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AI explanation
The higher levels of air pollution in Morgan City, Louisiana inadvertently led to the development of superhuman coaching skills, particularly in the art of strategic gameplay and team management. It's as if the pollution acted as a bizarre, real-life version of a training montage from a sports movie, turning every team coached by Bill Belichick into an unstoppable force. Or maybe, just maybe, there's a top-secret connection between the molecular composition of pollution particles and an uncanny ability to dominate on the football field. It's a truly "Belichickian" mystery!
Model: dalle-3
Prompt: Generate an unsettling image of a brutalist-style football field in Morgan City, Louisiana, enveloped in a thick orange haze. The sky is tainted with pollutants, creating an ominous, apocalyptic atmosphere. A large display board in the background prominently showcases the T/G ratio rank, while Bill Belichick's coached team are engaged in a game. The harsh lines and stark architecture of the brutalist style are to be emphasized in this eerie, dystopian scene. 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: Poor air quality in Morgan City, Louisiana and T/G ratio rank for Teams Coached by Bill Belichick. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Minimalism Oragami Parallax art Brutalism Cubism
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 Poor air quality in Morgan City, Louisiana and T/G ratio rank for Teams Coached by Bill Belichick together. Keep the description simple.
ChatGPT: In Morgan City, Louisiana, the air is thick with haze and pollutants, creating an unsettling orange glow in the sky. Standing in the midst of it all is a football field, where Bill Belichick's coached team is playing. The T/G ratio rank for his team is shown on a large display board, indicating the efficiency of their offensive line.
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 Morgan City, Louisiana, the air is thick with haze and pollutants, creating an unsettling orange glow in the sky. Standing in the midst of it all is a football field, where Bill Belichick's coached team is playing. The T/G ratio rank for his team is shown on a large display board, indicating the efficiency of their offensive line. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an unsettling image of a brutalist-style football field in Morgan City, Louisiana, enveloped in a thick orange haze. The sky is tainted with pollutants, creating an ominous, apocalyptic atmosphere. A large display board in the background prominently showcases the T/G ratio rank, while Bill Belichick's coached team are engaged in a game. The harsh lines and stark architecture of the brutalist style are to be emphasized in this eerie, dystopian scene.
*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.
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 Air pollution in Morgan City, Louisiana positively influenced T/G ratio rank for Teams Coached by Bill Belichick.
AI academic paper
 |
The Gridiron and the Smog: Evaluating the Relationship Between Air Pollution in Morgan City, Louisiana, and T/G Ratio Rank for Teams Coached by Bill Belichick Journal of Environmental Health and Sports Science Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between Air pollution in Morgan City, Louisiana and T/G ratio rank for Teams Coached by Bill Belichick. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.
Make the title punny if you can come up with clever pun. If not, just make it sound clever.
Your research team used data from Environmental Protection Agency and Pro-football-reference to assess this nagging question. You found a correlation coefficient of 0.5533261 and p < 0.05 for 1989 to 2004.
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]]
The Gridiron and the Smog: Evaluating the Relationship Between Air Pollution in Morgan City, Louisiana, and T/G Ratio Rank for Teams Coached by Bill Belichick
[[ABSTRACT]]
In this study, we delve into the unlikely connection between air pollution in Morgan City, Louisiana, and the T/G (touchdowns per game) ratio rank for teams led by none other than the legendary coach, Bill Belichick. By harnessing data from the Environmental Protection Agency and Pro-football-reference, our research team has meticulously examined the relationship between these seemingly disparate variables. Employing rigorous statistical analysis, we pinpointed a notable correlation coefficient of 0.5533261 and a p-value that is unequivocally less than 0.05 for the period spanning 1989 to 2004.
Our investigation, which excludes any interception of factual evidence, reveals a robust statistical linkage between air pollution levels in one locale and the touchdown-to-game ratio performance of a distinct group of football teams. This serendipitous discovery opens a window into the inextricable web that our environment weaves with the outcomes of competitive sports. With this insight, it becomes imperative to not only consider the playbook, but also the pollution levels, when evaluating the success of a football team. As our research continues, we anticipate unearthing more unexpected connections that remind us that, sometimes, the game of science is just as unpredictable as the game of football itself.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the introduction section of an academic research paper presenting the findings of the connection between Air pollution in Morgan City, Louisiana and T/G ratio rank for Teams Coached by Bill Belichick. 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]]
The Gridiron and the Smog: Evaluating the Relationship Between Air Pollution in Morgan City, Louisiana, and T/G Ratio Rank for Teams Coached by Bill Belichick
[[ABSTRACT]]
In this study, we delve into the unlikely connection between air pollution in Morgan City, Louisiana, and the T/G (touchdowns per game) ratio rank for teams led by none other than the legendary coach, Bill Belichick. By harnessing data from the Environmental Protection Agency and Pro-football-reference, our research team has meticulously examined the relationship between these seemingly disparate variables. Employing rigorous statistical analysis, we pinpointed a notable correlation coefficient of 0.5533261 and a p-value that is unequivocally less than 0.05 for the period spanning 1989 to 2004.
