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Spurious correlation #1,813 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The number of nuclear engineers in Tennessee and the second variable is Petroluem consumption in Togo.  The chart goes from 2003 to 2021, and the two variables track closely in value over that time. Small Image

AI explanation

As the number of nuclear engineers in Tennessee increased, it led to a surge in wacky science experiments. One such experiment involved a nuclear-powered car prototype, which accidentally teleported to Togo and somehow ran on petroleum, creating a local demand for gasoline. It's a classic case of Tennessee technologists inadvertently revving up Togo's petrol usage, all thanks to their atomic antics!

Model: dalle-3
Prompt: Generate an image that combines a black-and-white newspaper illustration style with the following scene: In Tennessee, a small group of nuclear engineers is diligently working inside a futuristic power plant, tending to the complex machinery of nuclear reactors. Simultaneously, in Togo, a bustling street scene unfolds with people using bicycles, walking, and showing minimal fuel consumption while going about their daily activities. Capture the stark contrast between the advanced technology in one location and the sustainable, eco-friendly practices in the other. 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 nuclear engineers in Tennessee and Petroluem consumption in Togo. 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: Surrealism Celtic art A black-and-white newspaper illustration Brutalism Pop art
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 nuclear engineers in Tennessee and Petroluem consumption in Togo together. Keep the description simple.
ChatGPT: In Tennessee, there are a few nuclear engineers working at a power plant, designing and maintaining the nuclear reactors. Meanwhile, in Togo, people are using bicycles, walking, and using minimal amounts of fuel as they go about their day.

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 Tennessee, there are a few nuclear engineers working at a power plant, designing and maintaining the nuclear reactors. Meanwhile, in Togo, people are using bicycles, walking, and using minimal amounts of fuel as they go about their day. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that combines a black-and-white newspaper illustration style with the following scene: In Tennessee, a small group of nuclear engineers is diligently working inside a futuristic power plant, tending to the complex machinery of nuclear reactors. Simultaneously, in Togo, a bustling street scene unfolds with people using bicycles, walking, and showing minimal fuel consumption while going about their daily activities. Capture the stark contrast between the advanced technology in one location and the sustainable, eco-friendly practices in the other.

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

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

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how increases in The number of nuclear engineers in Tennessee positively influenced Petroluem consumption in Togo. Make it feel plausible.

AI academic paper

(Because p < 0.01)
The Nuclear Equation: Exploring Tennessee's Engineers and Togo's Petroleum Consumption

The Journal of Comparative Engineering and Energy Studies

Jan 2024
Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.




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

Please draft the title and abstract of an academic research paper presenting the findings of the connection between The number of nuclear engineers in Tennessee and Petroluem consumption in Togo. Make lots of jokes, goofy observations, and puns.

Make the title punny if you can come up with clever pun. If not, just make it sound clever.

Your research team used data from Bureau of Larbor Statistics and Energy Information Administration to assess this nagging question. You found a correlation coefficient of 0.8625454 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]]
The Nuclear Equation: Exploring Tennessee's Engineers and Togo's Petroleum Consumption

[[ABSTRACT]]
In this research paper, we delve into the surprising and delightful relationship between the number of nuclear engineers in Tennessee and petroleum consumption in Togo. Our team utilized data from the Bureau of Labor Statistics and the Energy Information Administration to tackle this electrifying question. We uncovered a striking correlation coefficient of 0.8625454 and a p-value of less than 0.01 for the period spanning from 2003 to 2021. The findings of this study are sure to spark both curiosity and laughter as we uncover an unexpected connection between seemingly unrelated factors. Whether you're a fan of fusion or just love a good energy pun, this research will surely leave you feeling positively charged!


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 nuclear engineers in Tennessee and Petroluem consumption in Togo. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
The Nuclear Equation: Exploring Tennessee's Engineers and Togo's Petroleum Consumption

[[ABSTRACT]]
In this research paper, we delve into the surprising and delightful relationship between the number of nuclear engineers in Tennessee and petroleum consumption in Togo. Our team utilized data from the Bureau of Labor Statistics and the Energy Information Administration to tackle this electrifying question. We uncovered a striking correlation coefficient of 0.8625454 and a p-value of less than 0.01 for the period spanning from 2003 to 2021. The findings of this study are sure to spark both curiosity and laughter as we uncover an unexpected connection between seemingly unrelated factors. Whether you're a fan of fusion or just love a good energy pun, this research will surely leave you feeling positively charged!

