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Spurious correlation #5,932 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Bankruptcies in California and the second variable is The number of marketing managers in Guam.  The chart goes from 2003 to 2013, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As more businesses in California went bankrupt, there was a surplus of marketing managers looking for work. This led to a sudden migration of highly qualified marketing managers from California to Guam, a land of new opportunities. So, the increase in bankruptcies in California inadvertently boosted the pool of marketing talent in Guam, much to the surprise of everyone involved.

Model: dalle-3
Prompt: Prompt: Generate an image of two contrasting cityscapes—one set in California with closed storefronts and "For Lease" signs, and another in Guam with skilled marketing managers arriving. Incorporate elements of brutalist architecture to convey a sense of solidity and contrast. The image should capture the feeling of a looming exodus of talent in California and the arrival of expertise in Guam, with palm trees and tranquil waters integrating into the scenes. 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: Bankruptcies in California and The number of marketing managers in Guam. 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: a meme Cutsy graphics Low poly Magic realism Brutalism
ChatGPT: Brutalism

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Bankruptcies in California and The number of marketing managers in Guam, in the following situation: As more businesses in California went bankrupt, there was a surplus of marketing managers looking for work. This led to a sudden migration of highly qualified marketing managers from California to Guam, a land of new opportunities. So, the increase in bankruptcies in California inadvertently boosted the pool of marketing talent in Guam, much to the surprise of everyone involved.. Keep the description simple.
ChatGPT: In the bustling streets of California, closed storefronts and "For Lease" signs adorned the buildings, signaling the increase in business bankruptcies. Meanwhile, on the sunny shores of Guam, a wave of skilled marketing managers descended upon the island, eager to seize new opportunities. The California palm trees lamented the exodus of talent, while the tranquil waters of Guam welcomed the influx of marketing expertise.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ Brutalism ] and depicting this scene: In the bustling streets of California, closed storefronts and "For Lease" signs adorned the buildings, signaling the increase in business bankruptcies. Meanwhile, on the sunny shores of Guam, a wave of skilled marketing managers descended upon the island, eager to seize new opportunities. The California palm trees lamented the exodus of talent, while the tranquil waters of Guam welcomed the influx of marketing expertise. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Prompt: Generate an image of two contrasting cityscapes—one set in California with closed storefronts and "For Lease" signs, and another in Guam with skilled marketing managers arriving. Incorporate elements of brutalist architecture to convey a sense of solidity and contrast. The image should capture the feeling of a looming exodus of talent in California and the arrival of expertise in Guam, with palm trees and tranquil waters integrating into the scenes.

*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 Bankruptcies in California positively influenced The number of marketing managers in Guam.

AI academic paper

(Because p < 0.01)
From Banks to Banks: The Cross-Pollination of Bankruptcies in California and the Marketing Managers of Guam

The Journal of Cross-Continental Business Dynamics

Jan 2024

Reminder: This paper is AI-generated. Not real!
Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.




Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Bankruptcies in California and The number of marketing managers in Guam. Make lots of jokes, goofy observations, and puns.

Make the title a clever pun.

Your research team used data from Statsamerica and Bureau of Larbor Statistics to assess this nagging question. You found a correlation coefficient of 0.9610544 and p < 0.01 for 2003 to 2013.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
"From Banks to Banks: The Cross-Pollination of Bankruptcies in California and the Marketing Managers of Guam"

[[ABSTRACT]]
In this study, we analyze the surprising and, dare we say, quirky relationship between bankruptcies in the state of California and the number of marketing managers in the tropical paradise of Guam. While these two regions might seem as distant as mismatched socks, our research has uncovered a statistical connection that is both remarkable and, to put it mildly, entertaining. Utilizing data from Statsamerica and the Bureau of Labor Statistics, we found a correlation coefficient of 0.9610544 and a p-value less than 0.01 for the period between 2003 and 2013, making this correlation not just statistically significant, but also compellingly peculiar.

Through our rigorous analysis, we have unearthed a trend that is as unexpected as finding sand at the bottom of a swimming pool – a trend that has led us to question preconceived notions about the interconnectedness of seemingly unrelated economic variables. Our findings may even prompt further research into the whimsical dance of economic forces, where the ebb and flow of bankruptcy filings in one locale appears to be mirrored by the comings and goings of marketing managers in another. It is our hope that this study will inspire fellow researchers to delve into the eccentric and fascinating world of economic correlations, and perhaps uncover more delightful surprises along the way.


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 Bankruptcies in California and The number of marketing managers in Guam. Make lots of jokes, goofy observations, and puns.

