Spurious correlation #1,469 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Number of public school students in 9th grade and the second variable is Ticket sales for New York Yankees games. The chart goes from 1990 to 2019, 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 Number of public school students in 9th grade and the second variable is Ticket sales for New York Yankees games. The chart goes from 1990 to 2019, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the number of 9th graders grows, so does the demand for entertainment. With more students in the stands, the "youthful energy" at the games creates a "home run" atmosphere that attracts other fans, leading to a "grand slam" in ticket sales. The influx of 9th graders could be "pitching" in to boost the team spirit, turning the stadium into a "class act" and giving the Yankees a "major league" advantage in filling those seats. It seems like these young fans are really "stepping up to the plate" and driving the ticket sales "out of the park," proving that when it comes to filling the stands, the 9th graders are the real "MVPs"!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a vibrant high school hallway bustling with 9th-grade students eagerly rushing to their classes, while outside the enchanting Yankee Stadium, an energetic line of fans eagerly waits, brimming with excitement to purchase tickets for the next game. Capture the whimsical essence of the scene with playful, animated characters and bright, lively surroundings. 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: Number of public school students in 9th grade and Ticket sales for New York Yankees games. 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: Data cyber art Art nouveau Cute 2D animation Whimsical illustration Cyberpunk
ChatGPT: Whimsical illustration

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 Number of public school students in 9th grade and Ticket sales for New York Yankees games together. Keep the description simple.
ChatGPT: A busy high school hallway filled with 9th-grade students rushing to their classes, while a long line of excited fans waits outside the Yankee Stadium, eager to purchase tickets for the next game.

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: [ Whimsical illustration ] and depicting this scene: A busy high school hallway filled with 9th-grade students rushing to their classes, while a long line of excited fans waits outside the Yankee Stadium, eager to purchase tickets for the next game. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a vibrant high school hallway bustling with 9th-grade students eagerly rushing to their classes, while outside the enchanting Yankee Stadium, an energetic line of fans eagerly waits, brimming with excitement to purchase tickets for the next game. Capture the whimsical essence of the scene with playful, animated characters and bright, lively surroundings.

*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 humerus 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 Number of public school students in 9th grade caused Ticket sales for New York Yankees games to increase. Include a lot of jokes and puns.

AI academic paper

(Because p < 0.01)

The Ninth Grade Nine Innings: Exploring the Correlation Between Public School Enrollment and Yankees Ticket Sales

Journal of Educational Economics and Sports Sociology

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 Number of public school students in 9th grade and Ticket sales for New York Yankees games. 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]]
The Ninth Grade Nine Innings: Exploring the Correlation Between Public School Enrollment and Yankees Ticket Sales

[[ABSTRACT]]
This study delves into the intriguing relationship between the number of public school 9th-grade students and ticket sales for New York Yankees games. Leveraging data from the National Center for Education Statistics and Baseball-Reference.com, our research team conducted an in-depth analysis spanning the years 1990 to 2019. The results revealed a striking correlation coefficient of 0.8787610, with a statistically significant p-value of less than 0.01. Our findings suggest that as the population of 9th-grade students in public schools fluctuates, so too do the ticket sales for Yankees games. This unforeseen bond between educational enrollment and baseball spectatorship opens the door to a multitude of interpretations and speculations that extend beyond the confines of traditional academic discourse. Future research could investigate the underlying mechanisms driving this unexpected correlation and offer insight into the peculiar entanglement of academic beginnings and baseball fandom.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The relationship between educational enrollment and extracurricular activities has long been a topic of curiosity, prompting researchers to delve into the peculiar connection between the two seemingly unrelated domains. In this study, we set out to explore the unexpected correlation between the number of public school 9th-grade students and ticket sales for New York Yankees games. It is indeed a curious conundrum, as one might expect the enrollment in secondary education to have little bearing on the spectatorship of America's favorite pastime. Nevertheless, the intersection of academia and athletics often yields surprising revelations, much like the synthesis of sodium and chlorine to form table salt - an unpredictable chemical reaction resulting in a familiar yet unconventional compound.
The empirical investigation of this correlation involved a thorough examination of data sourced from the National Center for Education Statistics and Baseball-Reference.com, covering a temporal expanse from 1990 to 2019. By leveraging sophisticated statistical analyses, our research team diligently combed through the myriad data points to unearth the underlying patterns and associations that may underpin this intriguing relationship. Much like a meticulous entomologist examining the delicate wings of a butterfly under a microscope, we scrutinized the intricacies of these datasets, in search of peculiarities that might shed light on the intertwined nature of academic enrollment and baseball attendance.
The revelations uncovered in this study present an intellectual puzzle akin to a complex jigsaw, where each piece represents a unique facet of the correlation between educational beginnings and baseball fandom. Our pursuit of knowledge led us to ascertain a correlation coefficient of 0.8787610, a figure that elicits a sense of bewilderment akin to observing a chemical reaction yield unexpected products. Furthermore, the statistically significant p-value of less than 0.01 reinforced the robustness of this correlation, underscoring the weight of this unpredictable relationship.
As we navigate through the labyrinth of data and statistical analyses, our findings carry profound implications that transcend the realms of academia and athletics. This unforeseen entanglement between educational demographics and sports spectatorship beckons further exploration, much like a mysterious labyrinth waiting to be unravelled.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Smith et al. (2015) conducted a comprehensive analysis of factors influencing spectator attendance at professional sporting events. Their study focused on variables such as team performance, ticket pricing, and promotional activities. While their findings yielded valuable insights into the dynamics of spectator behavior, they did not specifically investigate the potential correlation between educational enrollment and attendance at sporting events. Similarly, Doe and Jones (2017) explored the economic impact of sports events on local communities, emphasizing the role of tourism and revenue generation. However, their research did not delve into the peculiar connection between the number of 9th-grade students in public schools and ticket sales for baseball games.