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

Nuclear engineers in Tennessee and petroleum consumption in Togo - two seemingly disparate entities, each with its own unique characteristics and challenges. One might wonder, what on earth could connect the land of Dolly Parton with a country known for its love of yams? Well, buckle up, folks, because we're about to take a wild ride through the world of statistical analysis and uncover an unexpected relationship that's bound to leave you feeling more energized than a cup of espresso!

As researchers, we often find ourselves venturing into uncharted territories, seeking connections that defy conventional wisdom and strike at the heart of human curiosity. In this case, we set out to explore the intriguing link between the number of nuclear engineers in the Volunteer State and the petroleum consumption patterns in the charming nation of Togo. Our quest was fueled by a sense of scientific wonder, peppered with a hefty dose of skepticism and a pinch of whimsy, because, let's face it, who doesn't love a good statistical surprise?

Now, you might be thinking, "Nuclear engineers and petroleum consumption? That's like mixing matter and antimatter - they should annihilate each other, right?" But hold onto your lab coats, because our findings are about to challenge your assumptions faster than you can say "nuclear fusion!"

Through rigorous analysis of data sourced from the Bureau of Labor Statistics and the Energy Information Administration, we set out to quantify the presumed incongruity between these two variables. We combed through the numbers with the determination of a scientist on the cusp of a groundbreaking discovery, and lo and behold, we stumbled upon a correlation coefficient of 0.8625454! That's right, folks, the tiniest state in the union and a West African gem share a statistically significant bond that would make even the most stoic researcher crack a smile.

In the following sections, we'll unveil the intricacies of this unexpected relationship, unpacking the statistics and weaving a narrative that will keep you on the edge of your seat. So, whether you're a fervent fan of fission or simply revel in the allure of peculiar connections, buckle up, because this nuclear equation is about to take you on a journey that's equal parts enlightening and delightfully absurd!


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 nuclear engineers in Tennessee and Petroluem consumption in Togo. Make lots of 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. Perhaps you also got inspiration from some board games that are vaugely related.

Here is the title and abstract of the paper:
[[TITLE]]
The Nuclear Equation: Exploring Tennessee's Engineers and Togo's Petroleum Consumption

[[ABSTRACT]]
In this research paper, we delve into the surprising and delightful relationship between the number of nuclear engineers in Tennessee and petroleum consumption in Togo. Our team utilized data from the Bureau of Labor Statistics and the Energy Information Administration to tackle this electrifying question. We uncovered a striking correlation coefficient of 0.8625454 and a p-value of less than 0.01 for the period spanning from 2003 to 2021. The findings of this study are sure to spark both curiosity and laughter as we uncover an unexpected connection between seemingly unrelated factors. Whether you're a fan of fusion or just love a good energy pun, this research will surely leave you feeling positively charged!

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Nuclear engineers in Tennessee and petroleum consumption in Togo - two seemingly disparate entities, each with its own unique characteristics and challenges. One might wonder, what on earth could connect the land of Dolly Parton with a country known for its love of yams? Well, buckle up, folks, because we're about to take a wild ride through the world of statistical analysis and uncover an unexpected relationship that's bound to leave you feeling more energized than a cup of espresso!
As researchers, we often find ourselves venturing into uncharted territories, seeking connections that defy conventional wisdom and strike at the heart of human curiosity. In this case, we set out to explore the intriguing link between the number of nuclear engineers in the Volunteer State and the petroleum consumption patterns in the charming nation of Togo. Our quest was fueled by a sense of scientific wonder, peppered with a hefty dose of skepticism and a pinch of whimsy, because, let's face it, who doesn't love a good statistical surprise?
Now, you might be thinking, "Nuclear engineers and petroleum consumption? That's like mixing matter and antimatter - they should annihilate each other, right?" But hold onto your lab coats, because our findings are about to challenge your assumptions faster than you can say "nuclear fusion!"
Through rigorous analysis of data sourced from the Bureau of Labor Statistics and the Energy Information Administration, we set out to quantify the presumed incongruity between these two variables. We combed through the numbers with the determination of a scientist on the cusp of a groundbreaking discovery, and lo and behold, we stumbled upon a correlation coefficient of 0.8625454! That's right, folks, the tiniest state in the union and a West African gem share a statistically significant bond that would make even the most stoic researcher crack a smile.
In the following sections, we'll unveil the intricacies of this unexpected relationship, unpacking the statistics and weaving a narrative that will keep you on the edge of your seat. So, whether you're a fervent fan of fission or simply revel in the allure of peculiar connections, buckle up, because this nuclear equation is about to take you on a journey that's equal parts enlightening and delightfully absurd!

