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Spurious correlation #1,092 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Total Runs Scored by Chicago Cubs Team in National League (Central and East Division) and the second variable is Wins for the Chicago White Sox.  The chart goes from 1975 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

The theory of baseball relativity states that as the Total Runs Scored by the Cubs increases, it creates a rippling effect in the baseball multiverse. This leads to a higher probability of White Sox pitchers throwing more strikes due to a cosmic alignment of pitching aerodynamics. The sheer excitement of increased run production in the city of Chicago causes a surge in the White Sox players' morale, leading to improved performance. Essentially, it's a case of crosstown baseball synergy where the Cubs' offensive output somehow channels its energy to propel the White Sox to victory.

Model: dalle-3
Prompt: [ Origami ] Generate an image of a cozy living room with a family seated on the couch. The family is engaged in watching the Chicago Cubs game on a large television. The room is filled with the aroma of freshly popped popcorn and the sound of potato chip bags being opened. The fans appear more focused on munching on their snacks than cheering for their team. Meanwhile, in the corner of the room, a smaller TV shows the Chicago White Sox game, with a few fans looking disappointed. Depict the frustration of local fans as they resort to snacking during games due to the scoring slump of the Cubs and the woes of the White Sox. 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 situation described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here is a situation: "Unbearable Curse: Chicago Cubs' Scoring Slump Linked to Chicago White Sox's Woes as Local Fans Report Increase in Snacking Time During Games!". Given that situation, which of the following image descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand and the tone of the explanation. Please respond with only one of the following potential descriptions: Hyper-realistic A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s Oragami A Discovery magazine cover image Oragami
ChatGPT: Oragami

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated and the explanation described. Do not reference graphs or charts; describe physical objects.
User prompt: Please describe a visual scene that depicts the following situation. Keep the description simple. "Unbearable Curse: Chicago Cubs' Scoring Slump Linked to Chicago White Sox's Woes as Local Fans Report Increase in Snacking Time During Games!"
ChatGPT: In a cozy living room, a family sits on the couch in front of the television, watching the Chicago Cubs play. The room is filled with the aroma of freshly popped popcorn and the sound of potato chip bags being opened. The fans seem more focused on munching on their snacks than cheering for their team. Meanwhile, the Chicago White Sox game is on a smaller TV in the corner, where the few fans left watch with a sense of disappointment. The scene highlights the frustration of local fans as they resort to snacking during games due to the scoring slump of the Cubs and the woes of the White Sox.

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: [ Oragami ] and depicting this scene: In a cozy living room, a family sits on the couch in front of the television, watching the Chicago Cubs play. The room is filled with the aroma of freshly popped popcorn and the sound of potato chip bags being opened. The fans seem more focused on munching on their snacks than cheering for their team. Meanwhile, the Chicago White Sox game is on a smaller TV in the corner, where the few fans left watch with a sense of disappointment. The scene highlights the frustration of local fans as they resort to snacking during games due to the scoring slump of the Cubs and the woes of the White Sox. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ Origami ] Generate an image of a cozy living room with a family seated on the couch. The family is engaged in watching the Chicago Cubs game on a large television. The room is filled with the aroma of freshly popped popcorn and the sound of potato chip bags being opened. The fans appear more focused on munching on their snacks than cheering for their team. Meanwhile, in the corner of the room, a smaller TV shows the Chicago White Sox game, with a few fans looking disappointed. Depict the frustration of local fans as they resort to snacking during games due to the scoring slump of the Cubs and the woes of the White Sox.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how increases in Total Runs Scored by Chicago Cubs Team in National League (Central and East Division) positively influenced Wins for the Chicago White Sox. Make it feel plausible.

AI academic paper

(Because p < 0.01)
Baseball Blues: Balancing the Bats and Brains of the Chicago Cubs and White Sox

Journal of Sports Psychology and Performance

Jan 2024

Reminder: This paper is AI-generated. Not real!
Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.




Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Total Runs Scored by Chicago Cubs Team in National League (Central and East Division) and Wins for the Chicago White Sox. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title an alliteration.

Your research team used data from Baseball Reference and Baseball-Reference.com to assess this nagging question. You found a correlation coefficient of 0.5563434 and p < 0.01 for 1975 to 2022.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
Baseball Blues: Balancing the Bats and Brains of the Chicago Cubs and White Sox

[[ABSTRACT]]
As the saying goes, "There's no crying in baseball," but perhaps there's a correlation worth crying over. This study delves into the relationship between the total runs scored by the Chicago Cubs team in the National League (Central and East Division) and the wins for the Chicago White Sox over a 47-year period. Utilizing data from Baseball Reference and Baseball-Reference.com, we calculated a correlation coefficient of 0.5563434, with a p-value less than 0.01, revealing a statistically significant connection between the two variables. While these findings may seem as unlikely as a triple play, the data speaks for itself. Our research sheds light on the nuances of baseball dynamics and may offer insights that are nothing to balk at for both Cubs and White Sox fanatics alike.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the introduction section of an academic research paper presenting the findings of the connection between Total Runs Scored by Chicago Cubs Team in National League (Central and East Division) and Wins for the Chicago White Sox. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Here is the title and abstract of the paper:
[[TITLE]]
Baseball Blues: Balancing the Bats and Brains of the Chicago Cubs and White Sox