Here is the title and abstract of the paper:
[[TITLE]]
"From Banks to Banks: The Cross-Pollination of Bankruptcies in California and the Marketing Managers of Guam"

[[ABSTRACT]]
In this study, we analyze the surprising and, dare we say, quirky relationship between bankruptcies in the state of California and the number of marketing managers in the tropical paradise of Guam. While these two regions might seem as distant as mismatched socks, our research has uncovered a statistical connection that is both remarkable and, to put it mildly, entertaining. Utilizing data from Statsamerica and the Bureau of Labor Statistics, we found a correlation coefficient of 0.9610544 and a p-value less than 0.01 for the period between 2003 and 2013, making this correlation not just statistically significant, but also compellingly peculiar.

Through our rigorous analysis, we have unearthed a trend that is as unexpected as finding sand at the bottom of a swimming pool – a trend that has led us to question preconceived notions about the interconnectedness of seemingly unrelated economic variables. Our findings may even prompt further research into the whimsical dance of economic forces, where the ebb and flow of bankruptcy filings in one locale appears to be mirrored by the comings and goings of marketing managers in another. It is our hope that this study will inspire fellow researchers to delve into the eccentric and fascinating world of economic correlations, and perhaps uncover more delightful surprises along the way.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

Welcome, fellow scholars and enthusiasts of the uncanny and the unorthodox! Prepare to embark on a journey through the uncharted waters of economic correlations, where the unexpected thrives and the peculiar reigns supreme. Today, we present to you a groundbreaking study that will challenge your perceptions, tickle your neurons, and perhaps leave you scratching your head in mild bewilderment.

As the title "From Banks to Banks: The Cross-Pollination of Bankruptcies in California and the Marketing Managers of Guam" whimsically suggests, our investigation dives deep into the realm of statistical harmony, or dare we say, disharmony, between the bankruptcies in the Golden State of California and the enigmatic world of marketing managers in the blissful haven of Guam. It's like watching a tango between a walrus and a penguin - unexpected, improbable, and yet strangely captivating.

On the surface, one might presume that these two economic phenomena have as much in common as a turtle does with a telephone. But fear not, dear readers, for our research has unravelled a tapestry of statistical intrigue that will certainly flip the script of your conventional economic musings.

Now, as we embark on this academic adventure, I invite you to fasten your seatbelts, caffeinate your senses, and prepare to be astounded by the enticing dance of data, the mystique of mathematical models, and the humorously bewildering correlations that lie ahead. So, without further ado, let us delve into the realm of economics with a touch of quirk and a hint of whimsy!


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 Bankruptcies in California and The number of marketing managers in Guam. 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]]
"From Banks to Banks: The Cross-Pollination of Bankruptcies in California and the Marketing Managers of Guam"

[[ABSTRACT]]
In this study, we analyze the surprising and, dare we say, quirky relationship between bankruptcies in the state of California and the number of marketing managers in the tropical paradise of Guam. While these two regions might seem as distant as mismatched socks, our research has uncovered a statistical connection that is both remarkable and, to put it mildly, entertaining. Utilizing data from Statsamerica and the Bureau of Labor Statistics, we found a correlation coefficient of 0.9610544 and a p-value less than 0.01 for the period between 2003 and 2013, making this correlation not just statistically significant, but also compellingly peculiar.

Through our rigorous analysis, we have unearthed a trend that is as unexpected as finding sand at the bottom of a swimming pool – a trend that has led us to question preconceived notions about the interconnectedness of seemingly unrelated economic variables. Our findings may even prompt further research into the whimsical dance of economic forces, where the ebb and flow of bankruptcy filings in one locale appears to be mirrored by the comings and goings of marketing managers in another. It is our hope that this study will inspire fellow researchers to delve into the eccentric and fascinating world of economic correlations, and perhaps uncover more delightful surprises along the way.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Welcome, fellow scholars and enthusiasts of the uncanny and the unorthodox! Prepare to embark on a journey through the uncharted waters of economic correlations, where the unexpected thrives and the peculiar reigns supreme. Today, we present to you a groundbreaking study that will challenge your perceptions, tickle your neurons, and perhaps leave you scratching your head in mild bewilderment.
As the title "From Banks to Banks: The Cross-Pollination of Bankruptcies in California and the Marketing Managers of Guam" whimsically suggests, our investigation dives deep into the realm of statistical harmony, or dare we say, disharmony, between the bankruptcies in the Golden State of California and the enigmatic world of marketing managers in the blissful haven of Guam. It's like watching a tango between a walrus and a penguin - unexpected, improbable, and yet strangely captivating.
On the surface, one might presume that these two economic phenomena have as much in common as a turtle does with a telephone. But fear not, dear readers, for our research has unravelled a tapestry of statistical intrigue that will certainly flip the script of your conventional economic musings.
Now, as we embark on this academic adventure, I invite you to fasten your seatbelts, caffeinate your senses, and prepare to be astounded by the enticing dance of data, the mystique of mathematical models, and the humorously bewildering correlations that lie ahead. So, without further ado, let us delve into the realm of economics with a touch of quirk and a hint of whimsy!

