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AI explanation
As more athletes trained in Florida, their competitive drive created a need for faster transportation. This led to a surge in private jet usage, causing an unexpected spike in jet fuel demand all the way in Burkina Faso, where the skies were suddenly busier than a championship game! It's a literal case of Florida's sporting success taking off and fueling the distant dreams of Burkina Faso's aviation industry.Model: dalle-3
Prompt: Prompt: Generate an image in the style of a classic black-and-white newspaper illustration. Depict a vibrant Florida stadium filled with athletes and sports competitors showcasing their talents in various events. In the background, show a plane being refueled with jet fuel in Burkina Faso, readying itself for its next journey across the skies. Capture the energy of the stadium atmosphere and the efficiency of the refueling process in a straightforward, evocative manner. 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 athletes and sports competitors in Florida and Jet fuel used in Burkina Faso. 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: Hyper-realistic A black-and-white newspaper illustration Cubism Cubism Surrealism
ChatGPT: A black-and-white newspaper illustration
Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both The number of athletes and sports competitors in Florida and Jet fuel used in Burkina Faso together. Keep the description simple.
ChatGPT: In a bustling stadium in Florida, a flock of athletes and sports competitors are engaging in various events, showcasing their talents and skills. Nearby, in Burkina Faso, a plane is being refueled with jet fuel, readying itself for its next journey across the skies.
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: [ A black-and-white newspaper illustration ] and depicting this scene: In a bustling stadium in Florida, a flock of athletes and sports competitors are engaging in various events, showcasing their talents and skills. Nearby, in Burkina Faso, a plane is being refueled with jet fuel, readying itself for its next journey across the skies. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image in the style of a classic black-and-white newspaper illustration. Depict a vibrant Florida stadium filled with athletes and sports competitors showcasing their talents in various events. In the background, show a plane being refueled with jet fuel in Burkina Faso, readying itself for its next journey across the skies. Capture the energy of the stadium atmosphere and the efficiency of the refueling process in a straightforward, evocative manner.
*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 an increase in The number of athletes and sports competitors in Florida caused Jet fuel used in Burkina Faso to increase.
AI academic paper
For the Exercise-Crazed and Fuel-Amazed: The Relationship Between Florida's Athletes and Burkina Faso's Jet Fuel The Journal of Exercise Science and Cross-Cultural Energy Studies Jan 2024 Reminder: This paper is AI-generated. Not real! |
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 athletes and sports competitors in Florida and Jet fuel used in Burkina Faso. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.
Rhyme words in the title.
Your research team used data from Bureau of Larbor Statistics and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.8511511 and p < 0.01 for 2003 to 2021.
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]]
For the Exercise-Crazed and Fuel-Amazed: The Relationship Between Florida's Athletes and Burkina Faso's Jet Fuel
[[ABSTRACT]]
This study delves into the curious correlation between the number of athletes and sports competitors in the sunshine state of Florida and the jet fuel consumption in the exotic land of Burkina Faso. Using data from the Bureau of Labor Statistics and the Energy Information Administration, we set out to explore this unexpected connection. Our findings reveal a striking correlation coefficient of 0.8511511 and a p-value less than 0.01 for the period spanning from 2003 to 2021. We wax poetic about the unexpected and uncanny relationship between the pounding of sneakers on Florida's tracks and the roaring of jet engines in Burkina Faso's skies. This paper offers a lighthearted look at an otherwise serious statistical study, providing insight with a touch of whimsy.
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 athletes and sports competitors in Florida and Jet fuel used in Burkina Faso. 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]]
For the Exercise-Crazed and Fuel-Amazed: The Relationship Between Florida's Athletes and Burkina Faso's Jet Fuel
[[ABSTRACT]]
This study delves into the curious correlation between the number of athletes and sports competitors in the sunshine state of Florida and the jet fuel consumption in the exotic land of Burkina Faso. Using data from the Bureau of Labor Statistics and the Energy Information Administration, we set out to explore this unexpected connection. Our findings reveal a striking correlation coefficient of 0.8511511 and a p-value less than 0.01 for the period spanning from 2003 to 2021. We wax poetic about the unexpected and uncanny relationship between the pounding of sneakers on Florida's tracks and the roaring of jet engines in Burkina Faso's skies. This paper offers a lighthearted look at an otherwise serious statistical study, providing insight with a touch of whimsy.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
1. INTRODUCTION
The world of statistical research is a curious one, filled with unexpected connections and uncanny correlations that leave even the most seasoned researchers scratching their heads. In our quest to unravel the mysteries of quantitative relationships, we stumbled upon a peculiar pairing that seemed to defy all conventional logic: the relationship between the number of athletes and sports competitors in Florida and the jet fuel consumption in Burkina Faso.
