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AI explanation
As more international tourists flocked to Australia, it created a 'plane' old increase in demand for flights within the country, leading to a higher consumption of jet fuel. It's like they say, when it comes to travel, the sky's the limit for both tourists and jet fuel usage Down Under!Model: dalle-3
Prompt: [An image that looks like it is a scene from a Pixar movie] Generate an image that showcases an airport runway set in the vibrant landscape of Australia. As the camera perspective spans the length of the runway, depict a flurry of airplanes both taking off and landing. Highlight the diversity of international airlines with distinctive and colorful liveries, representing the surge in global travel and trade. Capture the energetic activity on the tarmac, illustrating the bustling movement of airplanes and ground crews. Additionally, depict the incoming flights carrying a variety of exotic foods, showcasing the heightened demand for fresh and authentic ingredients to satisfy the evolving palate of tourists. Emphasize the blend of natural beauty and human activity in the scene, creating a visually captivating and dynamic portrayal of the airport runway setting. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.
This image generation prompt was also generated by AI, using the following sequence:
Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the situation described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here is a situation: An increase in the number of international tourist arrivals worldwide led to a surge in jet fuel used in Australia because the influx of tourists demanded a larger variety of cuisines, leading to an increase in flights delivering exotic foods to the land down under. As more tourists sampled and fell in love with Aussie delicacies, they insisted on the freshness and authenticity of the ingredients, resulting in airlines having to ramp up their jet fuel usage for more frequent food deliveries.. Given that situation, which of the following image descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand and the tone of the explanation. Please respond with only one of the following potential descriptions: 3D Pixar Style inspired by bauhaus Charcoal An image that looks like it is a scene from a Pixar movie Charcoal
ChatGPT: An image that looks like it is a scene from a Pixar movie
Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated and the explanation described. Do not reference graphs or charts; describe physical objects.
User prompt: Please describe a visual scene that depicts the following situation. Keep the description simple. An increase in the number of international tourist arrivals worldwide led to a surge in jet fuel used in Australia because the influx of tourists demanded a larger variety of cuisines, leading to an increase in flights delivering exotic foods to the land down under. As more tourists sampled and fell in love with Aussie delicacies, they insisted on the freshness and authenticity of the ingredients, resulting in airlines having to ramp up their jet fuel usage for more frequent food deliveries.
ChatGPT: Picture an airport runway in Australia where you see a significant increase in the number of airplanes taking off and landing. As the camera pans out, you spot various international airlines with colorful livery, symbolizing the surge in international flights. The bustling activity on the tarmac reflects the increased jet fuel usage due to the influx of tourists demanding a wider variety of cuisines. Additionally, the scene is animated by the frequent arrival of planes delivering exotic foods, portraying the heightened demand for fresh and authentic ingredients to cater to the tourists' evolving palate.
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: [ An image that looks like it is a scene from a Pixar movie ] and depicting this scene: Picture an airport runway in Australia where you see a significant increase in the number of airplanes taking off and landing. As the camera pans out, you spot various international airlines with colorful livery, symbolizing the surge in international flights. The bustling activity on the tarmac reflects the increased jet fuel usage due to the influx of tourists demanding a wider variety of cuisines. Additionally, the scene is animated by the frequent arrival of planes delivering exotic foods, portraying the heightened demand for fresh and authentic ingredients to cater to the tourists' evolving palate. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [An image that looks like it is a scene from a Pixar movie] Generate an image that showcases an airport runway set in the vibrant landscape of Australia. As the camera perspective spans the length of the runway, depict a flurry of airplanes both taking off and landing. Highlight the diversity of international airlines with distinctive and colorful liveries, representing the surge in global travel and trade. Capture the energetic activity on the tarmac, illustrating the bustling movement of airplanes and ground crews. Additionally, depict the incoming flights carrying a variety of exotic foods, showcasing the heightened demand for fresh and authentic ingredients to satisfy the evolving palate of tourists. Emphasize the blend of natural beauty and human activity in the scene, creating a visually captivating and dynamic portrayal of the airport runway setting.
*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 Number of International Tourist Arrivals Worldwide caused Jet fuel used in Australia to increase. Include one good pun.
AI academic paper
Travel Trends: Tracking the Ties between Tourist Traffic and Turbine Fuel Journal of Ecotourism and Energy Economics 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 Number of International Tourist Arrivals Worldwide and Jet fuel used in Australia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Make the title an alliteration.
Your research team used data from Statista and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.9654939 and p < 0.01 for 1995 to 2022.
Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)
[[TITLE]]
Lorem ipsum dolor sit
[[ABSTRACT]]
Lorem ipsum dolor sit
ChatGPT:
[[TITLE]]
Travel Trends: Tracking the Ties between Tourist Traffic and Turbine Fuel
[[ABSTRACT]]
The present study delves into the delightful dance between the Number of International Tourist Arrivals Worldwide and the Jet fuel consumption in Australia, unravelling the tangled web of wanderlust and winged wonders. The aim was to elucidate whether there exists a substantial relationship between these seemingly unrelated variables and to explore whether they march to the same beat or simply sway to their own symphony. Our research team pored over data from Statista and the Energy Information Administration to shed light on this quirky connection.
Unsurprisingly, we discovered a strikingly strong correlation between the influx of globetrotters and the amount of jet fuel guzzled by the land down under. The correlation coefficient of 0.9654939 and the p-value of less than 0.01 from our analysis of data spanning from 1995 to 2022 left us marveling at this bountiful bond, like two peas in a pod or mac and cheese. It seems that as vacation enthusiasts flock hither and thither, soars the jet fuel consumption in the sun-kissed expanses of Australia.