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

In the illustrious world of economic research, where dry data meets complex statistical analyses, our pursuit of the unexpected and the inexplicable has led us to unearth a treasure trove of literature that explores the most peculiar of correlations. As we delve into the enigmatic connection between bankruptcies in California and the number of marketing managers in Guam, we find ourselves tiptoeing through the serious works of Smith, Doe, and Jones before taking a delightful plunge into the realm of eccentricity.

In "Economic Correlations: A Fundamental Analysis," Smith proposes a rigorous framework for uncovering the intricacies of economic relationships. Smith's work is indeed enlightening, but one might wonder if it captures the sheer whimsy of our present investigation. Meanwhile, Doe's "Statistical Paradoxes in Economic Trends" offers a nuanced exploration of seemingly incongruous data points, but does it encapsulate the sheer offbeat nature of bankruptcies and marketing managers frolicking hand in hand? Lastly, Jones' "Economic Phenomena: From A to Z" lays out a comprehensive survey of economic variables, yet it falls short of capturing the sheer whimsical charm of our current endeavor.

Venturing beyond the traditional bounds of economic literature, one cannot ignore the classic works of non-fiction that tantalize the imagination and offer a glimpse into the unexpected. "Freakonomics" by Levitt and Dubner, while not directly related to our subject matter, embodies the spirit of unorthodox economic analysis – a spirit that resonates deeply with our own pursuit of charming correlations. Dare we say, the unexpected joy of finding a rubber duck in a bowl of fruit salad mirrors the exhilaration of stumbling upon a correlation between bankruptcies and marketing managers?

But let us not be confined by the shackles of non-fiction, for the fiction realm offers its own brand of whimsy that sparks the imagination. Consider "The Hitchhiker's Guide to the Galaxy" by Douglas Adams, a tale of intergalactic absurdity that mirrors the inexplicable dance of economic forces we uncover. Similarly, the whimsical world of "Charlie and the Chocolate Factory" by Roald Dahl may seem worlds apart from economic research, yet its fantastical charm speaks to the delight we find in unraveling the unexpected threads of correlation.

And who can forget the world of board games, where the roll of dice and the flip of cards often lead to unforeseen and mirthful outcomes? Games like Monopoly and The Game of Life, with their whimsical representation of economic ventures, may not offer direct parallels to our research, but they certainly remind us that even in the realm of make-believe, the interconnectedness of economic phenomena can bring a chuckle or two.

As we wade through the literature that both informs and intrigues, we are reminded that the pursuit of knowledge must be accompanied by a healthy dose of levity and a willingness to embrace the delightfully absurd. With this mindset, we are primed to venture further into the depths of economic correlations, where the unexpected awaits with open arms, ready to dance a merry jig with our curious minds.

And thus, dear reader, we invite you to join us in this fanciful and offbeat exploration, where we seek not just dry data, but the whimsical delight of uncovering correlations in the unlikeliest of places.


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 Bankruptcies in California and The number of marketing managers in Guam. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Statsamerica and Bureau of Larbor Statistics . You used data from 2003 to 2013

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
"From Banks to Banks: The Cross-Pollination of Bankruptcies in California and the Marketing Managers of Guam"

[[ABSTRACT]]
In this study, we analyze the surprising and, dare we say, quirky relationship between bankruptcies in the state of California and the number of marketing managers in the tropical paradise of Guam. While these two regions might seem as distant as mismatched socks, our research has uncovered a statistical connection that is both remarkable and, to put it mildly, entertaining. Utilizing data from Statsamerica and the Bureau of Labor Statistics, we found a correlation coefficient of 0.9610544 and a p-value less than 0.01 for the period between 2003 and 2013, making this correlation not just statistically significant, but also compellingly peculiar.

Through our rigorous analysis, we have unearthed a trend that is as unexpected as finding sand at the bottom of a swimming pool – a trend that has led us to question preconceived notions about the interconnectedness of seemingly unrelated economic variables. Our findings may even prompt further research into the whimsical dance of economic forces, where the ebb and flow of bankruptcy filings in one locale appears to be mirrored by the comings and goings of marketing managers in another. It is our hope that this study will inspire fellow researchers to delve into the eccentric and fascinating world of economic correlations, and perhaps uncover more delightful surprises along the way.

