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Spurious correlation #3,661 · 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 industrial engineers in Illinois and the second variable is Runs Scored by Winning Team in World Series.  The chart goes from 2003 to 2013, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As the number of industrial engineers in Illinois increased, so did the efficiency of the state's production lines. This led to a surplus of baseball bats being manufactured, ultimately giving the winning team in the World Series a competitive edge in scoring runs. It's proof that when it comes to baseball, you can always count on engineers to 'pitch' in and help the game 'swing' in the right direction!

Model: dalle-3
Prompt: Create an unsettling, brutalist-inspired scene that showcases the chaotic atmosphere on an Illinois baseball field. Fabricate an image of a team of engineers engrossed in meticulously adjusting the pitching machines and scrutinizing the players' batting techniques. The cluttered and overly complicated setup should evoke a sense of disarray, with an emphasis on the raw, imposing architecture. In the backdrop, the scoreboard displays a low number of runs for the winning team in the World Series. As the engineers leave the field, the players gain the freedom to focus solely on hitting the ball, resulting in a significant increase in runs scored by the winning team, as indicated on the scoreboard. Craft a visual representation that communicates the fusion of brutalist elements with the chaotic ambiance of the baseball field. 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 industrial engineers in Illinois and Runs Scored by Winning Team in World Series. 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: Charcoal Brutalism High-tech Symbolism a funny image macro
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 industrial engineers in Illinois and Runs Scored by Winning Team in World Series, in the following situation: Because the number of industrial engineers in Illinois decreased, the winning team in the World Series scored more runs. Industrial engineers are notorious for over-engineering things, so with fewer of them around, baseball players were able to focus on just hitting the ball instead of worrying about unnecessary efficiency improvements.. Keep the description simple.
ChatGPT: On the baseball field in Illinois, a team of engineers is seen meticulously adjusting the pitching machines and scrutinizing the players' batting techniques, creating a cluttered and overly complicated setup. Meanwhile, the scoreboard behind them displays a low number of runs for the winning team in the World Series. As the engineers leave the field, the players are now able to focus solely on hitting the ball, resulting in the scoreboard showing a significant increase in runs scored by the winning team.

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: On the baseball field in Illinois, a team of engineers is seen meticulously adjusting the pitching machines and scrutinizing the players' batting techniques, creating a cluttered and overly complicated setup. Meanwhile, the scoreboard behind them displays a low number of runs for the winning team in the World Series. As the engineers leave the field, the players are now able to focus solely on hitting the ball, resulting in the scoreboard showing a significant increase in runs scored by the winning team. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an unsettling, brutalist-inspired scene that showcases the chaotic atmosphere on an Illinois baseball field. Fabricate an image of a team of engineers engrossed in meticulously adjusting the pitching machines and scrutinizing the players' batting techniques. The cluttered and overly complicated setup should evoke a sense of disarray, with an emphasis on the raw, imposing architecture. In the backdrop, the scoreboard displays a low number of runs for the winning team in the World Series. As the engineers leave the field, the players gain the freedom to focus solely on hitting the ball, resulting in a significant increase in runs scored by the winning team, as indicated on the scoreboard. Craft a visual representation that communicates the fusion of brutalist elements with the chaotic ambiance of the baseball field.

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

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

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how increases in The number of industrial engineers in Illinois positively influenced Runs Scored by Winning Team in World Series. Include one good pun.

AI academic paper

(Because p < 0.01)
Engineered for Success: The Correlation Between Industrial Engineers in Illinois and Runs Scored by the Winning Team in the World Series

Journal of Industrial Engineering and Sports Analytics

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 witty academic researcher. Your writing sounds like it belongs in a statistics journal.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between The number of industrial engineers in Illinois and Runs Scored by Winning Team in World Series. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title a clever pun.

Your research team used data from Bureau of Larbor Statistics and Wikipedia to assess this nagging question. You found a correlation coefficient of 0.8541714 and p < 0.01 for 2003 to 2013.

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]]
"Engineered for Success: The Correlation Between Industrial Engineers in Illinois and Runs Scored by the Winning Team in the World Series"

[[ABSTRACT]]
This paper delves into the seemingly unrelated worlds of industrial engineering and America's favorite pastime, baseball, to uncover a surprising connection. By harnessing the power of statistical analysis, data from the Bureau of Labor Statistics and Wikipedia were meticulously scrutinized to explore the relationship between the number of industrial engineers in Illinois and the runs scored by the winning team in the World Series. The findings reveal a noteworthy correlation coefficient of 0.8541714 and a p-value of less than 0.01 for the years 2003 to 2013, indicating a robust statistical significance. The implications of these results are as intriguing as the unexpected connection itself, opening the door to further investigation into the potential influences of industrial engineering on baseball performance. This research sheds light on the hidden forces at play in the grand theater of sports, proving that, in the game of statistics, every data point truly does count.


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

Please make up the introduction section of an academic research paper presenting the findings of the connection between The number of industrial engineers in Illinois and Runs Scored by Winning Team in World Series. 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.

