Spurious correlation #3,187 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of umpires and referees in Louisiana and the second variable is Prudential Financial's stock price (PRU). The chart goes from 2005 to 2020, 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 The number of umpires and referees in Louisiana and the second variable is Prudential Financial's stock price (PRU). The chart goes from 2005 to 2020, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the number of umpires and referees in Louisiana increased, there was a corresponding rise in enthusiasm for officiating. This spike in enthusiasm led to a surge in whistle production, thereby increasing the demand for brass, a key component in whistles. Unbeknownst to many, Prudential Financial had recently invested heavily in brass mining and production. As the demand for brass skyrocketed, so did Prudential Financial's stock price (PRU).

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a stark, concrete sports field in Louisiana, dominated by a group of umpires and referees clad in minimalist, monochromatic uniforms. They stand in formation, each blowing their whistles with precision as they make calls. In the background, a towering, Brutalist-inspired stock ticker prominently displays Prudential Financial's rising stock price. Meanwhile, a group of stoic investors observes the correlation between fair play in sports and the financial market, their approval evident in measured nods. The scene is infused with a sense of disciplined order and the symbiotic relationship between sportsmanship and financial success. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: The number of umpires and referees in Louisiana and Prudential Financial's stock price (PRU). 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: Brutalism inspired by bauhaus Steampunk Brutalism Steampunk
ChatGPT: Brutalism

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both The number of umpires and referees in Louisiana and Prudential Financial's stock price (PRU), in the following situation: As the number of umpires and referees in Louisiana increased, so did Prudential Financial's stock price, because investors saw the correlation as a sign of more fair play in the financial markets.. Keep the description simple.
ChatGPT: In Louisiana, a growing cluster of umpires and referees can be seen gathered on the field, blowing their whistles and making calls with precision. In the background, a stock ticker prominently displays Prudential Financial's rising stock price, with investors nodding in approval as they watch the correlation between fair play in sports and the financial market.

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: [ Brutalism ] and depicting this scene: In Louisiana, a growing cluster of umpires and referees can be seen gathered on the field, blowing their whistles and making calls with precision. In the background, a stock ticker prominently displays Prudential Financial's rising stock price, with investors nodding in approval as they watch the correlation between fair play in sports and the financial market. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a stark, concrete sports field in Louisiana, dominated by a group of umpires and referees clad in minimalist, monochromatic uniforms. They stand in formation, each blowing their whistles with precision as they make calls. In the background, a towering, Brutalist-inspired stock ticker prominently displays Prudential Financial's rising stock price. Meanwhile, a group of stoic investors observes the correlation between fair play in sports and the financial market, their approval evident in measured nods. The scene is infused with a sense of disciplined order and the symbiotic relationship between sportsmanship and financial success.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in The number of umpires and referees in Louisiana caused Prudential Financial's stock price (PRU) to increase.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)

Calling the Shots: Umpiring the Stock Market - An Examination of the Connection between Referees in Louisiana and Prudential Financial's Stock Price

The Journal of Financial Officiating and Market Influences

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 goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between The number of umpires and referees in Louisiana and Prudential Financial's stock price (PRU). 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 cartoons and childrens' shows that you watched that are related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
"Calling the Shots: Umpiring the Stock Market - An Examination of the Connection between Referees in Louisiana and Prudential Financial's Stock Price"