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

As we venture into the wild world of statistical analysis and uncover the zany connection between Tennessee's nuclear engineers and Togo's petroleum consumption, we embark on a quest that defies traditional expectations and dares to blend seriousness with sheer whimsy. While the initial skepticism surrounding this peculiar pairing may have elicited a chuckle or two, rest assured, our findings are bound to leave you positively charged – pun most definitely intended!

Smith et al. (2018) took a serious approach in their study, delving into the demographic landscape of Tennessee's engineering workforce with a meticulous eye for detail. Meanwhile, Doe and Jones (2019) provided a comprehensive analysis of Togo's energy consumption patterns, shedding light on the intricate web of factors influencing petroleum use in this vibrant West African nation.

However, we cannot ignore the fictional influences that have imbued our research with unexpected inspirations and the occasional raised eyebrow. Borrowing a leaf from the works of Tom Clancy and Clive Cussler, whose high-octane thrillers have undoubtedly instilled in us a fervor for uncovering the unexpected and navigating uncharted terrain, our approach to this investigation has been anything but conventional.

Further elevating our expedition into unorthodox connections were popular board games such as "Power Grid" and "Nuclear War," which, with their tinge of whimsical irony, have underscored the essence of our research endeavors. After all, who can resist the siren call of blending serious research with a dash of playful frivolity?

In the realm of non-fiction, sources such as "Energy Transitions: History, Requirements, Prospects" by Vaclav Smil, and "Nuclear Energy: What Everyone Needs to Know" by Charles D. Ferguson have provided a sturdy foundation, grounding our pursuits in the complexities of energy systems and the fascinating world of nuclear technology.

While these esteemed academics and literary influences may have set the stage for a traditional foray into the depths of statistical exploration, our journey takes an unexpected turn as we unveil the startling connection between Tennessee's nuclear engineers and Togo's petroleum consumption. So, with a lighthearted grin and an academic fervor, let us proceed to unravel the enigma that awaits!


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 nuclear engineers in Tennessee and Petroluem consumption in Togo. Make lots of 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]]
The Nuclear Equation: Exploring Tennessee's Engineers and Togo's Petroleum Consumption

[[ABSTRACT]]
In this research paper, we delve into the surprising and delightful relationship between the number of nuclear engineers in Tennessee and petroleum consumption in Togo. Our team utilized data from the Bureau of Labor Statistics and the Energy Information Administration to tackle this electrifying question. We uncovered a striking correlation coefficient of 0.8625454 and a p-value of less than 0.01 for the period spanning from 2003 to 2021. The findings of this study are sure to spark both curiosity and laughter as we uncover an unexpected connection between seemingly unrelated factors. Whether you're a fan of fusion or just love a good energy pun, this research will surely leave you feeling positively charged!

[[INTRODUCTION]]
Nuclear engineers in Tennessee and petroleum consumption in Togo - two seemingly disparate entities, each with its own unique characteristics and challenges. One might wonder, what on earth could connect the land of Dolly Parton with a country known for its love of yams? Well, buckle up, folks, because we're about to take a wild ride through the world of statistical analysis and uncover an unexpected relationship that's bound to leave you feeling more energized than a cup of espresso!
As researchers, we often find ourselves venturing into uncharted territories, seeking connections that defy conventional wisdom and strike at the heart of human curiosity. In this case, we set out to explore the intriguing link between the number of nuclear engineers in the Volunteer State and the petroleum consumption patterns in the charming nation of Togo. Our quest was fueled by a sense of scientific wonder, peppered with a hefty dose of skepticism and a pinch of whimsy, because, let's face it, who doesn't love a good statistical surprise?
Now, you might be thinking, "Nuclear engineers and petroleum consumption? That's like mixing matter and antimatter - they should annihilate each other, right?" But hold onto your lab coats, because our findings are about to challenge your assumptions faster than you can say "nuclear fusion!"
Through rigorous analysis of data sourced from the Bureau of Labor Statistics and the Energy Information Administration, we set out to quantify the presumed incongruity between these two variables. We combed through the numbers with the determination of a scientist on the cusp of a groundbreaking discovery, and lo and behold, we stumbled upon a correlation coefficient of 0.8625454! That's right, folks, the tiniest state in the union and a West African gem share a statistically significant bond that would make even the most stoic researcher crack a smile.
In the following sections, we'll unveil the intricacies of this unexpected relationship, unpacking the statistics and weaving a narrative that will keep you on the edge of your seat. So, whether you're a fervent fan of fission or simply revel in the allure of peculiar connections, buckle up, because this nuclear equation is about to take you on a journey that's equal parts enlightening and delightfully absurd!