Here is the title and abstract of the paper:
[[TITLE]]
"Engineered for Success: The Correlation Between Industrial Engineers in Illinois and Runs Scored by the Winning Team in the World Series"

[[ABSTRACT]]
This paper delves into the seemingly unrelated worlds of industrial engineering and America's favorite pastime, baseball, to uncover a surprising connection. By harnessing the power of statistical analysis, data from the Bureau of Labor Statistics and Wikipedia were meticulously scrutinized to explore the relationship between the number of industrial engineers in Illinois and the runs scored by the winning team in the World Series. The findings reveal a noteworthy correlation coefficient of 0.8541714 and a p-value of less than 0.01 for the years 2003 to 2013, indicating a robust statistical significance. The implications of these results are as intriguing as the unexpected connection itself, opening the door to further investigation into the potential influences of industrial engineering on baseball performance. This research sheds light on the hidden forces at play in the grand theater of sports, proving that, in the game of statistics, every data point truly does count.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

In the annals of statistical research, there exist unprecedented occurrences where seemingly unrelated variables reveal unsuspected correlations. In this study, we embark on an exploration of the uncharted territory between the world of industrial engineering and the hallowed grounds of baseball, seeking to uncover an unlikely relationship between the number of industrial engineers in Illinois and the runs scored by the winning team in the World Series. The audacious nature of this inquiry rests upon the determination to peel back the layers of convention and unearth the buried gems of statistical significance.

While the sports world and the realm of industrial engineering may appear as distinct as chalk and cheese, our foray into this uncommon junction is rooted in the fervent belief that beneath the veneer of disparate disciplines lie hidden connections waiting to be unearthed. With unyielding dedication to the cause of statistical investigation, we set out to dissect the data encapsulating the number of industrial engineers in Illinois and the runs amassed by the victorious team in the pinnacle of baseball competition - the World Series.

This research stands as a testament to the adage that in the labyrinthine maze of statistical analysis, the journey is as enlightening as the destination. As we navigate the corridors of empirical inquiry, we remain steadfast in our pursuit of understanding the intricacies of this incongruous link. The significance of our findings not only resides in the numbers themselves but extends to the tantalizing prospect of unraveling the covert influences shaping the narrative of sporting triumphs.

The alliance between industrial engineering and the cherished pursuit of the national pastime may appear as unlikely bedfellows, yet the tantalizing prospect of uncovering an unexpected kinship lures us into the realm of statistical exploration. The rich tapestry of connections and consequences woven through the interplay of these variables beckons us to delve deeper into the recesses of this captivating affair, where the cadence of industrial prowess and the rhythm of baseball finesse converge in a symphony of statistical revelation.

As we embark on this exhilarating expedition, we are poised to confront not only the empirical truths nestled within our data but also the whimsical nature of statistical serendipity. The pursuit of knowledge must not be circumscribed by the confines of conventional wisdom; rather, it necessitates a willingness to embrace the unlikeliest of associations and unfurl the enigmatic veil of statistical anomalies. With this spirit of inquiry as our guiding beacon, we set sail on a voyage that endeavors to illuminate the shadowy recesses of statistical obscurity, affirming that within the labyrinth of empirical pursuit, the most unforeseen connections may yield the most profound insights.


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between The number of industrial engineers in Illinois and Runs Scored by Winning Team in World Series. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
"Engineered for Success: The Correlation Between Industrial Engineers in Illinois and Runs Scored by the Winning Team in the World Series"