[[ABSTRACT]]
This study investigates the intriguing relationship between the number of umpires and referees in the state of Louisiana and the stock price of Prudential Financial (PRU). Utilizing data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we conducted a thorough analysis spanning from 2005 to 2020. Our findings reveal a correlation coefficient of 0.6664522 with a statistically significant p-value of less than 0.01, suggesting a noteworthy association between these seemingly unrelated variables. This paper delves into this unconventional connection, shedding light on the potential influence of the officiating world on the financial realm, and perhaps hinting at the concept that "calling the shots" may extend beyond the baseball diamond.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Introduction
The intersection of sports and finance is a field ripe for exploration, and this study aims to uncover a peculiar relationship that raises eyebrows – the connection between the number of umpires and referees in the state of Louisiana and the stock price of Prudential Financial (PRU). It is a well-established fact that researchers often find correlations that are puzzling and seemingly nonsensical, but upon closer examination, unveil unexpected connections among variables.
While the casual observer may raise an incredulous eyebrow at the notion of tying the movements of stock prices to the number of officials in the world of sports, this study dives deep into the statistical rabbit hole to reveal surprising insights. This investigation is no mere game of chance; rather, it is rooted in robust statistical analysis spanning a 15-year period.
The relationship between umpires and referees and financial markets may seem as unrelated as a termite and a traffic cone, but recent studies have shown that seemingly incongruous variables can form a bizarrely harmonious pair, much like peanut butter and pickles (a culinary combination worth studying in its own right).
In this paper, we will dissect the underlying data with the precision of a surgeon wielding a scalpel, aiming to illuminate the potential influence of the officiating world on the ever-fluctuating landscape of the financial realm. The findings could serve as a cautionary tale to those who dismiss seemingly quirky associations as mere statistical noise – for buried beneath the surface, there may be diamonds in the rough, or in this case, diamonds in the rough calls made by umpires.
Moreover, this study adds a new dimension to the concept of "calling the shots." While traditionally reserved for the domain of sports, our analyses suggest that the phrase might extend beyond the baseball diamond and basketball court – it may have implications for the stock market as well. It appears that the act of making decisions on the field may echo in the halls of finance, not unlike the reverberation of a well-struck gong in a silent auditorium.
We kick off this journey with an exploration of statistics, economic theory, and the unyielding pursuit of uncovering unexpected, yet captivating, relationships – a pursuit akin to chasing down an illusive statistical unicorn. Join us as we embark on this whimsical statistical adventure, where the numbers tell tales just as enchanting as those found in the pages of a beloved fairy tale – albeit with a healthy dose of p-values and correlation coefficients.
In the proceeding sections, we methodically dissect the data, uncovering the intricate dance between the number of umpires and referees in Louisiana and the fluctuations of Prudential Financial's stock price. By the end of this quest, we aim to leave readers with a newfound appreciation for the exhilarating world of research, where the seemingly improbable can, at times, defy expectations and reveal itself as a symphony of unexpected harmony.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The connection between seemingly disparate entities has long been a source of intrigue in the world of research. In their seminal work, Smith and Doe (2010) delved into the concept of unexpected correlations, highlighting the potential for surprising connections to emerge from the depths of statistical analyses. Moreover, Jones et al. (2015) bolstered this perspective, emphasizing the importance of exploring unconventional relationships and the valuable insights they may yield.

Turning to the world of finance, "The Random Walk Down Wall Street" by Burton Malkiel presents a comprehensive exploration of stock market dynamics, offering valuable insights into the complex interplay of factors influencing stock prices. In a similar vein, "Freakonomics" by Steven D. Levitt and Stephen J. Dubner uncovers the hidden forces shaping economic outcomes, demonstrating the potential for non-traditional variables to exert significant influence in financial markets.

On the fictional front, "The Hitchhiker's Guide to the Galaxy" by Douglas Adams provides a whimsical exploration of the interconnectedness of seemingly unrelated phenomena, offering a lighthearted take on the potential for hidden relationships to underpin the fabric of existence. Additionally, the "Harry Potter" series by J.K. Rowling weaves a tale of magical connections and unexpected alliances, serving as a metaphorical nod to the surprising associations that may emerge in the world of statistical analyses.

Delving into the realm of childhood nostalgia, "Scooby-Doo" and "The Magic School Bus" stand as emblematic shows depicting the exploration of mysteries and unseen connections, serving as a playful reminder of the captivating nature of uncovering unexpected relationships. These cultural touchstones playfully mirror the spirit of this investigation, infusing a sense of wonder and curiosity into the pursuit of uncovering the link between umpires and Prudential Financial's stock price.

As we navigate the landscape of academic literature and cultural references, it becomes evident that the pursuit of understanding hidden linkages holds a place of significance in both scholarly pursuits and popular discourse. With this backdrop in mind, we embark on our own journey to unravel the enigmatic ties between the number of umpires and referees in Louisiana and the stock price of Prudential Financial, aiming to shed light on the enthralling world of statistical anomalies and unexpected connections.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between The number of umpires and referees in Louisiana and Prudential Financial's stock price (PRU). 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 Bureau of Larbor Statistics and LSEG Analytics (Refinitiv) . You used data from 2005 to 2020

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]]
"Calling the Shots: Umpiring the Stock Market - An Examination of the Connection between Referees in Louisiana and Prudential Financial's Stock Price"

[[ABSTRACT]]
This study investigates the intriguing relationship between the number of umpires and referees in the state of Louisiana and the stock price of Prudential Financial (PRU). Utilizing data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we conducted a thorough analysis spanning from 2005 to 2020. Our findings reveal a correlation coefficient of 0.6664522 with a statistically significant p-value of less than 0.01, suggesting a noteworthy association between these seemingly unrelated variables. This paper delves into this unconventional connection, shedding light on the potential influence of the officiating world on the financial realm, and perhaps hinting at the concept that "calling the shots" may extend beyond the baseball diamond.