Turning to the realm of non-fiction literature, "Moneyball: The Art of Winning an Unfair Game" by Michael Lewis provides a captivating account of the Oakland Athletics' innovative approach to team management and player selection. Although the book primarily focuses on the application of sabermetrics in baseball, it offers valuable insights into the intricate workings of the sports industry.

In a tangentially related vein, "Freakonomics: A Rogue Economist Explores the Hidden Side of Everything" by Steven D. Levitt and Stephen J. Dubner examines unconventional correlations and unexpected causal relationships in various domains. While the book does not specifically address the correlation between educational enrollment and baseball ticket sales, its exploration of unanticipated connections serves as a thought-provoking backdrop for our own investigation.

On a more fictional note, the classic novel "The Catcher in the Rye" by J.D. Salinger resonates with themes of adolescence and coming-of-age experiences, albeit in a context distinct from our focus on 9th-grade student enrollment and baseball attendance. Similarly, the whimsical "The Hitchhiker's Guide to the Galaxy" series by Douglas Adams, while primarily a work of science fiction, offers a humorous and imaginative perspective that provokes unconventional associations and unexpected confluences.

In an interesting twist, a social media post by @BaseballFanatic23 intriguingly posited that perhaps the enthusiasm for attending Yankees games is fueled by the collective energy of incoming 9th-grade students in public schools, creating a surge of youthful exuberance that resonates with the vibrant spirit of baseball fandom. While not a scholarly source, this speculative notion exemplifies the diverse interpretations and speculations that permeate public discourse regarding the unexpected correlation between educational enrollment and baseball spectatorship.

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 Number of public school students in 9th grade and Ticket sales for New York Yankees games. 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 National Center for Education Statistics and Baseball-Reference.com . You used data from 1990 to 2019

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 Ninth Grade Nine Innings: Exploring the Correlation Between Public School Enrollment and Yankees Ticket Sales

[[ABSTRACT]]
This study delves into the intriguing relationship between the number of public school 9th-grade students and ticket sales for New York Yankees games. Leveraging data from the National Center for Education Statistics and Baseball-Reference.com, our research team conducted an in-depth analysis spanning the years 1990 to 2019. The results revealed a striking correlation coefficient of 0.8787610, with a statistically significant p-value of less than 0.01. Our findings suggest that as the population of 9th-grade students in public schools fluctuates, so too do the ticket sales for Yankees games. This unforeseen bond between educational enrollment and baseball spectatorship opens the door to a multitude of interpretations and speculations that extend beyond the confines of traditional academic discourse. Future research could investigate the underlying mechanisms driving this unexpected correlation and offer insight into the peculiar entanglement of academic beginnings and baseball fandom.