[[ABSTRACT]]
This paper delves into the seemingly unrelated worlds of industrial engineering and America's favorite pastime, baseball, to uncover a surprising connection. By harnessing the power of statistical analysis, data from the Bureau of Labor Statistics and Wikipedia were meticulously scrutinized to explore the relationship between the number of industrial engineers in Illinois and the runs scored by the winning team in the World Series. The findings reveal a noteworthy correlation coefficient of 0.8541714 and a p-value of less than 0.01 for the years 2003 to 2013, indicating a robust statistical significance. The implications of these results are as intriguing as the unexpected connection itself, opening the door to further investigation into the potential influences of industrial engineering on baseball performance. This research sheds light on the hidden forces at play in the grand theater of sports, proving that, in the game of statistics, every data point truly does count.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the annals of statistical research, there exist unprecedented occurrences where seemingly unrelated variables reveal unsuspected correlations. In this study, we embark on an exploration of the uncharted territory between the world of industrial engineering and the hallowed grounds of baseball, seeking to uncover an unlikely relationship between the number of industrial engineers in Illinois and the runs scored by the winning team in the World Series. The audacious nature of this inquiry rests upon the determination to peel back the layers of convention and unearth the buried gems of statistical significance.
While the sports world and the realm of industrial engineering may appear as distinct as chalk and cheese, our foray into this uncommon junction is rooted in the fervent belief that beneath the veneer of disparate disciplines lie hidden connections waiting to be unearthed. With unyielding dedication to the cause of statistical investigation, we set out to dissect the data encapsulating the number of industrial engineers in Illinois and the runs amassed by the victorious team in the pinnacle of baseball competition - the World Series.
This research stands as a testament to the adage that in the labyrinthine maze of statistical analysis, the journey is as enlightening as the destination. As we navigate the corridors of empirical inquiry, we remain steadfast in our pursuit of understanding the intricacies of this incongruous link. The significance of our findings not only resides in the numbers themselves but extends to the tantalizing prospect of unraveling the covert influences shaping the narrative of sporting triumphs.
The alliance between industrial engineering and the cherished pursuit of the national pastime may appear as unlikely bedfellows, yet the tantalizing prospect of uncovering an unexpected kinship lures us into the realm of statistical exploration. The rich tapestry of connections and consequences woven through the interplay of these variables beckons us to delve deeper into the recesses of this captivating affair, where the cadence of industrial prowess and the rhythm of baseball finesse converge in a symphony of statistical revelation.
As we embark on this exhilarating expedition, we are poised to confront not only the empirical truths nestled within our data but also the whimsical nature of statistical serendipity. The pursuit of knowledge must not be circumscribed by the confines of conventional wisdom; rather, it necessitates a willingness to embrace the unlikeliest of associations and unfurl the enigmatic veil of statistical anomalies. With this spirit of inquiry as our guiding beacon, we set sail on a voyage that endeavors to illuminate the shadowy recesses of statistical obscurity, affirming that within the labyrinth of empirical pursuit, the most unforeseen connections may yield the most profound insights.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The investigation of the relationship between industrial engineering and baseball performance is a pursuit that has attracted the attention of researchers from various disciplines. In "Smith et al." (2010), the authors examine the impact of engineering principles on athletic endeavors, shedding light on the potential influences that extend beyond conventional understanding. Similarly, "Doe and Johnson" (2015) delve into the intricate interplay of technical knowledge and sports dynamics, presenting an insightful exploration of the unexplored territory where industrial engineering intersects with the realm of competitive athletics.

In the realm of literature, pertinent works such as "Industrial Engineering for Dummies" (Rowling, 2003) and "Moneyball: The Art of Winning an Unfair Game" (Lewis, 2003) offer valuable perspectives on the amalgamation of technical expertise and athletic prowess. The former provides a comprehensive overview of industrial engineering principles, while the latter presents a captivating narrative of statistical innovation within the context of baseball, unveiling the unorthodox strategies that revolutionized the perception of success in sports.

Moreover, the fictional narrative "The Legend of Sleepy Hollow" (Irving, 1820) offers a whimsical depiction of a headless horseman haunting a village, drawing an unexpected parallel to the ethereal nature of statistical relationships. While seemingly divergent in nature, the elements of unpredictability and serendipitous connections resonate with the theme of this research inquiry.

In the digital sphere, the viral phenomenon of "Distracted Boyfriend" meme serves as a metaphorical testament to the allure of unexpected attractions, mirroring the unpredictable allure of statistical coalescence in the unconventional pairing of industrial engineering and baseball performance. The captivating allure of this meme finds an uncanny parallel in the enigmatic nature of statistical associations, where seemingly incongruous variables coalesce to form intriguing relationships.

As this research converges upon the interface of industrial engineering and the sport of baseball, it is imperative to harness the wealth of knowledge and entertainment that spans across disciplinary boundaries. Through this eclectic array of literary and cultural dimensions, the stage is set for a vibrant examination of the underlying influences that govern the entwined narrative of industrial prowess and sporting triumph.


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

Please make up the methodology section of an academic research paper presenting the findings of the connection between The number of industrial engineers in Illinois and Runs Scored by Winning Team in World Series. 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 Wikipedia . You used data from 2003 to 2013

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]]
"Engineered for Success: The Correlation Between Industrial Engineers in Illinois and Runs Scored by the Winning Team in the World Series"

[[ABSTRACT]]
This paper delves into the seemingly unrelated worlds of industrial engineering and America's favorite pastime, baseball, to uncover a surprising connection. By harnessing the power of statistical analysis, data from the Bureau of Labor Statistics and Wikipedia were meticulously scrutinized to explore the relationship between the number of industrial engineers in Illinois and the runs scored by the winning team in the World Series. The findings reveal a noteworthy correlation coefficient of 0.8541714 and a p-value of less than 0.01 for the years 2003 to 2013, indicating a robust statistical significance. The implications of these results are as intriguing as the unexpected connection itself, opening the door to further investigation into the potential influences of industrial engineering on baseball performance. This research sheds light on the hidden forces at play in the grand theater of sports, proving that, in the game of statistics, every data point truly does count.

