about · email me · subscribe
Spurious correlation #2,303 · 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 Shaun and the second variable is Arson in Arizona.  The chart goes from 1985 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

The fewer Shauns there were, the less "on the lawn" mischief there was, leading to a reduction in Arizona's arson incidents. With fewer Shauns pulling pranks, the state could breathe a little easier, or should I say, not as easily ignited!

Model: dalle-3
Prompt: Create an image of a vibrant Arizona town scene with a focus on "Shaun's Tacos" food truck as the central point of interest. The bustling atmosphere should feature colorful characters gathered around the food truck, with anticipation and enthusiasm evident on their faces. In the background, show firefighters swiftly handling a small fire set by an arsonist, emphasizing the sense of urgency and action. The scene should be visually captivating, capturing the contrasting energy of enjoyment and urgency present in the Arizona town. 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 Shaun and Arson in Arizona. 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: Low poly Celtic art Cubism Parallax art Symbolism
ChatGPT: N/A

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 Shaun and Arson in Arizona together. Keep the description simple.
ChatGPT: In a bustling Arizona town, a group of people gather eagerly around a popular food truck adorned with the name "Shaun's Tacos." Nearby, firefighters work quickly to extinguish a small fire that has been set by an arsonist, while concerned onlookers watch from a safe distance.

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: [ N/A ] and depicting this scene: In a bustling Arizona town, a group of people gather eagerly around a popular food truck adorned with the name "Shaun's Tacos." Nearby, firefighters work quickly to extinguish a small fire that has been set by an arsonist, while concerned onlookers watch from a safe distance. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of a vibrant Arizona town scene with a focus on "Shaun's Tacos" food truck as the central point of interest. The bustling atmosphere should feature colorful characters gathered around the food truck, with anticipation and enthusiasm evident on their faces. In the background, show firefighters swiftly handling a small fire set by an arsonist, emphasizing the sense of urgency and action. The scene should be visually captivating, capturing the contrasting energy of enjoyment and urgency present in the Arizona town.

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

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

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how a decrease in Popularity of the first name Shaun caused Arson in Arizona to decrease.

AI academic paper

(Because p < 0.01)
Playing with Fire: The Shaun-arson Connection in Arizona

The Journal of Pyrological Psychology

Jan 2024

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




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

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Popularity of the first name Shaun and Arson in Arizona. 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 FBI Criminal Justice Information Services to assess this nagging question. You found a correlation coefficient of 0.9189290 and p < 0.01 for 1985 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]]
Playing with Fire: The Shaun-arson Connection in Arizona

[[ABSTRACT]]
This study aims to investigate the potential relationship between the popularity of the first name "Shaun" and the incidence of arson in the state of Arizona. Drawing from data provided by the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted a thorough analysis covering the years 1985 to 2022. Our findings revealed a remarkably high correlation coefficient of 0.9189290, with statistical significance at p < 0.01, suggesting a strong association between the prevalence of the name "Shaun" and arson occurrences in the state. While the exact mechanisms underlying this association remain elusive, the results impart a newfound appreciation for the impact of nomenclature on delinquent behavior. Our study underscores the importance of considering unconventional factors in the investigation of criminal activities and sparks further scholarly inquiry into the peculiar interplay between nomenclature and unlawful conduct.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the introduction section of an academic research paper presenting the findings of the connection between Popularity of the first name Shaun and Arson in Arizona. 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]]
Playing with Fire: The Shaun-arson Connection in Arizona

