has left our research team in rapt awe, attesting to the serendipitous discoveries that await amidst the tapestry of statistical analysis.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The enthralling nexus between the cinematic exploits of Ewan McGregor and the occupational domain of ophthalmic medical technicians in Connecticut has left our scholarly inclinations both intrigued and delighted. Our findings not only align with the existing literature, but also add a touch of whimsy to the often solemn world of statistical analysis.

The robust correlation coefficient of 0.8726826, combined with the decidedly significant p-value of less than 0.01, lends irrefutable support to the notion that McGregor's on-screen presence mirrors the proliferation of ophthalmic medical technicians in the picturesque state of Connecticut. This, in turn, harkens back to the captivating insights of Smith et al. (2015), who laid the groundwork for understanding the profound societal impact that leading actors can exert on workforce demographics. While they did not specifically delve into the mesmerizing gaze of McGregor or the meticulous precision of ophthalmic medical technicians, our findings validate the subtle, yet profound, ripple effects that thespian virtuosity can create in the labor pool, almost as if McGregor's cinematic charisma casts a mesmerizing spell on the burgeoning cadre of ocular care professionals.

Moreover, our exploration falls in line with the econometric entanglement of Hollywood stardom and specialized medical professions as expounded by Doe (2018). By shedding light on the enchanting metrics of McGregor's filmography and the occupational landscape of ophthalmic medical technicians, our study not only bridges the lacuna in prior research but also uncovers a nuanced interplay that captures the imagination and, dare we say, the inner eye.

Amidst the empirical tapestry, it is vital to recall the indirect influences that permeate the relationship between film and ocular care. The cognitive impact of visual stimuli and storytelling, emphasized by Gladwell (2000) and Pink (2009), mirrors the captivating narratives woven by McGregor's screen performances. These narratives, akin to a well-directed movie, may influence the public's perception of ocular health and its allied professions, adding layers of intrigue to our statistical odyssey.

The seemingly incongruous link between McGregor's cinematic escapades and the professional terrain of ophthalmic medical technicians in Connecticut echoes the unexpected, much like the "McGregor Blinking in Confusion" meme, a lighthearted testament to the serendipitous discoveries that often await in the enigmatic entanglement of statistics, cinema, and ocular care.

In conclusion, our study not only substantiates the mesmerizing connection between McGregor's cinematic embellishments and the cadre of ophthalmic medical technicians in Connecticut, but also infuses our academic scholasticism with a touch of humor and whimsy, reminding us of the delightful discoveries that often surface in unexpected correlations. This confluence of realms underpins the adage that, much like McGregor's bewitching performances, statistical analysis too can be an exquisite dance of discovery and delight.


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 movies Ewan McGregor appeared in and The number of ophthalmic medical technicians in Connecticut. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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]]
The Eye-scape of Cinema: A Correlational Study of Ewan McGregor's Filmography and Ophthalmic Medical Technicians in Connecticut

[[ABSTRACT]]
This enthralling research paper delves into the unexpected relationship between the cinematic endeavors of Ewan McGregor and the occupational presence of ophthalmic medical technicians in the picturesque state of Connecticut. Leveraging data sources from The Movie DB and the esteemed Bureau of Labor Statistics, our research team meticulously examined the period from 2012 to 2022, yielding a striking correlation coefficient of 0.8726826 and a fervently significant p-value of less than 0.01. Our findings not only illuminate the intertwining paths of McGregor's screen appearances and the number of ophthalmic medical technicians, but also offer a glimpse into the enigmatic interplay between the world of cinema and the realm of ocular care. Amidst the metrics and calculations, this study unveils a peculiar dynamic that is both captivating and, dare we say, eye-opening.

[[INTRDUCTION]]
In the labyrinth of statistical analysis, it is a rare delight to stumble upon a correlation that seems to defy the bounds of conventional reasoning. The adage "seeing is believing" takes on a whimsical twist as we embark on a journey through the celluloid universe of Ewan McGregor and the professional landscape of ophthalmic medical technicians in the idyllic state of Connecticut.
The intersection of the silver screen and the meticulous world of ocular care may at first appear as distant as the depths of space explored by McGregor's character in "The Phantom Menace." However, as astute researchers, we have harnessed the power of quantitative analysis to unearth a connection that is as mystifying as the bends and twists of a Christopher Nolan plotline.
While the mundanity of daily life would have us believe that McGregor's roles in "Moulin Rouge!" and "Trainspotting" are galaxies away from the meticulous work of ophthalmic medical technicians, our investigation has unearthed a correlation that demands more than just a cursory glance. The allure of the silver screen and the intricacies of ocular care seem to be entwined in a dance of statistical significance, harmonizing in a manner that would make even the most avant-garde filmmaker green with envy.
In the following sections, we will navigate through the intricacies of our data collection, statistical methods, and the revelatory findings that have left our research team both astounded and amused. As we delve into the heart of this enigmatic correlation, prepare yourselves for a journey that promises not only empirical rigor, but also a dash of the unexpected—much like stumbling upon a unicorn in a field of standard deviations.

[[RESULTS]]
The results of our investigation into the relationship between the number of movies featuring the charismatic Ewan McGregor and the count of ophthalmic medical technicians in the bucolic landscape of Connecticut are as intriguing as they are illuminating. The correlation coefficient of 0.8726826 underscores a strong positive relationship between these seemingly disparate variables. This statistical camaraderie is further validated by an r-squared value of 0.7615749, emphasizing the robustness of the association. Notably, the p-value of less than 0.01 showcases the resounding significance of our findings, reaffirming the magnetic interplay between McGregor's cinematic presence and the professional cadre of ophthalmic medical technicians.
Our sole figure (Fig. 1) offers a visual encapsulation of this compelling correlation. In this scatterplot, the upward trajectory of Ewan McGregor's filmography aligns harmoniously with the ascent in the number of ophthalmic medical technicians in Connecticut, akin to a well-choreographed dance sequence in one of McGregor's cinematic ventures. The enchanting synergy between these two domains is palpable, resonating with a resonance that is as captivating as McGregor's celebrated performances on the silver screen.
In summary, our results not only substantiate the unexpected bond between McGregor's cinematic endeavors and the occupational landscape of ophthalmic medical technicians in Connecticut but also spark further contemplation on the nuanced interplay between the world of cinema and the sphere of ocular care. This fortuitous union of realms has left our research team in rapt awe, attesting to the serendipitous discoveries that await amidst the tapestry of statistical analysis.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

As we draw the curtains on this enthralling exploration, we find ourselves in the midst of a narrative that, much like a classic McGregor plot twist, leaves us marveling at the unexpected connections that statistical analysis can unveil. The robust correlation between the number of movies featuring Ewan McGregor and the count of ophthalmic medical technicians in Connecticut signifies a fusion of two seemingly distant domains with a fervor that would be worthy of McGregor's on-screen passion.

The significance of our findings, as highlighted by the resounding p-value, cannot be overlooked, much like McGregor's striking presence in his cinematic endeavors. This correlation opens our eyes to the captivating interplay between the world of cinema and the realm of ocular care, offering a glimpse into a parallel universe where the enigmatic allure of McGregor's performances seems to resonate harmoniously with the meticulous dedication of ophthalmic medical technicians.

While one might be tempted to dismiss this correlation as a mere coincidence, our rigorous statistical analysis insists otherwise, showcasing a synchronicity that is as captivating as McGregor's command of the screen. The ripple effect of these findings cannot be underestimated, prompting contemplation on the intricate forces that weave together the fabric of our societal tapestry, much like a captivating McGregor monologue that leaves audiences pondering long after the credits roll.

In conclusion, the interwoven paths of McGregor's cinematic presence and the occupational landscape of ophthalmic medical technicians in Connecticut stand as a testament to the multifaceted nature of statistical analysis, where unexpected correlations lie waiting to be discovered, much like a hidden Easter egg in a blockbuster film. As we bid adieu to this illuminating journey, we assert with confidence that no further scrutiny is needed in this serendipitously delightful domain.


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 The Eye-scape of Cinema: A Correlational Study of Ewan McGregor's Filmography and Ophthalmic Medical Technicians in Connecticut. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Irreverent Ophthalmological Studies


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 The Eye-scape of Cinema: A Correlational Study of Ewan McGregor's Filmography and Ophthalmic Medical Technicians in Connecticut. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Cinematic Ophthalmology Studies (ICOS)


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 The Eye-scape of Cinema: A Correlational Study of Ewan McGregor's Filmography and Ophthalmic Medical Technicians in Connecticut with an abstract of This enthralling research paper delves into the unexpected relationship between the cinematic endeavors of Ewan McGregor and the occupational presence of ophthalmic medical technicians in the picturesque state of Connecticut. Leveraging data sources from The Movie DB and the esteemed Bureau of Labor Statistics, our research team meticulously examined the period from 2012 to 2022, yielding a striking correlation coefficient of 0.8726826 and a fervently significant p-value of less than 0.01. Our findings not only illuminate the intertwining paths of McGregor's screen appearances and the number of ophthalmic medical technicians, but also offer a glimpse into the enigmatic interplay between the world of cinema and the realm of ocular care. Amidst the metrics and calculations, this study unveils a peculiar dynamic that is both captivating and, dare we say, eye-opening.

ChatGPT:

Ewan McGregor filmography, ophthalmic medical technicians, Connecticut, cinematic endeavors, correlation study, The Movie DB, Bureau of Labor Statistics, correlation coefficient, p-value, ocular care, cinema, eye care, screen appearances, occupational presence, data sources, correlation analysis

*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 movies Ewan McGregor appeared in
Source: The Movie DB
Additional Info: Young Adam (2003); Big Fish (2003); Trainspotting (1996); Velvet Goldmine (1998); Nightwatch (1997); Faster (2003); Rogue Trader (1999); The Ghost Writer (2010); Stay (2005); A Life Less Ordinary (1997); Robots (2005); Nora (2000); Valiant (2005); Incendiary (2008); Humpback Whales (2015); The Doctor, The Tornado & The Kentucky Kid (2006); The Battle of Britain (2010); The Serpent's Kiss (1997); Eye of the Beholder (1999); Salmon Fishing in the Yemen (2012); Perfect Sense (2011); Beginners (2011); Jackboots on Whitehall (2010); Solid Geometry (2002); T2 Trainspotting (2017); Desserts (1999); Our Kind of Traitor (2016); Son of a Gun (2014); Killing Priscilla (2000); Last Days in the Desert (2016); American Pastoral (2016); The Bug: Life and Times of the People's Car (2016); Now You See It (2017); Red Point (2017); The Island (2005); Family Style (1993); Anno Domini (2000); Charge (2011); Christopher Robin (2018); Faster & Faster (2004); RAF at 100 with Ewan and Colin McGregor (2018); Doctor Sleep (2019); Teenage Wildlife (2011); Fastest (2011); Wild Shetland: Scotland's Viking Frontier (2019); Wild Ways of the Vikings (2019); Raymond & Ray (2022); Ice Bear (2014); Obi-Wan Kenobi: A Jedi's Return (2022); Moulin Rouge! (2001); Star Wars: Episode I - The Phantom Menace (1999); Star Wars: Episode II - Attack of the Clones (2002); Star Wars: Episode III - Revenge of the Sith (2005); The Men Who Stare at Goats (2009); Down with Love (2003); Cassandra's Dream (2007); I Love You Phillip Morris (2010); Deception (2008); Miss Potter (2006); The Impossible (2012); Miles Ahead (2016); Bomber Boys (2012); Zoe (2018); Angels & Demons (2009); Legacy: A Personal History of Barry Sheene (2007); Birds of Prey (and the Fantabulous Emancipation of One Harley Quinn) (2020); The Birthday Cake (2021); Guillermo del Toro's Pinocchio (2022); A Movie Is Made For Pooh (2018); Speed is Expensive: The Philip Vincent Story (2022); Mother, Couch (2023); Trips Money Can't Buy with Ewan McGregor (2001); Troy's Story (2005); CLONE WARS: BATTLE OF THE HEROES - A Star Wars Fan Animation (2023); Black Hawk Down (2001); Little Voice (1998); Brassed Off (1996); Shallow Grave (1994); Stormbreaker (2006); Jack the Giant Slayer (2013); Haywire (2011); Jane Got a Gun (2015); Mortdecai (2015); The Night Club of Your Dreams: The Making of 'Moulin Rouge' (2001); Emma (1996); Amelia (2009); Blue Juice (1995); Spooks & Creeps (2004); Star Wars: Within a Minute - The Making of Episode III (2005); The Beginning: Making 'Episode I' (2001); Doggin' Around (1994); Gina Carano in Training (2012); Guillermo del Toro's Pinocchio: Handcarved Cinema (2022); The Pillow Book (1995); August: Osage County (2013); WAMEGO: Addendum (2020); Nicole Kidman, eyes wide open (2023); Scenes of a Sexual Nature (2006); Nanny McPhee and the Big Bang (2010); 50 Films to See Before You Die (2006); Beauty and the Beast (2017); From Puppets to Pixels: Digital Characters in 'Episode II' (2002); Gimme Danger (2016); Being Human (1994); R2-D2: Beneath the Dome (2001); The Story of Star Wars (2004); A Million Ways to Die in the West (2014); Muse of Fire (2013); Welcome to Hollywood (1998); Final Cut: Ladies and Gentlemen (2012); And the Winner Isn't (2017); Star Wars: The Force Awakens (2015); Live 8 (2005); Star Wars: The Rise of Skywalker (2019)

See what else correlates with The number of movies Ewan McGregor appeared in

The number of ophthalmic medical technicians in Connecticut
Detailed data title: BLS estimate of ophthalmic medical technicians in Connecticut
Source: Bureau of Larbor Statistics
See what else correlates with The number of ophthalmic medical technicians in Connecticut

Correlation r = 0.8726826 (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 = 0.7615749 (Coefficient of determination)
This means 76.2% of the change in the one variable (i.e., The number of ophthalmic medical technicians in Connecticut) is predictable based on the change in the other (i.e., The number of movies Ewan McGregor appeared in) over the 11 years from 2012 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00046. 0.0004553028854706918700000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.87 in 0.046% of random cases. Said differently, if you correlated 2,196 random variables Which I absolutely did.
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.

[ 0.57, 0.97 ] 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
The number of movies Ewan McGregor appeared in (Movie appearances)53346544215
The number of ophthalmic medical technicians in Connecticut (Laborers)640680660690840920750660340280770




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([5,3,3,4,6,5,4,4,2,1,5,])
array_2 = np.array([640,680,660,690,840,920,750,660,340,280,770,])
array_1_name = "The number of movies Ewan McGregor appeared in"
array_2_name = "The number of ophthalmic medical technicians in Connecticut"

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

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



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

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

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

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

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Correlation ID: 5869 · Black Variable ID: 26494 · Red Variable ID: 18947
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