[[INTRODUCTION]]
In the annals of statistical research, there exist unprecedented occurrences where seemingly unrelated variables reveal unsuspected correlations. In this study, we embark on an exploration of the uncharted territory between the world of industrial engineering and the hallowed grounds of baseball, seeking to uncover an unlikely relationship between the number of industrial engineers in Illinois and the runs scored by the winning team in the World Series. The audacious nature of this inquiry rests upon the determination to peel back the layers of convention and unearth the buried gems of statistical significance.
While the sports world and the realm of industrial engineering may appear as distinct as chalk and cheese, our foray into this uncommon junction is rooted in the fervent belief that beneath the veneer of disparate disciplines lie hidden connections waiting to be unearthed. With unyielding dedication to the cause of statistical investigation, we set out to dissect the data encapsulating the number of industrial engineers in Illinois and the runs amassed by the victorious team in the pinnacle of baseball competition - the World Series.
This research stands as a testament to the adage that in the labyrinthine maze of statistical analysis, the journey is as enlightening as the destination. As we navigate the corridors of empirical inquiry, we remain steadfast in our pursuit of understanding the intricacies of this incongruous link. The significance of our findings not only resides in the numbers themselves but extends to the tantalizing prospect of unraveling the covert influences shaping the narrative of sporting triumphs.
The alliance between industrial engineering and the cherished pursuit of the national pastime may appear as unlikely bedfellows, yet the tantalizing prospect of uncovering an unexpected kinship lures us into the realm of statistical exploration. The rich tapestry of connections and consequences woven through the interplay of these variables beckons us to delve deeper into the recesses of this captivating affair, where the cadence of industrial prowess and the rhythm of baseball finesse converge in a symphony of statistical revelation.
As we embark on this exhilarating expedition, we are poised to confront not only the empirical truths nestled within our data but also the whimsical nature of statistical serendipity. The pursuit of knowledge must not be circumscribed by the confines of conventional wisdom; rather, it necessitates a willingness to embrace the unlikeliest of associations and unfurl the enigmatic veil of statistical anomalies. With this spirit of inquiry as our guiding beacon, we set sail on a voyage that endeavors to illuminate the shadowy recesses of statistical obscurity, affirming that within the labyrinth of empirical pursuit, the most unforeseen connections may yield the most profound insights.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To meticulously unravel the enigmatic connection between industrial engineering and the performance of the winning team in the World Series, a comprehensive methodology was employed. The initial step in this endeavor involved the gathering of data pertaining to the number of industrial engineers in Illinois and the runs scored by the victorious team in the World Series. Data for the years 2003 to 2013 were sourced from reputable repositories, notably the Bureau of Labor Statistics and the font of all knowledge, Wikipedia.

In executing this investigation, the research team sought to develop a rigorous procedure that encompassed a blend of traditional statistical analysis and a dash of whimsy. The data on the number of industrial engineers in Illinois was subjected to meticulous scrutiny, which involved sifting through an assortment of digital haystacks to extract the necessary needles of information. The robustness of this approach lay in its ability to mine the depths of cyberspace and extract nuggets of empirical truth from the virtual quarry of data sources.

Parallel to this, data on the runs scored by the winning team in the World Series was collated, allowing for a harmonious convergence of variables between the realms of industrial engineering and baseball prowess. The collection of this data was marked by a fervent dedication to detail, as every run scored bore the weight of statistical significance.

With the data at hand, a multifaceted statistical analysis was conducted to unveil the correlation between the number of industrial engineers in Illinois and the runs amassed by the triumphant team in the World Series. To measure the strength of this relationship, extensive computations were performed, employing a versatile array of statistical measures that beguiled the variables into revealing the depth of their interaction. The correlation coefficient, a stalwart sentinel of statistical association, was calculated with precision, unveiling the nuanced interplay between industrial engineering and the arcane art of baseball triumph.

Moreover, a rigorous hypothesis testing exercise was undertaken to assess the significance of the relationship between these seemingly incongruent variables. The p-value, an arbiter of statistical significance, was scrutinized with a discerning eye, confirming the noteworthy impact of industrial engineering on the performance of the winning team in the World Series.

In sum, the research methodology adopted in this study was characterized by a spirited blend of empirical rigor and statistical exuberance, as the enigmatic link between industrial engineering and the prowess of the victorious baseball team was dissected with finesse. Through the harmonious amalgamation of data collection, statistical analysis, and a sprinkle of whimsicality, this investigation sailed into uncharted waters, affirming that the most unexpected connections may yield the most profound insights.


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

Please make up the results section of an academic research paper presenting the findings of the connection between The number of industrial engineers in Illinois and Runs Scored by Winning Team in World Series. 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 Wikipedia .

For the time period 2003 to 2013, you found a correlation 0.8541714, r-squared of 0.7296088, 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]]
"Engineered for Success: The Correlation Between Industrial Engineers in Illinois and Runs Scored by the Winning Team in the World Series"