[[INTRODUCTION]]
Welcome, fellow scholars and enthusiasts of the uncanny and the unorthodox! Prepare to embark on a journey through the uncharted waters of economic correlations, where the unexpected thrives and the peculiar reigns supreme. Today, we present to you a groundbreaking study that will challenge your perceptions, tickle your neurons, and perhaps leave you scratching your head in mild bewilderment.
As the title "From Banks to Banks: The Cross-Pollination of Bankruptcies in California and the Marketing Managers of Guam" whimsically suggests, our investigation dives deep into the realm of statistical harmony, or dare we say, disharmony, between the bankruptcies in the Golden State of California and the enigmatic world of marketing managers in the blissful haven of Guam. It's like watching a tango between a walrus and a penguin - unexpected, improbable, and yet strangely captivating.
On the surface, one might presume that these two economic phenomena have as much in common as a turtle does with a telephone. But fear not, dear readers, for our research has unravelled a tapestry of statistical intrigue that will certainly flip the script of your conventional economic musings.
Now, as we embark on this academic adventure, I invite you to fasten your seatbelts, caffeinate your senses, and prepare to be astounded by the enticing dance of data, the mystique of mathematical models, and the humorously bewildering correlations that lie ahead. So, without further ado, let us delve into the realm of economics with a touch of quirk and a hint of whimsy!

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To extract the juicy nectar of economic data for our analysis, we embarked on an exhilarating quest through the vast expanse of digital archives and statistical repositories. Our trusty steeds, also known as internet browsers, gallantly carried us to the treasure troves of information from Statsamerica and the Bureau of Labor Statistics. There, amidst the binary landscapes and algorithmic mazes, we uncovered a bountiful harvest of data spanning the years from 2003 to 2013.

Now, to chart a course through this sea of numbers, we employed a methodological concoction that would make even the great alchemists of yore raise an approving eyebrow. Our approach, inspired by the enigmatic dance of economic forces, combined elements of correlation analysis, regression modeling, and a sprinkle of statistical wizardry - all coming together like the ingredients of a peculiar potion brewed in the cauldron of empirical inquiry.

First, in the spirit of unraveling the mystique of economic connections, we calculated correlation coefficients to measure the strength and direction of the relationship between the number of bankruptcies in California and the population of marketing managers in Guam. Seeing the numbers align and resonate with such statistical fervor was akin to witnessing the celestial bodies perform an unforeseen cosmic ballet.

Now, donning our metaphorical lab coats and wielding the tools of regression analysis, we sought to tease out the predictive power of bankruptcy filings in California on the population of marketing managers in Guam. This analytical journey was rife with twists and turns, akin to traversing a labyrinth with nothing but statistical insights as our guiding thread.

In addition to these methodological escapades, we danced with the ghosts of time series analysis, unraveling the temporal dynamics of bankruptcies and marketing manager populations over the years. This temporal tango offered a glimpse into the ebb and flow of these economic phenomena, akin to observing the tides of fortune washing upon the shores of economic interconnectedness.

Furthermore, to ensure the robustness and reliability of our findings, we subjected our data to a battery of statistical tests, sensitivity analyses, and Monte Carlo simulations. It was akin to sending our data through a rigorous boot camp, where only the fittest and most resilient statistical insights emerged victorious.

Armed with these methodological maneuvers and fortified by the spirit of inquiry, we ventured forth to uncover the unexpected, the delightful, and the puzzling correlations that beckoned from within the annals of economic data.


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 Bankruptcies in California and The number of marketing managers in Guam. Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from Statsamerica and Bureau of Larbor Statistics .

For the time period 2003 to 2013, you found a correlation 0.9610544, r-squared of 0.9236256, 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]]
"From Banks to Banks: The Cross-Pollination of Bankruptcies in California and the Marketing Managers of Guam"

[[ABSTRACT]]
In this study, we analyze the surprising and, dare we say, quirky relationship between bankruptcies in the state of California and the number of marketing managers in the tropical paradise of Guam. While these two regions might seem as distant as mismatched socks, our research has uncovered a statistical connection that is both remarkable and, to put it mildly, entertaining. Utilizing data from Statsamerica and the Bureau of Labor Statistics, we found a correlation coefficient of 0.9610544 and a p-value less than 0.01 for the period between 2003 and 2013, making this correlation not just statistically significant, but also compellingly peculiar.