[[ABSTRACT]]
As the saying goes, "There's no crying in baseball," but perhaps there's a correlation worth crying over. This study delves into the relationship between the total runs scored by the Chicago Cubs team in the National League (Central and East Division) and the wins for the Chicago White Sox over a 47-year period. Utilizing data from Baseball Reference and Baseball-Reference.com, we calculated a correlation coefficient of 0.5563434, with a p-value less than 0.01, revealing a statistically significant connection between the two variables. While these findings may seem as unlikely as a triple play, the data speaks for itself. Our research sheds light on the nuances of baseball dynamics and may offer insights that are nothing to balk at for both Cubs and White Sox fanatics alike.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

In the grand ol' game of baseball, the Chicago Cubs and the White Sox have captured the hearts and minds of fans across the Windy City and beyond. While some may assert that baseball is just a game of numbers, our research sought to explore the deeper connections and correlations between the performances of these two storied franchises. After all, it's not every day you get to analyze the intersection of runs, wins, and the enduring hopes of fans.

As the legendary Yogi Berra once quipped, "Baseball is 90% mental and the other half is physical." With this paradox in mind, we delved into the statistical realm to seek out potential relationships between the total runs scored by the Cubs in the National League (Central and East Division) and the victories accrued by the White Sox. Could it be that the fortunes of these teams are intertwined in ways not immediately visible to the scrutinizing eye?

Our inquiry was driven by a desire to uncover the underlying rhythms of the game, to untangle the complex web of statistical quirks that dictate the ebb and flow of baseball fortune. With the aid of data from Baseball Reference and Baseball-Reference.com, we navigated through an ocean of numbers, seeking the elusive pearls of correlation that might just shed light on a seemingly unending debate – are runs indeed the currency of victory?

The task at hand was formidable, yet we harnessed our batting gloves and statistical calculators and set out to navigate the diamond of data. As we honed in on the numbers, a tantalizing correlation coefficient of 0.5563434 emerged, beckoning us to contemplate the possibility of a robust link between runs and wins. The statistical gods had certainly smiled upon us, bestowing a p-value less than 0.01, a revelatory moment that seemed to suggest a connection as clear as a summer's day at Wrigley Field.

Therein lies the crux of our investigation, a quest to unravel the enigmatic dance of runs and victories, unfolding across a 47-year span that would make even the most diligent pitcher's arm grow weary. Our findings, as unexpected as a bunt turned home run, present a compelling case for the intertwined fates of these two Chicago titans. Indeed, the data spoke with an eloquence that transcended the cheers and groans of fans in packed stadiums, and we are compelled to share its voice with both the staunchest Cubs diehard and the most loyal White Sox devotee.

As we embark on this journey through the realm of baseball statistics, we invite readers to don their thinking caps and batting helmets, for our findings may be just the ticket to a new understanding of the game that holds us all in its delightful grip. So, without further ado, let us venture forth into the world of baseball's numerical symphony, drawing closer to unraveling the mystery of the interconnected histories of the Cubs and White Sox, and perhaps gaining some valuable insights along the way.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Total Runs Scored by Chicago Cubs Team in National League (Central and East Division) and Wins for the Chicago White Sox. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name some movies that you watched that are tangentially related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
Baseball Blues: Balancing the Bats and Brains of the Chicago Cubs and White Sox

[[ABSTRACT]]
As the saying goes, "There's no crying in baseball," but perhaps there's a correlation worth crying over. This study delves into the relationship between the total runs scored by the Chicago Cubs team in the National League (Central and East Division) and the wins for the Chicago White Sox over a 47-year period. Utilizing data from Baseball Reference and Baseball-Reference.com, we calculated a correlation coefficient of 0.5563434, with a p-value less than 0.01, revealing a statistically significant connection between the two variables. While these findings may seem as unlikely as a triple play, the data speaks for itself. Our research sheds light on the nuances of baseball dynamics and may offer insights that are nothing to balk at for both Cubs and White Sox fanatics alike.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the grand ol' game of baseball, the Chicago Cubs and the White Sox have captured the hearts and minds of fans across the Windy City and beyond. While some may assert that baseball is just a game of numbers, our research sought to explore the deeper connections and correlations between the performances of these two storied franchises. After all, it's not every day you get to analyze the intersection of runs, wins, and the enduring hopes of fans.
As the legendary Yogi Berra once quipped, "Baseball is 90% mental and the other half is physical." With this paradox in mind, we delved into the statistical realm to seek out potential relationships between the total runs scored by the Cubs in the National League (Central and East Division) and the victories accrued by the White Sox. Could it be that the fortunes of these teams are intertwined in ways not immediately visible to the scrutinizing eye?
Our inquiry was driven by a desire to uncover the underlying rhythms of the game, to untangle the complex web of statistical quirks that dictate the ebb and flow of baseball fortune. With the aid of data from Baseball Reference and Baseball-Reference.com, we navigated through an ocean of numbers, seeking the elusive pearls of correlation that might just shed light on a seemingly unending debate – are runs indeed the currency of victory?
The task at hand was formidable, yet we harnessed our batting gloves and statistical calculators and set out to navigate the diamond of data. As we honed in on the numbers, a tantalizing correlation coefficient of 0.5563434 emerged, beckoning us to contemplate the possibility of a robust link between runs and wins. The statistical gods had certainly smiled upon us, bestowing a p-value less than 0.01, a revelatory moment that seemed to suggest a connection as clear as a summer's day at Wrigley Field.
Therein lies the crux of our investigation, a quest to unravel the enigmatic dance of runs and victories, unfolding across a 47-year span that would make even the most diligent pitcher's arm grow weary. Our findings, as unexpected as a bunt turned home run, present a compelling case for the intertwined fates of these two Chicago titans. Indeed, the data spoke with an eloquence that transcended the cheers and groans of fans in packed stadiums, and we are compelled to share its voice with both the staunchest Cubs diehard and the most loyal White Sox devotee.
As we embark on this journey through the realm of baseball statistics, we invite readers to don their thinking caps and batting helmets, for our findings may be just the ticket to a new understanding of the game that holds us all in its delightful grip. So, without further ado, let us venture forth into the world of baseball's numerical symphony, drawing closer to unraveling the mystery of the interconnected histories of the Cubs and White Sox, and perhaps gaining some valuable insights along the way.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

