Spurious correlation #2,596 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Tristen and the second variable is Asthma attacks in American children. The chart goes from 1997 to 2019, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Tristen and the second variable is Asthma attacks in American children. The chart goes from 1997 to 2019, and the two variables track closely in value over that time.

Download png, svg

AI explanation

Fewer Tristens meant less air was being taken up by dramatic sighs, thereby reducing the overall respiratory distress in the country.

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a realistic playground scene with children playing and running around, with one child named Tristen in the center surrounded by friends and receiving lots of attention. In the background, depict a few children using inhalers, struggling to catch their breath due to asthma attacks. Ensure that the focus remains on Tristen and the interactions around him, while conveying the subtle presence of children with asthma in the background. 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 Tristen and Asthma attacks in American children. 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: Vaporwave Hyper-realistic Magic realism Low poly Realistic
ChatGPT: Realistic

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 Tristen and Asthma attacks in American children together. Keep the description simple.
ChatGPT: A playground filled with children, with one child named Tristen at the center, surrounded by friends and receiving lots of attention. In the background, a few children are seen with inhalers, struggling to catch their breath due to asthma attacks.

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: [ Realistic ] and depicting this scene: A playground filled with children, with one child named Tristen at the center, surrounded by friends and receiving lots of attention. In the background, a few children are seen with inhalers, struggling to catch their breath due to asthma attacks. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a realistic playground scene with children playing and running around, with one child named Tristen in the center surrounded by friends and receiving lots of attention. In the background, depict a few children using inhalers, struggling to catch their breath due to asthma attacks. Ensure that the focus remains on Tristen and the interactions around him, while conveying the subtle presence of children with asthma in the background.

*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.
^{Show prompt for explanation} 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 Popularity of the first name Tristen caused Asthma attacks in American children to decrease.

AI academic paper

(Because p < 0.01)

The Wheezy Woes of Tristen: A Statistical Analysis of the Link between Tristen's Popularity and Asthma Attacks in American Children

The Journal of Pediatric Palindromes

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} 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 goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Tristen and Asthma attacks in American children. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name some cartoons and childrens' shows that you watched that are related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
"The Wheezy Woes of Tristen: A Statistical Analysis of the Link between Tristen's Popularity and Asthma Attacks in American Children"

[[ABSTRACT]]
In this study, we delved into the intriguing realm of childhood asthma and the unlikely factor of first name popularity, honing in on the enigma of the name Tristen. As children across the United States wheeze their way through daily life, we set out to determine if there is a statistical association between the prevalence of the name Tristen and the exacerbation of asthma attacks. Utilizing data from the US Social Security Administration and the National Center for Health Statistics spanning the years 1997 to 2019, we embarked on a journey to uncover the potential correlation between the two. Our results revealed a correlation coefficient of 0.8854517 with a p-value of less than 0.01, shedding light on an unexpected connection.

Picture this: a Tristen with a nebulizer, or a Tristen with an inhaler - it sounds like a lyrical rhyme, but our findings suggest there may be more to it. As we wade through the data, we aim to strike a balance between levity and scholarly pursuit, holding onto the humor in the face of such an unconventional investigation. While the study invites a fair share of chuckles, the statistical significance of our findings cannot be dismissed lightly, urging us to ponder the implications and potential mechanisms behind this unlikely correlation. So, join us in this pursuit of knowledge and a sprinkle of whimsy, as we consider the wheezy woes of Tristen and their unanticipated intersection with childhood asthma.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The study of childhood asthma has long been a serious and pressing health concern, with researchers tirelessly working to identify the multitude of factors that contribute to its prevalence. However, our research takes an unexpected turn as we delve into the uncharted territory of first name popularity and its potential connection to asthma attacks in American children. It's a bit like finding a stethoscope in a hay bale - unexpected and intriguing!
As we pondered the vast landscape of potential variables, the name Tristen emerged as an unlikely candidate for investigation. Our initial reaction may have been to raise an eyebrow or let out a skeptical chuckle (insert eyebrow emoji here), but as we delved deeper, a statistical pattern began to emerge. It was like finding a spirometer in a stack of pancakes - surprising and a little bit confusing at first!
The decision to focus on the name Tristen was not without its fair share of whimsy, but as renowned scientist Dr. Seuss once said, "why fit in when you were born to stand out?" And stand out it did, as our analysis revealed a correlation coefficient of 0.8854517 and a p-value that practically waved a red flag, urging us to take a closer look. It was like uncovering a peak flow meter in a game of hide-and-seek - unexpectedly revealing and somewhat puzzling!
While the idea of a Tristen reaching for an inhaler might evoke amused disbelief, the statistical significance of our findings cannot be ignored. It's as if we discovered a peak flow meter at a comedy show - unexpected, but undeniably there! This study takes us on a journey through the intersection of whimsy and statistical significance, inviting us to ponder the peculiar connection between the name Tristen and childhood asthma. So, buckle up and prepare for a journey sprinkled with unexpected correlations and a dash of scholarly humor.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The potential link between first names and health outcomes has been a subject of curiosity and speculation for many years. In "The Correlation Conundrum" by Smith et al., the authors grapple with the perplexing notion of seemingly unrelated variables exhibiting statistical significance. It's like trying to fit a square peg into a round hole – a challenge that piques scientific skepticism and amusement in equal measure. As we dive into the literature, we find humor and inquiry intertwined, much like a questionable pun at a scientific conference.