A relevant dad joke related to this content: Why don't scientists trust atoms? Because they make up everything – just like the connection we found between tourist arrivals and jet fuel consumption!
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 Number of International Tourist Arrivals Worldwide and Jet fuel used in Australia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Here is the title and abstract of the paper:
[[TITLE]]
Travel Trends: Tracking the Ties between Tourist Traffic and Turbine Fuel
[[ABSTRACT]]
The present study delves into the delightful dance between the Number of International Tourist Arrivals Worldwide and the Jet fuel consumption in Australia, unravelling the tangled web of wanderlust and winged wonders. The aim was to elucidate whether there exists a substantial relationship between these seemingly unrelated variables and to explore whether they march to the same beat or simply sway to their own symphony. Our research team pored over data from Statista and the Energy Information Administration to shed light on this quirky connection.
Unsurprisingly, we discovered a strikingly strong correlation between the influx of globetrotters and the amount of jet fuel guzzled by the land down under. The correlation coefficient of 0.9654939 and the p-value of less than 0.01 from our analysis of data spanning from 1995 to 2022 left us marveling at this bountiful bond, like two peas in a pod or mac and cheese. It seems that as vacation enthusiasts flock hither and thither, soars the jet fuel consumption in the sun-kissed expanses of Australia.
A relevant dad joke related to this content: Why don't scientists trust atoms? Because they make up everything – just like the connection we found between tourist arrivals and jet fuel consumption!
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
Gather 'round, fellow academics and aficionados of statistics, for we are about to embark on a journey that will unravel the interconnectedness of two seemingly unrelated entities: the Number of International Tourist Arrivals Worldwide and the Jet fuel consumption in Australia. This enigmatic relationship has us scratching our heads and chuckling at the unexpected peculiarities of the world of data. It's like trying to find the correlation between a kangaroo's hopping distance and the number of boomerangs sold – peculiar, yet wholly intriguing.
As we delve into the delightful dance between travel trends and jet fuel usage, we must approach this topic with the seriousness it warrants, and yet be open to the unexpected twists and turns, akin to the plot of a scientific thriller (or a melodramatic episode of "CSI: Data Analysis"). It's like trying to find the link between a good cup of tea and the number of sheep in New Zealand – seemingly unrelated, but perhaps hiding an underlying kinship that only statistics can reveal.
Now, as we shed light on the tangled web of wanderlust and winged wonders – a connection that is as cryptic as a complicated math equation but as intriguing as a suspenseful crime novel – we aim to unravel the mystery of whether these variables are mere statistical bedfellows or if they hold a substantial relationship, akin to the bond between peanut butter and jelly. It's like trying to discern the connection between a bar of chocolate and a dentist's waiting room – not immediately obvious, but somehow intertwined in a way that leaves us pondering over the mysterious ways of the universe.
And so, with data from Statista and the Energy Information Administration in hand, we rolled up our sleeves and donned our metaphorical detective hats, ready to crack the case of this zany relationship between tourism and turbine fuel. The plot thickened, just like an expertly prepared gravy, as we uncovered a correlation coefficient of 0.9654939 – a number so robust, it would make even the most devout statistics skeptic raise an eyebrow in wonder. It's like discovering the astonishing resemblance between a coincidental correlation and a perfectly timed punchline – unexpected, yet undeniable.
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 Number of International Tourist Arrivals Worldwide and Jet fuel used in Australia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
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 CVS receipts.
Here is the title and abstract of the paper:
[[TITLE]]
Travel Trends: Tracking the Ties between Tourist Traffic and Turbine Fuel
[[ABSTRACT]]
The present study delves into the delightful dance between the Number of International Tourist Arrivals Worldwide and the Jet fuel consumption in Australia, unravelling the tangled web of wanderlust and winged wonders. The aim was to elucidate whether there exists a substantial relationship between these seemingly unrelated variables and to explore whether they march to the same beat or simply sway to their own symphony. Our research team pored over data from Statista and the Energy Information Administration to shed light on this quirky connection.
Unsurprisingly, we discovered a strikingly strong correlation between the influx of globetrotters and the amount of jet fuel guzzled by the land down under. The correlation coefficient of 0.9654939 and the p-value of less than 0.01 from our analysis of data spanning from 1995 to 2022 left us marveling at this bountiful bond, like two peas in a pod or mac and cheese. It seems that as vacation enthusiasts flock hither and thither, soars the jet fuel consumption in the sun-kissed expanses of Australia.
A relevant dad joke related to this content: Why don't scientists trust atoms? Because they make up everything – just like the connection we found between tourist arrivals and jet fuel consumption!
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Gather 'round, fellow academics and aficionados of statistics, for we are about to embark on a journey that will unravel the interconnectedness of two seemingly unrelated entities: the Number of International Tourist Arrivals Worldwide and the Jet fuel consumption in Australia. This enigmatic relationship has us scratching our heads and chuckling at the unexpected peculiarities of the world of data. It's like trying to find the correlation between a kangaroo's hopping distance and the number of boomerangs sold – peculiar, yet wholly intriguing.
As we delve into the delightful dance between travel trends and jet fuel usage, we must approach this topic with the seriousness it warrants, and yet be open to the unexpected twists and turns, akin to the plot of a scientific thriller (or a melodramatic episode of "CSI: Data Analysis"). It's like trying to find the link between a good cup of tea and the number of sheep in New Zealand – seemingly unrelated, but perhaps hiding an underlying kinship that only statistics can reveal.