At first glance, this pairing might appear to be as random as trying to correlate the price of tea in China with the number of stars in the galaxy. However, as any seasoned statistician will tell you, the beauty of our craft lies in uncovering the hidden threads that weave disparate data points into a coherent tapestry of insight. And so, armed with an arsenal of data from the Bureau of Labor Statistics and the Energy Information Administration, we embarked on a journey to untangle this enigmatic web of numbers.
The juxtaposition of Florida's bustling athletic scene against Burkina Faso's consumption of jet fuel may seem like an odd couple, akin to trying to mix oil and water in a statistical sense. Yet, as we dove deeper into the data, a curious pattern began to emerge, revealing a correlation that begged for further exploration. As our findings will demonstrate, the relationship between these seemingly unrelated variables is as intriguing as it is unexpected.
In the following pages, we will lead you through our whimsical wanderings into the world of statistical analysis, offering a lighthearted yet insightful perspective on the interplay of athletic prowess and aviation fuel. So buckle up, get your data goggles on, and prepare for a journey through the exhilarating labyrinth of statistical discovery. As the saying goes, "It's not rocket science – it's statistical magic!"
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 athletes and sports competitors in Florida and Jet fuel used in Burkina Faso. 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 you might move on to cartoons and children's shows that you watched for research.
Here is the title and abstract of the paper:
[[TITLE]]
For the Exercise-Crazed and Fuel-Amazed: The Relationship Between Florida's Athletes and Burkina Faso's Jet Fuel
[[ABSTRACT]]
This study delves into the curious correlation between the number of athletes and sports competitors in the sunshine state of Florida and the jet fuel consumption in the exotic land of Burkina Faso. Using data from the Bureau of Labor Statistics and the Energy Information Administration, we set out to explore this unexpected connection. Our findings reveal a striking correlation coefficient of 0.8511511 and a p-value less than 0.01 for the period spanning from 2003 to 2021. We wax poetic about the unexpected and uncanny relationship between the pounding of sneakers on Florida's tracks and the roaring of jet engines in Burkina Faso's skies. This paper offers a lighthearted look at an otherwise serious statistical study, providing insight with a touch of whimsy.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
1. INTRODUCTION
The world of statistical research is a curious one, filled with unexpected connections and uncanny correlations that leave even the most seasoned researchers scratching their heads. In our quest to unravel the mysteries of quantitative relationships, we stumbled upon a peculiar pairing that seemed to defy all conventional logic: the relationship between the number of athletes and sports competitors in Florida and the jet fuel consumption in Burkina Faso.
At first glance, this pairing might appear to be as random as trying to correlate the price of tea in China with the number of stars in the galaxy. However, as any seasoned statistician will tell you, the beauty of our craft lies in uncovering the hidden threads that weave disparate data points into a coherent tapestry of insight. And so, armed with an arsenal of data from the Bureau of Labor Statistics and the Energy Information Administration, we embarked on a journey to untangle this enigmatic web of numbers.
The juxtaposition of Florida's bustling athletic scene against Burkina Faso's consumption of jet fuel may seem like an odd couple, akin to trying to mix oil and water in a statistical sense. Yet, as we dove deeper into the data, a curious pattern began to emerge, revealing a correlation that begged for further exploration. As our findings will demonstrate, the relationship between these seemingly unrelated variables is as intriguing as it is unexpected.
In the following pages, we will lead you through our whimsical wanderings into the world of statistical analysis, offering a lighthearted yet insightful perspective on the interplay of athletic prowess and aviation fuel. So buckle up, get your data goggles on, and prepare for a journey through the exhilarating labyrinth of statistical discovery. As the saying goes, "It's not rocket science – it's statistical magic!"
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
In their seminal work, "The Impact of Athletic Pursuits on Global Fuel Consumption," Smith et al. explore the intricate dance of athletic activity and its ripple effects on the energy landscape of far-flung nations. Their rigorous analysis sheds light on the surprising link between the number of athletes and sports competitors in various regions and the consumption of jet fuel, uncovering a web of connections that stretches from the shimmering sands of Florida to the bustling airports of Burkina Faso.
Building upon this foundation, Doe's comprehensive study, "Fueling the Fire: A Statistical Analysis of Sports and Jet Fuel," delves into the economic and environmental repercussions of the burgeoning athletic scene and its intersection with the world of aviation. Doe's work unearths fascinating insights into how the sweat and toil of athletes in one corner of the globe can reverberate through the skies and into the fuel tanks of aircraft thousands of miles away.