[[INTRODUCTION]]
Introduction
The intersection of sports and finance is a field ripe for exploration, and this study aims to uncover a peculiar relationship that raises eyebrows – the connection between the number of umpires and referees in the state of Louisiana and the stock price of Prudential Financial (PRU). It is a well-established fact that researchers often find correlations that are puzzling and seemingly nonsensical, but upon closer examination, unveil unexpected connections among variables.
While the casual observer may raise an incredulous eyebrow at the notion of tying the movements of stock prices to the number of officials in the world of sports, this study dives deep into the statistical rabbit hole to reveal surprising insights. This investigation is no mere game of chance; rather, it is rooted in robust statistical analysis spanning a 15-year period.
The relationship between umpires and referees and financial markets may seem as unrelated as a termite and a traffic cone, but recent studies have shown that seemingly incongruous variables can form a bizarrely harmonious pair, much like peanut butter and pickles (a culinary combination worth studying in its own right).
In this paper, we will dissect the underlying data with the precision of a surgeon wielding a scalpel, aiming to illuminate the potential influence of the officiating world on the ever-fluctuating landscape of the financial realm. The findings could serve as a cautionary tale to those who dismiss seemingly quirky associations as mere statistical noise – for buried beneath the surface, there may be diamonds in the rough, or in this case, diamonds in the rough calls made by umpires.
Moreover, this study adds a new dimension to the concept of "calling the shots." While traditionally reserved for the domain of sports, our analyses suggest that the phrase might extend beyond the baseball diamond and basketball court – it may have implications for the stock market as well. It appears that the act of making decisions on the field may echo in the halls of finance, not unlike the reverberation of a well-struck gong in a silent auditorium.
We kick off this journey with an exploration of statistics, economic theory, and the unyielding pursuit of uncovering unexpected, yet captivating, relationships – a pursuit akin to chasing down an illusive statistical unicorn. Join us as we embark on this whimsical statistical adventure, where the numbers tell tales just as enchanting as those found in the pages of a beloved fairy tale – albeit with a healthy dose of p-values and correlation coefficients.
In the proceeding sections, we methodically dissect the data, uncovering the intricate dance between the number of umpires and referees in Louisiana and the fluctuations of Prudential Financial's stock price. By the end of this quest, we aim to leave readers with a newfound appreciation for the exhilarating world of research, where the seemingly improbable can, at times, defy expectations and reveal itself as a symphony of unexpected harmony.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

Data Collection:
The data for this study was sourced from various authoritative platforms, including the Bureau of Labor Statistics, LSEG Analytics (Refinitiv), and various other reputable sources on the World Wide Web. We sought to cast as wide a net as possible to capture the true essence of the relationship between the number of umpires and referees in Louisiana and the stock price of Prudential Financial. Our research team scoured through the digital expanse with the enthusiasm of a dedicated angler seeking the prized catch, albeit in a sea of statistical data. It is worth noting that the seductive lure of online information can be as thrilling as reeling in a big fish, albeit with fewer tales to tell at the local fisherman's tavern.

Data Period:
The time frame for our investigation spans from 2005 to 2020, offering a comprehensive view of the landscape over a 15-year period. This expanse of time allowed us to witness the undulating waves of changes in both the officiating world and the financial market, akin to observing the ebb and flow of the statistical tides.

Statistical Analysis:
Our approach to analyzing the collected data was tantamount to a carefully choreographed dance, as we sought to unveil the nuances of the connection between the variables at hand. We applied robust statistical methods, including correlation analysis, to quantify the relationship between the number of umpires and referees in Louisiana and the stock price of Prudential Financial. It should be noted that correlation does not imply causation, much like the mere presence of an umbrella does not summon rainclouds, though the two may often coincide.

Correlation Coefficient and P-Value:
The correlation coefficient between the aforementioned variables was found to be 0.6664522, a figure that raised an eyebrow or two among our research team. Furthermore, the resulting p-value was less than 0.01, firmly establishing the statistical significance of the relationship under scrutiny. It's as if statistical significance whispered in our ears like a cryptic riddle, challenging us to unravel the secrets hidden within the data.

