Spurious correlation #1,443 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Movie Releases in the US & Canada and the second variable is Number of websites on the internet. The chart goes from 1991 to 2018, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Movie Releases in the US & Canada and the second variable is Number of websites on the internet. The chart goes from 1991 to 2018, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As more movie releases flooded the market, people needed to go online to read reviews, watch trailers, and discuss the latest films. This led to a surge in internet usage, prompting an increase in the number of websites to accommodate the growing demand for all things movies. After all, it's a reel-y competitive industry, and everyone's just trying to make a site-seeing blockbuster!

^{Show image generation prompt} Model: dalle-3
Prompt: Create an image that resembles a scene from 'Star Wars' in which a crowded movie theater in the US and Canada is depicted. The theater features a huge screen displaying the latest movie releases, while people sit in their seats, excitedly discussing which movie to watch. Outside the theater, a vast network of websites spans across the sky, showcasing the myriad of online platforms available on the internet. The image should convey the contrast between the traditional cinema experience and the digital realm. 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: Movie Releases in the US & Canada and Number of websites on the internet. 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: Minimalism Art nouveau Psychedelic Realistic An image that looks like it is a scene from 'Star Wars'
ChatGPT: An image that looks like it is a scene from 'Star Wars'

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Movie Releases in the US & Canada and Number of websites on the internet together. Keep the description simple.
ChatGPT: In a crowded movie theater in the US and Canada, a huge screen displays the latest movie releases. People are sitting in their seats, excitedly discussing which movie they want to see. Meanwhile, outside the theater, a vast network of websites spans across the sky, showcasing the vast number of online platforms available on the internet.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ An image that looks like it is a scene from 'Star Wars' ] and depicting this scene: In a crowded movie theater in the US and Canada, a huge screen displays the latest movie releases. People are sitting in their seats, excitedly discussing which movie they want to see. Meanwhile, outside the theater, a vast network of websites spans across the sky, showcasing the vast number of online platforms available on the internet. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image that resembles a scene from 'Star Wars' in which a crowded movie theater in the US and Canada is depicted. The theater features a huge screen displaying the latest movie releases, while people sit in their seats, excitedly discussing which movie to watch. Outside the theater, a vast network of websites spans across the sky, showcasing the myriad of online platforms available on the internet. The image should convey the contrast between the traditional cinema experience and the digital realm.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Movie Releases in the US & Canada caused Number of websites on the internet to increase. Make it feel plausible.

AI academic paper

(Because p < 0.01)

Reel Connections: Exploring the Correlation between Movie Releases in the US & Canada and Number of Websites on the Internet

Journal of Film and Cybernetics

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Movie Releases in the US & Canada and Number of websites on the internet. 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 cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
"Reel Connections: Exploring the Correlation between Movie Releases in the US & Canada and Number of Websites on the Internet"

[[ABSTRACT]]
The relation between the number of websites on the internet and the release of movies in the US & Canada has long been an enigma in the field of media and entertainment. In this study, we embark on the formidable task of unraveling this complex connection by employing a quantitative approach with data spanning from 1991 to 2018. Our findings reveal a significant correlation coefficient of 0.8978111 with a p-value less than 0.01, thereby shedding light on the surprising and somewhat inexplicable link between these seemingly disparate elements. While causation cannot be inferred from this correlation, the mere existence of such a robust association prompts further exploration into the intricate interplay between cinematic output and digital domain expansion. This research paves the way for future investigations into the whimsical dance of movie premieres and the virtual world, prompting us to rethink the phrase "Lights, camera, websites!"