Jones, in "Run Like the Wind, Soar Like a Plane: The Unlikely Kinship of Athletes and Aviation," takes a more philosophical approach, contemplating the existential parallels between the striving of athletes and the propulsion of aircraft. Through a blend of statistical analysis and poetic rumination, Jones illuminates the symbiotic relationship between these seemingly disparate domains, beckoning readers to ponder the metaphorical tapestry that weaves together human physical prowess and the marvels of modern air travel.
Turning to more tangentially related literature, we find "The Jet Setting Jocks: A Comparative Study of Global Athletes and Aeronautical Advancements" by Book. This work offers a panoramic view of the interplay between athletic phenomena and the evolution of aviation technologies, drawing parallels between the soaring leaps of athletes and the forward thrust of technological progress.
On a slightly different tangent, "The Running Pilots of Burkina Faso" by Novel delves into the fictional realm, crafting a narrative that intertwines the lives of marathon runners and daring aviators in the heart of West Africa. While not grounded in empirical analysis, this work grants a glimpse into the whimsical fusion of athletic prowess and airborne ambitions, sparking the imagination with its captivating storytelling.
Shifting from the realm of non-fiction to fiction, "Wings of Speed: A Tale of Runners and Flyers" by Storyteller offers a charming narrative that blurs the boundaries between the kinetic energy of runners and the propulsive force of jet engines. Though not a scholarly work, this literary exploration provides an enchanting glimpse into the fanciful intersections of athleticism and aviation.
Expanding our purview beyond traditional academic sources, we come across the animated series "Turbo Tracks and Sky High: A Cartoon Convergence" and the children's show "Aerobic Aeronauts." While not conventional sources for scholarly inquiry, these whimsical portrayals of athletic endeavors and aerial exploits offer a playful lens through which to contemplate the unexpected threads that tie together the world of sports and the domain of aviation.
As this whirlwind tour of literature demonstrates, the intersection of athletic pursuits and jet fuel consumption is far from a dry and mundane subject. From scholarly treatises to flights of literary fancy, the diverse array of works on this topic reflects the multifaceted nature of the relationship at hand. With each source offering its own unique perspective, we are reminded that statistical inquiry can be as entertaining as it is enlightening.
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 athletes and sports competitors in Florida and Jet fuel used in Burkina Faso. 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 Energy Information Administration . You used data from 2003 to 2021
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]]
For the Exercise-Crazed and Fuel-Amazed: The Relationship Between Florida's Athletes and Burkina Faso's Jet Fuel
[[ABSTRACT]]
This study delves into the curious correlation between the number of athletes and sports competitors in the sunshine state of Florida and the jet fuel consumption in the exotic land of Burkina Faso. Using data from the Bureau of Labor Statistics and the Energy Information Administration, we set out to explore this unexpected connection. Our findings reveal a striking correlation coefficient of 0.8511511 and a p-value less than 0.01 for the period spanning from 2003 to 2021. We wax poetic about the unexpected and uncanny relationship between the pounding of sneakers on Florida's tracks and the roaring of jet engines in Burkina Faso's skies. This paper offers a lighthearted look at an otherwise serious statistical study, providing insight with a touch of whimsy.
[[INTRODUCTION]]
1. INTRODUCTION
The world of statistical research is a curious one, filled with unexpected connections and uncanny correlations that leave even the most seasoned researchers scratching their heads. In our quest to unravel the mysteries of quantitative relationships, we stumbled upon a peculiar pairing that seemed to defy all conventional logic: the relationship between the number of athletes and sports competitors in Florida and the jet fuel consumption in Burkina Faso.
At first glance, this pairing might appear to be as random as trying to correlate the price of tea in China with the number of stars in the galaxy. However, as any seasoned statistician will tell you, the beauty of our craft lies in uncovering the hidden threads that weave disparate data points into a coherent tapestry of insight. And so, armed with an arsenal of data from the Bureau of Labor Statistics and the Energy Information Administration, we embarked on a journey to untangle this enigmatic web of numbers.
The juxtaposition of Florida's bustling athletic scene against Burkina Faso's consumption of jet fuel may seem like an odd couple, akin to trying to mix oil and water in a statistical sense. Yet, as we dove deeper into the data, a curious pattern began to emerge, revealing a correlation that begged for further exploration. As our findings will demonstrate, the relationship between these seemingly unrelated variables is as intriguing as it is unexpected.
In the following pages, we will lead you through our whimsical wanderings into the world of statistical analysis, offering a lighthearted yet insightful perspective on the interplay of athletic prowess and aviation fuel. So buckle up, get your data goggles on, and prepare for a journey through the exhilarating labyrinth of statistical discovery. As the saying goes, "It's not rocket science – it's statistical magic!"