Regression Analysis:
Additionally, we employed regression analysis to delve deeper into the dynamics of this peculiar connection. The regression models served as our trusty guide, navigating the labyrinth of numerical relationships with the precision of a seasoned cartographer mapping out unexplored territories. The resulting coefficients provided us with valuable insights, akin to uncovering buried treasure in the vast expanse of numerical analyses.

Controls and Extraneous Variables:
We also took meticulous care to account for potential confounding factors and extraneous variables that could influence the relationship under examination. Much like a vigilant gardener plucking out invasive weeds threatening the beauty of a carefully tended flowerbed, we meticulously pruned our models to ensure a clear view of the targeted relationship.

In essence, our methodology was guided by a zealous pursuit of unraveling enigmatic connections, combined with the rigor demanded by the hallowed halls of statistical inquiry. Through this whimsical statistical odyssey, we sought not only to illuminate the relationship between these seemingly disparate variables but also to instill a sense of wonder in the marvelous, often confounding, world of research.

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

Please make up the results section of an academic research paper presenting the findings of the connection between The number of umpires and referees in Louisiana and Prudential Financial's stock price (PRU). 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 Bureau of Larbor Statistics and LSEG Analytics (Refinitiv) .

For the time period 2005 to 2020, you found a correlation 0.6664522, r-squared of 0.4441585, 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]]
"Calling the Shots: Umpiring the Stock Market - An Examination of the Connection between Referees in Louisiana and Prudential Financial's Stock Price"

[[ABSTRACT]]
This study investigates the intriguing relationship between the number of umpires and referees in the state of Louisiana and the stock price of Prudential Financial (PRU). Utilizing data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we conducted a thorough analysis spanning from 2005 to 2020. Our findings reveal a correlation coefficient of 0.6664522 with a statistically significant p-value of less than 0.01, suggesting a noteworthy association between these seemingly unrelated variables. This paper delves into this unconventional connection, shedding light on the potential influence of the officiating world on the financial realm, and perhaps hinting at the concept that "calling the shots" may extend beyond the baseball diamond.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Introduction
The intersection of sports and finance is a field ripe for exploration, and this study aims to uncover a peculiar relationship that raises eyebrows – the connection between the number of umpires and referees in the state of Louisiana and the stock price of Prudential Financial (PRU). It is a well-established fact that researchers often find correlations that are puzzling and seemingly nonsensical, but upon closer examination, unveil unexpected connections among variables.
While the casual observer may raise an incredulous eyebrow at the notion of tying the movements of stock prices to the number of officials in the world of sports, this study dives deep into the statistical rabbit hole to reveal surprising insights. This investigation is no mere game of chance; rather, it is rooted in robust statistical analysis spanning a 15-year period.
The relationship between umpires and referees and financial markets may seem as unrelated as a termite and a traffic cone, but recent studies have shown that seemingly incongruous variables can form a bizarrely harmonious pair, much like peanut butter and pickles (a culinary combination worth studying in its own right).
In this paper, we will dissect the underlying data with the precision of a surgeon wielding a scalpel, aiming to illuminate the potential influence of the officiating world on the ever-fluctuating landscape of the financial realm. The findings could serve as a cautionary tale to those who dismiss seemingly quirky associations as mere statistical noise – for buried beneath the surface, there may be diamonds in the rough, or in this case, diamonds in the rough calls made by umpires.
Moreover, this study adds a new dimension to the concept of "calling the shots." While traditionally reserved for the domain of sports, our analyses suggest that the phrase might extend beyond the baseball diamond and basketball court – it may have implications for the stock market as well. It appears that the act of making decisions on the field may echo in the halls of finance, not unlike the reverberation of a well-struck gong in a silent auditorium.
We kick off this journey with an exploration of statistics, economic theory, and the unyielding pursuit of uncovering unexpected, yet captivating, relationships – a pursuit akin to chasing down an illusive statistical unicorn. Join us as we embark on this whimsical statistical adventure, where the numbers tell tales just as enchanting as those found in the pages of a beloved fairy tale – albeit with a healthy dose of p-values and correlation coefficients.
In the proceeding sections, we methodically dissect the data, uncovering the intricate dance between the number of umpires and referees in Louisiana and the fluctuations of Prudential Financial's stock price. By the end of this quest, we aim to leave readers with a newfound appreciation for the exhilarating world of research, where the seemingly improbable can, at times, defy expectations and reveal itself as a symphony of unexpected harmony.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The analysis of the relationship between the number of umpires and referees in Louisiana and Prudential Financial's stock price yielded some eyebrow-raising results. Our findings revealed a correlation coefficient of 0.6664522, which can only be described as devilishly intriguing. With an r-squared value of 0.4441585, we can confidently say that about 44.4% of the movement in Prudential Financial's stock price can be explained by the number of officials in the sports realm. And to add a cherry on top of this statistical sundae, the p-value was less than 0.01, indicating that this relationship is indeed statistically significant.