Smith et al. (2015) examined the relationship between runs scored and wins in baseball, highlighting the intricate dance of statistics that govern the game. Their findings echoed the sentiments of many baseball enthusiasts, underscoring the importance of offensive prowess in securing victories on the diamond. Similarly, Doe and Jones (2018) delved into the nuances of baseball dynamics, unveiling the multifaceted nature of runs as a predictor of success for teams across various divisions.

As we navigate the landscape of baseball statistics, it is important to delve into the realm of literature that informs our understanding of the sport. In "Moneyball" by Michael Lewis, the author takes a deep dive into the world of baseball analytics, shedding light on the unorthodox strategies employed by the Oakland Athletics to defy conventional wisdom and achieve success on the field. The parallels between the quest for statistical advantage in "Moneyball" and our own pursuit of correlation between runs and wins are nothing short of striking – a home run of a revelation, if you will.

Taking a more philosophical approach to the game, "The Art of Fielding" by Chad Harbach offers a poignant exploration of the human drama inherent in baseball, intertwining the lives of its characters with the pursuit of excellence on the field. While not a statistical treatise per se, the novel captures the ethos of the game and the profound impact of victories and defeats on the players and fans alike.

In the realm of cinema, "A League of Their Own" presents a captivating narrative of the All-American Girls Professional Baseball League, offering a glimpse into the historical tapestry of baseball and the enduring passion it ignites. The film's portrayal of the trials and triumphs of women in baseball serves as a poignant reminder of the universal allure of the sport and the countless stories woven into its fabric.

As we wade through the literature and media that surround the world of baseball, it becomes evident that the quest for understanding transcends the confines of numerical analysis, embracing the emotional tapestry that intertwines with the ebb and flow of the game. Our journey to uncover the connection between the total runs scored by the Chicago Cubs and the wins for the White Sox is not merely a statistical endeavor; it is a testament to the enduring fascination with a sport that continues to capture the imagination of fans and researchers alike.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Total Runs Scored by Chicago Cubs Team in National League (Central and East Division) and Wins for the Chicago White Sox. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Baseball Reference and Baseball-Reference.com . You used data from 1975 to 2022

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Baseball Blues: Balancing the Bats and Brains of the Chicago Cubs and White Sox

[[ABSTRACT]]
As the saying goes, "There's no crying in baseball," but perhaps there's a correlation worth crying over. This study delves into the relationship between the total runs scored by the Chicago Cubs team in the National League (Central and East Division) and the wins for the Chicago White Sox over a 47-year period. Utilizing data from Baseball Reference and Baseball-Reference.com, we calculated a correlation coefficient of 0.5563434, with a p-value less than 0.01, revealing a statistically significant connection between the two variables. While these findings may seem as unlikely as a triple play, the data speaks for itself. Our research sheds light on the nuances of baseball dynamics and may offer insights that are nothing to balk at for both Cubs and White Sox fanatics alike.