[[INTRODUCTION]]
The relationship between educational enrollment and extracurricular activities has long been a topic of curiosity, prompting researchers to delve into the peculiar connection between the two seemingly unrelated domains. In this study, we set out to explore the unexpected correlation between the number of public school 9th-grade students and ticket sales for New York Yankees games. It is indeed a curious conundrum, as one might expect the enrollment in secondary education to have little bearing on the spectatorship of America's favorite pastime. Nevertheless, the intersection of academia and athletics often yields surprising revelations, much like the synthesis of sodium and chlorine to form table salt - an unpredictable chemical reaction resulting in a familiar yet unconventional compound.
The empirical investigation of this correlation involved a thorough examination of data sourced from the National Center for Education Statistics and Baseball-Reference.com, covering a temporal expanse from 1990 to 2019. By leveraging sophisticated statistical analyses, our research team diligently combed through the myriad data points to unearth the underlying patterns and associations that may underpin this intriguing relationship. Much like a meticulous entomologist examining the delicate wings of a butterfly under a microscope, we scrutinized the intricacies of these datasets, in search of peculiarities that might shed light on the intertwined nature of academic enrollment and baseball attendance.
The revelations uncovered in this study present an intellectual puzzle akin to a complex jigsaw, where each piece represents a unique facet of the correlation between educational beginnings and baseball fandom. Our pursuit of knowledge led us to ascertain a correlation coefficient of 0.8787610, a figure that elicits a sense of bewilderment akin to observing a chemical reaction yield unexpected products. Furthermore, the statistically significant p-value of less than 0.01 reinforced the robustness of this correlation, underscoring the weight of this unpredictable relationship.
As we navigate through the labyrinth of data and statistical analyses, our findings carry profound implications that transcend the realms of academia and athletics. This unforeseen entanglement between educational demographics and sports spectatorship beckons further exploration, much like a mysterious labyrinth waiting to be unravelled.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To explore the enigmatic correlation between the number of public school 9th-grade students and ticket sales for New York Yankees games, a multi-faceted methodology was meticulously devised. The research team traversed the intricate landscape of data collection and analysis, akin to intrepid botanists navigating through a dense jungle in search of rare specimens.

Data Collection:
The first step in this elaborate endeavor involved the gathering of pertinent data from a multitude of sources. The National Center for Education Statistics stood as a stalwart librarian, providing access to comprehensive information on public school enrollment across the United States. Simultaneously, Baseball-Reference.com emerged as an indispensable ally, furnishing detailed records of ticket sales for New York Yankees games from 1990 to 2019. The process of data collection was not unlike casting a wide net into the depths of the ocean, hoping to capture a diverse array of creatures to analyze and scrutinize.

Data Processing and Cleaning:
Upon the acquisition of raw data, rigorous and methodical procedures were enacted to process and cleanse the datasets. The data were akin to unrefined ore, requiring meticulous extraction and purification to extract the valuable insights embedded within. Outliers were identified and treated with the same suspicion as a curious anomaly in a scientific experiment, ensuring the integrity and reliability of the subsequent analyses.

Statistical Analyses:
A battery of statistical analyses was wielded with precision and sagacity, resembling an ensemble of carefully calibrated instruments in a laboratory. The correlation between the number of public school 9th-grade students and ticket sales for New York Yankees games was ascertained using the venerable Pearson correlation coefficient, along with its accompanying p-value for confirmation of statistical significance. The Linear Regression model was also applied to unravel the potential predictive nature of educational enrollment on baseball spectatorship. The statistical analyses were conducted with the same exactitude as an alchemist striving to transmute base metals into gold.

Control Variables:
A panoply of control variables were considered and included in the analyses to mitigate the potential influence of confounding factors. Economic indicators, such as median household income in the localities of the public schools, were accounted for to attenuate the spurious correlation between educational enrollment and ticket sales. Furthermore, the performance of the New York Yankees in the corresponding baseball seasons was factored into the analyses, preventing undue attribution of fluctuations in ticket sales solely to educational demographics.

Validation and Sensitivity Analyses:
Robustness of the findings was reinforced through validation and sensitivity analyses, employing various statistical techniques to stress-test the observed correlation. The results were scrutinized with the same discerning gaze as a seasoned cryptographer deciphering an intricate code, ensuring the reliability and resilience of the revealed relationship.

Ethical Considerations:
Throughout the research process, scrupulous adherence to ethical principles was upheld, safeguarding the integrity and confidentiality of the data sources. All analyses were conducted in accordance with established guidelines and standards, akin to a conscientious physician abiding by the Hippocratic Oath.

The amalgamation of these methodological approaches served as the compass guiding the expedition through the uncharted territory of our research inquiry, unraveling the enigmatic association between educational enrollment and baseball spectatorship.

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 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 Number of public school students in 9th grade and Ticket sales for New York Yankees games. 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 National Center for Education Statistics and Baseball-Reference.com .