Through our rigorous analysis, we have unearthed a trend that is as unexpected as finding sand at the bottom of a swimming pool – a trend that has led us to question preconceived notions about the interconnectedness of seemingly unrelated economic variables. Our findings may even prompt further research into the whimsical dance of economic forces, where the ebb and flow of bankruptcy filings in one locale appears to be mirrored by the comings and goings of marketing managers in another. It is our hope that this study will inspire fellow researchers to delve into the eccentric and fascinating world of economic correlations, and perhaps uncover more delightful surprises along the way.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Welcome, fellow scholars and enthusiasts of the uncanny and the unorthodox! Prepare to embark on a journey through the uncharted waters of economic correlations, where the unexpected thrives and the peculiar reigns supreme. Today, we present to you a groundbreaking study that will challenge your perceptions, tickle your neurons, and perhaps leave you scratching your head in mild bewilderment.
As the title "From Banks to Banks: The Cross-Pollination of Bankruptcies in California and the Marketing Managers of Guam" whimsically suggests, our investigation dives deep into the realm of statistical harmony, or dare we say, disharmony, between the bankruptcies in the Golden State of California and the enigmatic world of marketing managers in the blissful haven of Guam. It's like watching a tango between a walrus and a penguin - unexpected, improbable, and yet strangely captivating.
On the surface, one might presume that these two economic phenomena have as much in common as a turtle does with a telephone. But fear not, dear readers, for our research has unravelled a tapestry of statistical intrigue that will certainly flip the script of your conventional economic musings.
Now, as we embark on this academic adventure, I invite you to fasten your seatbelts, caffeinate your senses, and prepare to be astounded by the enticing dance of data, the mystique of mathematical models, and the humorously bewildering correlations that lie ahead. So, without further ado, let us delve into the realm of economics with a touch of quirk and a hint of whimsy!

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The results of our investigation reveal a correlation coefficient (r) of 0.9610544 and an r-squared value of 0.9236256, both of which are as robust as a sumo wrestler's handshake. The p-value of less than 0.01 adds an exclamation mark to our findings, highlighting the statistical significance of the relationship between bankruptcies in California and the number of marketing managers in Guam. It's like discovering that peanut butter and jelly are more than just sandwich companions; they're practically inseparable on the statistical plate of economic data.

As if these numeric revelations aren't fascinating enough, our research is backed by visual evidence in the form of a scatterplot (Fig. 1) that captures the unfathomable magnetism between these seemingly disparate variables. The figure graphically illustrates the striking correlation between bankruptcies in California and the population of marketing managers in Guam, leaving little doubt about the unexpected rapport between these two economic entities.

In summary, our rigorous analysis has revealed a connection that is as captivating as witnessing a synchronized swimming competition in a desert. The unexpected interplay between the economic fortunes of California and the occupational landscape of Guam has left us with more questions than answers, and has made us ponder the quirkiness of economic relationships in a whole new light. It is our hope that these findings will inspire further exploration of the delightful and unconventional side of economic research, encouraging scholars to embrace the peculiar and the unexpected with open arms and curious minds.


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 Bankruptcies in California and The number of marketing managers in Guam. Make lots of jokes, goofy observations, and puns.

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]]
"From Banks to Banks: The Cross-Pollination of Bankruptcies in California and the Marketing Managers of Guam"

[[ABSTRACT]]
In this study, we analyze the surprising and, dare we say, quirky relationship between bankruptcies in the state of California and the number of marketing managers in the tropical paradise of Guam. While these two regions might seem as distant as mismatched socks, our research has uncovered a statistical connection that is both remarkable and, to put it mildly, entertaining. Utilizing data from Statsamerica and the Bureau of Labor Statistics, we found a correlation coefficient of 0.9610544 and a p-value less than 0.01 for the period between 2003 and 2013, making this correlation not just statistically significant, but also compellingly peculiar.

Through our rigorous analysis, we have unearthed a trend that is as unexpected as finding sand at the bottom of a swimming pool – a trend that has led us to question preconceived notions about the interconnectedness of seemingly unrelated economic variables. Our findings may even prompt further research into the whimsical dance of economic forces, where the ebb and flow of bankruptcy filings in one locale appears to be mirrored by the comings and goings of marketing managers in another. It is our hope that this study will inspire fellow researchers to delve into the eccentric and fascinating world of economic correlations, and perhaps uncover more delightful surprises along the way.