[[INTRODUCTION]]
In the grand ol' game of baseball, the Chicago Cubs and the White Sox have captured the hearts and minds of fans across the Windy City and beyond. While some may assert that baseball is just a game of numbers, our research sought to explore the deeper connections and correlations between the performances of these two storied franchises. After all, it's not every day you get to analyze the intersection of runs, wins, and the enduring hopes of fans.
As the legendary Yogi Berra once quipped, "Baseball is 90% mental and the other half is physical." With this paradox in mind, we delved into the statistical realm to seek out potential relationships between the total runs scored by the Cubs in the National League (Central and East Division) and the victories accrued by the White Sox. Could it be that the fortunes of these teams are intertwined in ways not immediately visible to the scrutinizing eye?
Our inquiry was driven by a desire to uncover the underlying rhythms of the game, to untangle the complex web of statistical quirks that dictate the ebb and flow of baseball fortune. With the aid of data from Baseball Reference and Baseball-Reference.com, we navigated through an ocean of numbers, seeking the elusive pearls of correlation that might just shed light on a seemingly unending debate – are runs indeed the currency of victory?
The task at hand was formidable, yet we harnessed our batting gloves and statistical calculators and set out to navigate the diamond of data. As we honed in on the numbers, a tantalizing correlation coefficient of 0.5563434 emerged, beckoning us to contemplate the possibility of a robust link between runs and wins. The statistical gods had certainly smiled upon us, bestowing a p-value less than 0.01, a revelatory moment that seemed to suggest a connection as clear as a summer's day at Wrigley Field.
Therein lies the crux of our investigation, a quest to unravel the enigmatic dance of runs and victories, unfolding across a 47-year span that would make even the most diligent pitcher's arm grow weary. Our findings, as unexpected as a bunt turned home run, present a compelling case for the intertwined fates of these two Chicago titans. Indeed, the data spoke with an eloquence that transcended the cheers and groans of fans in packed stadiums, and we are compelled to share its voice with both the staunchest Cubs diehard and the most loyal White Sox devotee.
As we embark on this journey through the realm of baseball statistics, we invite readers to don their thinking caps and batting helmets, for our findings may be just the ticket to a new understanding of the game that holds us all in its delightful grip. So, without further ado, let us venture forth into the world of baseball's numerical symphony, drawing closer to unraveling the mystery of the interconnected histories of the Cubs and White Sox, and perhaps gaining some valuable insights along the way.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To uncover the mysterious dance of numbers that underpins the performances of the Chicago Cubs and the White Sox, our research team embarked on a journey that would rival even the most epic of extra-inning games. With a mixture of statistical savvy and unwavering enthusiasm, we undertook a methodical approach to synthesizing and analyzing the data with the precision of a Gold Glove-winning infielder.

Our dataset encompassed a generous swath of time, spanning from the year 1975 to 2022. This window of nearly half a century allowed us to capture the undulating tides of baseball fortune that ebbed and flowed through different eras, managerial strategies, and player lineups. Such a broad sampling of historical data provided the canvas upon which our statistical brushstrokes could unfurl, painting a comprehensive portrait of the interactions between runs scored and victories achieved.

The primary source of our data was the venerable Baseball Reference and its digital doppelganger, Baseball-Reference.com, where a trove of statistics awaited us like a hidden stash of home run balls hoarded by a hibernating bear. We meticulously extracted and curated the relevant information, cross-referencing it to ensure the accuracy and integrity of our dataset. Of course, in the spirit of thoroughness, we left no digital stone unturned in our pursuit of actionable data, scanning through a veritable league of baseball-related sources scattered across the vast expanse of the internet.

Having amassed our cornucopia of data, disentangling the intricate relationships between runs scored by the Cubs and the wins of the White Sox necessitated the summoning of formidable statistical tools and techniques. With the rigor and seriousness of a pitcher eyeing an opponent's batting stance, we employed correlation analysis to ascertain the degree of association between the two variables. The vaunted correlation coefficient, that esoteric number that would become the lodestar of our investigation, served to quantify the strength and direction of the linear relationship between total runs scored by the Cubs and the victories whispered into the annals of White Sox lore.

This statistical safari led us to a revelation that was as surprising as a utility player smashing a grand slam, as our efforts yielded a correlation coefficient of 0.5563434. This figure, imbued with significance akin to a walk-off home run, ignited our excitement and pushed us to the brink of statistical euphoria. And, to seal the deal as decisively as a swift double play, the p-value attached to our correlation coefficient strutted in at less than 0.01, deftly navigating the base paths to assert the statistical significance of the connection we had uncovered.

In striving to unshroud the enigmatic embrace of runs and victories, we approached our research with the solemnity of a ninth-inning save situation and the levity of a dugout full of wily pranksters. Our methodological journey, like a perfectly executed squeeze play, blended the precision of statistical analysis with the passion of baseball fandom, ultimately yielding a nuanced understanding of the intricate interplay between the Chicago Cubs and the White Sox. And as we present our findings, with as much exuberance as a post-game Gatorade shower, we invite the baseball community to ponder the implications of our discoveries and join us in celebrating the multifaceted tapestry of America's favorite pastime.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the results section of an academic research paper presenting the findings of the connection between Total Runs Scored by Chicago Cubs Team in National League (Central and East Division) and Wins for the Chicago White Sox. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Baseball Reference and Baseball-Reference.com .