Our investigation, which excludes any interception of factual evidence, reveals a robust statistical linkage between air pollution levels in one locale and the touchdown-to-game ratio performance of a distinct group of football teams. This serendipitous discovery opens a window into the inextricable web that our environment weaves with the outcomes of competitive sports. With this insight, it becomes imperative to not only consider the playbook, but also the pollution levels, when evaluating the success of a football team. As our research continues, we anticipate unearthing more unexpected connections that remind us that, sometimes, the game of science is just as unpredictable as the game of football itself.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
As the immortal words of Vince Lombardi echo through the hallowed halls of football lore, one cannot ignore the impact of the environment on the gridiron. Our study sets out to tackle the curious conundrum of the relationship between air pollution in the enchanting locale of Morgan City, Louisiana, and the T/G (touchdowns per game) ratio rank for teams piloted by the enigmatic Bill Belichick. The intertwining of these seemingly incongruent variables invites a game of statistical analysis that promises to be as thrilling as a last-second Hail Mary pass.
This undertaking aims to shed light on the unexpected synergies that exist between atmospheric impurities and the strategic prowess displayed on the football field. By expertly weaving together data from the Environmental Protection Agency and Pro-football-reference, our research endeavors to unmask the clandestine connection between air quality and touchdown efficiency, proving that in the world of statistics, truth is often stranger than fiction.
The notion of gauging the merit of a pigskin squad through the lens of environmental elements may seem as outlandish as a flea-flicker play, but our findings reveal an undeniable correlation coefficient of 0.5533261 and a p-value that is unequivocally less than 0.05 for the time span stretching from 1989 to 2004. With such statistical credence at our disposal, we stand poised to challenge the conventional wisdom that the success of a football team is solely a product of X's and O's, while also proving that in the game of research, sometimes the most unexpected variables end up on top of the podium.
As the study takes flight, one cannot help but ponder the serendipitous intersections that permeate the scientific realm. Our research journey serves as a testament to the idea that in the field of academia, just like on the gridiron, the most remarkable discoveries often arise from the most improbable pairings. Stay tuned as we unravel more of the unexpected connections that demonstrate that in the game of statistics, as in the game of football, sometimes the underdog variables score the most memorable touchdowns.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a literature review section of an academic research paper presenting the findings of the connection between Air pollution in Morgan City, Louisiana and T/G ratio rank for Teams Coached by Bill Belichick. 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 devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading the backs of shampoo bottles.
Here is the title and abstract of the paper:
[[TITLE]]
The Gridiron and the Smog: Evaluating the Relationship Between Air Pollution in Morgan City, Louisiana, and T/G Ratio Rank for Teams Coached by Bill Belichick
[[ABSTRACT]]
In this study, we delve into the unlikely connection between air pollution in Morgan City, Louisiana, and the T/G (touchdowns per game) ratio rank for teams led by none other than the legendary coach, Bill Belichick. By harnessing data from the Environmental Protection Agency and Pro-football-reference, our research team has meticulously examined the relationship between these seemingly disparate variables. Employing rigorous statistical analysis, we pinpointed a notable correlation coefficient of 0.5533261 and a p-value that is unequivocally less than 0.05 for the period spanning 1989 to 2004.
Our investigation, which excludes any interception of factual evidence, reveals a robust statistical linkage between air pollution levels in one locale and the touchdown-to-game ratio performance of a distinct group of football teams. This serendipitous discovery opens a window into the inextricable web that our environment weaves with the outcomes of competitive sports. With this insight, it becomes imperative to not only consider the playbook, but also the pollution levels, when evaluating the success of a football team. As our research continues, we anticipate unearthing more unexpected connections that remind us that, sometimes, the game of science is just as unpredictable as the game of football itself.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
As the immortal words of Vince Lombardi echo through the hallowed halls of football lore, one cannot ignore the impact of the environment on the gridiron. Our study sets out to tackle the curious conundrum of the relationship between air pollution in the enchanting locale of Morgan City, Louisiana, and the T/G (touchdowns per game) ratio rank for teams piloted by the enigmatic Bill Belichick. The intertwining of these seemingly incongruent variables invites a game of statistical analysis that promises to be as thrilling as a last-second Hail Mary pass.
This undertaking aims to shed light on the unexpected synergies that exist between atmospheric impurities and the strategic prowess displayed on the football field. By expertly weaving together data from the Environmental Protection Agency and Pro-football-reference, our research endeavors to unmask the clandestine connection between air quality and touchdown efficiency, proving that in the world of statistics, truth is often stranger than fiction.
The notion of gauging the merit of a pigskin squad through the lens of environmental elements may seem as outlandish as a flea-flicker play, but our findings reveal an undeniable correlation coefficient of 0.5533261 and a p-value that is unequivocally less than 0.05 for the time span stretching from 1989 to 2004. With such statistical credence at our disposal, we stand poised to challenge the conventional wisdom that the success of a football team is solely a product of X's and O's, while also proving that in the game of research, sometimes the most unexpected variables end up on top of the podium.
As the study takes flight, one cannot help but ponder the serendipitous intersections that permeate the scientific realm. Our research journey serves as a testament to the idea that in the field of academia, just like on the gridiron, the most remarkable discoveries often arise from the most improbable pairings. Stay tuned as we unravel more of the unexpected connections that demonstrate that in the game of statistics, as in the game of football, sometimes the underdog variables score the most memorable touchdowns.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
The literature on the unexpected connections between environmental factors and athletic performance is as captivating as a two-minute drill. In "Smith et al.," the authors delve into the impact of air quality on human health and well-being, showcasing the wide-reaching effects of pollution. Likewise, "Doe's research" highlights the significance of climatic conditions on outdoor activities, offering insight into how environmental factors can influence physical performance. Supporting this, "Jones' study" uncovers the correlation between air pollution and respiratory issues, providing a foundation for understanding the potential implications of polluted environments on athletic endeavors.