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To unravel the enigmatic connection between the number of nuclear engineers in Tennessee and petroleum consumption in Togo, our research team employed a blend of statistical wizardry and a pinch of scientific whimsy. We gathered data spanning from 2003 to 2021 from a variety of sources, with a heavy reliance on the Bureau of Labor Statistics and the Energy Information Administration. Our method of data collection was as rigorous as a nuclear containment protocol, ensuring that we left no statistical isotope unturned!

First, we embarked on the formidable task of tracking down the precise number of nuclear engineers gracing the state of Tennessee. With a keen eye for detail and a fervent love for puns, we scoured employment records and industry reports, navigating through the data with the dexterity of a subatomic particle. Like electrons orbiting a nucleus, we diligently documented the fluctuating population of these formidable engineers, accounting for every flux and fusion along the way.

On the other side of the equation, we delved into the world of Togo's petroleum consumption with the fervor of a petrolhead at a NASCAR race. Our quest for consumption data led us through the labyrinth of fuel statistics, where we deciphered the ebbs and flows of Togo's energy appetites. Much like unraveling a complex chemical compound, we meticulously parsed through the numbers, delighting in the euphoria of discovering unexpected patterns in the data.

Once armed with datasets that would make even the most fervent number-cruncher envious, we unleashed the power of statistical analysis upon them. With a fervent plea to the statistical gods, we calculated the correlation coefficient and p-value, hoping to uncover a connection so electrifying that it would set the scientific community abuzz.

Our analysis was more thorough than a double-blind clinical trial, and the results left us positively beaming! The correlation coefficient of 0.8625454 raised our eyebrows higher than an excited chemist observing a titration endpoint, while the p-value of less than 0.01 had us celebrating like it was the discovery of a new element.

In summary, our methodology was akin to embarking on a zany scientific expedition, complete with unexpected twists, statistical acrobatics, and the unyielding pursuit of uncovering the delightful and often surprising relationships that lurk within the world of data. So, fasten your seatbelts, dear readers, for the journey ahead promises to be as thrilling as a physics rollercoaster and as enlightening as a fusion-powered light bulb!


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 nuclear engineers in Tennessee and Petroluem consumption in Togo. Make lots of 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 0.8625454, r-squared of 0.7439846, 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]]
The Nuclear Equation: Exploring Tennessee's Engineers and Togo's Petroleum Consumption

[[ABSTRACT]]
In this research paper, we delve into the surprising and delightful relationship between the number of nuclear engineers in Tennessee and petroleum consumption in Togo. Our team utilized data from the Bureau of Labor Statistics and the Energy Information Administration to tackle this electrifying question. We uncovered a striking correlation coefficient of 0.8625454 and a p-value of less than 0.01 for the period spanning from 2003 to 2021. The findings of this study are sure to spark both curiosity and laughter as we uncover an unexpected connection between seemingly unrelated factors. Whether you're a fan of fusion or just love a good energy pun, this research will surely leave you feeling positively charged!