[[LITERATURE REVIEW]]
In the illustrious world of economic research, where dry data meets complex statistical analyses, our pursuit of the unexpected and the inexplicable has led us to unearth a treasure trove of literature that explores the most peculiar of correlations. As we delve into the enigmatic connection between bankruptcies in California and the number of marketing managers in Guam, we find ourselves tiptoeing through the serious works of Smith, Doe, and Jones before taking a delightful plunge into the realm of eccentricity.
In "Economic Correlations: A Fundamental Analysis," Smith proposes a rigorous framework for uncovering the intricacies of economic relationships. Smith's work is indeed enlightening, but one might wonder if it captures the sheer whimsy of our present investigation. Meanwhile, Doe's "Statistical Paradoxes in Economic Trends" offers a nuanced exploration of seemingly incongruous data points, but does it encapsulate the sheer offbeat nature of bankruptcies and marketing managers frolicking hand in hand? Lastly, Jones' "Economic Phenomena: From A to Z" lays out a comprehensive survey of economic variables, yet it falls short of capturing the sheer whimsical charm of our current endeavor.
Venturing beyond the traditional bounds of economic literature, one cannot ignore the classic works of non-fiction that tantalize the imagination and offer a glimpse into the unexpected. "Freakonomics" by Levitt and Dubner, while not directly related to our subject matter, embodies the spirit of unorthodox economic analysis – a spirit that resonates deeply with our own pursuit of charming correlations. Dare we say, the unexpected joy of finding a rubber duck in a bowl of fruit salad mirrors the exhilaration of stumbling upon a correlation between bankruptcies and marketing managers?
But let us not be confined by the shackles of non-fiction, for the fiction realm offers its own brand of whimsy that sparks the imagination. Consider "The Hitchhiker's Guide to the Galaxy" by Douglas Adams, a tale of intergalactic absurdity that mirrors the inexplicable dance of economic forces we uncover. Similarly, the whimsical world of "Charlie and the Chocolate Factory" by Roald Dahl may seem worlds apart from economic research, yet its fantastical charm speaks to the delight we find in unraveling the unexpected threads of correlation.
And who can forget the world of board games, where the roll of dice and the flip of cards often lead to unforeseen and mirthful outcomes? Games like Monopoly and The Game of Life, with their whimsical representation of economic ventures, may not offer direct parallels to our research, but they certainly remind us that even in the realm of make-believe, the interconnectedness of economic phenomena can bring a chuckle or two.
As we wade through the literature that both informs and intrigues, we are reminded that the pursuit of knowledge must be accompanied by a healthy dose of levity and a willingness to embrace the delightfully absurd. With this mindset, we are primed to venture further into the depths of economic correlations, where the unexpected awaits with open arms, ready to dance a merry jig with our curious minds.
And thus, dear reader, we invite you to join us in this fanciful and offbeat exploration, where we seek not just dry data, but the whimsical delight of uncovering correlations in the unlikeliest of places.

[[RESULTS]]
The results of our investigation reveal a correlation coefficient (r) of 0.9610544 and an r-squared value of 0.9236256, both of which are as robust as a sumo wrestler's handshake. The p-value of less than 0.01 adds an exclamation mark to our findings, highlighting the statistical significance of the relationship between bankruptcies in California and the number of marketing managers in Guam. It's like discovering that peanut butter and jelly are more than just sandwich companions; they're practically inseparable on the statistical plate of economic data.
As if these numeric revelations aren't fascinating enough, our research is backed by visual evidence in the form of a scatterplot (Fig. 1) that captures the unfathomable magnetism between these seemingly disparate variables. The figure graphically illustrates the striking correlation between bankruptcies in California and the population of marketing managers in Guam, leaving little doubt about the unexpected rapport between these two economic entities.
In summary, our rigorous analysis has revealed a connection that is as captivating as witnessing a synchronized swimming competition in a desert. The unexpected interplay between the economic fortunes of California and the occupational landscape of Guam has left us with more questions than answers, and has made us ponder the quirkiness of economic relationships in a whole new light. It is our hope that these findings will inspire further exploration of the delightful and unconventional side of economic research, encouraging scholars to embrace the peculiar and the unexpected with open arms and curious minds.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

Ah, the joy of uncovering correlations in the unlikeliest of places - it's like finding a four-leaf clover in a field of economic data! In this discussion, we embark on a delightful journey through the whimsical world of bankruptcies in California and the number of marketing managers in Guam, where the improbable becomes the very cornerstone of our research.

Our results not only support the prior literature that delves into the enigmatic world of economic correlations but also add a dash of vaudevillian flair to the mix. As we harken back to the literature review, our findings echo the offbeat spirit of Levitt and Dubner's "Freakonomics," where the unexpected is celebrated much like stumbling upon an economic treasure map in a fortune cookie. Similarly, the absurdity of Douglas Adams' "The Hitchhiker's Guide to the Galaxy" finds a kindred spirit in the flabbergasting correlation we've unraveled between Californian bankruptcies and the enigmatic presence of marketing managers in Guam.

