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Spurious correlation #4,592 · 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 sewing machine operators in Iowa and the second variable is The average number of likes on Computerphile YouTube videos.  The chart goes from 2013 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As sewing machine operators in Iowa decreased, so did the overall happiness levels in the state. This led to a statewide decrease in supportive thumbs-up gestures, ultimately resulting in fewer likes on Computerphile videos. After all, it's sewn in the fabric of Iowa to spread positivity and keep the digital world in stitches!

Model: dalle-3
Prompt: Generate an image of an Iowa sewing factory in a futuristic, sci-fi style. Show a line of robotic sewing machine operators, each with a frown on their face. As the number of operators decreases, the emptiness of the factory becomes even more noticeable. In the background, include a futuristic screen displaying the declining trend of thumbs-up gestures and likes on Computerphile YouTube videos. The scene should convey a sense of technological advancement and the impact of automation on human emotions. 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 sewing machine operators in Iowa and The average number of likes on Computerphile YouTube videos. 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: Steampunk a meme Sci-fi fantacy Glitch art A scene from Skyrim
ChatGPT: Sci-fi fantasy

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 sewing machine operators in Iowa and The average number of likes on Computerphile YouTube videos, in the following situation: As sewing machine operators in Iowa decreased, so did the overall happiness levels in the state. This led to a statewide decrease in supportive thumbs-up gestures, ultimately resulting in fewer likes on Computerphile videos. After all, it's sewn in the fabric of Iowa to spread positivity and keep the digital world in stitches!. Keep the description simple.
ChatGPT: In an Iowa sewing factory, the number of sewing machine operators decreases as a frown appeared on their faces. The decrease in supportive thumbs-up gestures is noticeable, and the average number of likes on Computerphile YouTube videos dropped as well.

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: [ Sci-fi fantasy ] and depicting this scene: In an Iowa sewing factory, the number of sewing machine operators decreases as a frown appeared on their faces. The decrease in supportive thumbs-up gestures is noticeable, and the average number of likes on Computerphile YouTube videos dropped as well. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of an Iowa sewing factory in a futuristic, sci-fi style. Show a line of robotic sewing machine operators, each with a frown on their face. As the number of operators decreases, the emptiness of the factory becomes even more noticeable. In the background, include a futuristic screen displaying the declining trend of thumbs-up gestures and likes on Computerphile YouTube videos. The scene should convey a sense of technological advancement and the impact of automation on human emotions.

*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 a decrease in The number of sewing machine operators in Iowa caused The average number of likes on Computerphile YouTube videos to decrease.

AI academic paper

(Because p < 0.01)
Sew Likeable: Exploring the Correlation Between Sewing Machine Operators in Iowa and Computerphile YouTube Video Likes

The Journal of Domestic Arts and Digital Engagement

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 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 sewing machine operators in Iowa and The average number of likes on Computerphile YouTube videos. Make lots of jokes, goofy observations, and puns.

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

Your research team used data from Bureau of Larbor Statistics and YouTube to assess this nagging question. You found a correlation coefficient of 0.8981915 and p < 0.01 for 2013 to 2022.

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

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
Sew Likeable: Exploring the Correlation Between Sewing Machine Operators in Iowa and Computerphile YouTube Video Likes

[[ABSTRACT]]
This paper investigates the peculiar relationship between the number of sewing machine operators in Iowa and the average number of likes on Computerphile YouTube videos. Drawing from data acquired from the Bureau of Labor Statistics and YouTube, our research team calculated a strikingly high correlation coefficient of 0.8981915, with the p-value indicating statistical significance (p < 0.01) for the period spanning from 2013 to 2022. The unexpected strength of this correlation raises intriguing questions about potential underlying connections or spurious associations. While our findings may seem unlikely, they point to the need for further investigation into the seemingly unrelated worlds of sewing and digital technology. This research not only adds a touch of whimsy to the field of statistical analysis but also highlights the potential for uncovering surprising relationships in diverse domains.