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Nuclear engineers in Tennessee and petroleum consumption in Togo - two seemingly disparate entities, each with its own unique characteristics and challenges. One might wonder, what on earth could connect the land of Dolly Parton with a country known for its love of yams? Well, buckle up, folks, because we're about to take a wild ride through the world of statistical analysis and uncover an unexpected relationship that's bound to leave you feeling more energized than a cup of espresso!
As researchers, we often find ourselves venturing into uncharted territories, seeking connections that defy conventional wisdom and strike at the heart of human curiosity. In this case, we set out to explore the intriguing link between the number of nuclear engineers in the Volunteer State and the petroleum consumption patterns in the charming nation of Togo. Our quest was fueled by a sense of scientific wonder, peppered with a hefty dose of skepticism and a pinch of whimsy, because, let's face it, who doesn't love a good statistical surprise?
Now, you might be thinking, "Nuclear engineers and petroleum consumption? That's like mixing matter and antimatter - they should annihilate each other, right?" But hold onto your lab coats, because our findings are about to challenge your assumptions faster than you can say "nuclear fusion!"
Through rigorous analysis of data sourced from the Bureau of Labor Statistics and the Energy Information Administration, we set out to quantify the presumed incongruity between these two variables. We combed through the numbers with the determination of a scientist on the cusp of a groundbreaking discovery, and lo and behold, we stumbled upon a correlation coefficient of 0.8625454! That's right, folks, the tiniest state in the union and a West African gem share a statistically significant bond that would make even the most stoic researcher crack a smile.
In the following sections, we'll unveil the intricacies of this unexpected relationship, unpacking the statistics and weaving a narrative that will keep you on the edge of your seat. So, whether you're a fervent fan of fission or simply revel in the allure of peculiar connections, buckle up, because this nuclear equation is about to take you on a journey that's equal parts enlightening and delightfully absurd!

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

In the electrifying world of statistical analysis, our investigation into the relationship between the number of nuclear engineers in Tennessee and petroleum consumption in Togo yielded a positively shocking revelation. For the time period of 2003 to 2021, we unearthed a correlation coefficient of 0.8625454, indicating a remarkably robust connection that had us feeling more energized than a charged particle in a magnetic field. With an r-squared value of 0.7439846 and a p-value less than 0.01, our findings left us positively charged with excitement!

But wait, there's more! Fig. 1 captures the essence of this unexpected correlation in a scatterplot that will make you think twice before underestimating the potential link between seemingly unrelated variables. The figure will leave you feeling as pleasantly surprised as stumbling upon a hidden treasure in the world of statistical analysis.

The strength of this correlation provides compelling evidence of a relationship that dances to its own statistical beat. As researchers, we always endeavor to uncover the unexpected and challenge preconceived notions, and this finding is a shining example of how the most unlikely pairings can hold a significant statistical bond.

This unexpected connection between the number of nuclear engineers in Tennessee and petroleum consumption in Togo not only defies conventional wisdom but also serves as a reminder that statistical analysis is as much an art as it is a science. Whether you're a fusion fanatic or simply appreciate the marvel of statistical serendipity, this finding is sure to leave you feeling positively charged and ready to explore further the thrilling world of statistical surprises.


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 nuclear engineers in Tennessee and Petroluem consumption in Togo. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
The Nuclear Equation: Exploring Tennessee's Engineers and Togo's Petroleum Consumption

[[ABSTRACT]]
In this research paper, we delve into the surprising and delightful relationship between the number of nuclear engineers in Tennessee and petroleum consumption in Togo. Our team utilized data from the Bureau of Labor Statistics and the Energy Information Administration to tackle this electrifying question. We uncovered a striking correlation coefficient of 0.8625454 and a p-value of less than 0.01 for the period spanning from 2003 to 2021. The findings of this study are sure to spark both curiosity and laughter as we uncover an unexpected connection between seemingly unrelated factors. Whether you're a fan of fusion or just love a good energy pun, this research will surely leave you feeling positively charged!

[[LITERATURE REVIEW]]
As we venture into the wild world of statistical analysis and uncover the zany connection between Tennessee's nuclear engineers and Togo's petroleum consumption, we embark on a quest that defies traditional expectations and dares to blend seriousness with sheer whimsy. While the initial skepticism surrounding this peculiar pairing may have elicited a chuckle or two, rest assured, our findings are bound to leave you positively charged – pun most definitely intended!
Smith et al. (2018) took a serious approach in their study, delving into the demographic landscape of Tennessee's engineering workforce with a meticulous eye for detail. Meanwhile, Doe and Jones (2019) provided a comprehensive analysis of Togo's energy consumption patterns, shedding light on the intricate web of factors influencing petroleum use in this vibrant West African nation.
However, we cannot ignore the fictional influences that have imbued our research with unexpected inspirations and the occasional raised eyebrow. Borrowing a leaf from the works of Tom Clancy and Clive Cussler, whose high-octane thrillers have undoubtedly instilled in us a fervor for uncovering the unexpected and navigating uncharted terrain, our approach to this investigation has been anything but conventional.
Further elevating our expedition into unorthodox connections were popular board games such as "Power Grid" and "Nuclear War," which, with their tinge of whimsical irony, have underscored the essence of our research endeavors. After all, who can resist the siren call of blending serious research with a dash of playful frivolity?
In the realm of non-fiction, sources such as "Energy Transitions: History, Requirements, Prospects" by Vaclav Smil, and "Nuclear Energy: What Everyone Needs to Know" by Charles D. Ferguson have provided a sturdy foundation, grounding our pursuits in the complexities of energy systems and the fascinating world of nuclear technology.
While these esteemed academics and literary influences may have set the stage for a traditional foray into the depths of statistical exploration, our journey takes an unexpected turn as we unveil the startling connection between Tennessee's nuclear engineers and Togo's petroleum consumption. So, with a lighthearted grin and an academic fervor, let us proceed to unravel the enigma that awaits!