Our correlation coefficient and p-value, akin to winning a lottery ticket in the realm of statistical significance, affirm the robustness of our findings. It's as if we've stumbled upon a pot of gold at the end of a colorful scatterplot rainbow, cementing the inexplicable yet undeniable relationship between these two seemingly disparate economic variables.

This whimsical correlation might leave one pondering the delightful unpredictability of economic phenomena, akin to witnessing a penguin tap-dancing with a flamingo - a marvelous spectacle that challenges preconceptions and invites further inquiry into the charmingly unpredictable dance of economic forces. As we move forward in unlocking the mysteries of economic correlations, let us not only embrace the peculiar and the unexpected but also revel in the sheer joy of uncovering the whimsical in the realm of economic research.

It is our hope that these findings will inspire fellow researchers to embark on their own foray into the delightful and unconventional side of economic research and perhaps unearth more surprising serendipities along the way.


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 Bankruptcies in California and The number of marketing managers in Guam. Make lots of jokes, goofy observations, and puns.

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]]
"From Banks to Banks: The Cross-Pollination of Bankruptcies in California and the Marketing Managers of Guam"

[[ABSTRACT]]
In this study, we analyze the surprising and, dare we say, quirky relationship between bankruptcies in the state of California and the number of marketing managers in the tropical paradise of Guam. While these two regions might seem as distant as mismatched socks, our research has uncovered a statistical connection that is both remarkable and, to put it mildly, entertaining. Utilizing data from Statsamerica and the Bureau of Labor Statistics, we found a correlation coefficient of 0.9610544 and a p-value less than 0.01 for the period between 2003 and 2013, making this correlation not just statistically significant, but also compellingly peculiar.

Through our rigorous analysis, we have unearthed a trend that is as unexpected as finding sand at the bottom of a swimming pool – a trend that has led us to question preconceived notions about the interconnectedness of seemingly unrelated economic variables. Our findings may even prompt further research into the whimsical dance of economic forces, where the ebb and flow of bankruptcy filings in one locale appears to be mirrored by the comings and goings of marketing managers in another. It is our hope that this study will inspire fellow researchers to delve into the eccentric and fascinating world of economic correlations, and perhaps uncover more delightful surprises along the way.

[[INTRDUCTION]]
Welcome, fellow scholars and enthusiasts of the uncanny and the unorthodox! Prepare to embark on a journey through the uncharted waters of economic correlations, where the unexpected thrives and the peculiar reigns supreme. Today, we present to you a groundbreaking study that will challenge your perceptions, tickle your neurons, and perhaps leave you scratching your head in mild bewilderment.
As the title "From Banks to Banks: The Cross-Pollination of Bankruptcies in California and the Marketing Managers of Guam" whimsically suggests, our investigation dives deep into the realm of statistical harmony, or dare we say, disharmony, between the bankruptcies in the Golden State of California and the enigmatic world of marketing managers in the blissful haven of Guam. It's like watching a tango between a walrus and a penguin - unexpected, improbable, and yet strangely captivating.
On the surface, one might presume that these two economic phenomena have as much in common as a turtle does with a telephone. But fear not, dear readers, for our research has unravelled a tapestry of statistical intrigue that will certainly flip the script of your conventional economic musings.
Now, as we embark on this academic adventure, I invite you to fasten your seatbelts, caffeinate your senses, and prepare to be astounded by the enticing dance of data, the mystique of mathematical models, and the humorously bewildering correlations that lie ahead. So, without further ado, let us delve into the realm of economics with a touch of quirk and a hint of whimsy!

[[RESULTS]]
The results of our investigation reveal a correlation coefficient (r) of 0.9610544 and an r-squared value of 0.9236256, both of which are as robust as a sumo wrestler's handshake. The p-value of less than 0.01 adds an exclamation mark to our findings, highlighting the statistical significance of the relationship between bankruptcies in California and the number of marketing managers in Guam. It's like discovering that peanut butter and jelly are more than just sandwich companions; they're practically inseparable on the statistical plate of economic data.
As if these numeric revelations aren't fascinating enough, our research is backed by visual evidence in the form of a scatterplot (Fig. 1) that captures the unfathomable magnetism between these seemingly disparate variables. The figure graphically illustrates the striking correlation between bankruptcies in California and the population of marketing managers in Guam, leaving little doubt about the unexpected rapport between these two economic entities.
In summary, our rigorous analysis has revealed a connection that is as captivating as witnessing a synchronized swimming competition in a desert. The unexpected interplay between the economic fortunes of California and the occupational landscape of Guam has left us with more questions than answers, and has made us ponder the quirkiness of economic relationships in a whole new light. It is our hope that these findings will inspire further exploration of the delightful and unconventional side of economic research, encouraging scholars to embrace the peculiar and the unexpected with open arms and curious minds.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our study has not only brought to light a surprising correlation between bankruptcies in California and the number of marketing managers in Guam, but has also reminded us that the world of economics is as full of unexpected twists and turns as a rollercoaster designed by a mischievous mathematician. It’s as if the economic forces of these two distinct locales have formed an uncanny pact, conspiring to keep us researchers both intrigued and amused.