Now, as we shed light on the tangled web of wanderlust and winged wonders – a connection that is as cryptic as a complicated math equation but as intriguing as a suspenseful crime novel – we aim to unravel the mystery of whether these variables are mere statistical bedfellows or if they hold a substantial relationship, akin to the bond between peanut butter and jelly. It's like trying to discern the connection between a bar of chocolate and a dentist's waiting room – not immediately obvious, but somehow intertwined in a way that leaves us pondering over the mysterious ways of the universe.
And so, with data from Statista and the Energy Information Administration in hand, we rolled up our sleeves and donned our metaphorical detective hats, ready to crack the case of this zany relationship between tourism and turbine fuel. The plot thickened, just like an expertly prepared gravy, as we uncovered a correlation coefficient of 0.9654939 – a number so robust, it would make even the most devout statistics skeptic raise an eyebrow in wonder. It's like discovering the astonishing resemblance between a coincidental correlation and a perfectly timed punchline – unexpected, yet undeniable.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
In "Smith et al.'s study," the authors find a positive relationship between the Number of International Tourist Arrivals Worldwide and jet fuel consumption in Australia. This finding is in line with the research of Doe and Jones, who also observed a similar connection between the two variables. These scholarly works underscore the interplay between global tourist traffic and the demand for turbine fuel Down Under.
Now, turning to non-fiction sources, "The Economics of Tourism Destinations" by David J. Telfer and Richard Sharpley sheds light on the economic impact of tourism on the energy sector, offering valuable insights that complement our investigation. In a similar vein, "Jet Fuel: A Cultural History of an Industrial Norm" by Patrick Kirchberg explores the societal implications of jet fuel usage, providing a nuanced perspective on the societal and environmental dynamics at play.
Venturing into the realm of fiction, "The Alchemist" by Paulo Coelho and "Around the World in Eighty Days" by Jules Verne, albeit not directly related to the topic at hand, evoke the spirit of exploration and adventure that are inherent in international travel and aircraft fuel consumption. These literary works, in their own whimsical ways, subtly echo the nuances of our research inquiry.
In a lighter vein, our search for relevant literature even extended to scanning CVS receipts in the hope of stumbling upon groundbreaking revelations – alas, only to be greeted by the mundane purchases of toothpaste and chips. However, as the saying goes, it's all about the journey, not just the destination – much like the quest to unravel the mysteries of tourist traffic and turbine fuel consumption.
Amidst our scholarly pursuit, we stumbled upon a hidden gem – a study titled "The Secret Life of Avocado Toast and Its Influence on Air Travel" by Dr. Punny McPunster, which, while not directly related to our research, provided a much-needed dose of levity in our otherwise data-laden endeavors. This tongue-in-cheek exploration of the culinary and aviation realms served as a lighthearted reminder that even the most mundane connections can spark joy, much like a well-timed dad joke in a room full of serious academics.
An unexpected revelation from our literature review was the discovery of an ancient scroll hidden deep within the annals of history, which, upon translation, purported to contain the answers to our research inquiry. Alas, the scroll unravelled tales of mythical creatures embarking on wondrous journeys, leaving us to ponder if perhaps the whimsical nature of its contents held a metaphorical key to understanding the whimsical connection between tourist traffic and turbine fuel usage.
As we bid adieu to the literature review section, we are reminded of the whimsical, interconnected nature of the world – much like the rapport between mundane airline data and the captivating allure of global tourism. In the words of an unknown sage, "May your data be robust, your correlations be lofty, and your sense of humor be dad-joke-worthy."
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 Number of International Tourist Arrivals Worldwide and Jet fuel used in Australia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 Statista and Energy Information Administration . You used data from 1995 to 2022
Make up the research methods you don't know. Make them a bit goofy and convoluted.
Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Travel Trends: Tracking the Ties between Tourist Traffic and Turbine Fuel
[[ABSTRACT]]
The present study delves into the delightful dance between the Number of International Tourist Arrivals Worldwide and the Jet fuel consumption in Australia, unravelling the tangled web of wanderlust and winged wonders. The aim was to elucidate whether there exists a substantial relationship between these seemingly unrelated variables and to explore whether they march to the same beat or simply sway to their own symphony. Our research team pored over data from Statista and the Energy Information Administration to shed light on this quirky connection.
Unsurprisingly, we discovered a strikingly strong correlation between the influx of globetrotters and the amount of jet fuel guzzled by the land down under. The correlation coefficient of 0.9654939 and the p-value of less than 0.01 from our analysis of data spanning from 1995 to 2022 left us marveling at this bountiful bond, like two peas in a pod or mac and cheese. It seems that as vacation enthusiasts flock hither and thither, soars the jet fuel consumption in the sun-kissed expanses of Australia.
A relevant dad joke related to this content: Why don't scientists trust atoms? Because they make up everything – just like the connection we found between tourist arrivals and jet fuel consumption!
[[INTRODUCTION]]
Gather 'round, fellow academics and aficionados of statistics, for we are about to embark on a journey that will unravel the interconnectedness of two seemingly unrelated entities: the Number of International Tourist Arrivals Worldwide and the Jet fuel consumption in Australia. This enigmatic relationship has us scratching our heads and chuckling at the unexpected peculiarities of the world of data. It's like trying to find the correlation between a kangaroo's hopping distance and the number of boomerangs sold – peculiar, yet wholly intriguing.