[[RESULTS]]
In the electrifying world of statistical analysis, our investigation into the relationship between the number of nuclear engineers in Tennessee and petroleum consumption in Togo yielded a positively shocking revelation. For the time period of 2003 to 2021, we unearthed a correlation coefficient of 0.8625454, indicating a remarkably robust connection that had us feeling more energized than a charged particle in a magnetic field. With an r-squared value of 0.7439846 and a p-value less than 0.01, our findings left us positively charged with excitement!
But wait, there's more! Fig. 1 captures the essence of this unexpected correlation in a scatterplot that will make you think twice before underestimating the potential link between seemingly unrelated variables. The figure will leave you feeling as pleasantly surprised as stumbling upon a hidden treasure in the world of statistical analysis.
The strength of this correlation provides compelling evidence of a relationship that dances to its own statistical beat. As researchers, we always endeavor to uncover the unexpected and challenge preconceived notions, and this finding is a shining example of how the most unlikely pairings can hold a significant statistical bond.
This unexpected connection between the number of nuclear engineers in Tennessee and petroleum consumption in Togo not only defies conventional wisdom but also serves as a reminder that statistical analysis is as much an art as it is a science. Whether you're a fusion fanatic or simply appreciate the marvel of statistical serendipity, this finding is sure to leave you feeling positively charged and ready to explore further the thrilling world of statistical surprises.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The results of our study reveal a shockingly strong correlation between the number of nuclear engineers in Tennessee and petroleum consumption in Togo. As we wade through the tidal wave of statistical significance, it becomes abundantly clear that this unexpected relationship is no mere statistical fluke. Our findings align with the prior research that delved into the demographic landscape of Tennessee's engineering workforce and the energy consumption patterns in Togo.

Smith et al. (2018) may have taken a serious approach to Tennessee's engineering landscape, but our lightning bolt of a finding has certainly injected a surge of excitement into the field. Likewise, the comprehensive analysis by Doe and Jones (2019) of Togo's energy consumption patterns now finds a delightful counterpart in our electrifying revelation. While the initial skepticism surrounding this pairing may have prompted a chuckle or two, our findings provide compelling evidence of a truly unexpected, positively charged relationship.

In our quest to uncover the mysterious connection between these seemingly unrelated variables, we have wandered into uncharted statistical territory, drawing inspiration from a blend of serious academic works and the unexpected influences of fictional thrillers and board games. Just as Tom Clancy and Clive Cussler have navigated high-octane adventures, our statistical journey has revealed its own pulse-quickening twist. And much like the strategic maneuvering in board games such as "Power Grid," our approach to this investigation has yielded a winning move that defies traditional expectations.

Our findings, captured in a scatterplot that is as visually captivating as a hidden treasure in the world of statistical analysis, underscore the magnitude of this surprising correlation. This statistical serendipity not only challenges preconceived notions but also reminds us that the most unlikely pairings can hold a significant statistical bond. Truly, statistical analysis is as much an art as it is a science, and our work demonstrates the delight of uncovering a gem of statistical surprise.

As we bask in the glow of this findings, we are reminded that sometimes, the most unexpected connections are the most illuminating. Whether you're a fusion fanatic or simply appreciate the marvel of statistical serendipity, this finding is sure to leave you feeling positively charged and ready to embark on further explorations into the thrilling world of statistical surprises.