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 sewing machine operators in Iowa and The average number of likes on Computerphile YouTube videos. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Here is the title and abstract of the paper:
[[TITLE]]
Sew Likeable: Exploring the Correlation Between Sewing Machine Operators in Iowa and Computerphile YouTube Video Likes

[[ABSTRACT]]
This paper investigates the peculiar relationship between the number of sewing machine operators in Iowa and the average number of likes on Computerphile YouTube videos. Drawing from data acquired from the Bureau of Labor Statistics and YouTube, our research team calculated a strikingly high correlation coefficient of 0.8981915, with the p-value indicating statistical significance (p < 0.01) for the period spanning from 2013 to 2022. The unexpected strength of this correlation raises intriguing questions about potential underlying connections or spurious associations. While our findings may seem unlikely, they point to the need for further investigation into the seemingly unrelated worlds of sewing and digital technology. This research not only adds a touch of whimsy to the field of statistical analysis but also highlights the potential for uncovering surprising relationships in diverse domains.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

Sew-rious statistical analysis meets the quirky world of YouTube in our investigation of the relationship between the number of sewing machine operators in Iowa and the average number of likes on Computerphile videos. At first glance, one might wonder what on earth these two seemingly unrelated entities have in common. Yet, as we delved into the data, we unearthed a striking correlation that has left many scratching their heads and quietly contemplating the mysteries of statistical analysis.

The pearls of wisdom we aim to sew together in this study stem from the broader trend of using unconventional data sources to uncover unexpected connections. With the rise of big data and the increasing availability of diverse datasets, researchers are no longer bound by traditional boundaries when it comes to exploring correlations and causal relationships. Who would have thought that the humble sewing machine operators in the heartland of Iowa could be linked to the digital aficionados' appreciation for Computerphile content?

While the topic might elicit a chuckle or two, we stand firmly on the solid ground of statistical rigor. Our analysis draws from comprehensive data sources, including the Bureau of Labor Statistics for the count of sewing machine operators and the treasure trove of YouTube analytics for the likes on Computerphile videos. Through meticulous data wrangling and sophisticated statistical techniques, we reveal a fantastically high correlation coefficient that commands attention, with a p-value that sends shivers down the spine of traditional statisticians (p < 0.01).

In this paper, we not only invite you to marvel at the unexpected link between stitches and clicks but to also ponder the larger implications of seemingly disparate phenomena converging in the realm of statistics. Hang on to your lab coats and sewing needles as we journey through the fabric of statistical analysis, where every stitch counts and every like adds a dash of intrigue to our quest for unusual associations.


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 sewing machine operators in Iowa and The average number of likes on Computerphile YouTube videos. 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. Then name some movies that you watched that are tangentially related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
Sew Likeable: Exploring the Correlation Between Sewing Machine Operators in Iowa and Computerphile YouTube Video Likes

[[ABSTRACT]]
This paper investigates the peculiar relationship between the number of sewing machine operators in Iowa and the average number of likes on Computerphile YouTube videos. Drawing from data acquired from the Bureau of Labor Statistics and YouTube, our research team calculated a strikingly high correlation coefficient of 0.8981915, with the p-value indicating statistical significance (p < 0.01) for the period spanning from 2013 to 2022. The unexpected strength of this correlation raises intriguing questions about potential underlying connections or spurious associations. While our findings may seem unlikely, they point to the need for further investigation into the seemingly unrelated worlds of sewing and digital technology. This research not only adds a touch of whimsy to the field of statistical analysis but also highlights the potential for uncovering surprising relationships in diverse domains.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Sew-rious statistical analysis meets the quirky world of YouTube in our investigation of the relationship between the number of sewing machine operators in Iowa and the average number of likes on Computerphile videos. At first glance, one might wonder what on earth these two seemingly unrelated entities have in common. Yet, as we delved into the data, we unearthed a striking correlation that has left many scratching their heads and quietly contemplating the mysteries of statistical analysis.
The pearls of wisdom we aim to sew together in this study stem from the broader trend of using unconventional data sources to uncover unexpected connections. With the rise of big data and the increasing availability of diverse datasets, researchers are no longer bound by traditional boundaries when it comes to exploring correlations and causal relationships. Who would have thought that the humble sewing machine operators in the heartland of Iowa could be linked to the digital aficionados' appreciation for Computerphile content?
While the topic might elicit a chuckle or two, we stand firmly on the solid ground of statistical rigor. Our analysis draws from comprehensive data sources, including the Bureau of Labor Statistics for the count of sewing machine operators and the treasure trove of YouTube analytics for the likes on Computerphile videos. Through meticulous data wrangling and sophisticated statistical techniques, we reveal a fantastically high correlation coefficient that commands attention, with a p-value that sends shivers down the spine of traditional statisticians (p < 0.01).
In this paper, we not only invite you to marvel at the unexpected link between stitches and clicks but to also ponder the larger implications of seemingly disparate phenomena converging in the realm of statistics. Hang on to your lab coats and sewing needles as we journey through the fabric of statistical analysis, where every stitch counts and every like adds a dash of intrigue to our quest for unusual associations.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

As we embark on our exploration of the correlation between the number of sewing machine operators in Iowa and the average number of likes on Computerphile YouTube videos, we first delve into the existing literature to discern any hints, however subtle, of a connection between these two seemingly unrelated entities.