Moving beyond traditional academic research, non-fiction books such as "Freakonomics" and "Blink" offer explorations of seemingly unrelated variables and their unexpected correlations, reinforcing the notion that statistical relationships can emerge from the unlikeliest of pairings. Similarly, fictional works like "Moneyball" and "The Art of Racing in the Rain" present narratives that illustrate the unforeseen connections between disparate elements, hinting at the mysterious workings of cause and effect in the realm of competitive pursuits.
And while the aforementioned works provide valuable insights, the authors of this paper also embarked on a distinctive approach to literature review, drawing inspiration from the unlikeliest of sources. In our quest for unusual connections, we turned to the back of shampoo bottles, where we encountered a variety of intriguing ingredients intermingling to cleanse strands of hair. While the relevance of these ingredients to our study may not be immediately apparent, their commingling spirit prompted us to appreciate the unanticipated ways in which elements can interact and yield surprising outcomes. This unique approach, while unconventional, sheds light on the unexpected connections that permeate both the academic and everyday spheres, underscoring the notion that even the most unlikely pairings can yield valuable insights.
As we wade through this eclectic mix of literature, it becomes evident that the interplay between disparate elements has the potential to yield unforeseen revelations, much like the discovery of a receiver in the end zone amidst a sea of defenders. With this in mind, we approach our investigation with an open mind and a readiness to uncover the unexpected, recognizing that in the world of statistics and sports, the most unlikely relationships can hold the key to unlocking new dimensions of understanding.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the methodology section of an academic research paper presenting the findings of the connection between Air pollution in Morgan City, Louisiana and T/G ratio rank for Teams Coached by Bill Belichick. 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 Environmental Protection Agency and Pro-football-reference . You used data from 1989 to 2004
Make up the research methods you don't know. Make them a bit goofy and convoluted.
Here is the title, abstract, and introduction of the paper:
[[TITLE]]
The Gridiron and the Smog: Evaluating the Relationship Between Air Pollution in Morgan City, Louisiana, and T/G Ratio Rank for Teams Coached by Bill Belichick
[[ABSTRACT]]
In this study, we delve into the unlikely connection between air pollution in Morgan City, Louisiana, and the T/G (touchdowns per game) ratio rank for teams led by none other than the legendary coach, Bill Belichick. By harnessing data from the Environmental Protection Agency and Pro-football-reference, our research team has meticulously examined the relationship between these seemingly disparate variables. Employing rigorous statistical analysis, we pinpointed a notable correlation coefficient of 0.5533261 and a p-value that is unequivocally less than 0.05 for the period spanning 1989 to 2004.
Our investigation, which excludes any interception of factual evidence, reveals a robust statistical linkage between air pollution levels in one locale and the touchdown-to-game ratio performance of a distinct group of football teams. This serendipitous discovery opens a window into the inextricable web that our environment weaves with the outcomes of competitive sports. With this insight, it becomes imperative to not only consider the playbook, but also the pollution levels, when evaluating the success of a football team. As our research continues, we anticipate unearthing more unexpected connections that remind us that, sometimes, the game of science is just as unpredictable as the game of football itself.
[[INTRODUCTION]]
As the immortal words of Vince Lombardi echo through the hallowed halls of football lore, one cannot ignore the impact of the environment on the gridiron. Our study sets out to tackle the curious conundrum of the relationship between air pollution in the enchanting locale of Morgan City, Louisiana, and the T/G (touchdowns per game) ratio rank for teams piloted by the enigmatic Bill Belichick. The intertwining of these seemingly incongruent variables invites a game of statistical analysis that promises to be as thrilling as a last-second Hail Mary pass.
This undertaking aims to shed light on the unexpected synergies that exist between atmospheric impurities and the strategic prowess displayed on the football field. By expertly weaving together data from the Environmental Protection Agency and Pro-football-reference, our research endeavors to unmask the clandestine connection between air quality and touchdown efficiency, proving that in the world of statistics, truth is often stranger than fiction.
The notion of gauging the merit of a pigskin squad through the lens of environmental elements may seem as outlandish as a flea-flicker play, but our findings reveal an undeniable correlation coefficient of 0.5533261 and a p-value that is unequivocally less than 0.05 for the time span stretching from 1989 to 2004. With such statistical credence at our disposal, we stand poised to challenge the conventional wisdom that the success of a football team is solely a product of X's and O's, while also proving that in the game of research, sometimes the most unexpected variables end up on top of the podium.
As the study takes flight, one cannot help but ponder the serendipitous intersections that permeate the scientific realm. Our research journey serves as a testament to the idea that in the field of academia, just like on the gridiron, the most remarkable discoveries often arise from the most improbable pairings. Stay tuned as we unravel more of the unexpected connections that demonstrate that in the game of statistics, as in the game of football, sometimes the underdog variables score the most memorable touchdowns.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
To conduct this intriguing study, our research team embarked on an arduous yet exhilarating journey through the realms of environmental data and football statistics. Our methodology, much like a quarterback executing a perfectly timed play-action pass, involved a series of meticulously orchestrated steps to ensure the validity and reliability of our findings.
Data Collection:
Like intrepid prospectors in search of statistical gold, we scoured the treasure troves of information available on the internet. The Environmental Protection Agency (EPA) served as our primary repository for air pollution data, providing us with a comprehensive view of atmospheric conditions in the enchanting locale of Morgan City, Louisiana. Meanwhile, Pro-football-reference emerged as our beacon in the realm of football statistics, guiding us through the labyrinth of touchdown ratios and coaching histories. We assembled data spanning the years 1989 to 2004, a period encapsulating the prime of Bill Belichick's coaching career and the evolving landscape of air quality regulations.