For the time period 1975 to 2022, you found a correlation 0.5563434, r-squared of 0.3095180, 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]]
Baseball Blues: Balancing the Bats and Brains of the Chicago Cubs and White Sox

[[ABSTRACT]]
As the saying goes, "There's no crying in baseball," but perhaps there's a correlation worth crying over. This study delves into the relationship between the total runs scored by the Chicago Cubs team in the National League (Central and East Division) and the wins for the Chicago White Sox over a 47-year period. Utilizing data from Baseball Reference and Baseball-Reference.com, we calculated a correlation coefficient of 0.5563434, with a p-value less than 0.01, revealing a statistically significant connection between the two variables. While these findings may seem as unlikely as a triple play, the data speaks for itself. Our research sheds light on the nuances of baseball dynamics and may offer insights that are nothing to balk at for both Cubs and White Sox fanatics alike.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
In the grand ol' game of baseball, the Chicago Cubs and the White Sox have captured the hearts and minds of fans across the Windy City and beyond. While some may assert that baseball is just a game of numbers, our research sought to explore the deeper connections and correlations between the performances of these two storied franchises. After all, it's not every day you get to analyze the intersection of runs, wins, and the enduring hopes of fans.
As the legendary Yogi Berra once quipped, "Baseball is 90% mental and the other half is physical." With this paradox in mind, we delved into the statistical realm to seek out potential relationships between the total runs scored by the Cubs in the National League (Central and East Division) and the victories accrued by the White Sox. Could it be that the fortunes of these teams are intertwined in ways not immediately visible to the scrutinizing eye?
Our inquiry was driven by a desire to uncover the underlying rhythms of the game, to untangle the complex web of statistical quirks that dictate the ebb and flow of baseball fortune. With the aid of data from Baseball Reference and Baseball-Reference.com, we navigated through an ocean of numbers, seeking the elusive pearls of correlation that might just shed light on a seemingly unending debate – are runs indeed the currency of victory?
The task at hand was formidable, yet we harnessed our batting gloves and statistical calculators and set out to navigate the diamond of data. As we honed in on the numbers, a tantalizing correlation coefficient of 0.5563434 emerged, beckoning us to contemplate the possibility of a robust link between runs and wins. The statistical gods had certainly smiled upon us, bestowing a p-value less than 0.01, a revelatory moment that seemed to suggest a connection as clear as a summer's day at Wrigley Field.
Therein lies the crux of our investigation, a quest to unravel the enigmatic dance of runs and victories, unfolding across a 47-year span that would make even the most diligent pitcher's arm grow weary. Our findings, as unexpected as a bunt turned home run, present a compelling case for the intertwined fates of these two Chicago titans. Indeed, the data spoke with an eloquence that transcended the cheers and groans of fans in packed stadiums, and we are compelled to share its voice with both the staunchest Cubs diehard and the most loyal White Sox devotee.
As we embark on this journey through the realm of baseball statistics, we invite readers to don their thinking caps and batting helmets, for our findings may be just the ticket to a new understanding of the game that holds us all in its delightful grip. So, without further ado, let us venture forth into the world of baseball's numerical symphony, drawing closer to unraveling the mystery of the interconnected histories of the Cubs and White Sox, and perhaps gaining some valuable insights along the way.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

Our analysis revealed a statistically significant correlation coefficient of 0.5563434 between the total runs scored by the Chicago Cubs in the National League (Central and East Division) and the wins for the Chicago White Sox. This correlation, with an r-squared value of 0.3095180 and a p-value less than 0.01, suggests that there is a moderate positive relationship between these two variables.

Further support for this connection is depicted in Figure 1, where a scatterplot illustrates the clear relationship between runs scored by the Cubs and wins for the White Sox. As the data points cascade across the graph like a well-executed double play, the substantial correlation becomes evident, providing a visual testament to the intertwining fortunes of these two Chicago baseball powerhouses.

While these results may seem miraculously as fortuitous as a fan catching a foul ball, they speak to the potential impact of the Cubs' offense on the White Sox's success. Whether it's the wind blowing out at Wrigley Field or the elusive strategies employed by the Cubs, there appears to be a tangible link between the runs they produce and the victories accumulated by the White Sox.

In conclusion, our findings suggest that the fates of these two teams may be more entwined than meets the eye, providing ample food for thought for both Cubs and White Sox enthusiasts. As we revise our understanding of the intricate dance of runs and wins, we invite fellow researchers and baseball aficionados to join us in unraveling the captivating statistical story that underpins the harmonious, and sometimes discordant, symphony of America's favorite pastime.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Total Runs Scored by Chicago Cubs Team in National League (Central and East Division) and Wins for the Chicago White Sox. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Baseball Blues: Balancing the Bats and Brains of the Chicago Cubs and White Sox

[[ABSTRACT]]
As the saying goes, "There's no crying in baseball," but perhaps there's a correlation worth crying over. This study delves into the relationship between the total runs scored by the Chicago Cubs team in the National League (Central and East Division) and the wins for the Chicago White Sox over a 47-year period. Utilizing data from Baseball Reference and Baseball-Reference.com, we calculated a correlation coefficient of 0.5563434, with a p-value less than 0.01, revealing a statistically significant connection between the two variables. While these findings may seem as unlikely as a triple play, the data speaks for itself. Our research sheds light on the nuances of baseball dynamics and may offer insights that are nothing to balk at for both Cubs and White Sox fanatics alike.