For the time period 1990 to 2019, you found a correlation 0.8787610, r-squared of 0.7722210, 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 Ninth Grade Nine Innings: Exploring the Correlation Between Public School Enrollment and Yankees Ticket Sales

[[ABSTRACT]]
This study delves into the intriguing relationship between the number of public school 9th-grade students and ticket sales for New York Yankees games. Leveraging data from the National Center for Education Statistics and Baseball-Reference.com, our research team conducted an in-depth analysis spanning the years 1990 to 2019. The results revealed a striking correlation coefficient of 0.8787610, with a statistically significant p-value of less than 0.01. Our findings suggest that as the population of 9th-grade students in public schools fluctuates, so too do the ticket sales for Yankees games. This unforeseen bond between educational enrollment and baseball spectatorship opens the door to a multitude of interpretations and speculations that extend beyond the confines of traditional academic discourse. Future research could investigate the underlying mechanisms driving this unexpected correlation and offer insight into the peculiar entanglement of academic beginnings and baseball fandom.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The relationship between educational enrollment and extracurricular activities has long been a topic of curiosity, prompting researchers to delve into the peculiar connection between the two seemingly unrelated domains. In this study, we set out to explore the unexpected correlation between the number of public school 9th-grade students and ticket sales for New York Yankees games. It is indeed a curious conundrum, as one might expect the enrollment in secondary education to have little bearing on the spectatorship of America's favorite pastime. Nevertheless, the intersection of academia and athletics often yields surprising revelations, much like the synthesis of sodium and chlorine to form table salt - an unpredictable chemical reaction resulting in a familiar yet unconventional compound.
The empirical investigation of this correlation involved a thorough examination of data sourced from the National Center for Education Statistics and Baseball-Reference.com, covering a temporal expanse from 1990 to 2019. By leveraging sophisticated statistical analyses, our research team diligently combed through the myriad data points to unearth the underlying patterns and associations that may underpin this intriguing relationship. Much like a meticulous entomologist examining the delicate wings of a butterfly under a microscope, we scrutinized the intricacies of these datasets, in search of peculiarities that might shed light on the intertwined nature of academic enrollment and baseball attendance.
The revelations uncovered in this study present an intellectual puzzle akin to a complex jigsaw, where each piece represents a unique facet of the correlation between educational beginnings and baseball fandom. Our pursuit of knowledge led us to ascertain a correlation coefficient of 0.8787610, a figure that elicits a sense of bewilderment akin to observing a chemical reaction yield unexpected products. Furthermore, the statistically significant p-value of less than 0.01 reinforced the robustness of this correlation, underscoring the weight of this unpredictable relationship.
As we navigate through the labyrinth of data and statistical analyses, our findings carry profound implications that transcend the realms of academia and athletics. This unforeseen entanglement between educational demographics and sports spectatorship beckons further exploration, much like a mysterious labyrinth waiting to be unravelled.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The results of the analysis unveiled a striking correlation between the number of public school 9th-grade students and ticket sales for New York Yankees games for the period from 1990 to 2019. The correlation coefficient of 0.8787610 suggests a robust relationship between these seemingly disparate variables. It seems that as the cohort of 9th-grade students waxed and waned, so too did the enthusiasm for witnessing baseball heroics unfold in the hallowed grounds of Yankee Stadium.

The coefficient of determination (r-squared) of 0.7722210 indicated that approximately 77.22% of the variability in Yankees ticket sales could be explained by fluctuations in the population of 9th-grade students. This finding reinforces the notion that a substantial portion of the ebbs and flows of ticket sales can be ascribed to the undulating tides of educational demographics. It appears that the concept of pivotal ninth grade milestones extends beyond scholarly achievements and navigates into the realm of baseball spectacles.

The p-value of less than 0.01 fortified the statistical significance of this association, affirming that this correlation is not merely a fortuitous alignment (much like the fortuitous alignment of celestial bodies, yielding a phenomenon of astronomical significance), but rather a robust and meaningful relationship deserving of further inquiry.

In Fig. 1, the scatterplot graphically illustrates the pronounced positive correlation between public school 9th-grade students and New York Yankees ticket sales. It lays bare the alignment of these two variables, much like an astrologer revealing the intricate intertwining of stars in the night sky. The figure further corroborates the substantial influence of educational enrollment on the commercial success of baseball events, painting a vivid picture of the unexpected connection between academic beginnings and sporting fervor.

These findings shed light on the covert dance between education and entertainment, reminding us that even in the realm of statistical analyses, the most unsuspecting pairs can form a meaningful and influential bond. As we unravel this enigmatic entanglement, it becomes increasingly evident that the academic and athletic arenas are more intertwined than meets the eye, offering a tapestry of unexpected correlations for future investigation and speculation.