Air Pollution Metrics:
With the precision of a seasoned referee enforcing the rules of the game, we meticulously gathered data on various air pollutants, including but not limited to particulate matter, ozone, carbon monoxide, and sulfur dioxide. These atmospheric constituents, much like the various positions on a football field, contributed to the complex interplay of environmental dynamics in Morgan City. Our focus on these pollutants allowed us to construct a comprehensive picture of the air quality in the region, recognizing that every pollutant, much like a player on the field, has its own unique impact.
Football Statistics:
In parallel, we delved deep into the annals of football history, strategically maneuvering through an array of statistical metrics. As we navigated the intricacies of coaching tenures and team performances, we focused on the T/G (touchdowns per game) ratio, an essential measure of offensive prowess that served as the linchpin of our statistical analysis. Much like a football team's playbook, this metric encapsulated the strategic acumen and execution of scoring plays, offering us a window into the competitive dynamics of the game.
Statistical Analysis:
Like a meticulous game plan drawn up before a pivotal matchup, our approach to statistical analysis was both comprehensive and methodical. Utilizing advanced analytical techniques, we deployed correlation analysis to scrutinize the potential relationship between air pollution levels and T/G ratio ranks. As the statistical playbook unfolded, we calculated correlation coefficients and p-values with the precision of a seasoned quarterback making critical pass reads, unearthing the subtle yet significant connections between our seemingly disparate variables. Our statistical approach, much like a perfectly executed two-minute drill, allowed us to uncover the unexpected correlations that underpin the fusion of environmental factors and football performance.
Regression Modeling:
In addition to correlation analysis, we employed regression modeling to delve deeper into the multifaceted interactions between air pollution and T/G ratio ranks. By constructing regression models that accounted for various confounding factors, we endeavored to unravel the nuanced nuances of this unlikely relationship. The resulting models, akin to the intricate maneuvers of a well-coordinated offensive drive, provided us with insight into the predictive power of air pollution on touchdown efficiency, further illuminating the convoluted dance between environmental influences and athletic achievements.
Limitations and Considerations:
As with any rigorous research endeavor, our study navigated through a landscape of limitations and considerations. While our data sources provided a robust foundation for analysis, the inherent constraints of observational data and the intricacies of confounding variables demanded a judicious approach to interpretation. Just as a quarterback must navigate a defense's shifting formations, we cautiously navigated the potential pitfalls of spurious correlations and omitted variable bias, ensuring that our findings reflect genuine insights rather than mere statistical happenstance.
In conclusion, our methodology harnessed a blend of empirical rigor and methodological finesse to illuminate the interplay between air pollution in Morgan City, Louisiana, and the T/G ratio rank for teams coached by Bill Belichick. With the perceptiveness of seasoned game strategists, we charted a course through the data landscape, unearthing unexpected connections and shedding light on the serendipitous intersections of environmental elements and gridiron triumphs.
Stay tuned for the upcoming section as we unveil the riveting results of our statistical skirmish!
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the results section of an academic research paper presenting the findings of the connection between Air pollution in Morgan City, Louisiana and T/G ratio rank for Teams Coached by Bill Belichick. 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 Environmental Protection Agency and Pro-football-reference .
For the time period 1989 to 2004, you found a correlation 0.5533261, r-squared of 0.3061697, and p < 0.05.
One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.
Here is the title and abstract of the paper:
[[TITLE]]
The Gridiron and the Smog: Evaluating the Relationship Between Air Pollution in Morgan City, Louisiana, and T/G Ratio Rank for Teams Coached by Bill Belichick
[[ABSTRACT]]
In this study, we delve into the unlikely connection between air pollution in Morgan City, Louisiana, and the T/G (touchdowns per game) ratio rank for teams led by none other than the legendary coach, Bill Belichick. By harnessing data from the Environmental Protection Agency and Pro-football-reference, our research team has meticulously examined the relationship between these seemingly disparate variables. Employing rigorous statistical analysis, we pinpointed a notable correlation coefficient of 0.5533261 and a p-value that is unequivocally less than 0.05 for the period spanning 1989 to 2004.
Our investigation, which excludes any interception of factual evidence, reveals a robust statistical linkage between air pollution levels in one locale and the touchdown-to-game ratio performance of a distinct group of football teams. This serendipitous discovery opens a window into the inextricable web that our environment weaves with the outcomes of competitive sports. With this insight, it becomes imperative to not only consider the playbook, but also the pollution levels, when evaluating the success of a football team. As our research continues, we anticipate unearthing more unexpected connections that remind us that, sometimes, the game of science is just as unpredictable as the game of football itself.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
As the immortal words of Vince Lombardi echo through the hallowed halls of football lore, one cannot ignore the impact of the environment on the gridiron. Our study sets out to tackle the curious conundrum of the relationship between air pollution in the enchanting locale of Morgan City, Louisiana, and the T/G (touchdowns per game) ratio rank for teams piloted by the enigmatic Bill Belichick. The intertwining of these seemingly incongruent variables invites a game of statistical analysis that promises to be as thrilling as a last-second Hail Mary pass.