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The ever-advancing landscape of the entertainment industry has sparked numerous inquiries into the influence of cinematic releases on various societal and cultural domains. One particularly unconventional relationship that has captured the attention of researchers and enthusiasts alike is the seemingly unforeseen association between the release of movies in the US & Canada and the burgeoning number of websites in the digital realm. As the internet continues to expand at an exponential rate, it poses an intriguing puzzle as to how and why it may be influenced by the ebb and flow of films making their way onto the silver screen.
This study delves into the mysteries of this cinematic-web correlation, utilizing a quantitative approach with data collected over a 28-year period from 1991 to 2018. By harnessing the power of statistical analyses, our aim is to shed light on this peculiar connection and offer new insights into the ever-evolving dynamics of media consumption and technological evolution. We recognize that the interrelationship between these variables elicits a certain degree of skepticism, much like a melodramatic plot twist in a Hollywood blockbuster, but the empirical evidence holds its own amidst the skepticism.
Our findings unearth a notable correlation coefficient of 0.8978111 with a p-value less than 0.01, underscoring the robust nature of the relationship between movie releases and internet expansion. The significance of this statistical relationship prompts not only a reevaluation of our assumptions about the intertwining of cultural phenomena but also a recognition of the quirky and often unexpected patterns that emerge in the world of data analysis.
While we do exercise caution in ascribing causation to this correlation, the sheer strength of the association prompts us to navigate further into the enigmatic connection between the glitz and glamor of Hollywood premieres and the digital proliferation within the online sphere. This research invites a reimagining of the conventional wisdom surrounding media influence and technological development, demonstrating that the world of statistics can indeed hold surprises of its own, much like a plot twist in a suspenseful film.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Smith et al.," the authors find that the release of movies in the US & Canada has a significant impact on various cultural and economic indicators. Similarly, in "Doe's study," the researchers evaluate the trends in internet usage and digital expansion, uncovering the ever-increasing proliferation of websites in the cyber domain. Furthermore, Jones' work offers insights into the sociocultural implications of media consumption and technological advancements, highlighting the intricate interplay between entertainment and digital landscapes.

Shifting our focus to relevant non-fiction literature, "The Long Tail: Why the Future of Business is Selling Less of More" by Chris Anderson presents a thought-provoking analysis of the digital economy and the influence of niche markets, offering a lens through which to explore the diverse array of websites catering to unique interests.

In a similar vein, "The Innovators: How a Group of Hackers, Geniuses, and Geeks Created the Digital Revolution" by Walter Isaacson delves into the historical evolution of the digital age, providing valuable context for understanding the exponential growth of internet content and its relationship to cultural phenomena.

On the fiction side, "Ready Player One" by Ernest Cline immerses readers in a virtual reality universe, raising questions about the impact of immersive media experiences on internet usage and societal engagement. In a more introspective exploration, "The Circle" by Dave Eggers offers a cautionary tale about the omnipresence of technology and its profound influence on human behavior, inviting contemplation on the interwoven nature of digital connectivity and cultural dynamics.

More recently, a series of social media posts have garnered attention for their anecdotal observations on the release of blockbuster movies coinciding with spikes in online activity. One post humorously suggests that the allure of movie trailers may lead individuals to seek out related content on the internet, inadvertently contributing to the expansion of web presence. Meanwhile, another post playfully speculates that the anticipation of film premieres may prompt internet users to engage in fervent discussions and sharing of movie-related content, further fueling the digital landscape.

As we examine these diverse sources, it becomes evident that the correlation between movie releases in the US & Canada and the number of websites on the internet elicits a fascinating blend of scholarly inquiry, literary exploration, and whimsical musings. The tapestry of connections woven across these sources beckons us to embrace the unexpected quirks of this curious relationship, reinforcing the notion that even the most seemingly disparate elements can converge in intriguing and, at times, confounding ways.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Movie Releases in the US & Canada and Number of websites on the internet. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Statista and Internet Live Stats . You used data from 1991 to 2018

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]]
"Reel Connections: Exploring the Correlation between Movie Releases in the US & Canada and Number of Websites on the Internet"

[[ABSTRACT]]
The relation between the number of websites on the internet and the release of movies in the US & Canada has long been an enigma in the field of media and entertainment. In this study, we embark on the formidable task of unraveling this complex connection by employing a quantitative approach with data spanning from 1991 to 2018. Our findings reveal a significant correlation coefficient of 0.8978111 with a p-value less than 0.01, thereby shedding light on the surprising and somewhat inexplicable link between these seemingly disparate elements. While causation cannot be inferred from this correlation, the mere existence of such a robust association prompts further exploration into the intricate interplay between cinematic output and digital domain expansion. This research paves the way for future investigations into the whimsical dance of movie premieres and the virtual world, prompting us to rethink the phrase "Lights, camera, websites!"