Doe and Jones, in "Patterns in Name Popularity and Public Health," explore the unexpected interplay between nomenclature and well-being, urging readers to consider the potential impact of a name on an individual's health. It's like discovering a stethoscope in a haystack – a curious finding that prompts both intrigue and a raised eyebrow, much like a dad joke at a serious medical conference.

Turning to non-fiction books, "The Name Book" by Moss delves into the origins and meanings of names, offering a kaleidoscope of linguistic diversity. Much like a nebulizer in a sea of baby names, the book presents an array of monikers, each with its own story to tell. "Freakonomics" by Levitt and Dubner examines unconventional correlations, shedding light on unexpected relationships. It's like stumbling upon a peak flow meter in a library – an unlikely discovery that prompts raised eyebrows and further investigation.

In the fictional realm, "Breathless" by Brigid Kemmerer weaves a tale of romance and intrigue, reminiscent of the unexpected connection between Tristen and childhood asthma. It's like finding a spacer in a fairy tale – a whimsical twist that adds an element of surprise to the narrative. "The Wheezy Wizard of Oz" by L. Frank Baum offers a fanciful journey through a land of enchantment and unexpected encounters, mirroring the curious correlation we explore in this study. It's like stumbling upon an inhaler in the Emerald City – a surprising twist that adds a touch of whimsy to the tale.

In the realm of children's shows and cartoons, who can forget the iconic "Arthur," where characters navigate everyday challenges and triumphs? It's like finding a peak flow meter in the world of animation – an unexpected detail that adds a layer of intrigue to the narrative. "SpongeBob SquarePants" immerses viewers in a vibrant undersea world, much like uncovering a nebulizer in a pineapple under the sea – a whimsical discovery that sets the stage for unexpected adventures.

As we sift through the literature, it becomes evident that the intersection of first names and health outcomes is a topic ripe for exploration and a fair share of lighthearted curiosity. Just like a dad joke at a medical convention, our study dances on the edge of levity and scholarly pursuit, inviting readers to consider the unexpected connections that shape our understanding of health and well-being.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Tristen and Asthma attacks in American children. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
"The Wheezy Woes of Tristen: A Statistical Analysis of the Link between Tristen's Popularity and Asthma Attacks in American Children"

[[ABSTRACT]]
In this study, we delved into the intriguing realm of childhood asthma and the unlikely factor of first name popularity, honing in on the enigma of the name Tristen. As children across the United States wheeze their way through daily life, we set out to determine if there is a statistical association between the prevalence of the name Tristen and the exacerbation of asthma attacks. Utilizing data from the US Social Security Administration and the National Center for Health Statistics spanning the years 1997 to 2019, we embarked on a journey to uncover the potential correlation between the two. Our results revealed a correlation coefficient of 0.8854517 with a p-value of less than 0.01, shedding light on an unexpected connection.