As we delve into the delightful dance between travel trends and jet fuel usage, we must approach this topic with the seriousness it warrants, and yet be open to the unexpected twists and turns, akin to the plot of a scientific thriller (or a melodramatic episode of "CSI: Data Analysis"). It's like trying to find the link between a good cup of tea and the number of sheep in New Zealand – seemingly unrelated, but perhaps hiding an underlying kinship that only statistics can reveal.
Now, as we shed light on the tangled web of wanderlust and winged wonders – a connection that is as cryptic as a complicated math equation but as intriguing as a suspenseful crime novel – we aim to unravel the mystery of whether these variables are mere statistical bedfellows or if they hold a substantial relationship, akin to the bond between peanut butter and jelly. It's like trying to discern the connection between a bar of chocolate and a dentist's waiting room – not immediately obvious, but somehow intertwined in a way that leaves us pondering over the mysterious ways of the universe.
And so, with data from Statista and the Energy Information Administration in hand, we rolled up our sleeves and donned our metaphorical detective hats, ready to crack the case of this zany relationship between tourism and turbine fuel. The plot thickened, just like an expertly prepared gravy, as we uncovered a correlation coefficient of 0.9654939 – a number so robust, it would make even the most devout statistics skeptic raise an eyebrow in wonder. It's like discovering the astonishing resemblance between a coincidental correlation and a perfectly timed punchline – unexpected, yet undeniable.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
In this quest to unravel the mysterious connection between the Number of International Tourist Arrivals Worldwide and Jet fuel consumption in Australia, we employed an arsenal of methodological tools, akin to the trusty Swiss army knife of statistical analysis. Our data collection journey took us through the winding alleys of the internet, traversing through the vast expanse of cyberspace like intrepid explorers in search of hidden treasure. We scoured databases, primarily relying on the treasure troves of information from Statista and the Energy Information Administration, where the wealth of data shimmered like nuggets of gold awaiting our expert extraction.
To concoct this mystical brew of statistical analysis, we delved into the realms of quantitative wizardry, harnessing the power of time-series analysis to unravel the temporal ebbs and flows of tourist arrivals and jet fuel consumption. We waved our statistical wands and summoned the spirits of regression analysis, conjuring up equations that danced around our data points like well-choreographed ballerinas. Like a carefully crafted potion, we believed that this union of methodologies would unveil the hidden patterns and connections between these seemingly disparate variables. It's like mixing together the right proportions of ingredients in a recipe – a pinch of correlation, a dash of regression, and a sprinkle of time-series analysis – to create a statistical masterpiece.
After cleaning and preparing our data with the meticulousness of a master chef, we embarked on the grand journey of analysis, unleashing the full might of our statistical arsenal to discern the patterns hidden within the sea of numbers. It was a bit like trying to untangle a spaghetti knot while blindfolded – a daunting task, but one that promised the satisfaction of unraveling the mystery within. Our interdisciplinary team, comprising statisticians, economists, and data aficionados, lent their distinct expertise to this grand endeavor, creating a symphony of perspectives that harmonized in our pursuit of uncovering the elusive bond between tourism and turbine fuel. It's like a collaboration between master chefs, each contributing their unique flavors to create a delectable dish – or in our case, a delectable statistical model.
As we journeyed through the rabbit hole of statistical inference, we encountered moments of revelation and surprise, akin to stumbling upon a hidden easter egg in the maze of data. The numbers seemed to whisper secrets to us, revealing the ebb and flow of tourist traffic and the synchronized rhythms of jet fuel consumption. It's like finding a treasure map in a sea of statistical noise – a guide that led us to the heart of this enigmatic relationship, unlocking the mysteries that lay within. And so, armed with our trusty statistical compass and the spirit of scientific inquiry, we braved the tangled thickets of data, determined to conquer the puzzle that lay before us.
In this grand odyssey of statistical investigation, we navigated the treacherous waters of correlation and causation, steering clear of the sirens' call of spurious relationships and statistical fallacies. We maintained a vigilant eye, like watchful guardians of truth, ensuring that our findings stood the test of statistical rigor and intellectual scrutiny. It's like embarking on a perilous quest for the Holy Grail of statistical significance, where the journey is fraught with pitfalls and false idols, but the ultimate prize is worth the toil and tribulations.
Having journeyed through the labyrinthine paths of data analysis, we emerged victorious, armed with empirical evidence that illuminated the captivating connection between the influx of globe-trotters and the soaring jet fuel consumption in the sun-kissed expanses of Australia. Our findings, like the climax of a thrilling detective novel, unfolded with dramatic flair, leaving us awestruck at the profound bond that lay concealed within the numbers. It's like unraveling a carefully woven mystery, where every clue leads to the next, culminating in a revelation that alters our perception of the world around us – an unexpected twist in the scientific narrative.
Oh, and speaking of twists, want to hear a joke about a jet fuel and an international tourist? It’s plain, it’s simple, and yet it takes you for a flight: Why did the jet fuel break up with the international tourist? It just couldn’t handle the baggage!
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 Number of International Tourist Arrivals Worldwide and Jet fuel used in Australia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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 Statista and Energy Information Administration .
For the time period 1995 to 2022, you found a correlation 0.9654939, r-squared of 0.9321784, 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]]
Travel Trends: Tracking the Ties between Tourist Traffic and Turbine Fuel
[[ABSTRACT]]
The present study delves into the delightful dance between the Number of International Tourist Arrivals Worldwide and the Jet fuel consumption in Australia, unravelling the tangled web of wanderlust and winged wonders. The aim was to elucidate whether there exists a substantial relationship between these seemingly unrelated variables and to explore whether they march to the same beat or simply sway to their own symphony. Our research team pored over data from Statista and the Energy Information Administration to shed light on this quirky connection.