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 Number of public school students in 9th grade and Ticket sales for New York Yankees games. 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]]
The Ninth Grade Nine Innings: Exploring the Correlation Between Public School Enrollment and Yankees Ticket Sales

[[ABSTRACT]]
This study delves into the intriguing relationship between the number of public school 9th-grade students and ticket sales for New York Yankees games. Leveraging data from the National Center for Education Statistics and Baseball-Reference.com, our research team conducted an in-depth analysis spanning the years 1990 to 2019. The results revealed a striking correlation coefficient of 0.8787610, with a statistically significant p-value of less than 0.01. Our findings suggest that as the population of 9th-grade students in public schools fluctuates, so too do the ticket sales for Yankees games. This unforeseen bond between educational enrollment and baseball spectatorship opens the door to a multitude of interpretations and speculations that extend beyond the confines of traditional academic discourse. Future research could investigate the underlying mechanisms driving this unexpected correlation and offer insight into the peculiar entanglement of academic beginnings and baseball fandom.

[[LITERATURE REVIEW]]
Smith et al. (2015) conducted a comprehensive analysis of factors influencing spectator attendance at professional sporting events. Their study focused on variables such as team performance, ticket pricing, and promotional activities. While their findings yielded valuable insights into the dynamics of spectator behavior, they did not specifically investigate the potential correlation between educational enrollment and attendance at sporting events. Similarly, Doe and Jones (2017) explored the economic impact of sports events on local communities, emphasizing the role of tourism and revenue generation. However, their research did not delve into the peculiar connection between the number of 9th-grade students in public schools and ticket sales for baseball games.
Turning to the realm of non-fiction literature, "Moneyball: The Art of Winning an Unfair Game" by Michael Lewis provides a captivating account of the Oakland Athletics' innovative approach to team management and player selection. Although the book primarily focuses on the application of sabermetrics in baseball, it offers valuable insights into the intricate workings of the sports industry.
In a tangentially related vein, "Freakonomics: A Rogue Economist Explores the Hidden Side of Everything" by Steven D. Levitt and Stephen J. Dubner examines unconventional correlations and unexpected causal relationships in various domains. While the book does not specifically address the correlation between educational enrollment and baseball ticket sales, its exploration of unanticipated connections serves as a thought-provoking backdrop for our own investigation.
On a more fictional note, the classic novel "The Catcher in the Rye" by J.D. Salinger resonates with themes of adolescence and coming-of-age experiences, albeit in a context distinct from our focus on 9th-grade student enrollment and baseball attendance. Similarly, the whimsical "The Hitchhiker's Guide to the Galaxy" series by Douglas Adams, while primarily a work of science fiction, offers a humorous and imaginative perspective that provokes unconventional associations and unexpected confluences.
In an interesting twist, a social media post by @BaseballFanatic23 intriguingly posited that perhaps the enthusiasm for attending Yankees games is fueled by the collective energy of incoming 9th-grade students in public schools, creating a surge of youthful exuberance that resonates with the vibrant spirit of baseball fandom. While not a scholarly source, this speculative notion exemplifies the diverse interpretations and speculations that permeate public discourse regarding the unexpected correlation between educational enrollment and baseball spectatorship.

[[RESULTS]]
The results of the analysis unveiled a striking correlation between the number of public school 9th-grade students and ticket sales for New York Yankees games for the period from 1990 to 2019. The correlation coefficient of 0.8787610 suggests a robust relationship between these seemingly disparate variables. It seems that as the cohort of 9th-grade students waxed and waned, so too did the enthusiasm for witnessing baseball heroics unfold in the hallowed grounds of Yankee Stadium.
The coefficient of determination (r-squared) of 0.7722210 indicated that approximately 77.22% of the variability in Yankees ticket sales could be explained by fluctuations in the population of 9th-grade students. This finding reinforces the notion that a substantial portion of the ebbs and flows of ticket sales can be ascribed to the undulating tides of educational demographics. It appears that the concept of pivotal ninth grade milestones extends beyond scholarly achievements and navigates into the realm of baseball spectacles.
The p-value of less than 0.01 fortified the statistical significance of this association, affirming that this correlation is not merely a fortuitous alignment (much like the fortuitous alignment of celestial bodies, yielding a phenomenon of astronomical significance), but rather a robust and meaningful relationship deserving of further inquiry.
In Fig. 1, the scatterplot graphically illustrates the pronounced positive correlation between public school 9th-grade students and New York Yankees ticket sales. It lays bare the alignment of these two variables, much like an astrologer revealing the intricate intertwining of stars in the night sky. The figure further corroborates the substantial influence of educational enrollment on the commercial success of baseball events, painting a vivid picture of the unexpected connection between academic beginnings and sporting fervor.
These findings shed light on the covert dance between education and entertainment, reminding us that even in the realm of statistical analyses, the most unsuspecting pairs can form a meaningful and influential bond. As we unravel this enigmatic entanglement, it becomes increasingly evident that the academic and athletic arenas are more intertwined than meets the eye, offering a tapestry of unexpected correlations for future investigation and speculation.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study fortify the previously uncharted notion that the number of public school 9th-grade students and ticket sales for New York Yankees games are entwined in an unforeseen symbiosis. Our findings not only corroborate, but also amplify the surprisingly strong correlation between these seemingly disparate variables, thus adding an unexpected dimension to the vast tapestry of statistical relationships.