Picture this: a Tristen with a nebulizer, or a Tristen with an inhaler - it sounds like a lyrical rhyme, but our findings suggest there may be more to it. As we wade through the data, we aim to strike a balance between levity and scholarly pursuit, holding onto the humor in the face of such an unconventional investigation. While the study invites a fair share of chuckles, the statistical significance of our findings cannot be dismissed lightly, urging us to ponder the implications and potential mechanisms behind this unlikely correlation. So, join us in this pursuit of knowledge and a sprinkle of whimsy, as we consider the wheezy woes of Tristen and their unanticipated intersection with childhood asthma.

[[LITERATURE REVIEW]]
The potential link between first names and health outcomes has been a subject of curiosity and speculation for many years. In "The Correlation Conundrum" by Smith et al., the authors grapple with the perplexing notion of seemingly unrelated variables exhibiting statistical significance. It's like trying to fit a square peg into a round hole – a challenge that piques scientific skepticism and amusement in equal measure. As we dive into the literature, we find humor and inquiry intertwined, much like a questionable pun at a scientific conference.
Doe and Jones, in "Patterns in Name Popularity and Public Health," explore the unexpected interplay between nomenclature and well-being, urging readers to consider the potential impact of a name on an individual's health. It's like discovering a stethoscope in a haystack – a curious finding that prompts both intrigue and a raised eyebrow, much like a dad joke at a serious medical conference.
Turning to non-fiction books, "The Name Book" by Moss delves into the origins and meanings of names, offering a kaleidoscope of linguistic diversity. Much like a nebulizer in a sea of baby names, the book presents an array of monikers, each with its own story to tell. "Freakonomics" by Levitt and Dubner examines unconventional correlations, shedding light on unexpected relationships. It's like stumbling upon a peak flow meter in a library – an unlikely discovery that prompts raised eyebrows and further investigation.
In the fictional realm, "Breathless" by Brigid Kemmerer weaves a tale of romance and intrigue, reminiscent of the unexpected connection between Tristen and childhood asthma. It's like finding a spacer in a fairy tale – a whimsical twist that adds an element of surprise to the narrative. "The Wheezy Wizard of Oz" by L. Frank Baum offers a fanciful journey through a land of enchantment and unexpected encounters, mirroring the curious correlation we explore in this study. It's like stumbling upon an inhaler in the Emerald City – a surprising twist that adds a touch of whimsy to the tale.
In the realm of children's shows and cartoons, who can forget the iconic "Arthur," where characters navigate everyday challenges and triumphs? It's like finding a peak flow meter in the world of animation – an unexpected detail that adds a layer of intrigue to the narrative. "SpongeBob SquarePants" immerses viewers in a vibrant undersea world, much like uncovering a nebulizer in a pineapple under the sea – a whimsical discovery that sets the stage for unexpected adventures.
As we sift through the literature, it becomes evident that the intersection of first names and health outcomes is a topic ripe for exploration and a fair share of lighthearted curiosity. Just like a dad joke at a medical convention, our study dances on the edge of levity and scholarly pursuit, inviting readers to consider the unexpected connections that shape our understanding of health and well-being.

[[RESULTS]]
The analysis of the data collected from the US Social Security Administration and the National Center for Health Statistics revealed a striking correlation between the popularity of the first name Tristen and asthma attacks in American children. The correlation coefficient, a staggering 0.8854517, indicated a remarkably strong relationship between these seemingly unrelated variables. It's as if naming a child Tristen puts them on the fast track to asthma attacks - talk about an unexpected plot twist!
Furthermore, the coefficient of determination (r-squared) was calculated to be 0.7840248, suggesting that a whopping 78.4% of the variation in asthma attacks can be explained by the popularity of the name Tristen. That’s right, it’s like saying “78.4% of the time, naming your kid Tristen may lead to wheezy troubles.”
The inferential statistics also painted a compelling picture, with a p-value of less than 0.01. For those unfamiliar with statistical lingo, this essentially means that the likelihood of this connection being due to mere chance is about as rare as finding a unicorn in a cornfield. In other words, our data provides robust evidence that there is, indeed, a significant association between the name Tristen and childhood asthma.
Fig. 1 (to be included) presents a scatterplot illustrating the remarkably strong positive correlation between the popularity of the name Tristen and the incidence of asthma attacks in American children. It's like a map showing the direct route from “Tristen” to “Trouble Breathing Lane.”
In summary, our findings unveil an unexpected link between the popularity of the name Tristen and childhood asthma, prompting further inquiry into the potential mechanisms underlying this peculiar association. As we navigate the realms of statistics and whimsy, our study sheds light on the wheezy woes of Tristen, inviting a new perspective on the factors influencing childhood asthma. It seems that when it comes to this particular name, there may be more than meets the eye, or the airways for that matter!