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
For the uninitiated, our journey into the world of statistical acrobatics began with the meticulous collection of data from the Bureau of Labor Statistics for the number of athletes and sports competitors in Florida and the Energy Information Administration for the jet fuel consumption in Burkina Faso. Our data-hungry team combed through the virtual haystack that is the internet, utilizing sophisticated search algorithms to extract the needles of information we sought. We cast our nets wide, but focused mainly on the data spanning from 2003 to 2021, as we sought to capture the essence of the intriguing relationship between athletic zeal and aviation fuel over nearly two decades.
To address the relentless demands of statistical rigor, we had to ensure that our data was as clean as a newly laundered lab coat. This involved a series of customary data scrubbing and preening procedures, wherein outliers were gently nudged back into the flock of legitimate data points, and missing values were coaxed out of hiding like shy woodland creatures. Once satisfied with the cleanliness and trimness of our data, we proceeded to perform a dance of correlation, unleashing the formidable powers of the Pearson correlation coefficient to discern the degree of association between the number of athletes in Florida and the jet fuel consumption in Burkina Faso.
The stages were set, the data was arrayed, and the statistical stagehands worked behind the scenes to execute a carefully choreographed routine of hypothesis testing. With a whimsical flourish of error terms and p-values, we determined the level of significance, invoking the mighty p-value of less than 0.01 to herald the intriguing character of the relationship we uncovered. To ensure the statistical spectacle was not a mere fluke, we conducted sensitivity analyses and robustness checks, probing our findings from every angle like a curious child inspecting a new toy.
In the end, our research methodology could be likened to a lively jig of statistical wizardry, weaving together the intricacies of data collection, scrubbing, analysis, and interpretation into a performance that both educates and entertains. As we navigated the twists and turns of our statistical labyrinth, we upheld the mantra that rigorous scientific inquiry need not be devoid of levity and joy. After all, who says statistical research can't be a romp through the wild meadows of data and discoveries?
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 athletes and sports competitors in Florida and Jet fuel used in Burkina Faso. 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 Energy Information Administration .
For the time period 2003 to 2021, you found a correlation 0.8511511, r-squared of 0.7244581, 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]]
For the Exercise-Crazed and Fuel-Amazed: The Relationship Between Florida's Athletes and Burkina Faso's Jet Fuel
[[ABSTRACT]]
This study delves into the curious correlation between the number of athletes and sports competitors in the sunshine state of Florida and the jet fuel consumption in the exotic land of Burkina Faso. Using data from the Bureau of Labor Statistics and the Energy Information Administration, we set out to explore this unexpected connection. Our findings reveal a striking correlation coefficient of 0.8511511 and a p-value less than 0.01 for the period spanning from 2003 to 2021. We wax poetic about the unexpected and uncanny relationship between the pounding of sneakers on Florida's tracks and the roaring of jet engines in Burkina Faso's skies. This paper offers a lighthearted look at an otherwise serious statistical study, providing insight with a touch of whimsy.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
1. INTRODUCTION
The world of statistical research is a curious one, filled with unexpected connections and uncanny correlations that leave even the most seasoned researchers scratching their heads. In our quest to unravel the mysteries of quantitative relationships, we stumbled upon a peculiar pairing that seemed to defy all conventional logic: the relationship between the number of athletes and sports competitors in Florida and the jet fuel consumption in Burkina Faso.
At first glance, this pairing might appear to be as random as trying to correlate the price of tea in China with the number of stars in the galaxy. However, as any seasoned statistician will tell you, the beauty of our craft lies in uncovering the hidden threads that weave disparate data points into a coherent tapestry of insight. And so, armed with an arsenal of data from the Bureau of Labor Statistics and the Energy Information Administration, we embarked on a journey to untangle this enigmatic web of numbers.
The juxtaposition of Florida's bustling athletic scene against Burkina Faso's consumption of jet fuel may seem like an odd couple, akin to trying to mix oil and water in a statistical sense. Yet, as we dove deeper into the data, a curious pattern began to emerge, revealing a correlation that begged for further exploration. As our findings will demonstrate, the relationship between these seemingly unrelated variables is as intriguing as it is unexpected.
In the following pages, we will lead you through our whimsical wanderings into the world of statistical analysis, offering a lighthearted yet insightful perspective on the interplay of athletic prowess and aviation fuel. So buckle up, get your data goggles on, and prepare for a journey through the exhilarating labyrinth of statistical discovery. As the saying goes, "It's not rocket science – it's statistical magic!"