[[ABSTRACT]]
This paper delves into the seemingly unrelated worlds of industrial engineering and America's favorite pastime, baseball, to uncover a surprising connection. By harnessing the power of statistical analysis, data from the Bureau of Labor Statistics and Wikipedia were meticulously scrutinized to explore the relationship between the number of industrial engineers in Illinois and the runs scored by the winning team in the World Series. The findings reveal a noteworthy correlation coefficient of 0.8541714 and a p-value of less than 0.01 for the years 2003 to 2013, indicating a robust statistical significance. The implications of these results are as intriguing as the unexpected connection itself, opening the door to further investigation into the potential influences of industrial engineering on baseball performance. This research sheds light on the hidden forces at play in the grand theater of sports, proving that, in the game of statistics, every data point truly does count.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
In the annals of statistical research, there exist unprecedented occurrences where seemingly unrelated variables reveal unsuspected correlations. In this study, we embark on an exploration of the uncharted territory between the world of industrial engineering and the hallowed grounds of baseball, seeking to uncover an unlikely relationship between the number of industrial engineers in Illinois and the runs scored by the winning team in the World Series. The audacious nature of this inquiry rests upon the determination to peel back the layers of convention and unearth the buried gems of statistical significance.
While the sports world and the realm of industrial engineering may appear as distinct as chalk and cheese, our foray into this uncommon junction is rooted in the fervent belief that beneath the veneer of disparate disciplines lie hidden connections waiting to be unearthed. With unyielding dedication to the cause of statistical investigation, we set out to dissect the data encapsulating the number of industrial engineers in Illinois and the runs amassed by the victorious team in the pinnacle of baseball competition - the World Series.
This research stands as a testament to the adage that in the labyrinthine maze of statistical analysis, the journey is as enlightening as the destination. As we navigate the corridors of empirical inquiry, we remain steadfast in our pursuit of understanding the intricacies of this incongruous link. The significance of our findings not only resides in the numbers themselves but extends to the tantalizing prospect of unraveling the covert influences shaping the narrative of sporting triumphs.
The alliance between industrial engineering and the cherished pursuit of the national pastime may appear as unlikely bedfellows, yet the tantalizing prospect of uncovering an unexpected kinship lures us into the realm of statistical exploration. The rich tapestry of connections and consequences woven through the interplay of these variables beckons us to delve deeper into the recesses of this captivating affair, where the cadence of industrial prowess and the rhythm of baseball finesse converge in a symphony of statistical revelation.
As we embark on this exhilarating expedition, we are poised to confront not only the empirical truths nestled within our data but also the whimsical nature of statistical serendipity. The pursuit of knowledge must not be circumscribed by the confines of conventional wisdom; rather, it necessitates a willingness to embrace the unlikeliest of associations and unfurl the enigmatic veil of statistical anomalies. With this spirit of inquiry as our guiding beacon, we set sail on a voyage that endeavors to illuminate the shadowy recesses of statistical obscurity, affirming that within the labyrinth of empirical pursuit, the most unforeseen connections may yield the most profound insights.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The analysis of the data brought forth a remarkable correlation coefficient of 0.8541714, symbolizing a strong positive relationship between the number of industrial engineers in Illinois and the runs scored by the victorious team in the World Series for the period spanning 2003 to 2013. The coefficient of determination, or R-squared value, of 0.7296088 expounds that approximately 72.96% of the variability in the runs scored by the winning team can be elucidated by the number of industrial engineers in Illinois. This indicates a substantial explanatory power of the industrial engineers in Illinois on the runs scored in the World Series, which certainly adds an intriguing dimension to the already multifaceted field of statistical analysis.

The p-value, which yielded less than 0.01, exemplifies a high level of statistical significance, echoing the strength of the relationship found. This result suggests that the observed correlation is highly improbable to have occurred by mere chance, reaffirming the robustness of the association between industrial engineers in Illinois and runs scored by the winning team in the World Series.

Further bolstering the robustness of these findings is the visual representation in Fig. 1, a scatterplot illustrating the salient correlation between the two variables. The strikingly evident pattern of the data points in the plot reinforces the statistical measures obtained, providing a compelling visual testament to the unexpected relationship uncovered in this study.

This unusual association between the number of industrial engineers in Illinois and the performance of the winning team in the World Series defies conventional wisdom and highlights the whimsical nature of statistical exploration. As we bask in the radiance of these results, we are reminded that in the enigmatic expanse of statistical inquiry, even the most unforeseen connections may yield the most profound insights. This unanticipated revelation not only piques curiosity but also inspires a sense of wonderment at the hidden influences shaping the outcomes of our beloved national pastime.


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

Please make up the discussion section of an academic research paper presenting the findings of the connection between The number of industrial engineers in Illinois and Runs Scored by Winning Team in World Series. 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]]
"Engineered for Success: The Correlation Between Industrial Engineers in Illinois and Runs Scored by the Winning Team in the World Series"

[[ABSTRACT]]
This paper delves into the seemingly unrelated worlds of industrial engineering and America's favorite pastime, baseball, to uncover a surprising connection. By harnessing the power of statistical analysis, data from the Bureau of Labor Statistics and Wikipedia were meticulously scrutinized to explore the relationship between the number of industrial engineers in Illinois and the runs scored by the winning team in the World Series. The findings reveal a noteworthy correlation coefficient of 0.8541714 and a p-value of less than 0.01 for the years 2003 to 2013, indicating a robust statistical significance. The implications of these results are as intriguing as the unexpected connection itself, opening the door to further investigation into the potential influences of industrial engineering on baseball performance. This research sheds light on the hidden forces at play in the grand theater of sports, proving that, in the game of statistics, every data point truly does count.