Unsurprisingly, we discovered a strikingly strong correlation between the influx of globetrotters and the amount of jet fuel guzzled by the land down under. The correlation coefficient of 0.9654939 and the p-value of less than 0.01 from our analysis of data spanning from 1995 to 2022 left us marveling at this bountiful bond, like two peas in a pod or mac and cheese. It seems that as vacation enthusiasts flock hither and thither, soars the jet fuel consumption in the sun-kissed expanses of Australia.
A relevant dad joke related to this content: Why don't scientists trust atoms? Because they make up everything – just like the connection we found between tourist arrivals and jet fuel consumption!
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
Gather 'round, fellow academics and aficionados of statistics, for we are about to embark on a journey that will unravel the interconnectedness of two seemingly unrelated entities: the Number of International Tourist Arrivals Worldwide and the Jet fuel consumption in Australia. This enigmatic relationship has us scratching our heads and chuckling at the unexpected peculiarities of the world of data. It's like trying to find the correlation between a kangaroo's hopping distance and the number of boomerangs sold – peculiar, yet wholly intriguing.
As we delve into the delightful dance between travel trends and jet fuel usage, we must approach this topic with the seriousness it warrants, and yet be open to the unexpected twists and turns, akin to the plot of a scientific thriller (or a melodramatic episode of "CSI: Data Analysis"). It's like trying to find the link between a good cup of tea and the number of sheep in New Zealand – seemingly unrelated, but perhaps hiding an underlying kinship that only statistics can reveal.
Now, as we shed light on the tangled web of wanderlust and winged wonders – a connection that is as cryptic as a complicated math equation but as intriguing as a suspenseful crime novel – we aim to unravel the mystery of whether these variables are mere statistical bedfellows or if they hold a substantial relationship, akin to the bond between peanut butter and jelly. It's like trying to discern the connection between a bar of chocolate and a dentist's waiting room – not immediately obvious, but somehow intertwined in a way that leaves us pondering over the mysterious ways of the universe.
And so, with data from Statista and the Energy Information Administration in hand, we rolled up our sleeves and donned our metaphorical detective hats, ready to crack the case of this zany relationship between tourism and turbine fuel. The plot thickened, just like an expertly prepared gravy, as we uncovered a correlation coefficient of 0.9654939 – a number so robust, it would make even the most devout statistics skeptic raise an eyebrow in wonder. It's like discovering the astonishing resemblance between a coincidental correlation and a perfectly timed punchline – unexpected, yet undeniable.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
Our analysis unveiled a striking correlation of 0.9654939 between the Number of International Tourist Arrivals Worldwide and Jet fuel consumption in Australia, revealing a relationship so robust that it would put the synchronized dance moves of a professional Riverdance troupe to shame. This correlation coefficient left us marveling at the interconnected elegance of these two variables, like a perfectly executed pun – seamlessly intertwined yet delightfully unexpected.
Furthermore, the r-squared value of 0.9321784 underscored the strength of this connection, as solid as a well-constructed research hypothesis and as dependable as a reliable lab assistant. The p-value of less than 0.01 provided further evidence of the statistical significance of this delightful duo, akin to stumbling upon a rare and precious artifact in the often unpredictable realm of data analysis.
As the data points formed a clear and compelling trajectory in the scatterplot (Fig. 1), showcasing the steadfast relationship between the variables, we couldn't help but marvel at the harmony of these seemingly disparate elements. It's like witnessing an unexpected fusion of musical genres – a harmonious blend that defies conventional expectations and leaves us tapping our toes in delighted surprise.
A relevant dad joke related to this content: Why don't scientists trust atoms? Because they make up everything – just like the connection we found between tourist arrivals and jet fuel consumption!
These findings not only highlight the intriguing connection between global travel patterns and the consumption of jet fuel in Australia but also emphasize the importance of considering unexpected relationships in the realm of statistical analysis. Just like stumbling upon a hidden Easter egg in a video game, this discovery adds a layer of depth and surprise to our understanding of the intricate interplay between diverse variables.
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 Number of International Tourist Arrivals Worldwide and Jet fuel used in Australia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
Travel Trends: Tracking the Ties between Tourist Traffic and Turbine Fuel
[[ABSTRACT]]
The present study delves into the delightful dance between the Number of International Tourist Arrivals Worldwide and the Jet fuel consumption in Australia, unravelling the tangled web of wanderlust and winged wonders. The aim was to elucidate whether there exists a substantial relationship between these seemingly unrelated variables and to explore whether they march to the same beat or simply sway to their own symphony. Our research team pored over data from Statista and the Energy Information Administration to shed light on this quirky connection.
Unsurprisingly, we discovered a strikingly strong correlation between the influx of globetrotters and the amount of jet fuel guzzled by the land down under. The correlation coefficient of 0.9654939 and the p-value of less than 0.01 from our analysis of data spanning from 1995 to 2022 left us marveling at this bountiful bond, like two peas in a pod or mac and cheese. It seems that as vacation enthusiasts flock hither and thither, soars the jet fuel consumption in the sun-kissed expanses of Australia.
A relevant dad joke related to this content: Why don't scientists trust atoms? Because they make up everything – just like the connection we found between tourist arrivals and jet fuel consumption!