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 nuclear engineers in Tennessee and Petroluem consumption in Togo. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
The Nuclear Equation: Exploring Tennessee's Engineers and Togo's Petroleum Consumption

[[ABSTRACT]]
In this research paper, we delve into the surprising and delightful relationship between the number of nuclear engineers in Tennessee and petroleum consumption in Togo. Our team utilized data from the Bureau of Labor Statistics and the Energy Information Administration to tackle this electrifying question. We uncovered a striking correlation coefficient of 0.8625454 and a p-value of less than 0.01 for the period spanning from 2003 to 2021. The findings of this study are sure to spark both curiosity and laughter as we uncover an unexpected connection between seemingly unrelated factors. Whether you're a fan of fusion or just love a good energy pun, this research will surely leave you feeling positively charged!

[[INTRDUCTION]]
Nuclear engineers in Tennessee and petroleum consumption in Togo - two seemingly disparate entities, each with its own unique characteristics and challenges. One might wonder, what on earth could connect the land of Dolly Parton with a country known for its love of yams? Well, buckle up, folks, because we're about to take a wild ride through the world of statistical analysis and uncover an unexpected relationship that's bound to leave you feeling more energized than a cup of espresso!
As researchers, we often find ourselves venturing into uncharted territories, seeking connections that defy conventional wisdom and strike at the heart of human curiosity. In this case, we set out to explore the intriguing link between the number of nuclear engineers in the Volunteer State and the petroleum consumption patterns in the charming nation of Togo. Our quest was fueled by a sense of scientific wonder, peppered with a hefty dose of skepticism and a pinch of whimsy, because, let's face it, who doesn't love a good statistical surprise?
Now, you might be thinking, "Nuclear engineers and petroleum consumption? That's like mixing matter and antimatter - they should annihilate each other, right?" But hold onto your lab coats, because our findings are about to challenge your assumptions faster than you can say "nuclear fusion!"
Through rigorous analysis of data sourced from the Bureau of Labor Statistics and the Energy Information Administration, we set out to quantify the presumed incongruity between these two variables. We combed through the numbers with the determination of a scientist on the cusp of a groundbreaking discovery, and lo and behold, we stumbled upon a correlation coefficient of 0.8625454! That's right, folks, the tiniest state in the union and a West African gem share a statistically significant bond that would make even the most stoic researcher crack a smile.
In the following sections, we'll unveil the intricacies of this unexpected relationship, unpacking the statistics and weaving a narrative that will keep you on the edge of your seat. So, whether you're a fervent fan of fission or simply revel in the allure of peculiar connections, buckle up, because this nuclear equation is about to take you on a journey that's equal parts enlightening and delightfully absurd!

[[RESULTS]]
In the electrifying world of statistical analysis, our investigation into the relationship between the number of nuclear engineers in Tennessee and petroleum consumption in Togo yielded a positively shocking revelation. For the time period of 2003 to 2021, we unearthed a correlation coefficient of 0.8625454, indicating a remarkably robust connection that had us feeling more energized than a charged particle in a magnetic field. With an r-squared value of 0.7439846 and a p-value less than 0.01, our findings left us positively charged with excitement!
But wait, there's more! Fig. 1 captures the essence of this unexpected correlation in a scatterplot that will make you think twice before underestimating the potential link between seemingly unrelated variables. The figure will leave you feeling as pleasantly surprised as stumbling upon a hidden treasure in the world of statistical analysis.
The strength of this correlation provides compelling evidence of a relationship that dances to its own statistical beat. As researchers, we always endeavor to uncover the unexpected and challenge preconceived notions, and this finding is a shining example of how the most unlikely pairings can hold a significant statistical bond.
This unexpected connection between the number of nuclear engineers in Tennessee and petroleum consumption in Togo not only defies conventional wisdom but also serves as a reminder that statistical analysis is as much an art as it is a science. Whether you're a fusion fanatic or simply appreciate the marvel of statistical serendipity, this finding is sure to leave you feeling positively charged and ready to explore further the thrilling world of statistical surprises.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our research has electrifyingly illuminated the captivating connection between the number of nuclear engineers in Tennessee and petroleum consumption in Togo. Who would have thought that these seemingly unrelated variables could form a statistical bond stronger than a covalent bond in chemistry class? Our findings have left us feeling positively charged with excitement - pun intended!