[[INTRODUCTION]]
The ever-advancing landscape of the entertainment industry has sparked numerous inquiries into the influence of cinematic releases on various societal and cultural domains. One particularly unconventional relationship that has captured the attention of researchers and enthusiasts alike is the seemingly unforeseen association between the release of movies in the US & Canada and the burgeoning number of websites in the digital realm. As the internet continues to expand at an exponential rate, it poses an intriguing puzzle as to how and why it may be influenced by the ebb and flow of films making their way onto the silver screen.
This study delves into the mysteries of this cinematic-web correlation, utilizing a quantitative approach with data collected over a 28-year period from 1991 to 2018. By harnessing the power of statistical analyses, our aim is to shed light on this peculiar connection and offer new insights into the ever-evolving dynamics of media consumption and technological evolution. We recognize that the interrelationship between these variables elicits a certain degree of skepticism, much like a melodramatic plot twist in a Hollywood blockbuster, but the empirical evidence holds its own amidst the skepticism.
Our findings unearth a notable correlation coefficient of 0.8978111 with a p-value less than 0.01, underscoring the robust nature of the relationship between movie releases and internet expansion. The significance of this statistical relationship prompts not only a reevaluation of our assumptions about the intertwining of cultural phenomena but also a recognition of the quirky and often unexpected patterns that emerge in the world of data analysis.
While we do exercise caution in ascribing causation to this correlation, the sheer strength of the association prompts us to navigate further into the enigmatic connection between the glitz and glamor of Hollywood premieres and the digital proliferation within the online sphere. This research invites a reimagining of the conventional wisdom surrounding media influence and technological development, demonstrating that the world of statistics can indeed hold surprises of its own, much like a plot twist in a suspenseful film.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

The methodology employed in this study utilized a combination of data mining, statistical analysis, and a dash of cinematic flair to unravel the perplexing correlation between movie releases in the US & Canada and the number of websites on the internet. Data collection involved scouring various sources across the digital expanse, with significant reliance on Statista and Internet Live Stats as the primary repositories of information. The time span for data collection extended from 1991 to 2018, encompassing a quarter-century of cinematic evolution and digital proliferation.

To quantify the release of movies in the US & Canada, the team employed a comprehensive census of major film premieres and theatrical debuts, cross-referencing data from reputable industry databases and archival records. This process involved meticulous scrutiny of release dates, box office performance, and genre classifications to ensure a comprehensive representation of cinematic output during the study period. Analogously, the ascertainment of the number of websites on the internet relied on extensive data sets and web traffic analyses, utilizing Internet Live Stats as the primary source for tracking the burgeoning digital frontier.

Following the compilation of these datasets, an intricate process of data cleansing and transformation ensued. This involved wrangling and harmonizing disparate sources of data, dealing with discrepancies in reporting standards, and mitigating the effects of outliers and anomalies. Akin to a skilled movie editor piecing together fragments of film footage, the data cleaning phase aimed to ensure the coherence and integrity of the datasets, providing a solid foundation for subsequent analyses.

With the pristine datasets in hand, the team navigated towards the realm of statistical analysis, employing correlation coefficients and regression models to discern the underlying patterns within the data. The application of Pearson's correlation coefficient allowed for the quantification of the relationship between movie releases and internet expansion, revealing a striking coefficient of 0.8978111 with a p-value less than 0.01. The orchestration of regression models further elucidated the predictive capacity of movie releases in forecasting the growth of websites on the internet, unearthing a whimsical dance of predictive variables reminiscent of a meticulously choreographed cinematic sequence.

To account for potential confounding variables and spurious correlations, robustness checks were conducted, encompassing sensitivity analyses and subgroup investigations. These checks aimed to ascertain the stability and generalizability of the observed relationship, akin to the meticulous scrutiny of continuity errors and plot holes in the context of cinematic storytelling.

In addition, a sensorial foray into the qualitative dimension of the data was undertaken, eliciting the emotive responses and perceptions of individuals towards movie releases and their impact on online interactions. This qualitative exploration provided a colorful backdrop to the quantitative analyses, enriching the narrative of the relationship between movie premieres and digital domain expansion.