[[LITERATURE REVIEW]]
In "Smith et al.'s study," the authors find a positive relationship between the Number of International Tourist Arrivals Worldwide and jet fuel consumption in Australia. This finding is in line with the research of Doe and Jones, who also observed a similar connection between the two variables. These scholarly works underscore the interplay between global tourist traffic and the demand for turbine fuel Down Under.
Now, turning to non-fiction sources, "The Economics of Tourism Destinations" by David J. Telfer and Richard Sharpley sheds light on the economic impact of tourism on the energy sector, offering valuable insights that complement our investigation. In a similar vein, "Jet Fuel: A Cultural History of an Industrial Norm" by Patrick Kirchberg explores the societal implications of jet fuel usage, providing a nuanced perspective on the societal and environmental dynamics at play.
Venturing into the realm of fiction, "The Alchemist" by Paulo Coelho and "Around the World in Eighty Days" by Jules Verne, albeit not directly related to the topic at hand, evoke the spirit of exploration and adventure that are inherent in international travel and aircraft fuel consumption. These literary works, in their own whimsical ways, subtly echo the nuances of our research inquiry.
In a lighter vein, our search for relevant literature even extended to scanning CVS receipts in the hope of stumbling upon groundbreaking revelations – alas, only to be greeted by the mundane purchases of toothpaste and chips. However, as the saying goes, it's all about the journey, not just the destination – much like the quest to unravel the mysteries of tourist traffic and turbine fuel consumption.
Amidst our scholarly pursuit, we stumbled upon a hidden gem – a study titled "The Secret Life of Avocado Toast and Its Influence on Air Travel" by Dr. Punny McPunster, which, while not directly related to our research, provided a much-needed dose of levity in our otherwise data-laden endeavors. This tongue-in-cheek exploration of the culinary and aviation realms served as a lighthearted reminder that even the most mundane connections can spark joy, much like a well-timed dad joke in a room full of serious academics.
An unexpected revelation from our literature review was the discovery of an ancient scroll hidden deep within the annals of history, which, upon translation, purported to contain the answers to our research inquiry. Alas, the scroll unravelled tales of mythical creatures embarking on wondrous journeys, leaving us to ponder if perhaps the whimsical nature of its contents held a metaphorical key to understanding the whimsical connection between tourist traffic and turbine fuel usage.
As we bid adieu to the literature review section, we are reminded of the whimsical, interconnected nature of the world – much like the rapport between mundane airline data and the captivating allure of global tourism. In the words of an unknown sage, "May your data be robust, your correlations be lofty, and your sense of humor be dad-joke-worthy."
[[RESULTS]]
Our analysis unveiled a striking correlation of 0.9654939 between the Number of International Tourist Arrivals Worldwide and Jet fuel consumption in Australia, revealing a relationship so robust that it would put the synchronized dance moves of a professional Riverdance troupe to shame. This correlation coefficient left us marveling at the interconnected elegance of these two variables, like a perfectly executed pun – seamlessly intertwined yet delightfully unexpected.
Furthermore, the r-squared value of 0.9321784 underscored the strength of this connection, as solid as a well-constructed research hypothesis and as dependable as a reliable lab assistant. The p-value of less than 0.01 provided further evidence of the statistical significance of this delightful duo, akin to stumbling upon a rare and precious artifact in the often unpredictable realm of data analysis.
As the data points formed a clear and compelling trajectory in the scatterplot (Fig. 1), showcasing the steadfast relationship between the variables, we couldn't help but marvel at the harmony of these seemingly disparate elements. It's like witnessing an unexpected fusion of musical genres – a harmonious blend that defies conventional expectations and leaves us tapping our toes in delighted surprise.
A relevant dad joke related to this content: Why don't scientists trust atoms? Because they make up everything – just like the connection we found between tourist arrivals and jet fuel consumption!
These findings not only highlight the intriguing connection between global travel patterns and the consumption of jet fuel in Australia but also emphasize the importance of considering unexpected relationships in the realm of statistical analysis. Just like stumbling upon a hidden Easter egg in a video game, this discovery adds a layer of depth and surprise to our understanding of the intricate interplay between diverse variables.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
Our investigation into the connection between the Number of International Tourist Arrivals Worldwide and Jet fuel consumption in Australia has brought to light a whimsical waltz between these seemingly unrelated variables. As we waded through the data, it became abundantly clear that these two elements are as interconnected as a scientist's love for beakers – it's a chemical reaction waiting to happen!
The results of our study harmonize with prior research, aligning like the stars in a statistical constellation. Smith et al.'s findings and those of Doe and Jones, like good wingmen on a statistical night out, supported our discovery of a robust correlation between tourist traffic and jet fuel demand. It's as if we stumbled upon a treasure trove of dad jokes – unexpected, yet reassuringly familiar.
The literature led us through navigating the economic implications, historical allegories, and even culinary aviation adventures, reminding us that in the vast landscape of knowledge, sometimes the best discoveries are hidden in the most unexpected places. This mirrors our own journey of unraveling the beguiling association between travel trends and turbine fuel usage – a scientific quest punctuated with sporadic dad jokes and unexpected twists.
The strong correlation coefficient and r-squared value in our analysis validate the substantial connection between these variables. It's like finding the missing puzzle piece in a scholarly jigsaw – a fitting conclusion to our data-driven expedition. The finding underscores the profound impact of global wanderlust on the fuel consumption landscape and highlights the enchanting, yet somewhat quirky, intricacies of statistical relationships.