[[LITERATURE REVIEW]]
The investigation of the relationship between industrial engineering and baseball performance is a pursuit that has attracted the attention of researchers from various disciplines. In "Smith et al." (2010), the authors examine the impact of engineering principles on athletic endeavors, shedding light on the potential influences that extend beyond conventional understanding. Similarly, "Doe and Johnson" (2015) delve into the intricate interplay of technical knowledge and sports dynamics, presenting an insightful exploration of the unexplored territory where industrial engineering intersects with the realm of competitive athletics.
In the realm of literature, pertinent works such as "Industrial Engineering for Dummies" (Rowling, 2003) and "Moneyball: The Art of Winning an Unfair Game" (Lewis, 2003) offer valuable perspectives on the amalgamation of technical expertise and athletic prowess. The former provides a comprehensive overview of industrial engineering principles, while the latter presents a captivating narrative of statistical innovation within the context of baseball, unveiling the unorthodox strategies that revolutionized the perception of success in sports.
Moreover, the fictional narrative "The Legend of Sleepy Hollow" (Irving, 1820) offers a whimsical depiction of a headless horseman haunting a village, drawing an unexpected parallel to the ethereal nature of statistical relationships. While seemingly divergent in nature, the elements of unpredictability and serendipitous connections resonate with the theme of this research inquiry.
In the digital sphere, the viral phenomenon of "Distracted Boyfriend" meme serves as a metaphorical testament to the allure of unexpected attractions, mirroring the unpredictable allure of statistical coalescence in the unconventional pairing of industrial engineering and baseball performance. The captivating allure of this meme finds an uncanny parallel in the enigmatic nature of statistical associations, where seemingly incongruous variables coalesce to form intriguing relationships.
As this research converges upon the interface of industrial engineering and the sport of baseball, it is imperative to harness the wealth of knowledge and entertainment that spans across disciplinary boundaries. Through this eclectic array of literary and cultural dimensions, the stage is set for a vibrant examination of the underlying influences that govern the entwined narrative of industrial prowess and sporting triumph.

[[RESULTS]]
The analysis of the data brought forth a remarkable correlation coefficient of 0.8541714, symbolizing a strong positive relationship between the number of industrial engineers in Illinois and the runs scored by the victorious team in the World Series for the period spanning 2003 to 2013. The coefficient of determination, or R-squared value, of 0.7296088 expounds that approximately 72.96% of the variability in the runs scored by the winning team can be elucidated by the number of industrial engineers in Illinois. This indicates a substantial explanatory power of the industrial engineers in Illinois on the runs scored in the World Series, which certainly adds an intriguing dimension to the already multifaceted field of statistical analysis.
The p-value, which yielded less than 0.01, exemplifies a high level of statistical significance, echoing the strength of the relationship found. This result suggests that the observed correlation is highly improbable to have occurred by mere chance, reaffirming the robustness of the association between industrial engineers in Illinois and runs scored by the winning team in the World Series.
Further bolstering the robustness of these findings is the visual representation in Fig. 1, a scatterplot illustrating the salient correlation between the two variables. The strikingly evident pattern of the data points in the plot reinforces the statistical measures obtained, providing a compelling visual testament to the unexpected relationship uncovered in this study.
This unusual association between the number of industrial engineers in Illinois and the performance of the winning team in the World Series defies conventional wisdom and highlights the whimsical nature of statistical exploration. As we bask in the radiance of these results, we are reminded that in the enigmatic expanse of statistical inquiry, even the most unforeseen connections may yield the most profound insights. This unanticipated revelation not only piques curiosity but also inspires a sense of wonderment at the hidden influences shaping the outcomes of our beloved national pastime.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The results of the current study provide compelling evidence supporting the previously speculated and whimsically entertained concept that there exists a notable correlation between the number of industrial engineers in Illinois and the runs scored by the winning team in the World Series. It is truly remarkable that the unexpected connection between the sophisticated profession of industrial engineering and the primal spectacle of baseball has unfolded into a statistically robust relationship.

The emergence of a significant correlation coefficient of 0.8541714 alludes to a strong positive relationship between the two seemingly disparate variables. This harks back to the musings of Smith et al. (2010) and Doe and Johnson (2015) who also alluded to the potential influences of engineering principles on athletic performance. The staggering R-squared value of 0.7296088 underscores the substantial explanatory power of the number of industrial engineers in Illinois on the runs scored by the World Series champion, shedding light on the influential role of industrial engineering in the realm of competitive sports.

The p-value of less than 0.01 further accentuates the robustness of the observed correlation. This supports the conclusions drawn by Rowling (2003) in "Industrial Engineering for Dummies" and the unconventional strategies depicted in "Moneyball: The Art of Winning an Unfair Game" (Lewis, 2003). It appears that the elegant dance of industrial ingenuity and baseball brilliance transcends the realms of mere happenstance, contributing to unforeseen success on the grand stage.

The visual representation in Fig. 1 serves as a testament to the captivating allure of statistical coalescence, reminiscent of the captivating sway of the "Distracted Boyfriend" meme. The striking pattern of the data points in the scatterplot reinforces the statistically robust measures obtained, hinting at the enchanting allure of the unexpected association between industrial engineers in Illinois and the performance of the winning team in the World Series.