Smith and Doe (2015) in their study "Sewing Machine Operators: Trends and Patterns" provide a comprehensive analysis of the demographics and employment trends of sewing machine operators in various regions. While their work primarily focuses on the job market and industry dynamics, their findings offer valuable insights into the cultural and societal implications of the sewing profession.

Jones and Smith (2018) in "YouTube Likes and Online Engagement" present a thorough examination of user engagement with online video content. Their study not only sheds light on the factors influencing the number of likes on YouTube videos but also highlights the evolving nature of digital media consumption and interaction.

Moving beyond the conventional research in the field, our exploration takes a whimsical turn as we consider the potential influences of non-traditional sources. "The Art and Craft of YouTube Analytics" by Patel et al. (2017) offers a detailed account of analyzing user behavior and preferences on YouTube. While the book focuses on leveraging analytics for digital marketing strategies, its insights provide a thought-provoking backdrop for our investigation into the enigmatic allure of Computerphile video likes.

Likewise, "The Sewing Revolution: Sewing, Hobbies, and Society" by Johnson (2019) provides an intriguing perspective on the cultural significance of sewing and its impact on leisure activities. While not directly related to digital realms, Johnson's exploration of the role of sewing in contemporary society prompts us to ponder the potential interplay between traditional crafts and modern media.

In a departure from traditional literature, we draw inspiration from the fiction realm, where the unexpected often reigns supreme. "The Stitch That Binds: A Tale of Threads and Technology" by Novelist (2016) weaves a fantastical narrative of a world where the art of sewing intersects with the digital domain, offering a whimsical portrayal of the uncharted possibilities that our research seeks to uncover.

Intrigued by the unexpected connections waiting to be unearthed, we took a lighthearted foray into the world of cinema, exploring movies that, in some divine twist of fate, touched upon elements vaguely reminiscent of our curious correlation. Films such as "The Social Network" and "Sewing through the Ages" led us on a merry chase through the realms of digital innovation and textile history, leaving us amused by the subtle symmetries between the two seemingly disparate domains.

With a nod to the quirky and the unforeseen, we step into the fray of statistical analysis, armed with both levity and rigor, poised to unravel the mysteries that lie at the intersection of stitching and digital appreciation.


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 sewing machine operators in Iowa and The average number of likes on Computerphile YouTube videos. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from Bureau of Larbor Statistics and YouTube . You used data from 2013 to 2022

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Sew Likeable: Exploring the Correlation Between Sewing Machine Operators in Iowa and Computerphile YouTube Video Likes

[[ABSTRACT]]
This paper investigates the peculiar relationship between the number of sewing machine operators in Iowa and the average number of likes on Computerphile YouTube videos. Drawing from data acquired from the Bureau of Labor Statistics and YouTube, our research team calculated a strikingly high correlation coefficient of 0.8981915, with the p-value indicating statistical significance (p < 0.01) for the period spanning from 2013 to 2022. The unexpected strength of this correlation raises intriguing questions about potential underlying connections or spurious associations. While our findings may seem unlikely, they point to the need for further investigation into the seemingly unrelated worlds of sewing and digital technology. This research not only adds a touch of whimsy to the field of statistical analysis but also highlights the potential for uncovering surprising relationships in diverse domains.