The scatterplot (Fig. 1) visually portrays this surprisingly strong correlation, effectively illustrating the dance between the number of umpires and referees in Louisiana and the fluctuations in Prudential Financial's stock price. It's almost as if the stock price and referees were engaged in a spirited tango on the graph, with each step mirroring the other in a mesmerizing display of statistical synchrony.

This unanticipated correlation may prompt some to question the fundamental fabric of causation and coincidence, but such is the enigmatic nature of statistics. As the great Mark Twain once said, "Facts are stubborn, but statistics are pliable," and indeed, in the realm of research, the unexpected often trumps the mundane.

The results of our study provide a peek behind the curtain of the financial world, hinting at the potential influence of the officiating universe on stock market movements. While it might seem as odd a pairing as pineapples on pizza, the statistical evidence tells a different tale – a tale of improbable yet tantalizing connections that tickle the fancy of both researchers and curious minds alike.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between The number of umpires and referees in Louisiana and Prudential Financial's stock price (PRU). 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]]
"Calling the Shots: Umpiring the Stock Market - An Examination of the Connection between Referees in Louisiana and Prudential Financial's Stock Price"

[[ABSTRACT]]
This study investigates the intriguing relationship between the number of umpires and referees in the state of Louisiana and the stock price of Prudential Financial (PRU). Utilizing data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we conducted a thorough analysis spanning from 2005 to 2020. Our findings reveal a correlation coefficient of 0.6664522 with a statistically significant p-value of less than 0.01, suggesting a noteworthy association between these seemingly unrelated variables. This paper delves into this unconventional connection, shedding light on the potential influence of the officiating world on the financial realm, and perhaps hinting at the concept that "calling the shots" may extend beyond the baseball diamond.

[[LITERATURE REVIEW]]
The connection between seemingly disparate entities has long been a source of intrigue in the world of research. In their seminal work, Smith and Doe (2010) delved into the concept of unexpected correlations, highlighting the potential for surprising connections to emerge from the depths of statistical analyses. Moreover, Jones et al. (2015) bolstered this perspective, emphasizing the importance of exploring unconventional relationships and the valuable insights they may yield.
Turning to the world of finance, "The Random Walk Down Wall Street" by Burton Malkiel presents a comprehensive exploration of stock market dynamics, offering valuable insights into the complex interplay of factors influencing stock prices. In a similar vein, "Freakonomics" by Steven D. Levitt and Stephen J. Dubner uncovers the hidden forces shaping economic outcomes, demonstrating the potential for non-traditional variables to exert significant influence in financial markets.
On the fictional front, "The Hitchhiker's Guide to the Galaxy" by Douglas Adams provides a whimsical exploration of the interconnectedness of seemingly unrelated phenomena, offering a lighthearted take on the potential for hidden relationships to underpin the fabric of existence. Additionally, the "Harry Potter" series by J.K. Rowling weaves a tale of magical connections and unexpected alliances, serving as a metaphorical nod to the surprising associations that may emerge in the world of statistical analyses.
Delving into the realm of childhood nostalgia, "Scooby-Doo" and "The Magic School Bus" stand as emblematic shows depicting the exploration of mysteries and unseen connections, serving as a playful reminder of the captivating nature of uncovering unexpected relationships. These cultural touchstones playfully mirror the spirit of this investigation, infusing a sense of wonder and curiosity into the pursuit of uncovering the link between umpires and Prudential Financial's stock price.
As we navigate the landscape of academic literature and cultural references, it becomes evident that the pursuit of understanding hidden linkages holds a place of significance in both scholarly pursuits and popular discourse. With this backdrop in mind, we embark on our own journey to unravel the enigmatic ties between the number of umpires and referees in Louisiana and the stock price of Prudential Financial, aiming to shed light on the enthralling world of statistical anomalies and unexpected connections.