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The statistical analysis revealed a noteworthy correlation between the number of athletes and sports competitors in Florida and the jet fuel consumption in Burkina Faso for the period from 2003 to 2021. The correlation coefficient of 0.8511511 indicated a strong positive relationship between these two seemingly disparate variables. This means that as the number of athletes and sports competitors in Florida increased, there was a corresponding increase in the jet fuel consumption in Burkina Faso.
The coefficient of determination (r-squared) was calculated to be 0.7244581, suggesting that approximately 72.45% of the variation in jet fuel usage in Burkina Faso can be explained by the number of athletes and sports competitors in Florida. This finding not only highlights the strength of the relationship between these variables but also emphasizes the impact of athletic activities in Florida on the demand for jet fuel in Burkina Faso.
The p-value, being less than 0.01, further supports the significance of this correlation, providing strong evidence against the null hypothesis of no relationship between the variables. In other words, our results indicate that the observed association is unlikely to be a result of random chance, but rather a genuine connection that merits further scrutiny. This statistical significance adds weight to the implications of our findings and underscores the potential implications for both athletic endeavors and aviation fuel consumption.
Moreover, the scatterplot in Figure 1 visually depicts the striking correlation between the number of athletes and sports competitors in Florida and the jet fuel consumption in Burkina Faso. The scatterplot serves as a compelling visual representation of the relationship uncovered by our analysis, further emphasizing the unexpected and thought-provoking nature of our findings.
In conclusion, our research provides compelling evidence of the entwined nature of athletic activity in Florida and jet fuel consumption in Burkina Faso, offering a whimsical yet thought-provoking insight into the world of statistical exploration. While our study has shed light on this peculiar correlation, it also opens the door for future investigations to unravel the underlying mechanisms driving this statistical magic.
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 athletes and sports competitors in Florida and Jet fuel used in Burkina Faso. 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]]
For the Exercise-Crazed and Fuel-Amazed: The Relationship Between Florida's Athletes and Burkina Faso's Jet Fuel
[[ABSTRACT]]
This study delves into the curious correlation between the number of athletes and sports competitors in the sunshine state of Florida and the jet fuel consumption in the exotic land of Burkina Faso. Using data from the Bureau of Labor Statistics and the Energy Information Administration, we set out to explore this unexpected connection. Our findings reveal a striking correlation coefficient of 0.8511511 and a p-value less than 0.01 for the period spanning from 2003 to 2021. We wax poetic about the unexpected and uncanny relationship between the pounding of sneakers on Florida's tracks and the roaring of jet engines in Burkina Faso's skies. This paper offers a lighthearted look at an otherwise serious statistical study, providing insight with a touch of whimsy.
[[LITERATURE REVIEW]]
In their seminal work, "The Impact of Athletic Pursuits on Global Fuel Consumption," Smith et al. explore the intricate dance of athletic activity and its ripple effects on the energy landscape of far-flung nations. Their rigorous analysis sheds light on the surprising link between the number of athletes and sports competitors in various regions and the consumption of jet fuel, uncovering a web of connections that stretches from the shimmering sands of Florida to the bustling airports of Burkina Faso.
Building upon this foundation, Doe's comprehensive study, "Fueling the Fire: A Statistical Analysis of Sports and Jet Fuel," delves into the economic and environmental repercussions of the burgeoning athletic scene and its intersection with the world of aviation. Doe's work unearths fascinating insights into how the sweat and toil of athletes in one corner of the globe can reverberate through the skies and into the fuel tanks of aircraft thousands of miles away.
Jones, in "Run Like the Wind, Soar Like a Plane: The Unlikely Kinship of Athletes and Aviation," takes a more philosophical approach, contemplating the existential parallels between the striving of athletes and the propulsion of aircraft. Through a blend of statistical analysis and poetic rumination, Jones illuminates the symbiotic relationship between these seemingly disparate domains, beckoning readers to ponder the metaphorical tapestry that weaves together human physical prowess and the marvels of modern air travel.
Turning to more tangentially related literature, we find "The Jet Setting Jocks: A Comparative Study of Global Athletes and Aeronautical Advancements" by Book. This work offers a panoramic view of the interplay between athletic phenomena and the evolution of aviation technologies, drawing parallels between the soaring leaps of athletes and the forward thrust of technological progress.
On a slightly different tangent, "The Running Pilots of Burkina Faso" by Novel delves into the fictional realm, crafting a narrative that intertwines the lives of marathon runners and daring aviators in the heart of West Africa. While not grounded in empirical analysis, this work grants a glimpse into the whimsical fusion of athletic prowess and airborne ambitions, sparking the imagination with its captivating storytelling.
Shifting from the realm of non-fiction to fiction, "Wings of Speed: A Tale of Runners and Flyers" by Storyteller offers a charming narrative that blurs the boundaries between the kinetic energy of runners and the propulsive force of jet engines. Though not a scholarly work, this literary exploration provides an enchanting glimpse into the fanciful intersections of athleticism and aviation.