Harking back to the clarification of our literature review, it is noteworthy that while Smith et al. (2015) and Doe and Jones (2017) did not explicitly explore this enchanting connection, their insights into spectator behavior and economic impacts of sporting events propelled us to unravel this unanticipated correlation. As we reflect on these foundational studies, we are reminded that even in the rigorous domain of academic research, serendipitous discoveries and hidden associations often lurk beneath the surface, waiting to be unveiled.

The coefficient of determination (r-squared) of 0.7722210 not only exemplifies the substantial influence of 9th-grade student population on Yankees ticket sales, but also underscores the intricate interplay between educational dynamics and the fervor of baseball fandom. This finding reinforces the notion that the whims of educational demographics sway the currents of baseball spectacles to a considerable extent, akin to the gravitational forces orchestrating the graceful movements of celestial bodies in the expanse of the universe – a correlation of astronomical significance indeed.

The statistical significance of our results, as manifested by the p-value of less than 0.01, serves as a robust testament to the authenticity of the observed connection. Much like the alignment of stars in the night sky heralding a significant celestial event, the alignment of these variables is not a mere chance occurrence, but a compelling relationship demanding further elucidation.

The scatterplot presented in Fig. 1 lucidly portrays the positive correlation between public school 9th-grade students and New York Yankees ticket sales, akin to a mural capturing the harmonious dance of seemingly incongruous elements. It is a vivid testament to the unexpected interplay between the academic beginnings of young minds and the pulse of sporting fervor, serving as a gentle reminder that statistical analyses have a penchant for knitting together the most inconspicuous pairs in the grand fabric of correlations.

In conclusion, our study not only broadens the horizons of statistical inquiry, but also adds a touch of whimsy and intrigue to the otherwise empirical discourse. The association between educational enrollment and baseball spectatorship unfurls a spectrum of unexpected correlations, beckoning future researchers to delve deeper into the enigmatic nexus of academic milestones and athletic endeavors. As we peer through the lens of statistical exploration, we are reminded that even the most unassuming variables have the propensity to unveil captivating secrets, akin to the mysterious allure of hidden chambers in an ancient labyrinth.

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 Number of public school students in 9th grade and Ticket sales for New York Yankees games. 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]]
The Ninth Grade Nine Innings: Exploring the Correlation Between Public School Enrollment and Yankees Ticket Sales

[[ABSTRACT]]
This study delves into the intriguing relationship between the number of public school 9th-grade students and ticket sales for New York Yankees games. Leveraging data from the National Center for Education Statistics and Baseball-Reference.com, our research team conducted an in-depth analysis spanning the years 1990 to 2019. The results revealed a striking correlation coefficient of 0.8787610, with a statistically significant p-value of less than 0.01. Our findings suggest that as the population of 9th-grade students in public schools fluctuates, so too do the ticket sales for Yankees games. This unforeseen bond between educational enrollment and baseball spectatorship opens the door to a multitude of interpretations and speculations that extend beyond the confines of traditional academic discourse. Future research could investigate the underlying mechanisms driving this unexpected correlation and offer insight into the peculiar entanglement of academic beginnings and baseball fandom.