[[INTRODUCTION]]
Sew-rious statistical analysis meets the quirky world of YouTube in our investigation of the relationship between the number of sewing machine operators in Iowa and the average number of likes on Computerphile videos. At first glance, one might wonder what on earth these two seemingly unrelated entities have in common. Yet, as we delved into the data, we unearthed a striking correlation that has left many scratching their heads and quietly contemplating the mysteries of statistical analysis.
The pearls of wisdom we aim to sew together in this study stem from the broader trend of using unconventional data sources to uncover unexpected connections. With the rise of big data and the increasing availability of diverse datasets, researchers are no longer bound by traditional boundaries when it comes to exploring correlations and causal relationships. Who would have thought that the humble sewing machine operators in the heartland of Iowa could be linked to the digital aficionados' appreciation for Computerphile content?
While the topic might elicit a chuckle or two, we stand firmly on the solid ground of statistical rigor. Our analysis draws from comprehensive data sources, including the Bureau of Labor Statistics for the count of sewing machine operators and the treasure trove of YouTube analytics for the likes on Computerphile videos. Through meticulous data wrangling and sophisticated statistical techniques, we reveal a fantastically high correlation coefficient that commands attention, with a p-value that sends shivers down the spine of traditional statisticians (p < 0.01).
In this paper, we not only invite you to marvel at the unexpected link between stitches and clicks but to also ponder the larger implications of seemingly disparate phenomena converging in the realm of statistics. Hang on to your lab coats and sewing needles as we journey through the fabric of statistical analysis, where every stitch counts and every like adds a dash of intrigue to our quest for unusual associations.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To untangle the threads of correlation between the number of sewing machine operators in Iowa and the average number of likes on Computerphile YouTube videos, we employed a multifaceted approach that combined traditional statistical methods with a dash of whimsy. Our research team scoured the vast expanse of the internet for data, ranging from the hallowed halls of the Bureau of Labor Statistics to the digital playground of YouTube. The data spanned the period from 2013 to 2022, providing a rich tapestry for our analysis.

First, we employed a time-series analysis to capture the dynamic interplay between sewing machine operators and YouTube likes over the years. Weaving through the annual data, we aimed to pinpoint any discernible patterns or fluctuations that might shed light on the curious association at hand. With a keen eye for detail and an appreciation for the unexpected, we identified the temporal ebbs and flows in both domains, pausing to marvel at the peculiar synchronicities that emerged.

Additionally, we resorted to a geographic analysis to examine potential regional nuances in the relationship. Iowa, with its storied history of sewing ingenuity, provided a fertile ground for exploration. Venturing into the heartland, we delved into the regional distribution of sewing machine operators and juxtaposed it with the digital footprints of Computerphile aficionados. The geographical lens unearthed intriguing nuggets of insight, underscoring the intricacies of the connection that transcended mere numerical patterns.

Furthermore, we dabbled in advanced regression analysis to model the interdependence between the two variables. Harnessing the power of statistical modeling, we sought to disentangle the complex web of factors that might contribute to the uncanny correlation. As we navigated the intricacies of regression, we found ourselves humbled by the sheer intricacies of the relationship, marveling at the statistical elegance that underpins the seemingly whimsical association.

Lastly, we approached the data with a sense of playfulness, embracing the inimitable spirit of exploration that defines unconventional research endeavors. As we ventured through the labyrinth of data points and statistical tests, we maintained a lighthearted curiosity, allowing for the unexpected to reveal itself in the unlikeliest of places. In doing so, we not only captured the statistical essence of the correlation but also celebrated the joy of discovery in the field of empirical inquiry.

In summary, our methodology encapsulated a blend of traditional statistical techniques, geographical exploration, and an unwavering sense of curiosity. Through this multifaceted approach, we sought to illuminate the enigmatic relationship between sewing machine operators and YouTube likes, weaving a narrative that transcends statistical conventions and invites the reader to embark on a whimsical journey of discovery.


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 sewing machine operators in Iowa and The average number of likes on Computerphile YouTube videos. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

For the time period 2013 to 2022, you found a correlation 0.8981915, r-squared of 0.8067480, 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]]
Sew Likeable: Exploring the Correlation Between Sewing Machine Operators in Iowa and Computerphile YouTube Video Likes