Expanding our purview beyond traditional academic sources, we come across the animated series "Turbo Tracks and Sky High: A Cartoon Convergence" and the children's show "Aerobic Aeronauts." While not conventional sources for scholarly inquiry, these whimsical portrayals of athletic endeavors and aerial exploits offer a playful lens through which to contemplate the unexpected threads that tie together the world of sports and the domain of aviation.
As this whirlwind tour of literature demonstrates, the intersection of athletic pursuits and jet fuel consumption is far from a dry and mundane subject. From scholarly treatises to flights of literary fancy, the diverse array of works on this topic reflects the multifaceted nature of the relationship at hand. With each source offering its own unique perspective, we are reminded that statistical inquiry can be as entertaining as it is enlightening.
[[RESULTS]]
The statistical analysis revealed a noteworthy correlation between the number of athletes and sports competitors in Florida and the jet fuel consumption in Burkina Faso for the period from 2003 to 2021. The correlation coefficient of 0.8511511 indicated a strong positive relationship between these two seemingly disparate variables. This means that as the number of athletes and sports competitors in Florida increased, there was a corresponding increase in the jet fuel consumption in Burkina Faso.
The coefficient of determination (r-squared) was calculated to be 0.7244581, suggesting that approximately 72.45% of the variation in jet fuel usage in Burkina Faso can be explained by the number of athletes and sports competitors in Florida. This finding not only highlights the strength of the relationship between these variables but also emphasizes the impact of athletic activities in Florida on the demand for jet fuel in Burkina Faso.
The p-value, being less than 0.01, further supports the significance of this correlation, providing strong evidence against the null hypothesis of no relationship between the variables. In other words, our results indicate that the observed association is unlikely to be a result of random chance, but rather a genuine connection that merits further scrutiny. This statistical significance adds weight to the implications of our findings and underscores the potential implications for both athletic endeavors and aviation fuel consumption.
Moreover, the scatterplot in Figure 1 visually depicts the striking correlation between the number of athletes and sports competitors in Florida and the jet fuel consumption in Burkina Faso. The scatterplot serves as a compelling visual representation of the relationship uncovered by our analysis, further emphasizing the unexpected and thought-provoking nature of our findings.
In conclusion, our research provides compelling evidence of the entwined nature of athletic activity in Florida and jet fuel consumption in Burkina Faso, offering a whimsical yet thought-provoking insight into the world of statistical exploration. While our study has shed light on this peculiar correlation, it also opens the door for future investigations to unravel the underlying mechanisms driving this statistical magic.
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Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
The results of our study have brought to light an intriguing association between the number of athletes and sports competitors in Florida and the jet fuel consumption in Burkina Faso. The strong positive correlation coefficient of 0.8511511 that we observed not only adds another dimension to the existing body of literature but also seems to validate the seemingly whimsical yet thought-provoking premises put forward in past studies. It's as if the statistical needle in our analysis decided to take a jog alongside the theme of athletic pursuits and jet-setting adventures proposed by Smith et al.
As we recall Doe's work on the economic and environmental repercussions of sports and jet fuel, our results echo the uncanny reverberations of athletic sweat and toil reaching the skies and fuel tanks of distant lands. The statistical significance of our findings, with a p-value less than 0.01, seems to smirk at skeptics and naysayers, saying, "Statistically speaking, this is no laughing matter!" Oh, but the joy of statistical exploration does have its moments of amusement, does it not?
The coefficient of determination (r-squared) of 0.7244581 further buttresses our findings, painting a picture of around 72.45% of the variation in jet fuel usage in Burkina Faso being swayed by the athletic activities in Florida. It's almost as if the athletes' pursuit of speed and excellence has become an airborne phenomenon, propelling itself into the very fabric of aviation fuel demand. Perhaps Jones, in their contemplation of the existential parallels between athletes and aircraft, was indeed onto something quite literal!
The scatterplot in Figure 1 stands as a whimsical yet visually striking testament to the statistical magic we've unraveled. The adage "seeing is believing" takes on a whole new meaning when it comes to witnessing the unexpected relationship between athletes in Florida and jet fuel consumption in Burkina Faso. As we stand at the precipice of further investigations, the statistical whimsy of this correlation beckons us to don our academic sleuth hats and uncover the mysterious mechanisms driving this statistical tango. Oh, the statistical wonders never cease in their quest for adventure, do they?