The culmination of these methodological endeavors serves to unravel the enigmatic interplay between cinematic artistry and digital proliferation, offering a clear yet whimsical lens through which to view the seemingly unforeseen association between these seemingly disparate realms. As with any captivating movie plot, the methodology applied in this study unfolded with a mixture of precision and panache, culminating in the unveiling of unexpected connections and delightful revelations amidst the seemingly mundane variables of movie releases and website proliferation.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Movie Releases in the US & Canada and Number of websites on the internet. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"Reel Connections: Exploring the Correlation between Movie Releases in the US & Canada and Number of Websites on the Internet"

[[ABSTRACT]]
The relation between the number of websites on the internet and the release of movies in the US & Canada has long been an enigma in the field of media and entertainment. In this study, we embark on the formidable task of unraveling this complex connection by employing a quantitative approach with data spanning from 1991 to 2018. Our findings reveal a significant correlation coefficient of 0.8978111 with a p-value less than 0.01, thereby shedding light on the surprising and somewhat inexplicable link between these seemingly disparate elements. While causation cannot be inferred from this correlation, the mere existence of such a robust association prompts further exploration into the intricate interplay between cinematic output and digital domain expansion. This research paves the way for future investigations into the whimsical dance of movie premieres and the virtual world, prompting us to rethink the phrase "Lights, camera, websites!"

[[LITERATURE REVIEW]]
In "Smith et al.," the authors find that the release of movies in the US & Canada has a significant impact on various cultural and economic indicators. Similarly, in "Doe's study," the researchers evaluate the trends in internet usage and digital expansion, uncovering the ever-increasing proliferation of websites in the cyber domain. Furthermore, Jones' work offers insights into the sociocultural implications of media consumption and technological advancements, highlighting the intricate interplay between entertainment and digital landscapes.
Shifting our focus to relevant non-fiction literature, "The Long Tail: Why the Future of Business is Selling Less of More" by Chris Anderson presents a thought-provoking analysis of the digital economy and the influence of niche markets, offering a lens through which to explore the diverse array of websites catering to unique interests.
In a similar vein, "The Innovators: How a Group of Hackers, Geniuses, and Geeks Created the Digital Revolution" by Walter Isaacson delves into the historical evolution of the digital age, providing valuable context for understanding the exponential growth of internet content and its relationship to cultural phenomena.
On the fiction side, "Ready Player One" by Ernest Cline immerses readers in a virtual reality universe, raising questions about the impact of immersive media experiences on internet usage and societal engagement. In a more introspective exploration, "The Circle" by Dave Eggers offers a cautionary tale about the omnipresence of technology and its profound influence on human behavior, inviting contemplation on the interwoven nature of digital connectivity and cultural dynamics.
More recently, a series of social media posts have garnered attention for their anecdotal observations on the release of blockbuster movies coinciding with spikes in online activity. One post humorously suggests that the allure of movie trailers may lead individuals to seek out related content on the internet, inadvertently contributing to the expansion of web presence. Meanwhile, another post playfully speculates that the anticipation of film premieres may prompt internet users to engage in fervent discussions and sharing of movie-related content, further fueling the digital landscape.
As we examine these diverse sources, it becomes evident that the correlation between movie releases in the US & Canada and the number of websites on the internet elicits a fascinating blend of scholarly inquiry, literary exploration, and whimsical musings. The tapestry of connections woven across these sources beckons us to embrace the unexpected quirks of this curious relationship, reinforcing the notion that even the most seemingly disparate elements can converge in intriguing and, at times, confounding ways.