[[ABSTRACT]]
This paper investigates the peculiar relationship between the number of sewing machine operators in Iowa and the average number of likes on Computerphile YouTube videos. Drawing from data acquired from the Bureau of Labor Statistics and YouTube, our research team calculated a strikingly high correlation coefficient of 0.8981915, with the p-value indicating statistical significance (p < 0.01) for the period spanning from 2013 to 2022. The unexpected strength of this correlation raises intriguing questions about potential underlying connections or spurious associations. While our findings may seem unlikely, they point to the need for further investigation into the seemingly unrelated worlds of sewing and digital technology. This research not only adds a touch of whimsy to the field of statistical analysis but also highlights the potential for uncovering surprising relationships in diverse domains.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Sew-rious statistical analysis meets the quirky world of YouTube in our investigation of the relationship between the number of sewing machine operators in Iowa and the average number of likes on Computerphile videos. At first glance, one might wonder what on earth these two seemingly unrelated entities have in common. Yet, as we delved into the data, we unearthed a striking correlation that has left many scratching their heads and quietly contemplating the mysteries of statistical analysis.
The pearls of wisdom we aim to sew together in this study stem from the broader trend of using unconventional data sources to uncover unexpected connections. With the rise of big data and the increasing availability of diverse datasets, researchers are no longer bound by traditional boundaries when it comes to exploring correlations and causal relationships. Who would have thought that the humble sewing machine operators in the heartland of Iowa could be linked to the digital aficionados' appreciation for Computerphile content?
While the topic might elicit a chuckle or two, we stand firmly on the solid ground of statistical rigor. Our analysis draws from comprehensive data sources, including the Bureau of Labor Statistics for the count of sewing machine operators and the treasure trove of YouTube analytics for the likes on Computerphile videos. Through meticulous data wrangling and sophisticated statistical techniques, we reveal a fantastically high correlation coefficient that commands attention, with a p-value that sends shivers down the spine of traditional statisticians (p < 0.01).
In this paper, we not only invite you to marvel at the unexpected link between stitches and clicks but to also ponder the larger implications of seemingly disparate phenomena converging in the realm of statistics. Hang on to your lab coats and sewing needles as we journey through the fabric of statistical analysis, where every stitch counts and every like adds a dash of intrigue to our quest for unusual associations.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The results of our analysis reveal a remarkably high correlation between the number of sewing machine operators in Iowa and the average number of likes on Computerphile YouTube videos. Over the period from 2013 to 2022, we identified a correlation coefficient of 0.8981915, indicating a strong positive relationship between these two seemingly unrelated variables. This finding is further supported by an r-squared value of 0.8067480, suggesting that approximately 80.7% of the variability in the likes on Computerphile videos can be explained by the number of sewing machine operators in Iowa.

The statistical significance of this relationship is underscored by the p-value of less than 0.01, affirming that the observed correlation is unlikely to have occurred by chance. These results challenge conventional expectations and beckon researchers to contemplate the underlying mechanisms or potential confounding factors driving this unexpected association.

In our scatterplot (Fig. 1), the data points form a tight cluster, unmistakably depicting the strong positive correlation between the number of sewing machine operators in Iowa and the average number of likes on Computerphile videos. This visual representation further reinforces the robustness of our findings and invites further scrutiny from both the statistical community and enthusiasts of quirky correlations.

While our results may elicit a chuckle or raise an eyebrow, they underscore the need for a broadened perspective in statistical analysis. The unassuming world of sewing in Iowa and the digital realm of YouTube likes have converged in a statistical embrace, opening the door to new avenues of inquiry and showcasing the whimsical nature of statistical exploration. As we unravel the fabric of this surprising correlation, we invite fellow researchers to join us in contemplating the profound and the peculiar within the realm of statistics.


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 sewing machine operators in Iowa and The average number of likes on Computerphile YouTube videos. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
Sew Likeable: Exploring the Correlation Between Sewing Machine Operators in Iowa and Computerphile YouTube Video Likes

[[ABSTRACT]]
This paper investigates the peculiar relationship between the number of sewing machine operators in Iowa and the average number of likes on Computerphile YouTube videos. Drawing from data acquired from the Bureau of Labor Statistics and YouTube, our research team calculated a strikingly high correlation coefficient of 0.8981915, with the p-value indicating statistical significance (p < 0.01) for the period spanning from 2013 to 2022. The unexpected strength of this correlation raises intriguing questions about potential underlying connections or spurious associations. While our findings may seem unlikely, they point to the need for further investigation into the seemingly unrelated worlds of sewing and digital technology. This research not only adds a touch of whimsy to the field of statistical analysis but also highlights the potential for uncovering surprising relationships in diverse domains.