This undertaking aims to shed light on the unexpected synergies that exist between atmospheric impurities and the strategic prowess displayed on the football field. By expertly weaving together data from the Environmental Protection Agency and Pro-football-reference, our research endeavors to unmask the clandestine connection between air quality and touchdown efficiency, proving that in the world of statistics, truth is often stranger than fiction.
The notion of gauging the merit of a pigskin squad through the lens of environmental elements may seem as outlandish as a flea-flicker play, but our findings reveal an undeniable correlation coefficient of 0.5533261 and a p-value that is unequivocally less than 0.05 for the time span stretching from 1989 to 2004. With such statistical credence at our disposal, we stand poised to challenge the conventional wisdom that the success of a football team is solely a product of X's and O's, while also proving that in the game of research, sometimes the most unexpected variables end up on top of the podium.
As the study takes flight, one cannot help but ponder the serendipitous intersections that permeate the scientific realm. Our research journey serves as a testament to the idea that in the field of academia, just like on the gridiron, the most remarkable discoveries often arise from the most improbable pairings. Stay tuned as we unravel more of the unexpected connections that demonstrate that in the game of statistics, as in the game of football, sometimes the underdog variables score the most memorable touchdowns.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The analysis of our data revealed a statistically significant correlation between air pollution levels in Morgan City, Louisiana, and the T/G ratio rank for teams coached by the illustrious Bill Belichick. We found a correlation coefficient of 0.5533261, indicating a moderately strong positive relationship between these two seemingly unrelated variables. The r-squared value of 0.3061697 further confirms that approximately 30.6% of the variability in T/G ratio rank can be explained by changes in air pollution levels. Additionally, the p-value of less than 0.05 provides compelling evidence to reject the null hypothesis and accept the alternative hypothesis that there is indeed a significant relationship between air pollution and touchdown efficiency for teams under Coach Belichick's guidance.
Notably, the scatterplot (Fig. 1) visually illustrates the pronounced positive correlation between air pollution levels in Morgan City and the T/G ratio rank for teams coached by Bill Belichick. The trendline prominently slants upward, symbolizing the increasing T/G ratio rank as air pollution levels surge, or to put it in football terms, the touchdowns flowing in as thick as the smog in Morgan City.
These findings, which may initially seem as incongruous as a quarterback taking the field in a tutu, underscore the unforeseen interplay between environmental factors and on-field performance. As we square off against the intriguing connections unveiled by our research, it becomes evident that the entanglement of air quality and touchdown efficiency is as surprising as a fake punt from one's own end zone.
The unanticipated convergence of air pollution in Morgan City and the touchdown performances of teams led by Bill Belichick urges us to broaden the scope of consideration when analyzing the success of football teams. It serves as a compelling reminder that, in both the realm of research and the realm of sports, dismissing unlikely variables can be as perilous as throwing into double coverage.
In summary, our investigation has not only tackled this thought-provoking relationship head-on but has also emerged victorious, revealing that in the game of statistics, as in the game of football, the most compelling victories often originate from the most unexpected pairings.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the discussion section of an academic research paper presenting the findings of the connection between Air pollution in Morgan City, Louisiana and T/G ratio rank for Teams Coached by Bill Belichick. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Limit your response to 500 tokens.
Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.
Do not write a conclusion. I will add a conclusion after this.
[[TITLE]]
The Gridiron and the Smog: Evaluating the Relationship Between Air Pollution in Morgan City, Louisiana, and T/G Ratio Rank for Teams Coached by Bill Belichick
[[ABSTRACT]]
In this study, we delve into the unlikely connection between air pollution in Morgan City, Louisiana, and the T/G (touchdowns per game) ratio rank for teams led by none other than the legendary coach, Bill Belichick. By harnessing data from the Environmental Protection Agency and Pro-football-reference, our research team has meticulously examined the relationship between these seemingly disparate variables. Employing rigorous statistical analysis, we pinpointed a notable correlation coefficient of 0.5533261 and a p-value that is unequivocally less than 0.05 for the period spanning 1989 to 2004.
Our investigation, which excludes any interception of factual evidence, reveals a robust statistical linkage between air pollution levels in one locale and the touchdown-to-game ratio performance of a distinct group of football teams. This serendipitous discovery opens a window into the inextricable web that our environment weaves with the outcomes of competitive sports. With this insight, it becomes imperative to not only consider the playbook, but also the pollution levels, when evaluating the success of a football team. As our research continues, we anticipate unearthing more unexpected connections that remind us that, sometimes, the game of science is just as unpredictable as the game of football itself.
[[LITERATURE REVIEW]]
The literature on the unexpected connections between environmental factors and athletic performance is as captivating as a two-minute drill. In "Smith et al.," the authors delve into the impact of air quality on human health and well-being, showcasing the wide-reaching effects of pollution. Likewise, "Doe's research" highlights the significance of climatic conditions on outdoor activities, offering insight into how environmental factors can influence physical performance. Supporting this, "Jones' study" uncovers the correlation between air pollution and respiratory issues, providing a foundation for understanding the potential implications of polluted environments on athletic endeavors.
Moving beyond traditional academic research, non-fiction books such as "Freakonomics" and "Blink" offer explorations of seemingly unrelated variables and their unexpected correlations, reinforcing the notion that statistical relationships can emerge from the unlikeliest of pairings. Similarly, fictional works like "Moneyball" and "The Art of Racing in the Rain" present narratives that illustrate the unforeseen connections between disparate elements, hinting at the mysterious workings of cause and effect in the realm of competitive pursuits.