The robust correlation coefficient of 0.8625454 and the remarkably high r-squared value of 0.7439846 defy expectations and showcase the sheer power of statistical analysis to uncover unexpected relationships. Just as protons and electrons attract each other, it appears that nuclear engineers in Tennessee and petroleum consumption in Togo have developed their own unique attraction, much to the surprise of researchers and statisticians alike.

The scatterplot in Fig. 1 serves as a visual testament to this astonishing correlation, reminding us that in the world of statistics, truth can indeed be stranger than fiction. It's like stumbling upon a statistically significant pot of gold at the end of a data rainbow!

As we wrap up this illuminating journey into the world of statistical serendipity, we must acknowledge that our findings have not only broadened our understanding of these distinct variables but have also injected a healthy dose of whimsy into the often-serious realm of academic research. After all, who said statistics couldn't be a barrel of laughs?

Therefore, based on the compelling evidence and the sheer delight of uncovering this unexpected relationship, we assert that no further research is needed in this area. The nuclear equation has been solved, and it's time to bask in the glow of this statistical triumph. As researchers, we couldn't be more positively charged about our findings!


Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited The Nuclear Equation: Exploring Tennessee's Engineers and Togo's Petroleum Consumption. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Comparative Engineering and 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 The Nuclear Equation: Exploring Tennessee's Engineers and Togo's Petroleum Consumption. Respond only with the name of a fictional organization.

ChatGPT:

The Federation for Transnational Engineering and Resources Development


Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled The Nuclear Equation: Exploring Tennessee's Engineers and Togo's Petroleum Consumption with an abstract of In this research paper, we delve into the surprising and delightful relationship between the number of nuclear engineers in Tennessee and petroleum consumption in Togo. Our team utilized data from the Bureau of Labor Statistics and the Energy Information Administration to tackle this electrifying question. We uncovered a striking correlation coefficient of 0.8625454 and a p-value of less than 0.01 for the period spanning from 2003 to 2021. The findings of this study are sure to spark both curiosity and laughter as we uncover an unexpected connection between seemingly unrelated factors. Whether you're a fan of fusion or just love a good energy pun, this research will surely leave you feeling positively charged!

ChatGPT:

nuclear engineers Tennessee, petroleum consumption Togo, correlation coefficient energy consumption, Bureau of Labor Statistics, Energy Information Administration, fusion energy research, petroleum industry correlation, energy consumption 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 nuclear engineers in Tennessee
Detailed data title: BLS estimate of nuclear engineers in Tennessee
Source: Bureau of Larbor Statistics
See what else correlates with The number of nuclear engineers in Tennessee

Petroluem consumption in Togo
Detailed data title: Volume of petroluem consumption consumed in Togo in millions of barrels per day
Source: Energy Information Administration
See what else correlates with Petroluem consumption in Togo

Correlation r = 0.8625454 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r2 = 0.7439846 (Coefficient of determination)
This means 74.4% of the change in the one variable (i.e., Petroluem consumption in Togo) is predictable based on the change in the other (i.e., The number of nuclear engineers in Tennessee) over the 19 years from 2003 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.03E-6. 0.0000020288113928514614000000
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 0.86 in 0.000203% of random cases. Said differently, if you correlated 492,899 random variables You don't actually need 492 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.

[ 0.67, 0.95 ] 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.
2003200420052006200720082009201020112012201320142015201620172018201920202021
The number of nuclear engineers in Tennessee (Nuclear Engineers)3804406504802603201520133017301050980720750680610460540840630
Petroluem consumption in Togo (Million Barrels/Day)8.040797.977247.821926.652277.192559.0310117.137315.845914.414712.814313.336410.03877.5400310.94269.6175110.76710.04849.5945110.1238




Why this works

  1. Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
  2. Lack of causal connection: There is probably Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
    no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
  3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
    p-value calculation does not take this into account, so mathematically it appears less probable than it really is.




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([380,440,650,480,260,320,1520,1330,1730,1050,980,720,750,680,610,460,540,840,630,])
array_2 = np.array([8.04079,7.97724,7.82192,6.65227,7.19255,9.03101,17.1373,15.8459,14.4147,12.8143,13.3364,10.0387,7.54003,10.9426,9.61751,10.767,10.0484,9.59451,10.1238,])
array_1_name = "The number of nuclear engineers in Tennessee"
array_2_name = "Petroluem consumption in Togo"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)



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Correlation ID: 1813 · Black Variable ID: 14416 · Red Variable ID: 24993
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