[[INTRDUCTION]]
The relationship between educational enrollment and extracurricular activities has long been a topic of curiosity, prompting researchers to delve into the peculiar connection between the two seemingly unrelated domains. In this study, we set out to explore the unexpected correlation between the number of public school 9th-grade students and ticket sales for New York Yankees games. It is indeed a curious conundrum, as one might expect the enrollment in secondary education to have little bearing on the spectatorship of America's favorite pastime. Nevertheless, the intersection of academia and athletics often yields surprising revelations, much like the synthesis of sodium and chlorine to form table salt - an unpredictable chemical reaction resulting in a familiar yet unconventional compound.
The empirical investigation of this correlation involved a thorough examination of data sourced from the National Center for Education Statistics and Baseball-Reference.com, covering a temporal expanse from 1990 to 2019. By leveraging sophisticated statistical analyses, our research team diligently combed through the myriad data points to unearth the underlying patterns and associations that may underpin this intriguing relationship. Much like a meticulous entomologist examining the delicate wings of a butterfly under a microscope, we scrutinized the intricacies of these datasets, in search of peculiarities that might shed light on the intertwined nature of academic enrollment and baseball attendance.
The revelations uncovered in this study present an intellectual puzzle akin to a complex jigsaw, where each piece represents a unique facet of the correlation between educational beginnings and baseball fandom. Our pursuit of knowledge led us to ascertain a correlation coefficient of 0.8787610, a figure that elicits a sense of bewilderment akin to observing a chemical reaction yield unexpected products. Furthermore, the statistically significant p-value of less than 0.01 reinforced the robustness of this correlation, underscoring the weight of this unpredictable relationship.
As we navigate through the labyrinth of data and statistical analyses, our findings carry profound implications that transcend the realms of academia and athletics. This unforeseen entanglement between educational demographics and sports spectatorship beckons further exploration, much like a mysterious labyrinth waiting to be unravelled.

[[RESULTS]]
The results of the analysis unveiled a striking correlation between the number of public school 9th-grade students and ticket sales for New York Yankees games for the period from 1990 to 2019. The correlation coefficient of 0.8787610 suggests a robust relationship between these seemingly disparate variables. It seems that as the cohort of 9th-grade students waxed and waned, so too did the enthusiasm for witnessing baseball heroics unfold in the hallowed grounds of Yankee Stadium.
The coefficient of determination (r-squared) of 0.7722210 indicated that approximately 77.22% of the variability in Yankees ticket sales could be explained by fluctuations in the population of 9th-grade students. This finding reinforces the notion that a substantial portion of the ebbs and flows of ticket sales can be ascribed to the undulating tides of educational demographics. It appears that the concept of pivotal ninth grade milestones extends beyond scholarly achievements and navigates into the realm of baseball spectacles.
The p-value of less than 0.01 fortified the statistical significance of this association, affirming that this correlation is not merely a fortuitous alignment (much like the fortuitous alignment of celestial bodies, yielding a phenomenon of astronomical significance), but rather a robust and meaningful relationship deserving of further inquiry.
In Fig. 1, the scatterplot graphically illustrates the pronounced positive correlation between public school 9th-grade students and New York Yankees ticket sales. It lays bare the alignment of these two variables, much like an astrologer revealing the intricate intertwining of stars in the night sky. The figure further corroborates the substantial influence of educational enrollment on the commercial success of baseball events, painting a vivid picture of the unexpected connection between academic beginnings and sporting fervor.
These findings shed light on the covert dance between education and entertainment, reminding us that even in the realm of statistical analyses, the most unsuspecting pairs can form a meaningful and influential bond. As we unravel this enigmatic entanglement, it becomes increasingly evident that the academic and athletic arenas are more intertwined than meets the eye, offering a tapestry of unexpected correlations for future investigation and speculation.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation has unveiled a robust and significant correlation between the number of public school 9th-grade students and ticket sales for New York Yankees games. This unexpected alliance between educational demographics and baseball spectatorship is reminiscent of an unlikely friendship formed between two disparate individuals at a quirky social gathering. The correlation coefficient of 0.8787610 illustrates a strong positive relationship, akin to the unanticipated bonding of two elements in a chemical compound.

The coefficient of determination (r-squared) of 0.7722210 further attests to the substantial influence of 9th-grade student population fluctuations on the variability of Yankees ticket sales, much like the unanticipated plot twists in a classic novel that keep readers on the edge of their seats. Additionally, the statistically significant p-value of less than 0.01 supports the compelling nature of this relationship – an unexpected find much like stumbling upon buried treasure in an unexplored territory.

The scatterplot in Fig. 1 visually encapsulates this correlation, laying it bare much like an unveiling of some clandestine mystery. As we unravel this scholarly puzzle, it becomes increasingly clear that the domain of academia and the realm of athletics intersect in unexpected ways, much like finding a secret passage between two distinct areas of a medieval castle.

In light of these intriguing findings, it is evident that our study presents a rich tapestry of unexpected correlations that extend beyond traditional academic musings. However, in the spirit of scholarly inquiry, we assert that no further research into this curious conundrum is necessary – for, after all, some correlations are best left unexplored, much like the enigmatic allure of uncharted territories.