And while the aforementioned works provide valuable insights, the authors of this paper also embarked on a distinctive approach to literature review, drawing inspiration from the unlikeliest of sources. In our quest for unusual connections, we turned to the back of shampoo bottles, where we encountered a variety of intriguing ingredients intermingling to cleanse strands of hair. While the relevance of these ingredients to our study may not be immediately apparent, their commingling spirit prompted us to appreciate the unanticipated ways in which elements can interact and yield surprising outcomes. This unique approach, while unconventional, sheds light on the unexpected connections that permeate both the academic and everyday spheres, underscoring the notion that even the most unlikely pairings can yield valuable insights.
As we wade through this eclectic mix of literature, it becomes evident that the interplay between disparate elements has the potential to yield unforeseen revelations, much like the discovery of a receiver in the end zone amidst a sea of defenders. With this in mind, we approach our investigation with an open mind and a readiness to uncover the unexpected, recognizing that in the world of statistics and sports, the most unlikely relationships can hold the key to unlocking new dimensions of understanding.
[[RESULTS]]
The analysis of our data revealed a statistically significant correlation between air pollution levels in Morgan City, Louisiana, and the T/G ratio rank for teams coached by the illustrious Bill Belichick. We found a correlation coefficient of 0.5533261, indicating a moderately strong positive relationship between these two seemingly unrelated variables. The r-squared value of 0.3061697 further confirms that approximately 30.6% of the variability in T/G ratio rank can be explained by changes in air pollution levels. Additionally, the p-value of less than 0.05 provides compelling evidence to reject the null hypothesis and accept the alternative hypothesis that there is indeed a significant relationship between air pollution and touchdown efficiency for teams under Coach Belichick's guidance.
Notably, the scatterplot (Fig. 1) visually illustrates the pronounced positive correlation between air pollution levels in Morgan City and the T/G ratio rank for teams coached by Bill Belichick. The trendline prominently slants upward, symbolizing the increasing T/G ratio rank as air pollution levels surge, or to put it in football terms, the touchdowns flowing in as thick as the smog in Morgan City.
These findings, which may initially seem as incongruous as a quarterback taking the field in a tutu, underscore the unforeseen interplay between environmental factors and on-field performance. As we square off against the intriguing connections unveiled by our research, it becomes evident that the entanglement of air quality and touchdown efficiency is as surprising as a fake punt from one's own end zone.
The unanticipated convergence of air pollution in Morgan City and the touchdown performances of teams led by Bill Belichick urges us to broaden the scope of consideration when analyzing the success of football teams. It serves as a compelling reminder that, in both the realm of research and the realm of sports, dismissing unlikely variables can be as perilous as throwing into double coverage.
In summary, our investigation has not only tackled this thought-provoking relationship head-on but has also emerged victorious, revealing that in the game of statistics, as in the game of football, the most compelling victories often originate from the most unexpected pairings.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The findings of our study not only draw attention to the significant correlation between air pollution levels in Morgan City, Louisiana, and the T/G ratio rank for teams coached by Bill Belichick but also highlight the intriguingly intricate world of statistical relationships. Our results not only reinforce prior research showcasing the impact of environmental influences on human activities but also add a unique twist akin to a well-executed trick play.
Harking back to our investigation into the unexpected, our study offers a subliminal nod to the back of shampoo bottles by uncovering the intermingling effects of air pollution and touchdown efficiency. The statistically significant correlation coefficient of 0.5533261 serves as a touchdown pass from the quarterback, defying expectations and reaffirming the unforeseen connections between seemingly unrelated elements.
Furthermore, the soaring r-squared value of 0.3061697 deftly intercepts any doubt, capturing approximately 30.6% of the variability in touchdown efficiency as explained by changes in air pollution levels. Such a robust explanatory power serves as a steadfast reminder that, much like an offensive line, environmental factors can play an integral role in shaping athletic performances.
As we navigate through this discussion, it is essential to recognize the pioneering spirit of our research, echoing the sentiments of "Freakonomics" and "Moneyball." By transcending traditional boundaries and unearthing connections that are as surprising as an onside kick, our study provides a compelling reminder that statistical relationships can emerge from the unlikeliest of pairings. The commingling spirit of the back of shampoo bottles lives on in the unexpected interplay between air pollution and sports, underscoring the unanticipated insights that permeate our investigation.
In summary, our results not only support prior research on the impact of environmental factors on human activities but also reveal the unexpected connections that lie at the intersection of statistics and sports. As we press forward in our academic pursuit, it becomes abundantly clear that the game of science, much like the game of football, contains an abundance of surprises, demonstrating that in the world of research, as in the world of sports, the most unassuming relationships can yield remarkable insights.
Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a short conclusion of an academic research paper presenting the findings of the connection between Air pollution in Morgan City, Louisiana and T/G ratio rank for Teams Coached by Bill Belichick. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.
Here are the title, abstract, introduction, and results sections.
[[TITLE]]
The Gridiron and the Smog: Evaluating the Relationship Between Air Pollution in Morgan City, Louisiana, and T/G Ratio Rank for Teams Coached by Bill Belichick
[[ABSTRACT]]
In this study, we delve into the unlikely connection between air pollution in Morgan City, Louisiana, and the T/G (touchdowns per game) ratio rank for teams led by none other than the legendary coach, Bill Belichick. By harnessing data from the Environmental Protection Agency and Pro-football-reference, our research team has meticulously examined the relationship between these seemingly disparate variables. Employing rigorous statistical analysis, we pinpointed a notable correlation coefficient of 0.5533261 and a p-value that is unequivocally less than 0.05 for the period spanning 1989 to 2004.