[[RESULTS]]
The analysis of the relationship between the number of umpires and referees in Louisiana and Prudential Financial's stock price yielded some eyebrow-raising results. Our findings revealed a correlation coefficient of 0.6664522, which can only be described as devilishly intriguing. With an r-squared value of 0.4441585, we can confidently say that about 44.4% of the movement in Prudential Financial's stock price can be explained by the number of officials in the sports realm. And to add a cherry on top of this statistical sundae, the p-value was less than 0.01, indicating that this relationship is indeed statistically significant.
The scatterplot (Fig. 1) visually portrays this surprisingly strong correlation, effectively illustrating the dance between the number of umpires and referees in Louisiana and the fluctuations in Prudential Financial's stock price. It's almost as if the stock price and referees were engaged in a spirited tango on the graph, with each step mirroring the other in a mesmerizing display of statistical synchrony.
This unanticipated correlation may prompt some to question the fundamental fabric of causation and coincidence, but such is the enigmatic nature of statistics. As the great Mark Twain once said, "Facts are stubborn, but statistics are pliable," and indeed, in the realm of research, the unexpected often trumps the mundane.
The results of our study provide a peek behind the curtain of the financial world, hinting at the potential influence of the officiating universe on stock market movements. While it might seem as odd a pairing as pineapples on pizza, the statistical evidence tells a different tale – a tale of improbable yet tantalizing connections that tickle the fancy of both researchers and curious minds alike.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

In the grand tapestry of statistical analyses, our study embarks on a whimsical journey through the uncharted territory of unexpected connections, guided by the spirit of curiosity and the pursuit of knowledge. Our findings, which unveiled a devilishly intriguing correlation coefficient of 0.6664522 between the number of umpires and referees in Louisiana and Prudential Financial's stock price, echo the sentiments espoused by Smith and Doe (2010). In their insightful work, the authors drew attention to the potential for surprising correlations to emerge, a sentiment our results wholeheartedly support.

As we reflect on the tango-like dance depicted in the scatterplot (Fig. 1), illustrating the mesmerizing synchrony between stock price fluctuations and the presence of referees, we are reminded of the spirit of exploration encapsulated in "The Hitchhiker's Guide to the Galaxy" by Douglas Adams. Much like the intrepid adventurers in the narrative, our foray into the world of statistical anomalies has unearthed a captivating link that defies conventional wisdom.

The statistically significant p-value, akin to a rare gem hidden amidst layers of data, invites contemplation on the often enigmatic nature of statistical findings. This discovery aligns with the principles elucidated by Jones et al. (2015), underscoring the significance of unraveling unconventional relationships and the unique insights they may yield. Furthermore, the substantial r-squared value of 0.4441585 reinforces the notion that almost half of Prudential Financial's stock price movements can be elucidated by the ebb and flow of officials populating the sports domain.

In the words of Steven D. Levitt and Stephen J. Dubner in "Freakonomics," our study peels back the layers of economic outcomes, shedding light on the unexpected forces that shape the financial landscape. Just as the Hogwarts School of Witchcraft and Wizardry in J.K. Rowling's "Harry Potter" series uncovers the magical connections and unexpected alliances, our analysis uncovers an improbable yet tantalizing relationship that teeters on the edge of disbelief and fascination.

The whimsical nod to childhood classics, such as "Scooby-Doo" and "The Magic School Bus," playfully mirrors the lighthearted spirit of our investigation, injecting a sense of wonder into the pursuit of unraveling the enigmatic ties between seemingly disparate phenomena.

The findings of our research, though seemingly whimsical, offer a thought-provoking glimpse into the enthralling realm of statistical anomalies and unforeseen connections. This unanticipated linkage tantalizes the inquisitive mind and beckons a deeper exploration of the intricate web of relationships that underpin the fabric of existence, financial or otherwise.

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between The number of umpires and referees in Louisiana and Prudential Financial's stock price (PRU). 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]]
"Calling the Shots: Umpiring the Stock Market - An Examination of the Connection between Referees in Louisiana and Prudential Financial's Stock Price"

[[ABSTRACT]]
This study investigates the intriguing relationship between the number of umpires and referees in the state of Louisiana and the stock price of Prudential Financial (PRU). Utilizing data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we conducted a thorough analysis spanning from 2005 to 2020. Our findings reveal a correlation coefficient of 0.6664522 with a statistically significant p-value of less than 0.01, suggesting a noteworthy association between these seemingly unrelated variables. This paper delves into this unconventional connection, shedding light on the potential influence of the officiating world on the financial realm, and perhaps hinting at the concept that "calling the shots" may extend beyond the baseball diamond.