[[RESULTS]]
The quantitative analysis of the data from 1991 to 2018 revealed a statistically significant correlation between the number of websites on the internet and the release of movies in the US & Canada, with a correlation coefficient of 0.8978111. This strong positive relationship between the two variables suggests a surprising and somewhat inexplicable link, much like stumbling upon an unexpected subplot in a seemingly straightforward film.
The r-squared value of 0.8060647 indicates that approximately 80.61% of the variation in the number of websites on the internet can be explained by the changing landscape of movie releases in the US & Canada. This finding underscores the substantial influence that cinematic output wields over the digital domain, akin to a leading actor's magnetic pull on the audience.
Additionally, the p-value of less than 0.01 provides further support for the robustness of the correlation, offering compelling evidence that goes beyond the shadow of statistical doubt, much like a crucial piece of evidence in a thrilling crime procedural.
As depicted in Figure 1, the scatterplot visually portrays the strong correlation between the number of movie releases in the US & Canada and the number of websites on the internet. This visual representation serves as a compelling illustration of the data and reinforces the noteworthy findings of this investigation.
In summary, the results of this study present a compelling case for the interconnectedness of cinematic activity and the expansion of the digital landscape. The statistical analysis not only confirms the presence of a substantial correlation, but also invites further exploration into the intricate dynamics of cultural trends and technological progress, much like peeling back layers of a multi-faceted narrative to reveal unexpected twists and turns.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of this study provide compelling evidence to support the previously speculated enigmatic relationship between the number of movie releases in the US & Canada and the burgeoning virtual expanse of websites. Our findings align with the scholarly work of Smith et al., Doe, and Jones, affirming the significant impact of cinematic output on digital expansion. Furthermore, the peculiar musings and whimsical speculations drawn from non-fiction and fiction literature, along with the lighthearted social media anecdotes, surprisingly resonate with our rigorous quantitative analysis.

The significant correlation coefficient of 0.8978111 lends credence to the notion that the proliferation of website entities may indeed be influenced by the ebb and flow of cinematic premieres. Much like a compelling plot twist in an investigative thriller, the robust association discovered in our study challenges conventional expectations, prompting a reevaluation of the intricate dance between movie releases and digital domain hyperactivity.

The r-squared value of 0.8060647 underscores the substantial explanatory power of movie releases in accounting for the variation in the number of websites on the internet, akin to an acclaimed lead actor commanding attention in a theatrical production. The remarkable influence of cinematic content on the digital stage mirrors the mesmerizing sway of a magnetic performer, captivating the audience with unparalleled charisma.

The p-value of less than 0.01 unequivocally reinforces the statistical robustness of the correlation, akin to a pivotal piece of evidence in a thrilling crime procedural that leaves little room for doubt. This compelling evidence resonates with the meticulous scrutiny of the web of connections between movie releases and the online realm, inviting further exploration into this captivating interplay.

The scatterplot, a visual manifestation of our compelling findings, serves as an illuminating tableau, much like a captivating scene in a cinematic masterpiece, vividly portraying the entwined relationship between the number of movie releases in the US & Canada and the corresponding expansion of websites. This visual representation not only bolsters the veracity of our results but also encapsulates the splendid drama unfolding in the realm of data analysis.

It is crucial to recognize that correlation does not imply causation. However, the striking correlation uncovered in this study poses intriguing questions, akin to the enigmatic allure of an unresolved plot point. As we ponder the intricate synergy between movie releases and digital proliferation, it becomes apparent that the world of data analysis is not devoid of its own brand of magic – a magic that unveils unexpected parallels and uncovers surprising ties, rendering the seemingly disparate as harmonious.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics 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 Movie Releases in the US & Canada and Number of websites on the internet. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"Reel Connections: Exploring the Correlation between Movie Releases in the US & Canada and Number of Websites on the Internet"

[[ABSTRACT]]
The relation between the number of websites on the internet and the release of movies in the US & Canada has long been an enigma in the field of media and entertainment. In this study, we embark on the formidable task of unraveling this complex connection by employing a quantitative approach with data spanning from 1991 to 2018. Our findings reveal a significant correlation coefficient of 0.8978111 with a p-value less than 0.01, thereby shedding light on the surprising and somewhat inexplicable link between these seemingly disparate elements. While causation cannot be inferred from this correlation, the mere existence of such a robust association prompts further exploration into the intricate interplay between cinematic output and digital domain expansion. This research paves the way for future investigations into the whimsical dance of movie premieres and the virtual world, prompting us to rethink the phrase "Lights, camera, websites!"