Our investigation, which excludes any interception of factual evidence, reveals a robust statistical linkage between air pollution levels in one locale and the touchdown-to-game ratio performance of a distinct group of football teams. This serendipitous discovery opens a window into the inextricable web that our environment weaves with the outcomes of competitive sports. With this insight, it becomes imperative to not only consider the playbook, but also the pollution levels, when evaluating the success of a football team. As our research continues, we anticipate unearthing more unexpected connections that remind us that, sometimes, the game of science is just as unpredictable as the game of football itself.
[[INTRDUCTION]]
As the immortal words of Vince Lombardi echo through the hallowed halls of football lore, one cannot ignore the impact of the environment on the gridiron. Our study sets out to tackle the curious conundrum of the relationship between air pollution in the enchanting locale of Morgan City, Louisiana, and the T/G (touchdowns per game) ratio rank for teams piloted by the enigmatic Bill Belichick. The intertwining of these seemingly incongruent variables invites a game of statistical analysis that promises to be as thrilling as a last-second Hail Mary pass.
This undertaking aims to shed light on the unexpected synergies that exist between atmospheric impurities and the strategic prowess displayed on the football field. By expertly weaving together data from the Environmental Protection Agency and Pro-football-reference, our research endeavors to unmask the clandestine connection between air quality and touchdown efficiency, proving that in the world of statistics, truth is often stranger than fiction.
The notion of gauging the merit of a pigskin squad through the lens of environmental elements may seem as outlandish as a flea-flicker play, but our findings reveal an undeniable correlation coefficient of 0.5533261 and a p-value that is unequivocally less than 0.05 for the time span stretching from 1989 to 2004. With such statistical credence at our disposal, we stand poised to challenge the conventional wisdom that the success of a football team is solely a product of X's and O's, while also proving that in the game of research, sometimes the most unexpected variables end up on top of the podium.
As the study takes flight, one cannot help but ponder the serendipitous intersections that permeate the scientific realm. Our research journey serves as a testament to the idea that in the field of academia, just like on the gridiron, the most remarkable discoveries often arise from the most improbable pairings. Stay tuned as we unravel more of the unexpected connections that demonstrate that in the game of statistics, as in the game of football, sometimes the underdog variables score the most memorable touchdowns.
[[RESULTS]]
The analysis of our data revealed a statistically significant correlation between air pollution levels in Morgan City, Louisiana, and the T/G ratio rank for teams coached by the illustrious Bill Belichick. We found a correlation coefficient of 0.5533261, indicating a moderately strong positive relationship between these two seemingly unrelated variables. The r-squared value of 0.3061697 further confirms that approximately 30.6% of the variability in T/G ratio rank can be explained by changes in air pollution levels. Additionally, the p-value of less than 0.05 provides compelling evidence to reject the null hypothesis and accept the alternative hypothesis that there is indeed a significant relationship between air pollution and touchdown efficiency for teams under Coach Belichick's guidance.
Notably, the scatterplot (Fig. 1) visually illustrates the pronounced positive correlation between air pollution levels in Morgan City and the T/G ratio rank for teams coached by Bill Belichick. The trendline prominently slants upward, symbolizing the increasing T/G ratio rank as air pollution levels surge, or to put it in football terms, the touchdowns flowing in as thick as the smog in Morgan City.
These findings, which may initially seem as incongruous as a quarterback taking the field in a tutu, underscore the unforeseen interplay between environmental factors and on-field performance. As we square off against the intriguing connections unveiled by our research, it becomes evident that the entanglement of air quality and touchdown efficiency is as surprising as a fake punt from one's own end zone.
The unanticipated convergence of air pollution in Morgan City and the touchdown performances of teams led by Bill Belichick urges us to broaden the scope of consideration when analyzing the success of football teams. It serves as a compelling reminder that, in both the realm of research and the realm of sports, dismissing unlikely variables can be as perilous as throwing into double coverage.
In summary, our investigation has not only tackled this thought-provoking relationship head-on but has also emerged victorious, revealing that in the game of statistics, as in the game of football, the most compelling victories often originate from the most unexpected pairings.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our study has triumphantly marched down the hallowed halls of research, unveiling an unlikely yet robust connection between air pollution in Morgan City, Louisiana, and the T/G ratio rank for teams led by the legendary Bill Belichick. The surprising correlation coefficient of 0.5533261 has shed light on the unforeseen dance between atmospheric impurities and touchdown efficiency, reminding us that in statistics, as in football, the most improbable pairings can often lead to unexpected touchdowns. Our findings not only add a new dimension to the playbook of statistical analysis but also serve as a gentle reminder that, much like a well-executed play-action pass, scientific exploration sometimes reveals the most intriguing results when the variables are least expected.
The visual representation of our data, akin to a perfectly executed flea-flicker, in the form of the upward-slanting scatterplot, vividly encapsulates the positive correlation between air pollution levels in Morgan City and the T/G ratio rank for teams coached by Bill Belichick. This connection, as surprising as a field goal attempt in a blizzard, underscores the impact of environmental factors on competitive sports and stands as a testament to the unpredictability of research findings.