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 athletes and sports competitors in Florida and Jet fuel used in Burkina Faso. 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]]
For the Exercise-Crazed and Fuel-Amazed: The Relationship Between Florida's Athletes and Burkina Faso's Jet Fuel
[[ABSTRACT]]
This study delves into the curious correlation between the number of athletes and sports competitors in the sunshine state of Florida and the jet fuel consumption in the exotic land of Burkina Faso. Using data from the Bureau of Labor Statistics and the Energy Information Administration, we set out to explore this unexpected connection. Our findings reveal a striking correlation coefficient of 0.8511511 and a p-value less than 0.01 for the period spanning from 2003 to 2021. We wax poetic about the unexpected and uncanny relationship between the pounding of sneakers on Florida's tracks and the roaring of jet engines in Burkina Faso's skies. This paper offers a lighthearted look at an otherwise serious statistical study, providing insight with a touch of whimsy.
[[INTRDUCTION]]
1. INTRODUCTION
The world of statistical research is a curious one, filled with unexpected connections and uncanny correlations that leave even the most seasoned researchers scratching their heads. In our quest to unravel the mysteries of quantitative relationships, we stumbled upon a peculiar pairing that seemed to defy all conventional logic: the relationship between the number of athletes and sports competitors in Florida and the jet fuel consumption in Burkina Faso.
At first glance, this pairing might appear to be as random as trying to correlate the price of tea in China with the number of stars in the galaxy. However, as any seasoned statistician will tell you, the beauty of our craft lies in uncovering the hidden threads that weave disparate data points into a coherent tapestry of insight. And so, armed with an arsenal of data from the Bureau of Labor Statistics and the Energy Information Administration, we embarked on a journey to untangle this enigmatic web of numbers.
The juxtaposition of Florida's bustling athletic scene against Burkina Faso's consumption of jet fuel may seem like an odd couple, akin to trying to mix oil and water in a statistical sense. Yet, as we dove deeper into the data, a curious pattern began to emerge, revealing a correlation that begged for further exploration. As our findings will demonstrate, the relationship between these seemingly unrelated variables is as intriguing as it is unexpected.
In the following pages, we will lead you through our whimsical wanderings into the world of statistical analysis, offering a lighthearted yet insightful perspective on the interplay of athletic prowess and aviation fuel. So buckle up, get your data goggles on, and prepare for a journey through the exhilarating labyrinth of statistical discovery. As the saying goes, "It's not rocket science – it's statistical magic!"
[[RESULTS]]
The statistical analysis revealed a noteworthy correlation between the number of athletes and sports competitors in Florida and the jet fuel consumption in Burkina Faso for the period from 2003 to 2021. The correlation coefficient of 0.8511511 indicated a strong positive relationship between these two seemingly disparate variables. This means that as the number of athletes and sports competitors in Florida increased, there was a corresponding increase in the jet fuel consumption in Burkina Faso.
The coefficient of determination (r-squared) was calculated to be 0.7244581, suggesting that approximately 72.45% of the variation in jet fuel usage in Burkina Faso can be explained by the number of athletes and sports competitors in Florida. This finding not only highlights the strength of the relationship between these variables but also emphasizes the impact of athletic activities in Florida on the demand for jet fuel in Burkina Faso.
The p-value, being less than 0.01, further supports the significance of this correlation, providing strong evidence against the null hypothesis of no relationship between the variables. In other words, our results indicate that the observed association is unlikely to be a result of random chance, but rather a genuine connection that merits further scrutiny. This statistical significance adds weight to the implications of our findings and underscores the potential implications for both athletic endeavors and aviation fuel consumption.
Moreover, the scatterplot in Figure 1 visually depicts the striking correlation between the number of athletes and sports competitors in Florida and the jet fuel consumption in Burkina Faso. The scatterplot serves as a compelling visual representation of the relationship uncovered by our analysis, further emphasizing the unexpected and thought-provoking nature of our findings.
In conclusion, our research provides compelling evidence of the entwined nature of athletic activity in Florida and jet fuel consumption in Burkina Faso, offering a whimsical yet thought-provoking insight into the world of statistical exploration. While our study has shed light on this peculiar correlation, it also opens the door for future investigations to unravel the underlying mechanisms driving this statistical magic.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
Our statistical foray into the peculiar pairing of Florida's athletes and Burkina Faso's jet fuel consumption has left us marveling at the unexpected dance of numbers. The strong positive relationship we've uncovered is a true testament to the whimsical world of statistical exploration. It seems that as athletes in Florida break a sweat, jet engines in Burkina Faso get fired up – a correlation that's as enigmatic as it is entertaining.
Our findings not only provide a lighthearted insight into the statistical realm but also showcase the playful side of quantitative analysis. As we bid adieu to this statistical extravaganza, we can't help but chuckle at the delightful mystery of it all. It's clear that in the world of statistics, there's always room for a quirky surprise or two – and this unusual connection between athletic endeavors and jet fuel consumption certainly sprinkles a dash of whimsy into the mix.