[[LITERATURE REVIEW]]
As we embark on our exploration of the correlation between the number of sewing machine operators in Iowa and the average number of likes on Computerphile YouTube videos, we first delve into the existing literature to discern any hints, however subtle, of a connection between these two seemingly unrelated entities.
Smith and Doe (2015) in their study "Sewing Machine Operators: Trends and Patterns" provide a comprehensive analysis of the demographics and employment trends of sewing machine operators in various regions. While their work primarily focuses on the job market and industry dynamics, their findings offer valuable insights into the cultural and societal implications of the sewing profession.
Jones and Smith (2018) in "YouTube Likes and Online Engagement" present a thorough examination of user engagement with online video content. Their study not only sheds light on the factors influencing the number of likes on YouTube videos but also highlights the evolving nature of digital media consumption and interaction.
Moving beyond the conventional research in the field, our exploration takes a whimsical turn as we consider the potential influences of non-traditional sources. "The Art and Craft of YouTube Analytics" by Patel et al. (2017) offers a detailed account of analyzing user behavior and preferences on YouTube. While the book focuses on leveraging analytics for digital marketing strategies, its insights provide a thought-provoking backdrop for our investigation into the enigmatic allure of Computerphile video likes.
Likewise, "The Sewing Revolution: Sewing, Hobbies, and Society" by Johnson (2019) provides an intriguing perspective on the cultural significance of sewing and its impact on leisure activities. While not directly related to digital realms, Johnson's exploration of the role of sewing in contemporary society prompts us to ponder the potential interplay between traditional crafts and modern media.
In a departure from traditional literature, we draw inspiration from the fiction realm, where the unexpected often reigns supreme. "The Stitch That Binds: A Tale of Threads and Technology" by Novelist (2016) weaves a fantastical narrative of a world where the art of sewing intersects with the digital domain, offering a whimsical portrayal of the uncharted possibilities that our research seeks to uncover.
Intrigued by the unexpected connections waiting to be unearthed, we took a lighthearted foray into the world of cinema, exploring movies that, in some divine twist of fate, touched upon elements vaguely reminiscent of our curious correlation. Films such as "The Social Network" and "Sewing through the Ages" led us on a merry chase through the realms of digital innovation and textile history, leaving us amused by the subtle symmetries between the two seemingly disparate domains.
With a nod to the quirky and the unforeseen, we step into the fray of statistical analysis, armed with both levity and rigor, poised to unravel the mysteries that lie at the intersection of stitching and digital appreciation.

[[RESULTS]]
The results of our analysis reveal a remarkably high correlation between the number of sewing machine operators in Iowa and the average number of likes on Computerphile YouTube videos. Over the period from 2013 to 2022, we identified a correlation coefficient of 0.8981915, indicating a strong positive relationship between these two seemingly unrelated variables. This finding is further supported by an r-squared value of 0.8067480, suggesting that approximately 80.7% of the variability in the likes on Computerphile videos can be explained by the number of sewing machine operators in Iowa.
The statistical significance of this relationship is underscored by the p-value of less than 0.01, affirming that the observed correlation is unlikely to have occurred by chance. These results challenge conventional expectations and beckon researchers to contemplate the underlying mechanisms or potential confounding factors driving this unexpected association.
In our scatterplot (Fig. 1), the data points form a tight cluster, unmistakably depicting the strong positive correlation between the number of sewing machine operators in Iowa and the average number of likes on Computerphile videos. This visual representation further reinforces the robustness of our findings and invites further scrutiny from both the statistical community and enthusiasts of quirky correlations.
While our results may elicit a chuckle or raise an eyebrow, they underscore the need for a broadened perspective in statistical analysis. The unassuming world of sewing in Iowa and the digital realm of YouTube likes have converged in a statistical embrace, opening the door to new avenues of inquiry and showcasing the whimsical nature of statistical exploration. As we unravel the fabric of this surprising correlation, we invite fellow researchers to join us in contemplating the profound and the peculiar within the realm of statistics.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The findings of our study have illuminated an unexpectedly strong correlation between the number of sewing machine operators in Iowa and the average number of likes on Computerphile YouTube videos, lending credence to the whimsical notion that the worlds of stitching and digital engagement may indeed intertwine in statistical harmony. Our results lend empirical support to the delightful speculations and seemingly far-fetched connections drawn from the literature, affirming the possibility of a genuine relationship between these seemingly disparate realms.

Drawing from the study by Smith and Doe (2015) on the trends and patterns of sewing machine operators, our findings align with the notion that the cultural and societal implications of the sewing profession may extend beyond the confines of the conventional labor market. The unsuspected bond between the number of sewing machine operators and the digital realm of YouTube engagement hints at the potential intertwining of traditional crafts and contemporary digital spaces, thus echoing the playful contemplations presented in Johnson's (2019) exploration of the cultural significance of sewing.

Furthermore, our results evoke the spirit of levity that permeated our literature review, where we playfully ventured into realms of fiction, cinema, and theoretical intersections. The unexpectedly high correlation coefficient underscores the lighthearted speculation drawn from Novelist's (2016) fantastical narrative, suggesting that the art of sewing may indeed intersect with the digital domain in remarkable ways. As we merrily delved into the unlikely cinematic connections that vaguely echoed our curious correlation, our findings lend an air of credibility to the whimsical musings inspired by movies such as "The Social Network" and "Sewing through the Ages." The statistical embrace of these ostensibly unrelated entities echoes the merry chase through the realms of digital innovation and textile history, validating the subtle symmetries that piqued our amusement during our literature review.

Our findings challenge conventional expectations and beckon researchers to embrace the unexpected and the playful within statistical analysis. The statistical significance of the observed correlation, paired with the robustness of our results, extends an invitation to the statistical community and enthusiasts of quirky correlations to join us in contemplating the profound and the peculiar within the realm of statistics. Through this improbable alliance of sewing machine operators and digital likes, our study highlights the whimsical nature of statistical exploration and underscores the potential for weaving unexpected threads of correlation in diverse domains.


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 sewing machine operators in Iowa and The average number of likes on Computerphile YouTube videos. Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
Sew Likeable: Exploring the Correlation Between Sewing Machine Operators in Iowa and Computerphile YouTube Video Likes

[[ABSTRACT]]
This paper investigates the peculiar relationship between the number of sewing machine operators in Iowa and the average number of likes on Computerphile YouTube videos. Drawing from data acquired from the Bureau of Labor Statistics and YouTube, our research team calculated a strikingly high correlation coefficient of 0.8981915, with the p-value indicating statistical significance (p < 0.01) for the period spanning from 2013 to 2022. The unexpected strength of this correlation raises intriguing questions about potential underlying connections or spurious associations. While our findings may seem unlikely, they point to the need for further investigation into the seemingly unrelated worlds of sewing and digital technology. This research not only adds a touch of whimsy to the field of statistical analysis but also highlights the potential for uncovering surprising relationships in diverse domains.

[[INTRDUCTION]]
Sew-rious statistical analysis meets the quirky world of YouTube in our investigation of the relationship between the number of sewing machine operators in Iowa and the average number of likes on Computerphile videos. At first glance, one might wonder what on earth these two seemingly unrelated entities have in common. Yet, as we delved into the data, we unearthed a striking correlation that has left many scratching their heads and quietly contemplating the mysteries of statistical analysis.
The pearls of wisdom we aim to sew together in this study stem from the broader trend of using unconventional data sources to uncover unexpected connections. With the rise of big data and the increasing availability of diverse datasets, researchers are no longer bound by traditional boundaries when it comes to exploring correlations and causal relationships. Who would have thought that the humble sewing machine operators in the heartland of Iowa could be linked to the digital aficionados' appreciation for Computerphile content?
While the topic might elicit a chuckle or two, we stand firmly on the solid ground of statistical rigor. Our analysis draws from comprehensive data sources, including the Bureau of Labor Statistics for the count of sewing machine operators and the treasure trove of YouTube analytics for the likes on Computerphile videos. Through meticulous data wrangling and sophisticated statistical techniques, we reveal a fantastically high correlation coefficient that commands attention, with a p-value that sends shivers down the spine of traditional statisticians (p < 0.01).
In this paper, we not only invite you to marvel at the unexpected link between stitches and clicks but to also ponder the larger implications of seemingly disparate phenomena converging in the realm of statistics. Hang on to your lab coats and sewing needles as we journey through the fabric of statistical analysis, where every stitch counts and every like adds a dash of intrigue to our quest for unusual associations.

[[RESULTS]]
The results of our analysis reveal a remarkably high correlation between the number of sewing machine operators in Iowa and the average number of likes on Computerphile YouTube videos. Over the period from 2013 to 2022, we identified a correlation coefficient of 0.8981915, indicating a strong positive relationship between these two seemingly unrelated variables. This finding is further supported by an r-squared value of 0.8067480, suggesting that approximately 80.7% of the variability in the likes on Computerphile videos can be explained by the number of sewing machine operators in Iowa.
The statistical significance of this relationship is underscored by the p-value of less than 0.01, affirming that the observed correlation is unlikely to have occurred by chance. These results challenge conventional expectations and beckon researchers to contemplate the underlying mechanisms or potential confounding factors driving this unexpected association.
In our scatterplot (Fig. 1), the data points form a tight cluster, unmistakably depicting the strong positive correlation between the number of sewing machine operators in Iowa and the average number of likes on Computerphile videos. This visual representation further reinforces the robustness of our findings and invites further scrutiny from both the statistical community and enthusiasts of quirky correlations.
While our results may elicit a chuckle or raise an eyebrow, they underscore the need for a broadened perspective in statistical analysis. The unassuming world of sewing in Iowa and the digital realm of YouTube likes have converged in a statistical embrace, opening the door to new avenues of inquiry and showcasing the whimsical nature of statistical exploration. As we unravel the fabric of this surprising correlation, we invite fellow researchers to join us in contemplating the profound and the peculiar within the realm of statistics.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation into the unexpectedly strong correlation between the number of sewing machine operators in Iowa and the average number of likes on Computerphile YouTube videos has left us in stitches. The conspicuous connection between these two seemingly disparate domains has not only challenged our preconceived notions but has also added a whimsical touch to the tapestry of statistical analysis.

The remarkable correlation coefficient of 0.8981915, along with a p-value of less than 0.01, has certainly left us in awe of the intricate dance between stitches and clicks. It’s as if every stitch in Iowa sends a wave of appreciation through the digital expanse, resonating with the YouTube audience in an inexplicable manner. The r-squared value of 0.8067480 further emphasizes the strong explanatory power of the number of sewing machine operators in Iowa in predicting the likes on Computerphile videos, perhaps pointing to the existence of an underground subculture of quilting enthusiasts secretly driving the likes on digital content.

The tight cluster of data points in our scatterplot (Fig. 1) leaves no thread of doubt about the robustness of our findings, paving the way for a new era of statistical exploration where the unexpected reigns supreme. As we wrap up this peculiar journey of statistical discovery, we are left with an enduring sense of wonder about the interconnectedness of the world around us, from the quiet hum of sewing machines to the digital symphony of likes on YouTube.

In light of our findings, we confidently assert that no more research is needed in this area, as we have certainly sewn up this captivating correlation with finesse and flair.


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 Sew Likeable: Exploring the Correlation Between Sewing Machine Operators in Iowa and Computerphile YouTube Video Likes. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Domestic Arts and Digital Engagement


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 Sew Likeable: Exploring the Correlation Between Sewing Machine Operators in Iowa and Computerphile YouTube Video Likes. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Technological Textile Traditions


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 Sew Likeable: Exploring the Correlation Between Sewing Machine Operators in Iowa and Computerphile YouTube Video Likes with an abstract of This paper investigates the peculiar relationship between the number of sewing machine operators in Iowa and the average number of likes on Computerphile YouTube videos. Drawing from data acquired from the Bureau of Labor Statistics and YouTube, our research team calculated a strikingly high correlation coefficient of 0.8981915, with the p-value indicating statistical significance (p < 0.01) for the period spanning from 2013 to 2022. The unexpected strength of this correlation raises intriguing questions about potential underlying connections or spurious associations. While our findings may seem unlikely, they point to the need for further investigation into the seemingly unrelated worlds of sewing and digital technology. This research not only adds a touch of whimsy to the field of statistical analysis but also highlights the potential for uncovering surprising relationships in diverse domains.

ChatGPT:

sewing machine operators, Iowa, Computerphile YouTube, video likes, correlation, statistical analysis, Bureau of Labor Statistics, YouTube data, correlation coefficient, p-value, spurious associations, digital technology, sewing, technology, statistical significance, research 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 sewing machine operators in Iowa
Detailed data title: BLS estimate of sewing machine operators in Iowa
Source: Bureau of Larbor Statistics
See what else correlates with The number of sewing machine operators in Iowa

The average number of likes on Computerphile YouTube videos
Detailed data title: The average number of likes on Computerphile YouTube videos.
Source: YouTube
See what else correlates with The average number of likes on Computerphile YouTube videos

Correlation r = 0.8981915 (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 = 0.8067480 (Coefficient of determination)
This means 80.7% of the change in the one variable (i.e., The average number of likes on Computerphile YouTube videos) is predictable based on the change in the other (i.e., The number of sewing machine operators in Iowa) over the 10 years from 2013 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00041. 0.0004149955200172375000000000
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 0.9 in 0.041% of random cases. Said differently, if you correlated 2,410 random variables Which I absolutely did.
with the same 9 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 9 because we have two variables measured over a period of 10 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.

[ 0.62, 0.98 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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


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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
2013201420152016201720182019202020212022
The number of sewing machine operators in Iowa (Sewing Machine Operators)1090810770860810720770700760740
The average number of likes on Computerphile YouTube videos (Average likes)10763.57034.925357.947557.918106.74507.24776.925561.156784.085844.37




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([1090,810,770,860,810,720,770,700,760,740,])
array_2 = np.array([10763.5,7034.92,5357.94,7557.91,8106.7,4507.2,4776.92,5561.15,6784.08,5844.37,])
array_1_name = "The number of sewing machine operators in Iowa"
array_2_name = "The average number of likes on Computerphile YouTube videos"

# 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 may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

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

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

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

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Correlation ID: 4592 · Black Variable ID: 8087 · Red Variable ID: 25909
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