Our findings, akin to stumbling upon a unicorn in a cornfield, have pushed the boundaries of conventional economic analysis, challenging us to embrace the playful side of statistical relationships. The robust correlation coefficient and the eye-popping p-value, like a magician’s sleight of hand, have defied expectations and left us spellbound.

With our research, we hope to have sparked a newfound appreciation for the delightful dance of economic data, like witnessing a flash mob appearing in the unlikeliest of places. However, as we wrap up this whimsical adventure, we assert with confident whimsy that no more research is needed in this particular, joyfully quirky realm. The curtains have fallen, the show has ended, and it’s time to bid adieu to the enchanting correlation between these economic oddities. Let our findings stand as a testament to the whimsical wonders that await those who dare to delve into the unconventional and embrace the unexpected in the realm of economic correlations.


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 From Banks to Banks: The Cross-Pollination of Bankruptcies in California and the Marketing Managers of Guam. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Cross-Continental Business Dynamics


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 From Banks to Banks: The Cross-Pollination of Bankruptcies in California and the Marketing Managers of Guam. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Economic Bifurcation and Transnational Market Dynamics


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 From Banks to Banks: The Cross-Pollination of Bankruptcies in California and the Marketing Managers of Guam with an abstract of In this study, we analyze the surprising and, dare we say, quirky relationship between bankruptcies in the state of California and the number of marketing managers in the tropical paradise of Guam. While these two regions might seem as distant as mismatched socks, our research has uncovered a statistical connection that is both remarkable and, to put it mildly, entertaining. Utilizing data from Statsamerica and the Bureau of Labor Statistics, we found a correlation coefficient of 0.9610544 and a p-value less than 0.01 for the period between 2003 and 2013, making this correlation not just statistically significant, but also compellingly peculiar.
Through our rigorous analysis, we have unearthed a trend that is as unexpected as finding sand at the bottom of a swimming pool – a trend that has led us to question preconceived notions about the interconnectedness of seemingly unrelated economic variables. Our findings may even prompt further research into the whimsical dance of economic forces, where the ebb and flow of bankruptcy filings in one locale appears to be mirrored by the comings and goings of marketing managers in another. It is our hope that this study will inspire fellow researchers to delve into the eccentric and fascinating world of economic correlations, and perhaps uncover more delightful surprises along the way.

ChatGPT:

bankruptcies, California, marketing managers, Guam, correlation, statistical analysis, economic variables, data analysis, Statsamerica, Bureau of Labor Statistics

*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.



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Data details

Bankruptcies in California
Source: Statsamerica
See what else correlates with Bankruptcies in California

The number of marketing managers in Guam
Detailed data title: BLS estimate of marketing managers in Guam
Source: Bureau of Larbor Statistics
See what else correlates with The number of marketing managers in Guam

Correlation r = 0.9610544 (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 = 0.9236256 (Coefficient of determination)
This means 92.4% of the change in the one variable (i.e., The number of marketing managers in Guam) is predictable based on the change in the other (i.e., Bankruptcies in California) over the 11 years from 2003 through 2013.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.5E-6. 0.0000025123541430718660000000
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 0.96 in 0.00025% of random cases. Said differently, if you correlated 398,033 random variables You don't actually need 398 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 10 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 10 because we have two variables measured over a period of 11 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.85, 0.99 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!


All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
20032004200520062007200820092010201120122013
Bankruptcies in California (Bankruptcies)1416591226961667683920572615133223209818260210240151187322136485
The number of marketing managers in Guam (Marketing Managers)100809060709012014012012090




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([141659,122696,166768,39205,72615,133223,209818,260210,240151,187322,136485,])
array_2 = np.array([100,80,90,60,70,90,120,140,120,120,90,])
array_1_name = "Bankruptcies in California"
array_2_name = "The number of marketing managers in Guam"

# 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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You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

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Correlation ID: 5932 · Black Variable ID: 375 · Red Variable ID: 16562
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