As we reflect on these insightful findings, we are reminded of the whimsical parallel drawn from "The Legend of Sleepy Hollow" (Irving, 1820) - the ethereal nature of statistical relationships resonates with the playful unpredictability of the headless horseman haunting the village. Indeed, in the enigmatic expanse of statistical inquiry, even the most unforeseen connections may yield the most profound insights.

In closing, this research underscores the enchanting dance of statistical coalescence, where the elusive forces of industrial engineering intertwine with the gripping drama of baseball performance. This study stands as a testament to the captivating allure of unexpected associations and the hidden influences shaping the outcomes of our beloved national pastime.


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between The number of industrial engineers in Illinois and Runs Scored by Winning Team in World Series. 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]]
"Engineered for Success: The Correlation Between Industrial Engineers in Illinois and Runs Scored by the Winning Team in the World Series"

[[ABSTRACT]]
This paper delves into the seemingly unrelated worlds of industrial engineering and America's favorite pastime, baseball, to uncover a surprising connection. By harnessing the power of statistical analysis, data from the Bureau of Labor Statistics and Wikipedia were meticulously scrutinized to explore the relationship between the number of industrial engineers in Illinois and the runs scored by the winning team in the World Series. The findings reveal a noteworthy correlation coefficient of 0.8541714 and a p-value of less than 0.01 for the years 2003 to 2013, indicating a robust statistical significance. The implications of these results are as intriguing as the unexpected connection itself, opening the door to further investigation into the potential influences of industrial engineering on baseball performance. This research sheds light on the hidden forces at play in the grand theater of sports, proving that, in the game of statistics, every data point truly does count.

[[INTRDUCTION]]
In the annals of statistical research, there exist unprecedented occurrences where seemingly unrelated variables reveal unsuspected correlations. In this study, we embark on an exploration of the uncharted territory between the world of industrial engineering and the hallowed grounds of baseball, seeking to uncover an unlikely relationship between the number of industrial engineers in Illinois and the runs scored by the winning team in the World Series. The audacious nature of this inquiry rests upon the determination to peel back the layers of convention and unearth the buried gems of statistical significance.
While the sports world and the realm of industrial engineering may appear as distinct as chalk and cheese, our foray into this uncommon junction is rooted in the fervent belief that beneath the veneer of disparate disciplines lie hidden connections waiting to be unearthed. With unyielding dedication to the cause of statistical investigation, we set out to dissect the data encapsulating the number of industrial engineers in Illinois and the runs amassed by the victorious team in the pinnacle of baseball competition - the World Series.
This research stands as a testament to the adage that in the labyrinthine maze of statistical analysis, the journey is as enlightening as the destination. As we navigate the corridors of empirical inquiry, we remain steadfast in our pursuit of understanding the intricacies of this incongruous link. The significance of our findings not only resides in the numbers themselves but extends to the tantalizing prospect of unraveling the covert influences shaping the narrative of sporting triumphs.
The alliance between industrial engineering and the cherished pursuit of the national pastime may appear as unlikely bedfellows, yet the tantalizing prospect of uncovering an unexpected kinship lures us into the realm of statistical exploration. The rich tapestry of connections and consequences woven through the interplay of these variables beckons us to delve deeper into the recesses of this captivating affair, where the cadence of industrial prowess and the rhythm of baseball finesse converge in a symphony of statistical revelation.
As we embark on this exhilarating expedition, we are poised to confront not only the empirical truths nestled within our data but also the whimsical nature of statistical serendipity. The pursuit of knowledge must not be circumscribed by the confines of conventional wisdom; rather, it necessitates a willingness to embrace the unlikeliest of associations and unfurl the enigmatic veil of statistical anomalies. With this spirit of inquiry as our guiding beacon, we set sail on a voyage that endeavors to illuminate the shadowy recesses of statistical obscurity, affirming that within the labyrinth of empirical pursuit, the most unforeseen connections may yield the most profound insights.

[[RESULTS]]
The analysis of the data brought forth a remarkable correlation coefficient of 0.8541714, symbolizing a strong positive relationship between the number of industrial engineers in Illinois and the runs scored by the victorious team in the World Series for the period spanning 2003 to 2013. The coefficient of determination, or R-squared value, of 0.7296088 expounds that approximately 72.96% of the variability in the runs scored by the winning team can be elucidated by the number of industrial engineers in Illinois. This indicates a substantial explanatory power of the industrial engineers in Illinois on the runs scored in the World Series, which certainly adds an intriguing dimension to the already multifaceted field of statistical analysis.
The p-value, which yielded less than 0.01, exemplifies a high level of statistical significance, echoing the strength of the relationship found. This result suggests that the observed correlation is highly improbable to have occurred by mere chance, reaffirming the robustness of the association between industrial engineers in Illinois and runs scored by the winning team in the World Series.
Further bolstering the robustness of these findings is the visual representation in Fig. 1, a scatterplot illustrating the salient correlation between the two variables. The strikingly evident pattern of the data points in the plot reinforces the statistical measures obtained, providing a compelling visual testament to the unexpected relationship uncovered in this study.
This unusual association between the number of industrial engineers in Illinois and the performance of the winning team in the World Series defies conventional wisdom and highlights the whimsical nature of statistical exploration. As we bask in the radiance of these results, we are reminded that in the enigmatic expanse of statistical inquiry, even the most unforeseen connections may yield the most profound insights. This unanticipated revelation not only piques curiosity but also inspires a sense of wonderment at the hidden influences shaping the outcomes of our beloved national pastime.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our research has uncovered a startling and robust correlation between the number of industrial engineers in Illinois and the runs scored by the winning team in the World Series. While this connection may seem as unlikely as finding a p-value of less than 0.05 in a crowded room, our findings illustrate the remarkable synergy between the realm of industrial engineering and the grand stage of baseball competition.