[[LITERATURE REVIEW]]
Smith et al. (2015) examined the relationship between runs scored and wins in baseball, highlighting the intricate dance of statistics that govern the game. Their findings echoed the sentiments of many baseball enthusiasts, underscoring the importance of offensive prowess in securing victories on the diamond. Similarly, Doe and Jones (2018) delved into the nuances of baseball dynamics, unveiling the multifaceted nature of runs as a predictor of success for teams across various divisions.
As we navigate the landscape of baseball statistics, it is important to delve into the realm of literature that informs our understanding of the sport. In "Moneyball" by Michael Lewis, the author takes a deep dive into the world of baseball analytics, shedding light on the unorthodox strategies employed by the Oakland Athletics to defy conventional wisdom and achieve success on the field. The parallels between the quest for statistical advantage in "Moneyball" and our own pursuit of correlation between runs and wins are nothing short of striking – a home run of a revelation, if you will.
Taking a more philosophical approach to the game, "The Art of Fielding" by Chad Harbach offers a poignant exploration of the human drama inherent in baseball, intertwining the lives of its characters with the pursuit of excellence on the field. While not a statistical treatise per se, the novel captures the ethos of the game and the profound impact of victories and defeats on the players and fans alike.
In the realm of cinema, "A League of Their Own" presents a captivating narrative of the All-American Girls Professional Baseball League, offering a glimpse into the historical tapestry of baseball and the enduring passion it ignites. The film's portrayal of the trials and triumphs of women in baseball serves as a poignant reminder of the universal allure of the sport and the countless stories woven into its fabric.
As we wade through the literature and media that surround the world of baseball, it becomes evident that the quest for understanding transcends the confines of numerical analysis, embracing the emotional tapestry that intertwines with the ebb and flow of the game. Our journey to uncover the connection between the total runs scored by the Chicago Cubs and the wins for the White Sox is not merely a statistical endeavor; it is a testament to the enduring fascination with a sport that continues to capture the imagination of fans and researchers alike.

[[RESULTS]]
Our analysis revealed a statistically significant correlation coefficient of 0.5563434 between the total runs scored by the Chicago Cubs in the National League (Central and East Division) and the wins for the Chicago White Sox. This correlation, with an r-squared value of 0.3095180 and a p-value less than 0.01, suggests that there is a moderate positive relationship between these two variables.
Further support for this connection is depicted in Figure 1, where a scatterplot illustrates the clear relationship between runs scored by the Cubs and wins for the White Sox. As the data points cascade across the graph like a well-executed double play, the substantial correlation becomes evident, providing a visual testament to the intertwining fortunes of these two Chicago baseball powerhouses.
While these results may seem miraculously as fortuitous as a fan catching a foul ball, they speak to the potential impact of the Cubs' offense on the White Sox's success. Whether it's the wind blowing out at Wrigley Field or the elusive strategies employed by the Cubs, there appears to be a tangible link between the runs they produce and the victories accumulated by the White Sox.
In conclusion, our findings suggest that the fates of these two teams may be more entwined than meets the eye, providing ample food for thought for both Cubs and White Sox enthusiasts. As we revise our understanding of the intricate dance of runs and wins, we invite fellow researchers and baseball aficionados to join us in unraveling the captivating statistical story that underpins the harmonious, and sometimes discordant, symphony of America's favorite pastime.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our study sought to unravel the mysteries of the baseball universe by investigating the relationship between the total runs scored by the Chicago Cubs and the wins for the Chicago White Sox. The statistically significant correlation coefficient of 0.5563434 we uncovered seems as surprising as a hidden ball trick but aligns with previous research. Smith et al. (2015) and Doe and Jones (2018) also waded into the web of statistics surrounding baseball, echoing the importance of offensive performance in securing victories.

The parallels between our findings and "Moneyball" by Michael Lewis are undeniable. Just as the Oakland Athletics defied conventional wisdom through innovative strategies, our research reveals a nontraditional link between the Cubs’ scoring prowess and the White Sox's success. This correlation is not a mere statistical anomaly but an essential piece of the puzzle in the game of baseball.

Our results are not just numerical; they encompass the emotional tapestry that weaves through the baseball narrative. Much like "The Art of Fielding" by Chad Harbach and "A League of Their Own," our study delves beyond numbers and delves into the enduring passion for baseball. The emotional impact of victories and defeats on players and fans is as crucial as the statistical patterns on the field.

The moderate positive relationship we established between the Cubs' runs and the White Sox's wins, depicted in our scatterplot like a finely executed play, provides visual evidence to complement the numerical connection. It's heartening to see the tangible link between the Cubs' offensive prowess and the victories accumulated by the White Sox.

The winds blowing out at Wrigley Field and the elusive strategies employed by the Cubs may all play a role in this interconnected fate. We have shed light on the harmonious, and sometimes discordant, symphony of America's favorite pastime, offering ample food for thought for both Cubs and White Sox enthusiasts. As we continue this journey, we invite fellow researchers and baseball aficionados to join us in divulging the captivating statistical story that underpins the wondrous spectacle of baseball.


Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Total Runs Scored by Chicago Cubs Team in National League (Central and East Division) and Wins for the Chicago White Sox. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Baseball Blues: Balancing the Bats and Brains of the Chicago Cubs and White Sox

[[ABSTRACT]]
As the saying goes, "There's no crying in baseball," but perhaps there's a correlation worth crying over. This study delves into the relationship between the total runs scored by the Chicago Cubs team in the National League (Central and East Division) and the wins for the Chicago White Sox over a 47-year period. Utilizing data from Baseball Reference and Baseball-Reference.com, we calculated a correlation coefficient of 0.5563434, with a p-value less than 0.01, revealing a statistically significant connection between the two variables. While these findings may seem as unlikely as a triple play, the data speaks for itself. Our research sheds light on the nuances of baseball dynamics and may offer insights that are nothing to balk at for both Cubs and White Sox fanatics alike.

[[INTRDUCTION]]
In the grand ol' game of baseball, the Chicago Cubs and the White Sox have captured the hearts and minds of fans across the Windy City and beyond. While some may assert that baseball is just a game of numbers, our research sought to explore the deeper connections and correlations between the performances of these two storied franchises. After all, it's not every day you get to analyze the intersection of runs, wins, and the enduring hopes of fans.
As the legendary Yogi Berra once quipped, "Baseball is 90% mental and the other half is physical." With this paradox in mind, we delved into the statistical realm to seek out potential relationships between the total runs scored by the Cubs in the National League (Central and East Division) and the victories accrued by the White Sox. Could it be that the fortunes of these teams are intertwined in ways not immediately visible to the scrutinizing eye?
Our inquiry was driven by a desire to uncover the underlying rhythms of the game, to untangle the complex web of statistical quirks that dictate the ebb and flow of baseball fortune. With the aid of data from Baseball Reference and Baseball-Reference.com, we navigated through an ocean of numbers, seeking the elusive pearls of correlation that might just shed light on a seemingly unending debate – are runs indeed the currency of victory?
The task at hand was formidable, yet we harnessed our batting gloves and statistical calculators and set out to navigate the diamond of data. As we honed in on the numbers, a tantalizing correlation coefficient of 0.5563434 emerged, beckoning us to contemplate the possibility of a robust link between runs and wins. The statistical gods had certainly smiled upon us, bestowing a p-value less than 0.01, a revelatory moment that seemed to suggest a connection as clear as a summer's day at Wrigley Field.
Therein lies the crux of our investigation, a quest to unravel the enigmatic dance of runs and victories, unfolding across a 47-year span that would make even the most diligent pitcher's arm grow weary. Our findings, as unexpected as a bunt turned home run, present a compelling case for the intertwined fates of these two Chicago titans. Indeed, the data spoke with an eloquence that transcended the cheers and groans of fans in packed stadiums, and we are compelled to share its voice with both the staunchest Cubs diehard and the most loyal White Sox devotee.
As we embark on this journey through the realm of baseball statistics, we invite readers to don their thinking caps and batting helmets, for our findings may be just the ticket to a new understanding of the game that holds us all in its delightful grip. So, without further ado, let us venture forth into the world of baseball's numerical symphony, drawing closer to unraveling the mystery of the interconnected histories of the Cubs and White Sox, and perhaps gaining some valuable insights along the way.

[[RESULTS]]
Our analysis revealed a statistically significant correlation coefficient of 0.5563434 between the total runs scored by the Chicago Cubs in the National League (Central and East Division) and the wins for the Chicago White Sox. This correlation, with an r-squared value of 0.3095180 and a p-value less than 0.01, suggests that there is a moderate positive relationship between these two variables.
Further support for this connection is depicted in Figure 1, where a scatterplot illustrates the clear relationship between runs scored by the Cubs and wins for the White Sox. As the data points cascade across the graph like a well-executed double play, the substantial correlation becomes evident, providing a visual testament to the intertwining fortunes of these two Chicago baseball powerhouses.
While these results may seem miraculously as fortuitous as a fan catching a foul ball, they speak to the potential impact of the Cubs' offense on the White Sox's success. Whether it's the wind blowing out at Wrigley Field or the elusive strategies employed by the Cubs, there appears to be a tangible link between the runs they produce and the victories accumulated by the White Sox.
In conclusion, our findings suggest that the fates of these two teams may be more entwined than meets the eye, providing ample food for thought for both Cubs and White Sox enthusiasts. As we revise our understanding of the intricate dance of runs and wins, we invite fellow researchers and baseball aficionados to join us in unraveling the captivating statistical story that underpins the harmonious, and sometimes discordant, symphony of America's favorite pastime.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In summary, our study has revealed a statistically significant correlation between the total runs scored by the Chicago Cubs in the National League (Central and East Division) and the wins for the Chicago White Sox. This intriguing connection, akin to a well-timed squeeze play, suggests a moderate positive relationship between the offensive performance of the Cubs and the success of the White Sox. The results depicted in Figure 1 provide a visual representation of this correlation, as clear as a perfectly executed double steal.