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The results of our study unequivocally support the prior research that delved into the unexpected connections between nomenclature and health outcomes. Our findings soar off the pages of statistical analyses, like a dad joke at a scientific symposium – simultaneously surprising and thought-provoking. The correlation coefficient of 0.8854517 that we uncovered is as robust as a double-double cheeseburger order at a fast-food drive-thru. It's clear that there's more to the name Tristen than meets the eye, just like finding a stethoscope in a haystack – an unexpected discovery that prompts both intrigue and a raised eyebrow, much like a dad joke at a serious medical conference.

Our study holds significant implications for public health and underscores the importance of considering unexpected factors in the realm of childhood asthma. The statistical evidence firmly points to a substantial association between the popularity of the name Tristen and asthma attacks in American children. It's like stumbling upon a peak flow meter in a library – an unlikely discovery that prompts raised eyebrows and further investigation. Our results exude robustness, warranting serious consideration and further exploration of the potential mechanisms underlying this curious correlation.

The coefficient of determination (r-squared) of 0.7840248 further solidifies the strength of the relationship between the name Tristen and childhood asthma. It's as if naming a child Tristen puts them on the fast track to asthma attacks – talk about an unexpected plot twist! The inferential statistics, with a p-value of less than 0.01, offered resounding support for the statistical significance of our findings. This essentially means that the likelihood of this connection being due to mere chance is about as rare as finding a unicorn in a cornfield. In other words, our data provides robust evidence that there is, indeed, a significant association between the name Tristen and childhood asthma – it's like encountering a nebulizer in a sea of baby names, prompting a moment of awe and curiosity.

As we navigate the landscape of statistical analyses and whimsy, our study highlights the need for continued exploration and consideration of unconventional factors in health outcomes. It seems that when it comes to the name Tristen, there may be more than meets the eye, or the airways for that matter – cue the parental chuckles as they ponder future baby names. Our findings lay the groundwork for future research endeavors and open avenues for understanding the wheezy woes of Tristen from a new perspective – much like a stethoscope in a haystack, prompting both intrigue and curiosity in equal measure.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Tristen and Asthma attacks in American children. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
"The Wheezy Woes of Tristen: A Statistical Analysis of the Link between Tristen's Popularity and Asthma Attacks in American Children"

[[ABSTRACT]]
In this study, we delved into the intriguing realm of childhood asthma and the unlikely factor of first name popularity, honing in on the enigma of the name Tristen. As children across the United States wheeze their way through daily life, we set out to determine if there is a statistical association between the prevalence of the name Tristen and the exacerbation of asthma attacks. Utilizing data from the US Social Security Administration and the National Center for Health Statistics spanning the years 1997 to 2019, we embarked on a journey to uncover the potential correlation between the two. Our results revealed a correlation coefficient of 0.8854517 with a p-value of less than 0.01, shedding light on an unexpected connection.

Picture this: a Tristen with a nebulizer, or a Tristen with an inhaler - it sounds like a lyrical rhyme, but our findings suggest there may be more to it. As we wade through the data, we aim to strike a balance between levity and scholarly pursuit, holding onto the humor in the face of such an unconventional investigation. While the study invites a fair share of chuckles, the statistical significance of our findings cannot be dismissed lightly, urging us to ponder the implications and potential mechanisms behind this unlikely correlation. So, join us in this pursuit of knowledge and a sprinkle of whimsy, as we consider the wheezy woes of Tristen and their unanticipated intersection with childhood asthma.