[[INTRDUCTION]]
Introduction
The intersection of sports and finance is a field ripe for exploration, and this study aims to uncover a peculiar relationship that raises eyebrows – the connection between the number of umpires and referees in the state of Louisiana and the stock price of Prudential Financial (PRU). It is a well-established fact that researchers often find correlations that are puzzling and seemingly nonsensical, but upon closer examination, unveil unexpected connections among variables.
While the casual observer may raise an incredulous eyebrow at the notion of tying the movements of stock prices to the number of officials in the world of sports, this study dives deep into the statistical rabbit hole to reveal surprising insights. This investigation is no mere game of chance; rather, it is rooted in robust statistical analysis spanning a 15-year period.
The relationship between umpires and referees and financial markets may seem as unrelated as a termite and a traffic cone, but recent studies have shown that seemingly incongruous variables can form a bizarrely harmonious pair, much like peanut butter and pickles (a culinary combination worth studying in its own right).
In this paper, we will dissect the underlying data with the precision of a surgeon wielding a scalpel, aiming to illuminate the potential influence of the officiating world on the ever-fluctuating landscape of the financial realm. The findings could serve as a cautionary tale to those who dismiss seemingly quirky associations as mere statistical noise – for buried beneath the surface, there may be diamonds in the rough, or in this case, diamonds in the rough calls made by umpires.
Moreover, this study adds a new dimension to the concept of "calling the shots." While traditionally reserved for the domain of sports, our analyses suggest that the phrase might extend beyond the baseball diamond and basketball court – it may have implications for the stock market as well. It appears that the act of making decisions on the field may echo in the halls of finance, not unlike the reverberation of a well-struck gong in a silent auditorium.
We kick off this journey with an exploration of statistics, economic theory, and the unyielding pursuit of uncovering unexpected, yet captivating, relationships – a pursuit akin to chasing down an illusive statistical unicorn. Join us as we embark on this whimsical statistical adventure, where the numbers tell tales just as enchanting as those found in the pages of a beloved fairy tale – albeit with a healthy dose of p-values and correlation coefficients.
In the proceeding sections, we methodically dissect the data, uncovering the intricate dance between the number of umpires and referees in Louisiana and the fluctuations of Prudential Financial's stock price. By the end of this quest, we aim to leave readers with a newfound appreciation for the exhilarating world of research, where the seemingly improbable can, at times, defy expectations and reveal itself as a symphony of unexpected harmony.

[[RESULTS]]
The analysis of the relationship between the number of umpires and referees in Louisiana and Prudential Financial's stock price yielded some eyebrow-raising results. Our findings revealed a correlation coefficient of 0.6664522, which can only be described as devilishly intriguing. With an r-squared value of 0.4441585, we can confidently say that about 44.4% of the movement in Prudential Financial's stock price can be explained by the number of officials in the sports realm. And to add a cherry on top of this statistical sundae, the p-value was less than 0.01, indicating that this relationship is indeed statistically significant.
The scatterplot (Fig. 1) visually portrays this surprisingly strong correlation, effectively illustrating the dance between the number of umpires and referees in Louisiana and the fluctuations in Prudential Financial's stock price. It's almost as if the stock price and referees were engaged in a spirited tango on the graph, with each step mirroring the other in a mesmerizing display of statistical synchrony.
This unanticipated correlation may prompt some to question the fundamental fabric of causation and coincidence, but such is the enigmatic nature of statistics. As the great Mark Twain once said, "Facts are stubborn, but statistics are pliable," and indeed, in the realm of research, the unexpected often trumps the mundane.
The results of our study provide a peek behind the curtain of the financial world, hinting at the potential influence of the officiating universe on stock market movements. While it might seem as odd a pairing as pineapples on pizza, the statistical evidence tells a different tale – a tale of improbable yet tantalizing connections that tickle the fancy of both researchers and curious minds alike.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study uncovers a statistically significant correlation between the number of umpires and referees in Louisiana and the stock price of Prudential Financial. The devilishly intriguing correlation coefficient of 0.6664522, accompanied by a statistically significant p-value of less than 0.01, paints a compelling picture of the dance between the officiating world and stock market fluctuations. This finding is akin to stumbling upon a unicorn in a statistical forest, a rare and whimsical discovery that challenges conventional wisdom.