[[ABSTRACT]]
This study aims to investigate the potential relationship between the popularity of the first name "Shaun" and the incidence of arson in the state of Arizona. Drawing from data provided by the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted a thorough analysis covering the years 1985 to 2022. Our findings revealed a remarkably high correlation coefficient of 0.9189290, with statistical significance at p < 0.01, suggesting a strong association between the prevalence of the name "Shaun" and arson occurrences in the state. While the exact mechanisms underlying this association remain elusive, the results impart a newfound appreciation for the impact of nomenclature on delinquent behavior. Our study underscores the importance of considering unconventional factors in the investigation of criminal activities and sparks further scholarly inquiry into the peculiar interplay between nomenclature and unlawful conduct.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The etymology of names has long been a subject of intrigue, encompassing both linguistic and sociocultural dimensions. Within the realm of statistical analysis, the investigation of names in relation to various phenomena has ventured into territory as diverse as the names themselves. In this vein, the present study seeks to unravel the enigmatic correlation between the prevalence of the first name "Shaun" and the incidence of arson in the state of Arizona. Despite its seemingly whimsical nature, one cannot help but ponder the potential impact of nomenclature on criminal proclivity. Are there hidden sparks within the cultural fabric that ignite the flames of unlawful behavior, or is the connection merely a statistical anomaly flickering in the winds of chance?

Fueled by the burgeoning availability of data and the passion for uncovering unexpected associations, our research team embarked on a quest to decipher the tangled web of nomenclature and delinquency. Leveraging information from the US Social Security Administration and the FBI Criminal Justice Information Services, we undertook a meticulous analysis spanning nearly four decades. The resulting revelations, laced with statistical significance and phenomenological peculiarity, set ablaze the notion that a name is merely an innocuous label.

As we delve into the labyrinthine world of statistical analysis, it is impossible to overlook the sparks of curiosity that ignite the flames of investigation. Our quest for understanding leads us to question not only the peculiar connection between the name "Shaun" and arson, but also the broader implications for our understanding of criminal behavior. How might the embers of nomenclature kindle the fires of deviance, and what unforeseen variables lurk amidst the smoke and mirrors of statistical inference? With these questions smoldering at the periphery of empirical inquiry, we cast our wide net of analysis into the vast expanse of data, seeking to shed light on this curious conflagration of nomenclature and criminality.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Popularity of the first name Shaun and Arson in Arizona. 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 some cartoons and childrens' shows that you watched that are related to the topic.

Here is the title and abstract of the paper:
[[TITLE]]
Playing with Fire: The Shaun-arson Connection in Arizona

[[ABSTRACT]]
This study aims to investigate the potential relationship between the popularity of the first name "Shaun" and the incidence of arson in the state of Arizona. Drawing from data provided by the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted a thorough analysis covering the years 1985 to 2022. Our findings revealed a remarkably high correlation coefficient of 0.9189290, with statistical significance at p < 0.01, suggesting a strong association between the prevalence of the name "Shaun" and arson occurrences in the state. While the exact mechanisms underlying this association remain elusive, the results impart a newfound appreciation for the impact of nomenclature on delinquent behavior. Our study underscores the importance of considering unconventional factors in the investigation of criminal activities and sparks further scholarly inquiry into the peculiar interplay between nomenclature and unlawful conduct.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The etymology of names has long been a subject of intrigue, encompassing both linguistic and sociocultural dimensions. Within the realm of statistical analysis, the investigation of names in relation to various phenomena has ventured into territory as diverse as the names themselves. In this vein, the present study seeks to unravel the enigmatic correlation between the prevalence of the first name "Shaun" and the incidence of arson in the state of Arizona. Despite its seemingly whimsical nature, one cannot help but ponder the potential impact of nomenclature on criminal proclivity. Are there hidden sparks within the cultural fabric that ignite the flames of unlawful behavior, or is the connection merely a statistical anomaly flickering in the winds of chance?
Fueled by the burgeoning availability of data and the passion for uncovering unexpected associations, our research team embarked on a quest to decipher the tangled web of nomenclature and delinquency. Leveraging information from the US Social Security Administration and the FBI Criminal Justice Information Services, we undertook a meticulous analysis spanning nearly four decades. The resulting revelations, laced with statistical significance and phenomenological peculiarity, set ablaze the notion that a name is merely an innocuous label.
As we delve into the labyrinthine world of statistical analysis, it is impossible to overlook the sparks of curiosity that ignite the flames of investigation. Our quest for understanding leads us to question not only the peculiar connection between the name "Shaun" and arson, but also the broader implications for our understanding of criminal behavior. How might the embers of nomenclature kindle the fires of deviance, and what unforeseen variables lurk amidst the smoke and mirrors of statistical inference? With these questions smoldering at the periphery of empirical inquiry, we cast our wide net of analysis into the vast expanse of data, seeking to shed light on this curious conflagration of nomenclature and criminality.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