In essence, our study not only cements the link between tourist arrivals and jet fuel usage but also adds a touch of whimsy to the somewhat austere world of statistical analysis. It's akin to discovering that the square root of 69 is 8-something – an unexpected yet delightful revelation that injects a dose of levity into the rigors of empirical research.
As our research journey continues, we look forward to unraveling even more statistical oddities, forging connections between variables as surprising as a pop-up toaster and toast. After all, the pursuit of knowledge is much like a good dad joke – surrounded by a heap of statistical equations, yet always punctuated with an unexpected zinger or two.
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 Number of International Tourist Arrivals Worldwide and Jet fuel used in Australia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
Travel Trends: Tracking the Ties between Tourist Traffic and Turbine Fuel
[[ABSTRACT]]
The present study delves into the delightful dance between the Number of International Tourist Arrivals Worldwide and the Jet fuel consumption in Australia, unravelling the tangled web of wanderlust and winged wonders. The aim was to elucidate whether there exists a substantial relationship between these seemingly unrelated variables and to explore whether they march to the same beat or simply sway to their own symphony. Our research team pored over data from Statista and the Energy Information Administration to shed light on this quirky connection.
Unsurprisingly, we discovered a strikingly strong correlation between the influx of globetrotters and the amount of jet fuel guzzled by the land down under. The correlation coefficient of 0.9654939 and the p-value of less than 0.01 from our analysis of data spanning from 1995 to 2022 left us marveling at this bountiful bond, like two peas in a pod or mac and cheese. It seems that as vacation enthusiasts flock hither and thither, soars the jet fuel consumption in the sun-kissed expanses of Australia.
A relevant dad joke related to this content: Why don't scientists trust atoms? Because they make up everything – just like the connection we found between tourist arrivals and jet fuel consumption!
[[INTRDUCTION]]
Gather 'round, fellow academics and aficionados of statistics, for we are about to embark on a journey that will unravel the interconnectedness of two seemingly unrelated entities: the Number of International Tourist Arrivals Worldwide and the Jet fuel consumption in Australia. This enigmatic relationship has us scratching our heads and chuckling at the unexpected peculiarities of the world of data. It's like trying to find the correlation between a kangaroo's hopping distance and the number of boomerangs sold – peculiar, yet wholly intriguing.
As we delve into the delightful dance between travel trends and jet fuel usage, we must approach this topic with the seriousness it warrants, and yet be open to the unexpected twists and turns, akin to the plot of a scientific thriller (or a melodramatic episode of "CSI: Data Analysis"). It's like trying to find the link between a good cup of tea and the number of sheep in New Zealand – seemingly unrelated, but perhaps hiding an underlying kinship that only statistics can reveal.
Now, as we shed light on the tangled web of wanderlust and winged wonders – a connection that is as cryptic as a complicated math equation but as intriguing as a suspenseful crime novel – we aim to unravel the mystery of whether these variables are mere statistical bedfellows or if they hold a substantial relationship, akin to the bond between peanut butter and jelly. It's like trying to discern the connection between a bar of chocolate and a dentist's waiting room – not immediately obvious, but somehow intertwined in a way that leaves us pondering over the mysterious ways of the universe.
And so, with data from Statista and the Energy Information Administration in hand, we rolled up our sleeves and donned our metaphorical detective hats, ready to crack the case of this zany relationship between tourism and turbine fuel. The plot thickened, just like an expertly prepared gravy, as we uncovered a correlation coefficient of 0.9654939 – a number so robust, it would make even the most devout statistics skeptic raise an eyebrow in wonder. It's like discovering the astonishing resemblance between a coincidental correlation and a perfectly timed punchline – unexpected, yet undeniable.
[[RESULTS]]
Our analysis unveiled a striking correlation of 0.9654939 between the Number of International Tourist Arrivals Worldwide and Jet fuel consumption in Australia, revealing a relationship so robust that it would put the synchronized dance moves of a professional Riverdance troupe to shame. This correlation coefficient left us marveling at the interconnected elegance of these two variables, like a perfectly executed pun – seamlessly intertwined yet delightfully unexpected.
Furthermore, the r-squared value of 0.9321784 underscored the strength of this connection, as solid as a well-constructed research hypothesis and as dependable as a reliable lab assistant. The p-value of less than 0.01 provided further evidence of the statistical significance of this delightful duo, akin to stumbling upon a rare and precious artifact in the often unpredictable realm of data analysis.
As the data points formed a clear and compelling trajectory in the scatterplot (Fig. 1), showcasing the steadfast relationship between the variables, we couldn't help but marvel at the harmony of these seemingly disparate elements. It's like witnessing an unexpected fusion of musical genres – a harmonious blend that defies conventional expectations and leaves us tapping our toes in delighted surprise.
A relevant dad joke related to this content: Why don't scientists trust atoms? Because they make up everything – just like the connection we found between tourist arrivals and jet fuel consumption!
These findings not only highlight the intriguing connection between global travel patterns and the consumption of jet fuel in Australia but also emphasize the importance of considering unexpected relationships in the realm of statistical analysis. Just like stumbling upon a hidden Easter egg in a video game, this discovery adds a layer of depth and surprise to our understanding of the intricate interplay between diverse variables.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our study has illuminated a compelling and quirkily harmonious relationship between the Number of International Tourist Arrivals Worldwide and Jet fuel consumption in Australia. Like uncovering a perfectly timed punchline, we have marveled at the robust correlation coefficient and the statistically significant p-value, leaving us with a sense of wonder akin to discovering a mind-bending magic trick. It seems that as globetrotters jet-set across the world, the demand for fuel in the land down under takes flight, showcasing a connection as seamless as a well-crafted dad joke.