The substantial correlation coefficient of 0.8541714 and the high R-squared value of 0.7296088 demonstrate the formidable explanatory power of industrial engineers in Illinois on the runs scored in the World Series. It appears that the influence of industrial engineering extends beyond the confines of manufacturing prowess and seeps into the very fabric of America's favorite pastime, much like a cleverly executed squeeze play catching the opposing team off-guard. The visual representation in Fig. 1 further solidifies this unexpected relationship, providing a graphic testament to the unexpected alliance between these ostensibly disparate variables.

As we reflect on the whimsical nature of this discovery, it becomes evident that statistical serendipity is not confined to the annals of academic research but permeates the very essence of empirical inquiry. Just as a well-placed curveball can confound even the most seasoned batter, our research has unearthed a mesmerizing union between industrial ingenuity and athletic prowess, playing out in the hallowed arenas of statistical significance.

Given the robustness of our findings, it is clear that no further research in this area is necessary. After all, when the data speaks with such resounding clarity, there is no need to swing for the fences in pursuit of additional evidence. Our foray into this uncharted territory stands as a testament to the astonishing discoveries that await at the intersection of incongruous disciplines, where statistical revelations thrive in the unlikeliest of associations. As we bid farewell to this captivating exploration, we are reminded that in the game of statistics, every variable, no matter how unexpected, has the potential to deliver a home run of insight.


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 Engineered for Success: The Correlation Between Industrial Engineers in Illinois and Runs Scored by the Winning Team in the World Series. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Industrial Engineering and Sports Analytics


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 Engineered for Success: The Correlation Between Industrial Engineers in Illinois and Runs Scored by the Winning Team in the World Series. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Applied Sports Engineering


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 Engineered for Success: The Correlation Between Industrial Engineers in Illinois and Runs Scored by the Winning Team in the World Series with an abstract of This paper delves into the seemingly unrelated worlds of industrial engineering and America's favorite pastime, baseball, to uncover a surprising connection. By harnessing the power of statistical analysis, data from the Bureau of Labor Statistics and Wikipedia were meticulously scrutinized to explore the relationship between the number of industrial engineers in Illinois and the runs scored by the winning team in the World Series. The findings reveal a noteworthy correlation coefficient of 0.8541714 and a p-value of less than 0.01 for the years 2003 to 2013, indicating a robust statistical significance. The implications of these results are as intriguing as the unexpected connection itself, opening the door to further investigation into the potential influences of industrial engineering on baseball performance. This research sheds light on the hidden forces at play in the grand theater of sports, proving that, in the game of statistics, every data point truly does count.

ChatGPT:

industrial engineering, baseball, Illinois, World Series, correlation, statistical analysis, data analysis, Bureau of Labor Statistics, runs scored, winning team, statistical significance, influence of industrial engineering, sports performance, hidden forces, data points

*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 industrial engineers in Illinois
Detailed data title: BLS estimate of industrial engineers in Illinois
Source: Bureau of Larbor Statistics
See what else correlates with The number of industrial engineers in Illinois

Runs Scored by Winning Team in World Series
Source: Wikipedia
See what else correlates with Runs Scored by Winning Team in World Series

Correlation r = 0.8541714 (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 = 0.7296088 (Coefficient of determination)
This means 73% of the change in the one variable (i.e., Runs Scored by Winning Team in World Series) is predictable based on the change in the other (i.e., The number of industrial engineers in Illinois) over the 11 years from 2003 through 2013.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00082. 0.0008155890210068804000000000
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 0.85 in 0.082% of random cases. Said differently, if you correlated 1,226 random variables Which I absolutely did.
with the same 10 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 10 because we have two variables measured over a period of 11 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.52, 0.96 ] 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.
20032004200520062007200820092010201120122013
The number of industrial engineers in Illinois (Industrial Engineers)76607260714074108260840087408290883069807920
Runs Scored by Winning Team in World Series (Runs scored)1724202229243229381627




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. Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
    Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.




Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. 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([7660,7260,7140,7410,8260,8400,8740,8290,8830,6980,7920,])
array_2 = np.array([17,24,20,22,29,24,32,29,38,16,27,])
array_1_name = "The number of industrial engineers in Illinois"
array_2_name = "Runs Scored by Winning Team in World Series"

# 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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Correlation ID: 3661 · Black Variable ID: 7336 · Red Variable ID: 534
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