Our investigation into the relationship between the prevalence of the first name "Shaun" and the incidence of arson in Arizona was ignited by a series of scholarly works that sought to illuminate the influence of names on societal phenomena. Smith, in "The Namesake's Impact: Uncovering Hidden Connections," delved into the nexus of nomenclature and behavior, presenting compelling theories that kindle curiosity about the potential impact of names on individual life paths. Meanwhile, Doe, in "Monikers and Misdeeds: A Statistical Inquiry," embarked on a meticulous exploration of the association between names and criminal activities, albeit stopping short of igniting any definite conclusions.

The literary blaze of our inquiry was further fueled by Jones, whose work "Title TBD" kindled our curiosity with a wide-ranging investigation into the idiosyncrasies of names and their resonance within societal trends.

Venturing beyond the academic realm, our curiosity was piqued by the non-fiction works "The Fire Within: Understanding Pyromania" by John Blaze and "Red, Hot, and Blue: The Psychology of Arsonists" by B. A. Burn. These scorching texts provided invaluable insights into the psychological underpinnings of incendiary behavior, albeit from a perspective not directly correlated with nomenclature.

In the realm of fiction, we found ourselves drawn to "The Arsonist's Apprentice" by Lucy Combustion and "Kindling Hearts: A Love Story Set Ablaze" by Blaze Kindle. While these works did not directly address the Shaun-arson connection, they certainly stoked the flames of our imagination.

Our literature review then took an unexpected turn as we stumbled into the whimsical world of cartoons and children's shows. The fiery escapades of "The Adventures of Shaun the Sheep" and "Shaun the Firefighter" provided lighthearted entertainment, albeit with no substantial insights into the perplexing Shaun-arson correlation. However, the suggestive nature of the titles could not be overlooked, leaving a lingering ember of curiosity in our analytical pursuits.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Popularity of the first name Shaun and Arson in Arizona. 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 FBI Criminal Justice Information Services . You used data from 1985 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]]
Playing with Fire: The Shaun-arson Connection in Arizona

[[ABSTRACT]]
This study aims to investigate the potential relationship between the popularity of the first name "Shaun" and the incidence of arson in the state of Arizona. Drawing from data provided by the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted a thorough analysis covering the years 1985 to 2022. Our findings revealed a remarkably high correlation coefficient of 0.9189290, with statistical significance at p < 0.01, suggesting a strong association between the prevalence of the name "Shaun" and arson occurrences in the state. While the exact mechanisms underlying this association remain elusive, the results impart a newfound appreciation for the impact of nomenclature on delinquent behavior. Our study underscores the importance of considering unconventional factors in the investigation of criminal activities and sparks further scholarly inquiry into the peculiar interplay between nomenclature and unlawful conduct.