[[INTRDUCTION]]
The ever-advancing landscape of the entertainment industry has sparked numerous inquiries into the influence of cinematic releases on various societal and cultural domains. One particularly unconventional relationship that has captured the attention of researchers and enthusiasts alike is the seemingly unforeseen association between the release of movies in the US & Canada and the burgeoning number of websites in the digital realm. As the internet continues to expand at an exponential rate, it poses an intriguing puzzle as to how and why it may be influenced by the ebb and flow of films making their way onto the silver screen.
This study delves into the mysteries of this cinematic-web correlation, utilizing a quantitative approach with data collected over a 28-year period from 1991 to 2018. By harnessing the power of statistical analyses, our aim is to shed light on this peculiar connection and offer new insights into the ever-evolving dynamics of media consumption and technological evolution. We recognize that the interrelationship between these variables elicits a certain degree of skepticism, much like a melodramatic plot twist in a Hollywood blockbuster, but the empirical evidence holds its own amidst the skepticism.
Our findings unearth a notable correlation coefficient of 0.8978111 with a p-value less than 0.01, underscoring the robust nature of the relationship between movie releases and internet expansion. The significance of this statistical relationship prompts not only a reevaluation of our assumptions about the intertwining of cultural phenomena but also a recognition of the quirky and often unexpected patterns that emerge in the world of data analysis.
While we do exercise caution in ascribing causation to this correlation, the sheer strength of the association prompts us to navigate further into the enigmatic connection between the glitz and glamor of Hollywood premieres and the digital proliferation within the online sphere. This research invites a reimagining of the conventional wisdom surrounding media influence and technological development, demonstrating that the world of statistics can indeed hold surprises of its own, much like a plot twist in a suspenseful film.

[[RESULTS]]
The quantitative analysis of the data from 1991 to 2018 revealed a statistically significant correlation between the number of websites on the internet and the release of movies in the US & Canada, with a correlation coefficient of 0.8978111. This strong positive relationship between the two variables suggests a surprising and somewhat inexplicable link, much like stumbling upon an unexpected subplot in a seemingly straightforward film.
The r-squared value of 0.8060647 indicates that approximately 80.61% of the variation in the number of websites on the internet can be explained by the changing landscape of movie releases in the US & Canada. This finding underscores the substantial influence that cinematic output wields over the digital domain, akin to a leading actor's magnetic pull on the audience.
Additionally, the p-value of less than 0.01 provides further support for the robustness of the correlation, offering compelling evidence that goes beyond the shadow of statistical doubt, much like a crucial piece of evidence in a thrilling crime procedural.
As depicted in Figure 1, the scatterplot visually portrays the strong correlation between the number of movie releases in the US & Canada and the number of websites on the internet. This visual representation serves as a compelling illustration of the data and reinforces the noteworthy findings of this investigation.
In summary, the results of this study present a compelling case for the interconnectedness of cinematic activity and the expansion of the digital landscape. The statistical analysis not only confirms the presence of a substantial correlation, but also invites further exploration into the intricate dynamics of cultural trends and technological progress, much like peeling back layers of a multi-faceted narrative to reveal unexpected twists and turns.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation has unveiled a striking correlation between the release of movies in the US & Canada and the proliferation of websites on the internet. The robust correlation coefficient of 0.8978111, accompanied by an r-squared value of 0.8060647, illuminates the captivating tango between these seemingly unrelated entities. It seems that the digital domain has found itself spellbound by the mesmerizing allure of Hollywood premieres, much like a wide-eyed audience captivated by a gripping plot twist.

The compelling evidence presented in this study not only highlights the unforeseen kinship between cinematic debuts and virtual expansion but also invites contemplation of the idiosyncratic patterns that underpin statistical analyses. The p-value of less than 0.01 stands as a testament to the undeniable significance of this correlation, akin to a meticulously crafted clue in an elaborate mystery.

While the direction of causation remains elusive, the strength of the association between movie releases and internet growth prompts us to ponder the intricate interplay between cultural phenomena and technological advancement. As we contemplate the whimsical dance of these variables, one cannot help but marvel at the surprising twists and turns that the realm of data analysis can yield, akin to a well-crafted comedic plotline.

In light of these findings, we assert that no further research is needed in this area, as our study has sufficiently untangled the reel connections between movie premieres and the digital domain. This research not only sheds light on the curious interrelationship between cultural output and technological evolution but also reminds us that statistical investigations can harbor their fair share of unexpected entertainment, much like a lighthearted subplot in an otherwise serious academic discourse.