As we wrap up this exhilarating adventure of statistical sleuthing, our findings underscore the importance of considering unlikely connections in the world of data analysis. Just as a surprising plot twist can elevate a mundane movie into a masterpiece, this unexpected correlation adds depth and intrigue to our understanding of the interplay between disparate variables. It's like stumbling upon an unexpected fusion of musical genres – a harmonious blend that defies conventional expectations and leaves us tapping our toes in delighted surprise.
And with that said, we assert that no more research is needed in this area - unless, of course, you'd like to share a joke about statistical analysis or jet fuel consumption. After all, there's always room for a little more laughter amidst the serious business of scholarly pursuits!
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 Travel Trends: Tracking the Ties between Tourist Traffic and Turbine Fuel. Respond only with the name of a fictional academic journal.
ChatGPT:
Journal of Ecotourism and Energy Economics
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 Travel Trends: Tracking the Ties between Tourist Traffic and Turbine Fuel. Respond only with the name of a fictional organization.
ChatGPT:
The Society for Sustainable Tourism Studies
Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Travel Trends: Tracking the Ties between Tourist Traffic and Turbine Fuel with an abstract of The present study delves into the delightful dance between the Number of International Tourist Arrivals Worldwide and the Jet fuel consumption in Australia, unravelling the tangled web of wanderlust and winged wonders. The aim was to elucidate whether there exists a substantial relationship between these seemingly unrelated variables and to explore whether they march to the same beat or simply sway to their own symphony. Our research team pored over data from Statista and the Energy Information Administration to shed light on this quirky connection.
Unsurprisingly, we discovered a strikingly strong correlation between the influx of globetrotters and the amount of jet fuel guzzled by the land down under. The correlation coefficient of 0.9654939 and the p-value of less than 0.01 from our analysis of data spanning from 1995 to 2022 left us marveling at this bountiful bond, like two peas in a pod or mac and cheese. It seems that as vacation enthusiasts flock hither and thither, soars the jet fuel consumption in the sun-kissed expanses of Australia.
A relevant dad joke related to this content: Why don't scientists trust atoms? Because they make up everything – just like the connection we found between tourist arrivals and jet fuel consumption!
ChatGPT:
Travel trends, international tourist arrivals, jet fuel consumption, correlation, relationship, tourism statistics, energy consumption, statistical analysis, tourism impact, aviation fuel, wanderlust, tourism data analysis
*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
Number of International Tourist Arrivals WorldwideSource: Statista
See what else correlates with Number of International Tourist Arrivals Worldwide
Jet fuel used in Australia
Detailed data title: Volume of jet fuel used consumed in Australia in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Jet fuel used in Australia
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 = 0.9321784 (Coefficient of determination)
This means 93.2% of the change in the one variable (i.e., Jet fuel used in Australia) is predictable based on the change in the other (i.e., Number of International Tourist Arrivals Worldwide) over the 28 years from 1995 through 2022.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.03E-16. 0.0000000000000001028474607909
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 0.97 in 1.03E-14% of random cases. Said differently, if you correlated 9,723,137,472,816,252 random variables You don't actually need 9 quadrillion 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 27 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 27 because we have two variables measured over a period of 28 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.
[ 0.93, 0.98 ] 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.
1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | |
Number of International Tourist Arrivals Worldwide (Million) | 528000000 | 563000000 | 589000000 | 605000000 | 627000000 | 677000000 | 678000000 | 698000000 | 689000000 | 760000000 | 807000000 | 851000000 | 911000000 | 929000000 | 894000000 | 948000000 | 1008740000 | 1059260000 | 1110830000 | 1154750000 | 1207080000 | 1248120000 | 1347570000 | 1414070000 | 1465460000 | 406890000 | 455770000 | 962800000 |
Jet fuel used in Australia (Million Barrels/Day) | 77.7918 | 82.4754 | 84.1863 | 83.274 | 83.7836 | 90.5792 | 88.3096 | 76.8986 | 71.3589 | 78.2486 | 85.1233 | 99.7836 | 100.901 | 105.872 | 109.877 | 120.718 | 124.436 | 129.672 | 138.803 | 139.389 | 142.334 | 151.03 | 157.707 | 162.545 | 161.762 | 69.8169 | 61.5014 | 103.43 |
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([528000000,563000000,589000000,605000000,627000000,677000000,678000000,698000000,689000000,760000000,807000000,851000000,911000000,929000000,894000000,948000000,1008740000,1059260000,1110830000,1154750000,1207080000,1248120000,1347570000,1414070000,1465460000,406890000,455770000,962800000,])
array_2 = np.array([77.7918,82.4754,84.1863,83.274,83.7836,90.5792,88.3096,76.8986,71.3589,78.2486,85.1233,99.7836,100.901,105.872,109.877,120.718,124.436,129.672,138.803,139.389,142.334,151.03,157.707,162.545,161.762,69.8169,61.5014,103.43,])
array_1_name = "Number of International Tourist Arrivals Worldwide"
array_2_name = "Jet fuel used in Australia"
# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)
# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)
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For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."
When spoken, my last name is pronounced "vegan," like I don't eat meat.
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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 Number of International Tourist Arrivals Worldwide
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- The spurious research paper: Travel Trends: Tracking the Ties between Tourist Traffic and Turbine Fuel
Your rating is stellar!
Correlation ID: 1166 · Black Variable ID: 123 · Red Variable ID: 24158