In the words of William Shakespeare, "There are more things in heaven and earth, Horatio, than are dreamt of in your philosophy." And indeed, the entanglement of educational enrollment and baseball fervor stands as a testament to the captivating mysteries awaiting discovery in the world of research.

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited The Ninth Grade Nine Innings: Exploring the Correlation Between Public School Enrollment and Yankees Ticket Sales. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Educational Economics and Sports Sociology

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 Ninth Grade Nine Innings: Exploring the Correlation Between Public School Enrollment and Yankees Ticket Sales. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Educational and Sports Economics

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 Ninth Grade Nine Innings: Exploring the Correlation Between Public School Enrollment and Yankees Ticket Sales with an abstract of This study delves into the intriguing relationship between the number of public school 9th-grade students and ticket sales for New York Yankees games. Leveraging data from the National Center for Education Statistics and Baseball-Reference.com, our research team conducted an in-depth analysis spanning the years 1990 to 2019. The results revealed a striking correlation coefficient of 0.8787610, with a statistically significant p-value of less than 0.01. Our findings suggest that as the population of 9th-grade students in public schools fluctuates, so too do the ticket sales for Yankees games. This unforeseen bond between educational enrollment and baseball spectatorship opens the door to a multitude of interpretations and speculations that extend beyond the confines of traditional academic discourse. Future research could investigate the underlying mechanisms driving this unexpected correlation and offer insight into the peculiar entanglement of academic beginnings and baseball fandom.

ChatGPT:

public school enrollment, 9th grade students, New York Yankees, ticket sales, correlation analysis, National Center for Education Statistics, Baseball-Reference.com, educational enrollment, baseball spectatorship, academic beginnings, baseball fandom

*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

Number of public school students in 9th grade
Detailed data title: 9th grade enrollment in public elementary and secondary schools
Source: National Center for Education Statistics
See what else correlates with Number of public school students in 9th grade

Ticket sales for New York Yankees games
Detailed data title: Total tickets sold in home games for the New York Yankees
Source: Baseball-Reference.com
See what else correlates with Ticket sales for New York Yankees games

Correlation r = 0.8787610 (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 = 0.7722210 (Coefficient of determination)
This means 77.2% of the change in the one variable (i.e., Ticket sales for New York Yankees games) is predictable based on the change in the other (i.e., Number of public school students in 9th grade) over the 30 years from 1990 through 2019.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.7E-10.^Show 0.0000000001704624982913902500
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 0.88 in 1.7E-8% of random cases. Said differently, if you correlated 5,866,392,960 random variables^Note You don't actually need 5 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 29 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 29 because we have two variables measured over a period of 30 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.

[ 0.76, 0.94 ] 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.

	1990	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	2019
Number of public school students in 9th grade (Students)	3168630	3313240	3351830	3486960	3604120	3704460	3801220	3818840	3856460	3934880	3963290	4012350	4104720	4190240	4281340	4287120	4259910	4199830	4122550	4080020	4007860	3956990	3975260	3979520	4032530	4019480	3986170	3995570	4004440	4044230
Ticket sales for New York Yankees games (Tickets sold)	2006440	1863730	1748740	2416940	1675560	1705260	2250880	2580320	2955190	3292740	3055440	3264910	3465810	3465600	3775290	4090700	4248070	4271080	4298660	3719360	3765810	3653680	3542410	3279590	3401620	3193800	3063400	3154940	3482860	3304400

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.

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([3168630,3313240,3351830,3486960,3604120,3704460,3801220,3818840,3856460,3934880,3963290,4012350,4104720,4190240,4281340,4287120,4259910,4199830,4122550,4080020,4007860,3956990,3975260,3979520,4032530,4019480,3986170,3995570,4004440,4044230,])
array_2 = np.array([2006440,1863730,1748740,2416940,1675560,1705260,2250880,2580320,2955190,3292740,3055440,3264910,3465810,3465600,3775290,4090700,4248070,4271080,4298660,3719360,3765810,3653680,3542410,3279590,3401620,3193800,3063400,3154940,3482860,3304400,])
array_1_name = "Number of public school students in 9th grade"
array_2_name = "Ticket sales for New York Yankees games"

# 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 Number of public school students in 9th grade
Line chart for only Ticket sales for New York Yankees games
AI-generated correlation image
The spurious research paper: The Ninth Grade Nine Innings: Exploring the Correlation Between Public School Enrollment and Yankees Ticket Sales

View another random correlation

How fun was this correlation?

You're a rater extraordinaire!

Correlation ID: 1469 · Black Variable ID: 1307 · Red Variable ID: 4416


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