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 Reel Connections: Exploring the Correlation between Movie Releases in the US & Canada and Number of Websites on the Internet. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Film and Cybernetics

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 Reel Connections: Exploring the Correlation between Movie Releases in the US & Canada and Number of Websites on the Internet. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Cinematic Cyber 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 Reel Connections: Exploring the Correlation between Movie Releases in the US & Canada and Number of Websites on the Internet with an abstract of The relation between the number of websites on the internet and the release of movies in the US & Canada has long been an enigma in the field of media and entertainment. In this study, we embark on the formidable task of unraveling this complex connection by employing a quantitative approach with data spanning from 1991 to 2018. Our findings reveal a significant correlation coefficient of 0.8978111 with a p-value less than 0.01, thereby shedding light on the surprising and somewhat inexplicable link between these seemingly disparate elements. While causation cannot be inferred from this correlation, the mere existence of such a robust association prompts further exploration into the intricate interplay between cinematic output and digital domain expansion. This research paves the way for future investigations into the whimsical dance of movie premieres and the virtual world, prompting us to rethink the phrase "Lights, camera, websites!

ChatGPT:

movie releases, internet websites, correlation, US, Canada, quantitative approach, media and entertainment, data analysis, correlation coefficient, causation, cinematic output, digital domain expansion, virtual world

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

Random correlation

Discover a new correlation

View all correlations

View all research papers

Report an error

Data details

Movie Releases in the US & Canada
Source: Statista
See what else correlates with Movie Releases in the US & Canada

Number of websites on the internet
Detailed data title: Number of websites, measured by unique hostnames
Source: Internet Live Stats
See what else correlates with Number of websites on the internet

Correlation r = 0.8978111 (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 = 0.8060647 (Coefficient of determination)
This means 80.6% of the change in the one variable (i.e., Number of websites on the internet) is predictable based on the change in the other (i.e., Movie Releases in the US & Canada) over the 28 years from 1991 through 2018.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 9.4E-11.^Show 0.0000000000939662861744053000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.9 in 9.4E-9% of random cases. Said differently, if you correlated 10,642,114,749 random variables^Note You don't actually need 10 billion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 27 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 27 because we have two variables measured over a period of 28 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.79, 0.95 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

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

	1991	1992	1993	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018
Movie Releases in the US & Canada (Movies Released)	458	480	462	453	411	471	510	509	461	478	482	478	506	551	547	608	631	608	521	536	601	669	687	708	708	737	742	873
Number of websites on the internet (Websites)	1	10	130	2738	23500	257601	1117260	2410070	3177450	17087200	29254400	38760400	40912300	51611600	64780600	85507300	121893000	172339000	238028000	206957000	346004000	697089000	672985000	968882000	863106000	1045530000	1766930000	1630320000

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.
Outlandish outliers: There are "outliers" in this data.^Note In concept, "outlier" just means "way different than the rest of your dataset." When calculating a correlation like this, they are particularly impactful because a single outlier can substantially increase your correlation.

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

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

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([458,480,462,453,411,471,510,509,461,478,482,478,506,551,547,608,631,608,521,536,601,669,687,708,708,737,742,873,])
array_2 = np.array([1,10,130,2738,23500,257601,1117260,2410070,3177450,17087200,29254400,38760400,40912300,51611600,64780600,85507300,121893000,172339000,238028000,206957000,346004000,697089000,672985000,968882000,863106000,1045530000,1766930000,1630320000,])
array_1_name = "Movie Releases in the US & Canada"
array_2_name = "Number of websites on the internet"

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

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

Reuseable content

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

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

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

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

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

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Movie Releases in the US & Canada
Line chart for only Number of websites on the internet
AI-generated correlation image
The spurious research paper: Reel Connections: Exploring the Correlation between Movie Releases in the US & Canada and Number of Websites on the Internet

View another random correlation

How fun was this correlation?

Hats off to you for rating!

Correlation ID: 1443 · Black Variable ID: 70 · Red Variable ID: 370


Problem variable:
Issue:
Additional details: Optional
Confirm you are a human: