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AI explanation
Fewer Teds meant fewer people asking, "Hey, how's it goin'?" to each other, leading to a significant reduction in unnecessary idle chit-chat. This, in turn, lowered overall carbon emissions and improved the air quality in Vernal, Utah. Who would've thought that the key to cleaner air lay in being a little less Ted-dious?
Model: dalle-3
Prompt: Image Generation Prompt: Generate a cutesy art illustration of a small town scene in Vernal, Utah. Depict a quaint street with storefronts and personalized license plates on cars. Show fewer "Ted" personalized plates and signs, indicating a decrease in traffic. Illustrate a clear, bright sky with a noticeable improvement in air quality. Highlight happy residents enjoying the outdoors, taking in deep breaths, and engaging in leisurely activities. 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: Popularity of the first name Ted and Air pollution in Vernal, Utah. 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: Macabre Brutalism Cutsy graphics High-tech Cutsy art illustration
ChatGPT: Cutsy art illustration
Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Popularity of the first name Ted and Air pollution in Vernal, Utah, in the following situation: Fewer Teds meant fewer people asking, "Hey, how's it goin'?" to each other, leading to a significant reduction in unnecessary idle chit-chat. This, in turn, lowered overall carbon emissions and improved the air quality in Vernal, Utah. Who would've thought that the key to cleaner air lay in being a little less Ted-dious?. Keep the description simple.
ChatGPT: In a small town in Vernal, Utah, fewer "Ted"s were seen on personalized license plates and storefront signs. As a result, there was a noticeable decrease in traffic congestion and a reduction in the amount of cars idling around town, causing a noticeable improvement in air quality. The air felt cleaner and fresher, making it easier for residents to take in deep breaths and enjoy the outdoors.
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: [ Cutsy art illustration ] and depicting this scene: In a small town in Vernal, Utah, fewer "Ted"s were seen on personalized license plates and storefront signs. As a result, there was a noticeable decrease in traffic congestion and a reduction in the amount of cars idling around town, causing a noticeable improvement in air quality. The air felt cleaner and fresher, making it easier for residents to take in deep breaths and enjoy the outdoors. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Image Generation Prompt: Generate a cutesy art illustration of a small town scene in Vernal, Utah. Depict a quaint street with storefronts and personalized license plates on cars. Show fewer "Ted" personalized plates and signs, indicating a decrease in traffic. Illustrate a clear, bright sky with a noticeable improvement in air quality. Highlight happy residents enjoying the outdoors, taking in deep breaths, and engaging in leisurely activities.
*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.
I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how a decrease in Popularity of the first name Ted caused Air pollution in Vernal, Utah to decrease.
AI academic paper
 |
The Ted-dy Bear Effect: The Unbearable Lightness of Ted in Vernal, Utah The Journal of Whimsical Anthropology Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Popularity of the first name Ted and Air pollution in Vernal, Utah. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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 US Social Security Administration and Environmental Protection Agency to assess this nagging question. You found a correlation coefficient of 0.8032710 and p < 0.01 for 2009 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]]
The "Ted-dy Bear Effect": The Unbearable Lightness of Ted in Vernal, Utah
[[ABSTRACT]]
This paper explores the unexpected and whimsical correlation between the popularity of the first name Ted and air pollution levels in the charming town of Vernal, Utah. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, our research team delved into the enigmatic relationship between Ted and atmospheric contaminants. Our findings reveal a striking correlation coefficient of 0.8032710, with a statistically significant p-value of less than 0.01 for the years 2009 to 2022. The results are as surprising and perplexing as finding a speckled bear in the desert: the more Teds there are, the more polluted the air becomes. The implications of this peculiar correlation prompt the need for further investigation into the enchanting yet confounding "Ted-dy Bear Effect" and its implications for air quality dynamics in Vernal.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Popularity of the first name Ted and Air pollution in Vernal, Utah. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Here is the title and abstract of the paper:
[[TITLE]]
The "Ted-dy Bear Effect": The Unbearable Lightness of Ted in Vernal, Utah
[[ABSTRACT]]
This paper explores the unexpected and whimsical correlation between the popularity of the first name Ted and air pollution levels in the charming town of Vernal, Utah. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, our research team delved into the enigmatic relationship between Ted and atmospheric contaminants. Our findings reveal a striking correlation coefficient of 0.8032710, with a statistically significant p-value of less than 0.01 for the years 2009 to 2022. The results are as surprising and perplexing as finding a speckled bear in the desert: the more Teds there are, the more polluted the air becomes. The implications of this peculiar correlation prompt the need for further investigation into the enchanting yet confounding "Ted-dy Bear Effect" and its implications for air quality dynamics in Vernal.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
Introduction
The whimsical world of statistical analysis often leads researchers down unexpected paths, where unlikely correlations and peculiar relationships emerge from the data like hidden treasures waiting to be discovered. In the enchanting town of Vernal, Utah, our research team stumbled upon one such peculiar correlation that left us scratching our heads and pondering the enigmatic interplay of variables. Our investigation centered around the seemingly unrelated phenomena of the popularity of the first name "Ted" and air pollution levels in Vernal. The quaint and idyllic scenery of Vernal, with its majestic landscapes and serene atmosphere, offered the perfect backdrop for unraveling this unexpected mystery.
The study originated from a lighthearted curiosity but quickly evolved into a scientific pursuit, driven by the tantalizing prospect of uncovering a correlation that seemed as improbable as encountering a polar bear sunbathing on the equator. The unexpected merger of social nomenclature and environmental dynamics epitomized the fusion of statistical analysis and whimsy, adding an element of delight to what would have otherwise been a mundane statistical exploration.
As we delved into the depths of data sets from the United States Social Security Administration and the Environmental Protection Agency, we found ourselves embracing the inherent unpredictability of research. The initial levity of our investigation soon gave way to genuine intrigue as the numbers began to paint a peculiar picture that defied traditional expectations. The "Ted-dy Bear Effect," as we whimsically dubbed it, stood as a testament to the serendipitous nature of scientific inquiry, proving that even the most unassuming variables can harbor surprising secrets.
Our foray into the "Ted-dy Bear Effect" not only entertained our scientific curiosity but also raised thought-provoking questions about the intricate web of factors that shape air quality dynamics. The striking correlation coefficient of 0.8032710, accompanied by a statistically significant p-value of less than 0.01 for the years 2009 to 2022, added layers of intrigue to our already captivating journey. While we had initially set out to explore correlations, we found ourselves reveling in the delightful dance of teddy bears and air pollutants, an unexpected and charming intersection of human monikers and environmental phenomena.
In this paper, we invite you to join us on this whimsical scientific odyssey as we unpack the "Ted-dy Bear Effect," celebrate the curious and fascinating nature of statistical analysis, and contemplate the unforeseen connections that grace the world of research. Our findings and insights not only shed light on the peculiar relationship between the popularity of the name "Ted" and air pollution in Vernal, but also serve as an invitation to embrace the delightful surprises that await those who venture into the captivating realm of scientific exploration.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Popularity of the first name Ted and Air pollution in Vernal, Utah. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.
Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.
Make up the lorem and ipsum part, but make it sound related to the topic at hand.
Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a couple popular internet memes that are related to one of the topics.
Here is the title and abstract of the paper:
[[TITLE]]
The "Ted-dy Bear Effect": The Unbearable Lightness of Ted in Vernal, Utah
[[ABSTRACT]]
This paper explores the unexpected and whimsical correlation between the popularity of the first name Ted and air pollution levels in the charming town of Vernal, Utah. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, our research team delved into the enigmatic relationship between Ted and atmospheric contaminants. Our findings reveal a striking correlation coefficient of 0.8032710, with a statistically significant p-value of less than 0.01 for the years 2009 to 2022. The results are as surprising and perplexing as finding a speckled bear in the desert: the more Teds there are, the more polluted the air becomes. The implications of this peculiar correlation prompt the need for further investigation into the enchanting yet confounding "Ted-dy Bear Effect" and its implications for air quality dynamics in Vernal.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Introduction
The whimsical world of statistical analysis often leads researchers down unexpected paths, where unlikely correlations and peculiar relationships emerge from the data like hidden treasures waiting to be discovered. In the enchanting town of Vernal, Utah, our research team stumbled upon one such peculiar correlation that left us scratching our heads and pondering the enigmatic interplay of variables. Our investigation centered around the seemingly unrelated phenomena of the popularity of the first name "Ted" and air pollution levels in Vernal. The quaint and idyllic scenery of Vernal, with its majestic landscapes and serene atmosphere, offered the perfect backdrop for unraveling this unexpected mystery.
The study originated from a lighthearted curiosity but quickly evolved into a scientific pursuit, driven by the tantalizing prospect of uncovering a correlation that seemed as improbable as encountering a polar bear sunbathing on the equator. The unexpected merger of social nomenclature and environmental dynamics epitomized the fusion of statistical analysis and whimsy, adding an element of delight to what would have otherwise been a mundane statistical exploration.
As we delved into the depths of data sets from the United States Social Security Administration and the Environmental Protection Agency, we found ourselves embracing the inherent unpredictability of research. The initial levity of our investigation soon gave way to genuine intrigue as the numbers began to paint a peculiar picture that defied traditional expectations. The "Ted-dy Bear Effect," as we whimsically dubbed it, stood as a testament to the serendipitous nature of scientific inquiry, proving that even the most unassuming variables can harbor surprising secrets.
Our foray into the "Ted-dy Bear Effect" not only entertained our scientific curiosity but also raised thought-provoking questions about the intricate web of factors that shape air quality dynamics. The striking correlation coefficient of 0.8032710, accompanied by a statistically significant p-value of less than 0.01 for the years 2009 to 2022, added layers of intrigue to our already captivating journey. While we had initially set out to explore correlations, we found ourselves reveling in the delightful dance of teddy bears and air pollutants, an unexpected and charming intersection of human monikers and environmental phenomena.
In this paper, we invite you to join us on this whimsical scientific odyssey as we unpack the "Ted-dy Bear Effect," celebrate the curious and fascinating nature of statistical analysis, and contemplate the unforeseen connections that grace the world of research. Our findings and insights not only shed light on the peculiar relationship between the popularity of the name "Ted" and air pollution in Vernal, but also serve as an invitation to embrace the delightful surprises that await those who venture into the captivating realm of scientific exploration.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
The unexpected correlation between the popularity of the first name "Ted" and air pollution levels in Vernal, Utah has spurred our curiosity and prompted an exploratory review of existing literature. In "Smith et al. (2015)," the authors examine the societal impact of naming trends and its potential implications for environmental phenomena. Their findings offer intriguing insights into the influence of nomenclature on regional dynamics, laying a foundation for our investigation into the "Ted-dy Bear Effect."
Building upon this foundation, "Doe and Jones (2018)" delve into the intricate relationship between human behavior and environmental factors, highlighting the interconnected nature of seemingly disparate variables. Their work sparks a contemplation of the whimsical interplay between human names and atmospheric constituents, setting the stage for our unconventional exploration in Vernal, Utah.
Expanding beyond academic studies, "The Names We Call Ourselves" by Laura Smith provides a comprehensive analysis of the cultural significance of names and their impact on societal perceptions. While the book may not directly address air pollution, its examination of the profound influence of names offers a broader context for understanding the potential ramifications of the "Ted-dy Bear Effect" on the town of Vernal.
In a similarly whimsical vein, the fictional novel "The Airbenders of Vernal" imaginatively depicts a world where air quality is shaped by the whims of fantastical beings, offering a lighthearted parallel to our investigation. Although the book exists purely in the realm of fantasy, its playful take on environmental dynamics resonates with the peculiar nature of our own findings.
Furthermore, "Name of the Wind" by Patrick Rothfuss and "Gone with the Wind" by Margaret Mitchell, while not explicitly related to air quality or naming trends, inadvertently draw attention to the ethereal nature of winds and the enduring power of names, forming tangential connections to the eclectic tapestry of our research.
In a delightfully digital twist, the ubiquitous internet meme featuring the phrase "Teddy Bear Picnic" conjures whimsical images of bears frolicking in the forest, serving as a charming nod to the coincidental correlation between the name "Ted" and air pollution in Vernal.
While the literature review may initially venture into conventional territory, the unexpected mingling of serious discourse with whimsy mirrors the delightful intersection of our research topic. As we navigate the meandering pathways of academic inquiry, the amalgamation of scholarly works and playful references reinforces the captivating nature of our investigation into the "Ted-dy Bear Effect" in Vernal, Utah.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Popularity of the first name Ted and Air pollution in Vernal, Utah. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and Environmental Protection Agency . You used data from 2009 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]]
The "Ted-dy Bear Effect": The Unbearable Lightness of Ted in Vernal, Utah
[[ABSTRACT]]
This paper explores the unexpected and whimsical correlation between the popularity of the first name Ted and air pollution levels in the charming town of Vernal, Utah. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, our research team delved into the enigmatic relationship between Ted and atmospheric contaminants. Our findings reveal a striking correlation coefficient of 0.8032710, with a statistically significant p-value of less than 0.01 for the years 2009 to 2022. The results are as surprising and perplexing as finding a speckled bear in the desert: the more Teds there are, the more polluted the air becomes. The implications of this peculiar correlation prompt the need for further investigation into the enchanting yet confounding "Ted-dy Bear Effect" and its implications for air quality dynamics in Vernal.
[[INTRODUCTION]]
Introduction
The whimsical world of statistical analysis often leads researchers down unexpected paths, where unlikely correlations and peculiar relationships emerge from the data like hidden treasures waiting to be discovered. In the enchanting town of Vernal, Utah, our research team stumbled upon one such peculiar correlation that left us scratching our heads and pondering the enigmatic interplay of variables. Our investigation centered around the seemingly unrelated phenomena of the popularity of the first name "Ted" and air pollution levels in Vernal. The quaint and idyllic scenery of Vernal, with its majestic landscapes and serene atmosphere, offered the perfect backdrop for unraveling this unexpected mystery.
The study originated from a lighthearted curiosity but quickly evolved into a scientific pursuit, driven by the tantalizing prospect of uncovering a correlation that seemed as improbable as encountering a polar bear sunbathing on the equator. The unexpected merger of social nomenclature and environmental dynamics epitomized the fusion of statistical analysis and whimsy, adding an element of delight to what would have otherwise been a mundane statistical exploration.
As we delved into the depths of data sets from the United States Social Security Administration and the Environmental Protection Agency, we found ourselves embracing the inherent unpredictability of research. The initial levity of our investigation soon gave way to genuine intrigue as the numbers began to paint a peculiar picture that defied traditional expectations. The "Ted-dy Bear Effect," as we whimsically dubbed it, stood as a testament to the serendipitous nature of scientific inquiry, proving that even the most unassuming variables can harbor surprising secrets.
Our foray into the "Ted-dy Bear Effect" not only entertained our scientific curiosity but also raised thought-provoking questions about the intricate web of factors that shape air quality dynamics. The striking correlation coefficient of 0.8032710, accompanied by a statistically significant p-value of less than 0.01 for the years 2009 to 2022, added layers of intrigue to our already captivating journey. While we had initially set out to explore correlations, we found ourselves reveling in the delightful dance of teddy bears and air pollutants, an unexpected and charming intersection of human monikers and environmental phenomena.
In this paper, we invite you to join us on this whimsical scientific odyssey as we unpack the "Ted-dy Bear Effect," celebrate the curious and fascinating nature of statistical analysis, and contemplate the unforeseen connections that grace the world of research. Our findings and insights not only shed light on the peculiar relationship between the popularity of the name "Ted" and air pollution in Vernal, but also serve as an invitation to embrace the delightful surprises that await those who venture into the captivating realm of scientific exploration.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
METHODOLOGY
In the pursuit of unraveling the enchanting mystery of the "Ted-dy Bear Effect" and its connection to air pollution in Vernal, Utah, our research team embarked on a methodological journey that incorporated a blend of data mining, statistical analysis, and a healthy dose of whimsy.
Data Collection:
We commenced our investigation by scouring the digital archives of the United States Social Security Administration to obtain comprehensive data on the popularity of the first name "Ted" from 2009 to 2022. The TEDious task of data compilation allowed us to capture the ebbs and flows of Ted's prevalence over the years, creating a comprehensive portrait of the TEDntious trajectory of this endearing moniker.
Simultaneously, we turned to the Environmental Protection Agency to acquire detailed records of air quality measurements in Vernal, Utah, during the same time frame. Amidst the sea of environmental data, we navigated through air pollutant concentrations, meteorological conditions, and atmospheric dynamics, all while keeping our gaze fixed on the peculiar correlation waiting to be unveiled.
Variable Transformation and Adjustment:
To facilitate a robust analysis, we transformed the raw data into a format that lent itself to comparative examination. Applying our scientific sorcery, we conjured statistical incantations to align the temporal dimensions of the two datasets, ensuring that the chronicles of Teddy popularity harmonized with the atmospheric escapades in Vernal.
Statistical Analysis:
With our data sets primed and polished, we delved into the realm of statistical analysis, employing the time-honored tools of correlation coefficients and p-values to unveil the mysterious relationship between Ted and air pollution. As we navigated the labyrinth of statistical significance, we approached our analysis with a calculating curiosity, ever mindful of the flickering potential for unexpected revelations.
The UnVEILing of the "TED-dy Bear Effect":
Armed with our findings and a sense of whimsical wonder, we uncovered a striking correlation coefficient of 0.8032710, a metric that exceeded our most extravagant expectations. The statistically significant p-value of less than 0.01 further illuminated the profound, if perplexing, bond between the prevalence of Ted and the atmospheric dance of pollutants in Vernal.
Embracing the Unexpected:
To complement our quantitative analysis, we cultivated an appreciation for the serendipitous nature of scientific inquiry, fostering an environment where the unpredictable reins supreme. As we navigated the dance of teddy bears and air pollutants, we remained open to the delightful surprises that emerge when statistical analysis intertwines with the whimsical quirks of human nomenclature and environmental dynamics.
In summary, our methodology blended rigorous statistical analysis with a lighthearted embrace of the unexpected, yielding a research endeavor that not only celebrates the charm of scientific exploration but also sheds light on the endearing "Ted-dy Bear Effect" and its implications for air quality dynamics in Vernal.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Popularity of the first name Ted and Air pollution in Vernal, Utah. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and Environmental Protection Agency .
For the time period 2009 to 2022, you found a correlation 0.8032710, r-squared of 0.6452443, and p < 0.01.
One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.
Here is the title and abstract of the paper:
[[TITLE]]
The "Ted-dy Bear Effect": The Unbearable Lightness of Ted in Vernal, Utah
[[ABSTRACT]]
This paper explores the unexpected and whimsical correlation between the popularity of the first name Ted and air pollution levels in the charming town of Vernal, Utah. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, our research team delved into the enigmatic relationship between Ted and atmospheric contaminants. Our findings reveal a striking correlation coefficient of 0.8032710, with a statistically significant p-value of less than 0.01 for the years 2009 to 2022. The results are as surprising and perplexing as finding a speckled bear in the desert: the more Teds there are, the more polluted the air becomes. The implications of this peculiar correlation prompt the need for further investigation into the enchanting yet confounding "Ted-dy Bear Effect" and its implications for air quality dynamics in Vernal.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
Introduction
The whimsical world of statistical analysis often leads researchers down unexpected paths, where unlikely correlations and peculiar relationships emerge from the data like hidden treasures waiting to be discovered. In the enchanting town of Vernal, Utah, our research team stumbled upon one such peculiar correlation that left us scratching our heads and pondering the enigmatic interplay of variables. Our investigation centered around the seemingly unrelated phenomena of the popularity of the first name "Ted" and air pollution levels in Vernal. The quaint and idyllic scenery of Vernal, with its majestic landscapes and serene atmosphere, offered the perfect backdrop for unraveling this unexpected mystery.
The study originated from a lighthearted curiosity but quickly evolved into a scientific pursuit, driven by the tantalizing prospect of uncovering a correlation that seemed as improbable as encountering a polar bear sunbathing on the equator. The unexpected merger of social nomenclature and environmental dynamics epitomized the fusion of statistical analysis and whimsy, adding an element of delight to what would have otherwise been a mundane statistical exploration.
As we delved into the depths of data sets from the United States Social Security Administration and the Environmental Protection Agency, we found ourselves embracing the inherent unpredictability of research. The initial levity of our investigation soon gave way to genuine intrigue as the numbers began to paint a peculiar picture that defied traditional expectations. The "Ted-dy Bear Effect," as we whimsically dubbed it, stood as a testament to the serendipitous nature of scientific inquiry, proving that even the most unassuming variables can harbor surprising secrets.
Our foray into the "Ted-dy Bear Effect" not only entertained our scientific curiosity but also raised thought-provoking questions about the intricate web of factors that shape air quality dynamics. The striking correlation coefficient of 0.8032710, accompanied by a statistically significant p-value of less than 0.01 for the years 2009 to 2022, added layers of intrigue to our already captivating journey. While we had initially set out to explore correlations, we found ourselves reveling in the delightful dance of teddy bears and air pollutants, an unexpected and charming intersection of human monikers and environmental phenomena.
In this paper, we invite you to join us on this whimsical scientific odyssey as we unpack the "Ted-dy Bear Effect," celebrate the curious and fascinating nature of statistical analysis, and contemplate the unforeseen connections that grace the world of research. Our findings and insights not only shed light on the peculiar relationship between the popularity of the name "Ted" and air pollution in Vernal, but also serve as an invitation to embrace the delightful surprises that await those who venture into the captivating realm of scientific exploration.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The results of our investigation into the whimsical "Ted-dy Bear Effect" unveiled a surprising and substantial correlation between the popularity of the first name Ted and air pollution levels in Vernal, Utah. Our statistical analysis unveiled a correlation coefficient of 0.8032710, indicating a strong positive relationship between these seemingly unrelated variables. The r-squared value of 0.6452443 further underscored the robustness of this connection, suggesting that approximately 64.5% of the variability in air pollution levels can be explained by the popularity of the name Ted. Moreover, the p-value of less than 0.01 lent statistical significance to our findings, affirming the validity of the observed relationship.
The compelling nature of our results is visually encapsulated in Figure 1, a scatterplot that vividly illustrates the pronounced association between the prevalence of the name Ted and air pollution levels in Vernal. This charming depiction of numerical aesthetics serves as a testament to the enchanting dance of data points, where the whimsical "Ted-dy Bear Effect" comes to life in the form of a graph.
Our findings, while undoubtedly entertaining, also beckon the scientific community to ponder the underlying mechanisms driving this unexpected correlation. As we wade through the lighthearted waters of statistical analysis, it becomes clear that the world of research is not without its whimsical surprises. The "Ted-dy Bear Effect" stands as a cheerful reminder that even the most unlikely variables can engage in a charming tango of correlation, urging researchers to approach scientific inquiry with both rigor and a dash of whimsy.
The implications of our discovery extend beyond the confines of statistical intrigue, prodding at the deeper mysteries of societal nomenclature and environmental dynamics. As we contemplate the allure of this serendipitous correlation, we are reminded that science, much like life, can be delightfully unpredictable and filled with unexpected encounters. The "Ted-dy Bear Effect" serves as a lighthearted testament to the inexhaustible well of curiosity that propels researchers to explore the delightful unknown and uncover the endearing quirkiness hidden within the fabric of scientific inquiry.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Popularity of the first name Ted and Air pollution in Vernal, Utah. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Limit your response to 500 tokens.
Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.
Do not write a conclusion. I will add a conclusion after this.
[[TITLE]]
The "Ted-dy Bear Effect": The Unbearable Lightness of Ted in Vernal, Utah
[[ABSTRACT]]
This paper explores the unexpected and whimsical correlation between the popularity of the first name Ted and air pollution levels in the charming town of Vernal, Utah. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, our research team delved into the enigmatic relationship between Ted and atmospheric contaminants. Our findings reveal a striking correlation coefficient of 0.8032710, with a statistically significant p-value of less than 0.01 for the years 2009 to 2022. The results are as surprising and perplexing as finding a speckled bear in the desert: the more Teds there are, the more polluted the air becomes. The implications of this peculiar correlation prompt the need for further investigation into the enchanting yet confounding "Ted-dy Bear Effect" and its implications for air quality dynamics in Vernal.
[[LITERATURE REVIEW]]
The unexpected correlation between the popularity of the first name "Ted" and air pollution levels in Vernal, Utah has spurred our curiosity and prompted an exploratory review of existing literature. In "Smith et al. (2015)," the authors examine the societal impact of naming trends and its potential implications for environmental phenomena. Their findings offer intriguing insights into the influence of nomenclature on regional dynamics, laying a foundation for our investigation into the "Ted-dy Bear Effect."
Building upon this foundation, "Doe and Jones (2018)" delve into the intricate relationship between human behavior and environmental factors, highlighting the interconnected nature of seemingly disparate variables. Their work sparks a contemplation of the whimsical interplay between human names and atmospheric constituents, setting the stage for our unconventional exploration in Vernal, Utah.
Expanding beyond academic studies, "The Names We Call Ourselves" by Laura Smith provides a comprehensive analysis of the cultural significance of names and their impact on societal perceptions. While the book may not directly address air pollution, its examination of the profound influence of names offers a broader context for understanding the potential ramifications of the "Ted-dy Bear Effect" on the town of Vernal.
In a similarly whimsical vein, the fictional novel "The Airbenders of Vernal" imaginatively depicts a world where air quality is shaped by the whims of fantastical beings, offering a lighthearted parallel to our investigation. Although the book exists purely in the realm of fantasy, its playful take on environmental dynamics resonates with the peculiar nature of our own findings.
Furthermore, "Name of the Wind" by Patrick Rothfuss and "Gone with the Wind" by Margaret Mitchell, while not explicitly related to air quality or naming trends, inadvertently draw attention to the ethereal nature of winds and the enduring power of names, forming tangential connections to the eclectic tapestry of our research.
In a delightfully digital twist, the ubiquitous internet meme featuring the phrase "Teddy Bear Picnic" conjures whimsical images of bears frolicking in the forest, serving as a charming nod to the coincidental correlation between the name "Ted" and air pollution in Vernal.
While the literature review may initially venture into conventional territory, the unexpected mingling of serious discourse with whimsy mirrors the delightful intersection of our research topic. As we navigate the meandering pathways of academic inquiry, the amalgamation of scholarly works and playful references reinforces the captivating nature of our investigation into the "Ted-dy Bear Effect" in Vernal, Utah.
[[RESULTS]]
The results of our investigation into the whimsical "Ted-dy Bear Effect" unveiled a surprising and substantial correlation between the popularity of the first name Ted and air pollution levels in Vernal, Utah. Our statistical analysis unveiled a correlation coefficient of 0.8032710, indicating a strong positive relationship between these seemingly unrelated variables. The r-squared value of 0.6452443 further underscored the robustness of this connection, suggesting that approximately 64.5% of the variability in air pollution levels can be explained by the popularity of the name Ted. Moreover, the p-value of less than 0.01 lent statistical significance to our findings, affirming the validity of the observed relationship.
The compelling nature of our results is visually encapsulated in Figure 1, a scatterplot that vividly illustrates the pronounced association between the prevalence of the name Ted and air pollution levels in Vernal. This charming depiction of numerical aesthetics serves as a testament to the enchanting dance of data points, where the whimsical "Ted-dy Bear Effect" comes to life in the form of a graph.
Our findings, while undoubtedly entertaining, also beckon the scientific community to ponder the underlying mechanisms driving this unexpected correlation. As we wade through the lighthearted waters of statistical analysis, it becomes clear that the world of research is not without its whimsical surprises. The "Ted-dy Bear Effect" stands as a cheerful reminder that even the most unlikely variables can engage in a charming tango of correlation, urging researchers to approach scientific inquiry with both rigor and a dash of whimsy.
The implications of our discovery extend beyond the confines of statistical intrigue, prodding at the deeper mysteries of societal nomenclature and environmental dynamics. As we contemplate the allure of this serendipitous correlation, we are reminded that science, much like life, can be delightfully unpredictable and filled with unexpected encounters. The "Ted-dy Bear Effect" serves as a lighthearted testament to the inexhaustible well of curiosity that propels researchers to explore the delightful unknown and uncover the endearing quirkiness hidden within the fabric of scientific inquiry.
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Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
Our investigation into the "Ted-dy Bear Effect" has provided compelling evidence of the unforeseen connection between the prevalence of the name Ted and air pollution levels in the captivating town of Vernal, Utah. The robust correlation coefficient of 0.8032710 not only defies the traditionally staid boundaries of research but also tickles the fancy of statistical enthusiasts and whimsy seekers alike. By embracing the seemingly nonsensical and adorning it with scientific rigor, our study has adorned the illustrious tapestry of research with an amusing, albeit perplexing, stitch.
The litany of prior research, ranging from the salient societal impact of naming trends to whimsical musings on the ethereal nature of winds and the enduring power of names, has lent credence to our findings. It's as if the scholarly realm conspired to play a practical joke, uniting scholarly discourse and whimsy in an unlikely union, urging us to confront the delightful enigma that is the "Ted-dy Bear Effect."
The visually mesmerizing scatterplot in Figure 1 not only captures the unmistakable relationship between the prevalence of the name Ted and air pollution levels but also serves as a whimsical testament to the allure of data visualization. Like a captivating dance, the data points entwine in a charming rendezvous, echoing the playful spirit of our investigations. Ultimately, the graph serves as a reminder that research is not merely a pursuit of empirical truths but a fanciful exploration of unexpected revelations.
Our results have not only delighted the scientific community with statistical intrigue but have also beckoned an inquisitive spirit to ponder the underlying mechanisms behind this cheerfully confounding correlation. Indeed, our findings beckon researchers to contemplate the delightful uncertainties that pervade the world of scientific inquiry and to recognize that even the most improbable variables can engage in a joyful tango of statistical significance.
As we navigate through the meandering pathways of academic inquiry, the amalgamation of scholarly works and that whimsical contingency reinforces the captivating nature of our investigation into the "Ted-dy Bear Effect" in Vernal, Utah. This whimsical mishmash of scholarly discourse with amusing interludes has elevated our research into a delightful, if not entirely serious, venture that speaks to the heart of scientific exploration. Much like a surprising encounter with a speckled bear in the desert, our findings remind the scientific community that even the most unlikely correlations can elicit a sense of wonder and curiosity, infusing the rigorous pursuit of knowledge with an endearing touch of whimsy.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly 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 Popularity of the first name Ted and Air pollution in Vernal, Utah. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.
Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.
Here are the title, abstract, introduction, and results sections.
[[TITLE]]
The "Ted-dy Bear Effect": The Unbearable Lightness of Ted in Vernal, Utah
[[ABSTRACT]]
This paper explores the unexpected and whimsical correlation between the popularity of the first name Ted and air pollution levels in the charming town of Vernal, Utah. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, our research team delved into the enigmatic relationship between Ted and atmospheric contaminants. Our findings reveal a striking correlation coefficient of 0.8032710, with a statistically significant p-value of less than 0.01 for the years 2009 to 2022. The results are as surprising and perplexing as finding a speckled bear in the desert: the more Teds there are, the more polluted the air becomes. The implications of this peculiar correlation prompt the need for further investigation into the enchanting yet confounding "Ted-dy Bear Effect" and its implications for air quality dynamics in Vernal.
[[INTRDUCTION]]
Introduction
The whimsical world of statistical analysis often leads researchers down unexpected paths, where unlikely correlations and peculiar relationships emerge from the data like hidden treasures waiting to be discovered. In the enchanting town of Vernal, Utah, our research team stumbled upon one such peculiar correlation that left us scratching our heads and pondering the enigmatic interplay of variables. Our investigation centered around the seemingly unrelated phenomena of the popularity of the first name "Ted" and air pollution levels in Vernal. The quaint and idyllic scenery of Vernal, with its majestic landscapes and serene atmosphere, offered the perfect backdrop for unraveling this unexpected mystery.
The study originated from a lighthearted curiosity but quickly evolved into a scientific pursuit, driven by the tantalizing prospect of uncovering a correlation that seemed as improbable as encountering a polar bear sunbathing on the equator. The unexpected merger of social nomenclature and environmental dynamics epitomized the fusion of statistical analysis and whimsy, adding an element of delight to what would have otherwise been a mundane statistical exploration.
As we delved into the depths of data sets from the United States Social Security Administration and the Environmental Protection Agency, we found ourselves embracing the inherent unpredictability of research. The initial levity of our investigation soon gave way to genuine intrigue as the numbers began to paint a peculiar picture that defied traditional expectations. The "Ted-dy Bear Effect," as we whimsically dubbed it, stood as a testament to the serendipitous nature of scientific inquiry, proving that even the most unassuming variables can harbor surprising secrets.
Our foray into the "Ted-dy Bear Effect" not only entertained our scientific curiosity but also raised thought-provoking questions about the intricate web of factors that shape air quality dynamics. The striking correlation coefficient of 0.8032710, accompanied by a statistically significant p-value of less than 0.01 for the years 2009 to 2022, added layers of intrigue to our already captivating journey. While we had initially set out to explore correlations, we found ourselves reveling in the delightful dance of teddy bears and air pollutants, an unexpected and charming intersection of human monikers and environmental phenomena.
In this paper, we invite you to join us on this whimsical scientific odyssey as we unpack the "Ted-dy Bear Effect," celebrate the curious and fascinating nature of statistical analysis, and contemplate the unforeseen connections that grace the world of research. Our findings and insights not only shed light on the peculiar relationship between the popularity of the name "Ted" and air pollution in Vernal, but also serve as an invitation to embrace the delightful surprises that await those who venture into the captivating realm of scientific exploration.
[[RESULTS]]
The results of our investigation into the whimsical "Ted-dy Bear Effect" unveiled a surprising and substantial correlation between the popularity of the first name Ted and air pollution levels in Vernal, Utah. Our statistical analysis unveiled a correlation coefficient of 0.8032710, indicating a strong positive relationship between these seemingly unrelated variables. The r-squared value of 0.6452443 further underscored the robustness of this connection, suggesting that approximately 64.5% of the variability in air pollution levels can be explained by the popularity of the name Ted. Moreover, the p-value of less than 0.01 lent statistical significance to our findings, affirming the validity of the observed relationship.
The compelling nature of our results is visually encapsulated in Figure 1, a scatterplot that vividly illustrates the pronounced association between the prevalence of the name Ted and air pollution levels in Vernal. This charming depiction of numerical aesthetics serves as a testament to the enchanting dance of data points, where the whimsical "Ted-dy Bear Effect" comes to life in the form of a graph.
Our findings, while undoubtedly entertaining, also beckon the scientific community to ponder the underlying mechanisms driving this unexpected correlation. As we wade through the lighthearted waters of statistical analysis, it becomes clear that the world of research is not without its whimsical surprises. The "Ted-dy Bear Effect" stands as a cheerful reminder that even the most unlikely variables can engage in a charming tango of correlation, urging researchers to approach scientific inquiry with both rigor and a dash of whimsy.
The implications of our discovery extend beyond the confines of statistical intrigue, prodding at the deeper mysteries of societal nomenclature and environmental dynamics. As we contemplate the allure of this serendipitous correlation, we are reminded that science, much like life, can be delightfully unpredictable and filled with unexpected encounters. The "Ted-dy Bear Effect" serves as a lighthearted testament to the inexhaustible well of curiosity that propels researchers to explore the delightful unknown and uncover the endearing quirkiness hidden within the fabric of scientific inquiry.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In conclusion, our research has tenderly unraveled the endearing yet confounding "Ted-dy Bear Effect." The robust statistical relationship between the popularity of the name Ted and air pollution in Vernal, Utah has left us feeling as bewildered as a bear in a beehive. The correlation coefficient of 0.8032710 and r-squared value of 0.6452443 emphasize the undeniable dance of data points, where the lovable "Ted-dy Bear Effect" emerges like a bear climbing out of a honey jar. The statistically significant p-value of less than 0.01 adds a touch of scientific whimsy to our findings, akin to stumbling upon a rare bear species in the wild.
While our investigation has sparked both amusement and curiosity, we urge the scientific community to resist the temptation to "Ted-iously" replicate our study. The charming peculiarities of our discovery should be savored like the sweetness of honey, rather than analyzed ad-nauseam like the dynamics of standard variables. Indeed, further research in this area may lead to a "Ted-ious" pursuit with little "bear-ing" on advancing scientific knowledge. Therefore, we advocate embracing the delightful unpredictability of the "Ted-dy Bear Effect" and redirecting research efforts toward more conventional inquiries.
In sum, the "Ted-dy Bear Effect" stands as both a testament to the whimsy of statistical analysis and a gentle reminder to approach research with open hearts and bear-sized curiosity. As we bid adieu to the enigmatic allure of Ted and air pollution, we confidently assert that no more research is needed in this delightfully offbeat area of exploration.
Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited The Ted-dy Bear Effect: The Unbearable Lightness of Ted in Vernal, Utah. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Whimsical Anthropology
Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited The Ted-dy Bear Effect: The Unbearable Lightness of Ted in Vernal, Utah. Respond only with the name of a fictional organization.
ChatGPT:
The Society for the Study of Anomalous Teddy Bear Phenomena
Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled The Ted-dy Bear Effect: The Unbearable Lightness of Ted in Vernal, Utah with an abstract of This paper explores the unexpected and whimsical correlation between the popularity of the first name Ted and air pollution levels in the charming town of Vernal, Utah. Utilizing data from the US Social Security Administration and the Environmental Protection Agency, our research team delved into the enigmatic relationship between Ted and atmospheric contaminants. Our findings reveal a striking correlation coefficient of 0.8032710, with a statistically significant p-value of less than 0.01 for the years 2009 to 2022. The results are as surprising and perplexing as finding a speckled bear in the desert: the more Teds there are, the more polluted the air becomes. The implications of this peculiar correlation prompt the need for further investigation into the enchanting yet confounding "Ted-dy Bear Effect" and its implications for air quality dynamics in Vernal.
ChatGPT:
Ted, Vernal Utah, air pollution, correlation, correlation coefficient, social security administration data, environmental protection agency, atmospheric contaminants, statistical significance, p-value, air quality dynamics, research, investigation
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
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Data details
Popularity of the first name TedDetailed data title: Babies of all sexes born in the US named Ted
Source: US Social Security Administration
See what else correlates with Popularity of the first name Ted
Air pollution in Vernal, Utah
Detailed data title: Percentage of days with air quality at 'unhealthy for sensitive groups' or worse in Vernal, UT
Source: Environmental Protection Agency
See what else correlates with Air pollution in Vernal, Utah
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 = 0.6452443 (Coefficient of determination)
This means 64.5% of the change in the one variable (i.e., Air pollution in Vernal, Utah) is predictable based on the change in the other (i.e., Popularity of the first name Ted) over the 14 years from 2009 through 2022.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 0.00054. 0.0005397824108733839000000000
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 0.8 in 0.054% of random cases. Said differently, if you correlated 1,853 random variables Which I absolutely did.
with the same 13 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 13 because we have two variables measured over a period of 14 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.
[ 0.48, 0.94 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.
This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!
All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.
Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
| 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | |
| Popularity of the first name Ted (Babies born) | 53 | 81 | 66 | 67 | 73 | 59 | 48 | 56 | 56 | 49 | 55 | 35 | 37 | 41 |
| Air pollution in Vernal, Utah (Bad air quality days) | 0.787402 | 12.8767 | 8.76712 | 4.37158 | 17.5342 | 2.19178 | 0.547945 | 3.00546 | 3.0137 | 3.0137 | 4.65753 | 0.819672 | 2.19178 | 0 |
Why this works
- Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
- Lack of causal connection: There is probably
Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied. - Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple
Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is. - Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves.
Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.
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([53,81,66,67,73,59,48,56,56,49,55,35,37,41,])
array_2 = np.array([0.787402,12.8767,8.76712,4.37158,17.5342,2.19178,0.547945,3.00546,3.0137,3.0137,4.65753,0.819672,2.19178,0,])
array_1_name = "Popularity of the first name Ted"
array_2_name = "Air pollution in Vernal, Utah"
# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)
# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)Reuseable content
You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.
For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."
When spoken, my last name is pronounced "vegan," like I don't eat meat.
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Download images for these variables:
- High resolution line chart
The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.
If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.
Alternatively you can use a tool like Inkscape. - High resolution line chart, optimized for mobile
- Alternative high resolution line chart
- Scatterplot
- Portable line chart (png)
- Portable line chart (png), optimized for mobile
- Line chart for only Popularity of the first name Ted
- Line chart for only Air pollution in Vernal, Utah
- AI-generated correlation image
- The spurious research paper: The Ted-dy Bear Effect: The Unbearable Lightness of Ted in Vernal, Utah
Your rating is much appreciated!
Correlation ID: 4585 · Black Variable ID: 4184 · Red Variable ID: 21391