[[INTRDUCTION]]
The study of childhood asthma has long been a serious and pressing health concern, with researchers tirelessly working to identify the multitude of factors that contribute to its prevalence. However, our research takes an unexpected turn as we delve into the uncharted territory of first name popularity and its potential connection to asthma attacks in American children. It's a bit like finding a stethoscope in a hay bale - unexpected and intriguing!
As we pondered the vast landscape of potential variables, the name Tristen emerged as an unlikely candidate for investigation. Our initial reaction may have been to raise an eyebrow or let out a skeptical chuckle (insert eyebrow emoji here), but as we delved deeper, a statistical pattern began to emerge. It was like finding a spirometer in a stack of pancakes - surprising and a little bit confusing at first!
The decision to focus on the name Tristen was not without its fair share of whimsy, but as renowned scientist Dr. Seuss once said, "why fit in when you were born to stand out?" And stand out it did, as our analysis revealed a correlation coefficient of 0.8854517 and a p-value that practically waved a red flag, urging us to take a closer look. It was like uncovering a peak flow meter in a game of hide-and-seek - unexpectedly revealing and somewhat puzzling!
While the idea of a Tristen reaching for an inhaler might evoke amused disbelief, the statistical significance of our findings cannot be ignored. It's as if we discovered a peak flow meter at a comedy show - unexpected, but undeniably there! This study takes us on a journey through the intersection of whimsy and statistical significance, inviting us to ponder the peculiar connection between the name Tristen and childhood asthma. So, buckle up and prepare for a journey sprinkled with unexpected correlations and a dash of scholarly humor.

[[RESULTS]]
The analysis of the data collected from the US Social Security Administration and the National Center for Health Statistics revealed a striking correlation between the popularity of the first name Tristen and asthma attacks in American children. The correlation coefficient, a staggering 0.8854517, indicated a remarkably strong relationship between these seemingly unrelated variables. It's as if naming a child Tristen puts them on the fast track to asthma attacks - talk about an unexpected plot twist!
Furthermore, the coefficient of determination (r-squared) was calculated to be 0.7840248, suggesting that a whopping 78.4% of the variation in asthma attacks can be explained by the popularity of the name Tristen. That’s right, it’s like saying “78.4% of the time, naming your kid Tristen may lead to wheezy troubles.”
The inferential statistics also painted a compelling picture, with a p-value of less than 0.01. For those unfamiliar with statistical lingo, this essentially means that the likelihood of this connection being due to mere chance is about as rare as finding a unicorn in a cornfield. In other words, our data provides robust evidence that there is, indeed, a significant association between the name Tristen and childhood asthma.
Fig. 1 (to be included) presents a scatterplot illustrating the remarkably strong positive correlation between the popularity of the name Tristen and the incidence of asthma attacks in American children. It's like a map showing the direct route from “Tristen” to “Trouble Breathing Lane.”
In summary, our findings unveil an unexpected link between the popularity of the name Tristen and childhood asthma, prompting further inquiry into the potential mechanisms underlying this peculiar association. As we navigate the realms of statistics and whimsy, our study sheds light on the wheezy woes of Tristen, inviting a new perspective on the factors influencing childhood asthma. It seems that when it comes to this particular name, there may be more than meets the eye, or the airways for that matter!

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has harnessed the power of statistical analysis to reveal a surprising correlation between the prevalence of the first name Tristen and childhood asthma attacks. It's like doing a DNA test and finding out that your genealogy leads straight to the Department of Respiratory Issues - talk about a twist in the family tree! Our findings, with a correlation coefficient that practically raised its hand and said “pick me!”, along with a p-value lower than an underground mole's living quarters, make a compelling case for the association between Tristen and wheezy woes.

As we reflect on the implications of our research, it’s important to consider the potential real-world impact of our findings. Perhaps parents-to-be will think twice before bestowing the name Tristen upon their bundle of joy, just to err on the side of caution. After all, it's like choosing between “Asthma Avenue” and “Easy Breathing Boulevard” in the neighborhood of baby names.

In the grand scheme of scientific endeavors, our study may seem like an oddball in the realm of childhood asthma research, but it just goes to show that sometimes the most unexpected leads can unravel puzzling mysteries. So, let’s raise our peak flow meters to the wheezy woes of Tristen, and the whimsical revelations they bring to the table. It’s like a breath of fresh air in the world of research – pun intended!

In light of our significant findings, we confidently assert that further research in this area may yield diminishing returns, much like trying to find the best pun after making the peak flow meter joke. No need to beat that dead horse – or should we say, overinflate that lung capacity? It’s time for our research to take a deep breath and call it a day. As we exhale our conclusions, let’s bid adieu to the wheezy whims of Tristen’s saga in the realm of childhood asthma – case closed!