The implications of these findings may prompt one to ponder the whims of fate and the capricious winds at Wrigley Field. It seems that the Cubs' offensive prowess may indeed have an impact on the fortunes of their crosstown rivals, echoing the sentiment that in baseball, as in life, one team's success can sometimes be another's downfall.

As we reflect on the complex interplay of statistics and sporting triumph, one cannot help but marvel at the seemingly serendipitous nature of this correlation. Are the Cubs' runs truly the currency of victory for the White Sox, or is there a deeper, more intricate narrative at play? These questions beckon further exploration and contemplation, reminding us that the fascinating world of baseball is as enigmatic as a knuckleball on a windy day.

In conclusion, while our study sheds light on the intertwined fates of these two iconic teams, it also raises further questions and opportunities for future research. However, pondering the reams of data, the subtle nuances of the game, and the ever-elusive search for the perfect statistical home run, one is left wondering – is there any need for further research, or have we hit a grand slam with these findings? Indeed, it seems that the time has come to halt our analytical at-bats and revel in the delightful mystery of baseball statistics. After all, as the old adage goes, "Sometimes you win, sometimes you lose, sometimes it rains." It's time to call this game and pack away the calculators; the diamond of statistical inquiry has revealed its secrets.


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 Baseball Blues: Balancing the Bats and Brains of the Chicago Cubs and White Sox. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Sports Psychology and Performance


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 Baseball Blues: Balancing the Bats and Brains of the Chicago Cubs and White Sox. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Sports Psychology and Statistical Analysis


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 Baseball Blues: Balancing the Bats and Brains of the Chicago Cubs and White Sox with an abstract of As the saying goes, "There's no crying in baseball," but perhaps there's a correlation worth crying over. This study delves into the relationship between the total runs scored by the Chicago Cubs team in the National League (Central and East Division) and the wins for the Chicago White Sox over a 47-year period. Utilizing data from Baseball Reference and Baseball-Reference.com, we calculated a correlation coefficient of 0.5563434, with a p-value less than 0.01, revealing a statistically significant connection between the two variables. While these findings may seem as unlikely as a triple play, the data speaks for itself. Our research sheds light on the nuances of baseball dynamics and may offer insights that are nothing to balk at for both Cubs and White Sox fanatics alike.

ChatGPT:

Chicago Cubs, White Sox, baseball, runs scored, wins, correlation, National League, Central Division, East Division, Baseball Reference, dynamics, statistics, baseball dynamics

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



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Data details

Total Runs Scored by Chicago Cubs Team in National League (Central and East Division)
Source: Baseball Reference
See what else correlates with Total Runs Scored by Chicago Cubs Team in National League (Central and East Division)

Wins for the Chicago White Sox
Detailed data title: The total number of season wins for the Chicago White Sox
Source: Baseball-Reference.com
See what else correlates with Wins for the Chicago White Sox

Correlation r = 0.5563434 (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 = 0.3095180 (Coefficient of determination)
This means 31% of the change in the one variable (i.e., Wins for the Chicago White Sox) is predictable based on the change in the other (i.e., Total Runs Scored by Chicago Cubs Team in National League (Central and East Division)) over the 48 years from 1975 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 4.03E-5. 0.0000402758087859161660000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.56 in 0.00403% of random cases. Said differently, if you correlated 24,829 random variables You don't actually need 24 thousand variables to find a correlation like this one. 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.

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 47 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 47 because we have two variables measured over a period of 48 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.

[ 0.32, 0.73 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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


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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
197519761977197819791980198119821983198419851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007200820092010201120122013201420152016201720182019202020212022
Total Runs Scored by Chicago Cubs Team in National League (Central and East Division) (Runs Scored)712611692664706614370676701762686680720660702690695593738500693772687831747764777706724789703716752855707685654613602614689808822761814265705657
Wins for the Chicago White Sox (Game wins)756490717370548799748572777169948786946768858080759583818683999072897988798563737678676272359381




Why this works

  1. Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
  2. Lack of causal connection: There is probably Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
    no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
  3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
    p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
  4. Confounding variable: 2020 is particularly different from the other years on this graph. Confounding variables (like global pandemics) will cause two variables to look connected when in fact a "sneaky third" variable is influencing both of them behind the scenes.




Try it yourself

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

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

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

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

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

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

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

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

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


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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([712,611,692,664,706,614,370,676,701,762,686,680,720,660,702,690,695,593,738,500,693,772,687,831,747,764,777,706,724,789,703,716,752,855,707,685,654,613,602,614,689,808,822,761,814,265,705,657,])
array_2 = np.array([75,64,90,71,73,70,54,87,99,74,85,72,77,71,69,94,87,86,94,67,68,85,80,80,75,95,83,81,86,83,99,90,72,89,79,88,79,85,63,73,76,78,67,62,72,35,93,81,])
array_1_name = "Total Runs Scored by Chicago Cubs Team in National League (Central and East Division)"
array_2_name = "Wins for the Chicago White Sox"

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

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



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

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

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

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Correlation ID: 1092 · Black Variable ID: 206 · Red Variable ID: 4303
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