While our study has shed light on this delightfully odd correlation, it's safe to say that no further research is needed in chasing this statistical fairy tale. As the dust settles on this peculiar connection, we can confidently declare that sometimes, in the words of the great statistical bard, "it's not just correlation, it's a statistical revelation!"
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 For the Exercise-Crazed and Fuel-Amazed: The Relationship Between Florida's Athletes and Burkina Faso's Jet Fuel. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Exercise Science and Cross-Cultural Energy Studies
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 For the Exercise-Crazed and Fuel-Amazed: The Relationship Between Florida's Athletes and Burkina Faso's Jet Fuel. Respond only with the name of a fictional organization.
ChatGPT:
The Center for Global Athlete Fuel Research
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 For the Exercise-Crazed and Fuel-Amazed: The Relationship Between Florida's Athletes and Burkina Faso's Jet Fuel with an abstract of This study delves into the curious correlation between the number of athletes and sports competitors in the sunshine state of Florida and the jet fuel consumption in the exotic land of Burkina Faso. Using data from the Bureau of Labor Statistics and the Energy Information Administration, we set out to explore this unexpected connection. Our findings reveal a striking correlation coefficient of 0.8511511 and a p-value less than 0.01 for the period spanning from 2003 to 2021. We wax poetic about the unexpected and uncanny relationship between the pounding of sneakers on Florida's tracks and the roaring of jet engines in Burkina Faso's skies. This paper offers a lighthearted look at an otherwise serious statistical study, providing insight with a touch of whimsy.
ChatGPT:
Florida, athletes, sports competitors, jet fuel consumption, correlation, Bureau of Labor Statistics, Energy Information Administration, correlation coefficient, p-value, statistical study, Burkina Faso, data analysis
*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 athletes and sports competitors in FloridaDetailed data title: BLS estimate of athletes and sports competitors in Florida
Source: Bureau of Larbor Statistics
See what else correlates with The number of athletes and sports competitors in Florida
Jet fuel used in Burkina Faso
Detailed data title: Volume of jet fuel used consumed in Burkina Faso in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Jet fuel used in Burkina Faso
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 = 0.7244581 (Coefficient of determination)
This means 72.4% of the change in the one variable (i.e., Jet fuel used in Burkina Faso) is predictable based on the change in the other (i.e., The number of athletes and sports competitors in Florida) over the 19 years from 2003 through 2021.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 3.8E-6. 0.0000038333997612797180000000
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 0.00038% of random cases. Said differently, if you correlated 260,865 random variables You don't actually need 260 thousand variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.
p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.
In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.
Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 18 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 18 because we have two variables measured over a period of 19 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.
[ 0.65, 0.94 ] 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.
2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | |
The number of athletes and sports competitors in Florida (Laborers) | 1170 | 1090 | 770 | 980 | 1140 | 1500 | 2190 | 2150 | 2930 | 2920 | 3860 | 3200 | 2840 | 1340 | 1310 | 1320 | 1250 | 550 | 2010 |
Jet fuel used in Burkina Faso (Million Barrels/Day) | 0.445384 | 0.3445 | 0.438866 | 0.599638 | 0.454487 | 0.5005 | 0.611848 | 0.75537 | 0.890615 | 0.921722 | 1.19189 | 0.747375 | 0.788654 | 0.486663 | 0.587526 | 0.647383 | 0.651781 | 0.622366 | 0.656702 |
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([1170,1090,770,980,1140,1500,2190,2150,2930,2920,3860,3200,2840,1340,1310,1320,1250,550,2010,])
array_2 = np.array([0.445384,0.3445,0.438866,0.599638,0.454487,0.5005,0.611848,0.75537,0.890615,0.921722,1.19189,0.747375,0.788654,0.486663,0.587526,0.647383,0.651781,0.622366,0.656702,])
array_1_name = "The number of athletes and sports competitors in Florida"
array_2_name = "Jet fuel used in Burkina Faso"
# 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.
For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."
When spoken, my last name is pronounced "vegan," like I don't eat meat.
Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.
Download images for these variables:
- High resolution line chart
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 The number of athletes and sports competitors in Florida
- Line chart for only Jet fuel used in Burkina Faso
- AI-generated correlation image
- The spurious research paper: For the Exercise-Crazed and Fuel-Amazed: The Relationship Between Florida's Athletes and Burkina Faso's Jet Fuel
Your rating skills are legendary!
Correlation ID: 2287 · Black Variable ID: 6487 · Red Variable ID: 24247