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 Wheezy Woes of Tristen: A Statistical Analysis of the Link between Tristen's Popularity and Asthma Attacks in American Children. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Pediatric Palindromes

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 Wheezy Woes of Tristen: A Statistical Analysis of the Link between Tristen's Popularity and Asthma Attacks in American Children. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Whimsical Health Studies

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled The Wheezy Woes of Tristen: A Statistical Analysis of the Link between Tristen's Popularity and Asthma Attacks in American Children with an abstract of In this study, we delved into the intriguing realm of childhood asthma and the unlikely factor of first name popularity, honing in on the enigma of the name Tristen. As children across the United States wheeze their way through daily life, we set out to determine if there is a statistical association between the prevalence of the name Tristen and the exacerbation of asthma attacks. Utilizing data from the US Social Security Administration and the National Center for Health Statistics spanning the years 1997 to 2019, we embarked on a journey to uncover the potential correlation between the two. Our results revealed a correlation coefficient of 0.8854517 with a p-value of less than 0.01, shedding light on an unexpected connection.
Picture this: a Tristen with a nebulizer, or a Tristen with an inhaler - it sounds like a lyrical rhyme, but our findings suggest there may be more to it. As we wade through the data, we aim to strike a balance between levity and scholarly pursuit, holding onto the humor in the face of such an unconventional investigation. While the study invites a fair share of chuckles, the statistical significance of our findings cannot be dismissed lightly, urging us to ponder the implications and potential mechanisms behind this unlikely correlation. So, join us in this pursuit of knowledge and a sprinkle of whimsy, as we consider the wheezy woes of Tristen and their unanticipated intersection with childhood asthma.

ChatGPT:

Tristen, childhood asthma, first name popularity, statistical analysis, US Social Security Administration, National Center for Health Statistics, asthma attacks, correlation coefficient, p-value, United States, American children, asthma exacerbation, Tristen's popularity

*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 Tristen
Detailed data title: Babies of all sexes born in the US named Tristen
Source: US Social Security Administration
See what else correlates with Popularity of the first name Tristen

Asthma attacks in American children
Detailed data title: Percent of children in the US who have had an asthma attack in the past year
Source: National Center for Health Statistics
See what else correlates with Asthma attacks in American children

Correlation r = 0.8854517 (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 = 0.7840248 (Coefficient of determination)
This means 78.4% of the change in the one variable (i.e., Asthma attacks in American children) is predictable based on the change in the other (i.e., Popularity of the first name Tristen) over the 23 years from 1997 through 2019.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.0E-8.^Show 0.0000000197092815885450660000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note 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 0.89 in 2.0E-6% of random cases. Said differently, if you correlated 50,737,517 random variables^Note You don't actually need 50 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 22 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 22 because we have two variables measured over a period of 23 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.

[ 0.75, 0.95 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} 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: ^Note 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.

	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019
Popularity of the first name Tristen (Babies born)	1307	1241	990	1036	1096	1094	1094	1128	1030	1089	1073	1081	1141	1009	914	905	680	596	449	445	405	341	274
Asthma attacks in American children (Percent of children)	5.5	5.3	5.3	5.5	5.7	5.8	5.5	5.5	5.2	5.6	5.2	5.6	5.5	5.7	5.5	5.4	4.9	4.3	4.2	4.7	4.6	4.3	3.3

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^Note 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^Note 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. ^Note 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. ^{Show the steps to do this.} 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([1307,1241,990,1036,1096,1094,1094,1128,1030,1089,1073,1081,1141,1009,914,905,680,596,449,445,405,341,274,])
array_2 = np.array([5.5,5.3,5.3,5.5,5.7,5.8,5.5,5.5,5.2,5.6,5.2,5.6,5.5,5.7,5.5,5.4,4.9,4.3,4.2,4.7,4.6,4.3,3.3,])
array_1_name = "Popularity of the first name Tristen"
array_2_name = "Asthma attacks in American children"

# 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. ^Note 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.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note 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 Tristen
Line chart for only Asthma attacks in American children
AI-generated correlation image
The spurious research paper: The Wheezy Woes of Tristen: A Statistical Analysis of the Link between Tristen's Popularity and Asthma Attacks in American Children

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Correlation ID: 2596 · Black Variable ID: 2388 · Red Variable ID: 1141


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