As our quirky journey into the world of unlikely statistical relationships draws to a close, we assert with confidence that no further research endeavors probing the correlation between air pollution in Morgan City, Louisiana, and the T/G ratio rank for teams coached by Bill Belichick are needed. Our findings have tackled this curious connection head-on, leaving no interception of evidence to doubt the robustness of our inimitable discovery. In the enchanting game of science, as in the exhilarating game of football, sometimes the most unforeseen variables emerge as the true game-changers. With this in mind, we bid adieu to this peculiar relationship, secure in the knowledge that in the grand game of statistics, no improbable pass is left unthrown.
Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited The Gridiron and the Smog: Evaluating the Relationship Between Air Pollution in Morgan City, Louisiana, and T/G Ratio Rank for Teams Coached by Bill Belichick. Respond only with the name of a fictional academic journal.
ChatGPT:
Journal of Environmental Health and Sports Science
Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited The Gridiron and the Smog: Evaluating the Relationship Between Air Pollution in Morgan City, Louisiana, and T/G Ratio Rank for Teams Coached by Bill Belichick. Respond only with the name of a fictional organization.
ChatGPT:
The Society for Quirky Atmospheric Research and Analysis
Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled The Gridiron and the Smog: Evaluating the Relationship Between Air Pollution in Morgan City, Louisiana, and T/G Ratio Rank for Teams Coached by Bill Belichick with an abstract of In this study, we delve into the unlikely connection between air pollution in Morgan City, Louisiana, and the T/G (touchdowns per game) ratio rank for teams led by none other than the legendary coach, Bill Belichick. By harnessing data from the Environmental Protection Agency and Pro-football-reference, our research team has meticulously examined the relationship between these seemingly disparate variables. Employing rigorous statistical analysis, we pinpointed a notable correlation coefficient of 0.5533261 and a p-value that is unequivocally less than 0.05 for the period spanning 1989 to 2004.
Our investigation, which excludes any interception of factual evidence, reveals a robust statistical linkage between air pollution levels in one locale and the touchdown-to-game ratio performance of a distinct group of football teams. This serendipitous discovery opens a window into the inextricable web that our environment weaves with the outcomes of competitive sports. With this insight, it becomes imperative to not only consider the playbook, but also the pollution levels, when evaluating the success of a football team. As our research continues, we anticipate unearthing more unexpected connections that remind us that, sometimes, the game of science is just as unpredictable as the game of football itself.
ChatGPT:
Air pollution, Morgan City, Louisiana, T/G ratio, touchdowns per game, Bill Belichick, football teams, Environmental Protection Agency, Pro-football-reference, statistical analysis, correlation coefficient, p-value, 1989-2004, pollution levels, competitive sports, environmental impact on sports success, science of football
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
Discover a new correlation
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Data details
Air pollution in Morgan City, LouisianaDetailed data title: Percentage of days 'unhealthy' or worse air quality in Morgan City, LA
Source: Environmental Protection Agency
See what else correlates with Air pollution in Morgan City, Louisiana
T/G ratio rank for Teams Coached by Bill Belichick
Detailed data title: Ranking of Point Differential for Teams Coached by Bill Belichick
Source: Pro-football-reference
See what else correlates with T/G ratio rank for Teams Coached by Bill Belichick
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 = 0.3061697 (Coefficient of determination)
This means 30.6% of the change in the one variable (i.e., T/G ratio rank for Teams Coached by Bill Belichick) is predictable based on the change in the other (i.e., Air pollution in Morgan City, Louisiana) over the 16 years from 1989 through 2004.
p < 0.05, which statistically significant(Null hypothesis significance test)
The p-value is 0.026. 0.0261883416422259400000000000
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 0.55 in 2.6% of random cases. Said differently, if you correlated 38 random variables Which I absolutely did.
with the same 15 degrees of freedom, 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.
[ 0.08, 0.82 ] 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.
| 1989 | 1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | |
| Air pollution in Morgan City, Louisiana (Bad air quality days) | 0.00290698 | 0.00280899 | 0 | 0 | 0.00273973 | 0 | 0.0262172 | 0 | 0.00275482 | 0.0169972 | 0.0142045 | 0.0139665 | 0 | 0 | 0 | 0.00286533 |
| T/G ratio rank for Teams Coached by Bill Belichick (Rank) | 4 | 2 | 16 | 13 | 16 | 3 | 24 | 0 | 9 | 5 | 17 | 23 | 7 | 14 | 6 | 1 |
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
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
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. 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([0.00290698,0.00280899,0,0,0.00273973,0,0.0262172,0,0.00275482,0.0169972,0.0142045,0.0139665,0,0,0,0.00286533,])
array_2 = np.array([4,2,16,13,16,3,24,0,9,5,17,23,7,14,6,1,])
array_1_name = "Air pollution in Morgan City, Louisiana"
array_2_name = "T/G ratio rank for Teams Coached by Bill Belichick"
# 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. 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.
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Download images for these variables:
- High resolution line chart
The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.
If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.
Alternatively you can use a tool like Inkscape. - High resolution line chart, optimized for mobile
- Alternative high resolution line chart
- Scatterplot
- Portable line chart (png)
- Portable line chart (png), optimized for mobile
- Line chart for only Air pollution in Morgan City, Louisiana
- Line chart for only T/G ratio rank for Teams Coached by Bill Belichick
- AI-generated correlation image
- The spurious research paper: The Gridiron and the Smog: Evaluating the Relationship Between Air Pollution in Morgan City, Louisiana, and T/G Ratio Rank for Teams Coached by Bill Belichick
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Correlation ID: 2077 · Black Variable ID: 21669 · Red Variable ID: 329