Our results, illustrated by the spirited tango between stock prices and referees in our scatterplot, add a new layer of intrigue to the concept of "calling the shots." It appears that decisions made on the field may carry a weight that extends far beyond the boundaries of the sports arena, much like a butterfly flapping its wings on one side of the world leading to a hurricane on the other (albeit in a financial sense, and without the catastrophic consequences).

In the grand theater of statistics, where outliers often steal the spotlight, our findings shine a spotlight on the charmingly unconventional relationship between seemingly disparate variables. This study serves as a reminder that within the vast landscape of research, there are hidden gems waiting to be unearthed, buried beneath layers of data and statistical analyses.

While our findings provide a thought-provoking insight into the interconnectedness of seemingly unrelated domains, we assert that no further research is needed in this area. Sometimes, it is best to leave the statistical unicorn grazing in its enchanted meadow, content in the knowledge that we have peered through the looking glass and glimpsed the unexpected harmony between the officiating world and the stock market.

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 Calling the Shots: Umpiring the Stock Market - An Examination of the Connection between Referees in Louisiana and Prudential Financial's Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Financial Officiating and Market Influences

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 Calling the Shots: Umpiring the Stock Market - An Examination of the Connection between Referees in Louisiana and Prudential Financial's Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Financial Referee Studies

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Calling the Shots: Umpiring the Stock Market - An Examination of the Connection between Referees in Louisiana and Prudential Financial's Stock Price with an abstract of This study investigates the intriguing relationship between the number of umpires and referees in the state of Louisiana and the stock price of Prudential Financial (PRU). Utilizing data from the Bureau of Labor Statistics and LSEG Analytics (Refinitiv), we conducted a thorough analysis spanning from 2005 to 2020. Our findings reveal a correlation coefficient of 0.6664522 with a statistically significant p-value of less than 0.01, suggesting a noteworthy association between these seemingly unrelated variables. This paper delves into this unconventional connection, shedding light on the potential influence of the officiating world on the financial realm, and perhaps hinting at the concept that "calling the shots" may extend beyond the baseball diamond.

ChatGPT:

"umpires in Louisiana, referees, stock price, Prudential Financial, correlation, Bureau of Labor Statistics, LSEG Analytics, Refinitiv, statistical analysis, financial influence, officiating world, stock market connection, relationship between umpires and stock price, Louisiana referees and stock price"

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

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Data details

The number of umpires and referees in Louisiana
Detailed data title: BLS estimate of umpires, referees, and other sports officials in Louisiana
Source: Bureau of Larbor Statistics
See what else correlates with The number of umpires and referees in Louisiana

Prudential Financial's stock price (PRU)
Detailed data title: Opening price of Prudential Financial (PRU) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: ^{See full details} Via Microsoft Excel Stockhistory function

See what else correlates with Prudential Financial's stock price (PRU)

Correlation r = 0.6664522 (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 = 0.4441585 (Coefficient of determination)
This means 44.4% of the change in the one variable (i.e., Prudential Financial's stock price (PRU)) is predictable based on the change in the other (i.e., The number of umpires and referees in Louisiana) over the 16 years from 2005 through 2020.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.0048.^Show 0.0048144415274429410000000000
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 0.67 in 0.48% of random cases. Said differently, if you correlated 208 random variables^Note Which I absolutely did.
with the same 15 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 15 because we have two variables measured over a period of 16 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.

[ 0.25, 0.87 ] 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.

	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
The number of umpires and referees in Louisiana (Laborers)	60	330	440	370	220	200	260	280	210	230	370	270	420	440	340	210
Prudential Financial's stock price (PRU) (Stock price)	54.85	73.8	85.97	93.01	30.29	50.43	59.43	51.47	54.94	91.5	91.01	79.55	105.23	115.17	79.94	94.04

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.

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([60,330,440,370,220,200,260,280,210,230,370,270,420,440,340,210,])
array_2 = np.array([54.85,73.8,85.97,93.01,30.29,50.43,59.43,51.47,54.94,91.5,91.01,79.55,105.23,115.17,79.94,94.04,])
array_1_name = "The number of umpires and referees in Louisiana"
array_2_name = "Prudential Financial's stock price (PRU)"

# 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)
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Line chart for only The number of umpires and referees in Louisiana
Line chart for only Prudential Financial's stock price (PRU)
AI-generated correlation image
The spurious research paper: Calling the Shots: Umpiring the Stock Market - An Examination of the Connection between Referees in Louisiana and Prudential Financial's Stock Price

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Correlation ID: 3187 · Black Variable ID: 17583 · Red Variable ID: 1804


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