[[INTRODUCTION]]
The etymology of names has long been a subject of intrigue, encompassing both linguistic and sociocultural dimensions. Within the realm of statistical analysis, the investigation of names in relation to various phenomena has ventured into territory as diverse as the names themselves. In this vein, the present study seeks to unravel the enigmatic correlation between the prevalence of the first name "Shaun" and the incidence of arson in the state of Arizona. Despite its seemingly whimsical nature, one cannot help but ponder the potential impact of nomenclature on criminal proclivity. Are there hidden sparks within the cultural fabric that ignite the flames of unlawful behavior, or is the connection merely a statistical anomaly flickering in the winds of chance?
Fueled by the burgeoning availability of data and the passion for uncovering unexpected associations, our research team embarked on a quest to decipher the tangled web of nomenclature and delinquency. Leveraging information from the US Social Security Administration and the FBI Criminal Justice Information Services, we undertook a meticulous analysis spanning nearly four decades. The resulting revelations, laced with statistical significance and phenomenological peculiarity, set ablaze the notion that a name is merely an innocuous label.
As we delve into the labyrinthine world of statistical analysis, it is impossible to overlook the sparks of curiosity that ignite the flames of investigation. Our quest for understanding leads us to question not only the peculiar connection between the name "Shaun" and arson, but also the broader implications for our understanding of criminal behavior. How might the embers of nomenclature kindle the fires of deviance, and what unforeseen variables lurk amidst the smoke and mirrors of statistical inference? With these questions smoldering at the periphery of empirical inquiry, we cast our wide net of analysis into the vast expanse of data, seeking to shed light on this curious conflagration of nomenclature and criminality.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To kindle the flames of understanding in our investigation, our research team employed a multifaceted methodology to unearth the potential connection between the popularity of the first name "Shaun" and instances of arson in Arizona. Drawing from the troves of data provided by the US Social Security Administration and the FBI Criminal Justice Information Services, our endeavor can be likened to stirring a cauldron of statistical alchemy.

Firstly, we waved our magic wand that is data collection and harnessed records spanning from 1985 to 2022, carefully tending to every data point as if they were precious embers waiting to ignite a hypothesis. The abundance of data allowed us to stoke the flames of statistical significance within our analysis, ensuring that our findings would not fizzle out like a faulty Bunsen burner.

Next, we conjured the spirits of correlation and regression analysis to scrutinize the potential relationship between the name "Shaun" and arson occurrences in Arizona. Our chi-squared statistical tests acted as spells to decipher whether the observed connection was more than a mere hocus-pocus. We utilized a range of statistical tools reminiscent of a wizard's arsenal, including t-tests, ANOVA, and logistic regression, to unveil the true nature of the association, skirting the line between knowable causality and mystical coincidence.

Additionally, we danced around the bonfire of controls and covariates, ensuring that we did not neglect the myriad factors that could dim the brightness of our findings. Demographic variables such as age, gender, and socioeconomic status were stirred into the cauldron to illuminate the potential confounding shadows that might otherwise distort our understanding of the Shaun-arson relationship.

Lastly, we invoked the spirits of significance and systematic uncertainty by subjecting our findings to the crucible of rigorous statistical inference. The flames of hypothesis testing were diligently tended to, ensuring that our conclusions were not mere will-o'-the-wisps leading us astray in the murky marshes of empirical inquiry.

In short, our methodology embodied the spirit of scientific rigor while maintaining a certain flair for the arcane, weaving together data, statistical analyses, and a dash of enchantment to unravel the enigmatic connection between the name "Shaun" and arson in the arid plains of Arizona.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the results section of an academic research paper presenting the findings of the connection between Popularity of the first name Shaun and Arson in Arizona. 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 FBI Criminal Justice Information Services .

For the time period 1985 to 2022, you found a correlation 0.9189290, r-squared of 0.8444306, 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]]
Playing with Fire: The Shaun-arson Connection in Arizona

[[ABSTRACT]]
This study aims to investigate the potential relationship between the popularity of the first name "Shaun" and the incidence of arson in the state of Arizona. Drawing from data provided by the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted a thorough analysis covering the years 1985 to 2022. Our findings revealed a remarkably high correlation coefficient of 0.9189290, with statistical significance at p < 0.01, suggesting a strong association between the prevalence of the name "Shaun" and arson occurrences in the state. While the exact mechanisms underlying this association remain elusive, the results impart a newfound appreciation for the impact of nomenclature on delinquent behavior. Our study underscores the importance of considering unconventional factors in the investigation of criminal activities and sparks further scholarly inquiry into the peculiar interplay between nomenclature and unlawful conduct.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The etymology of names has long been a subject of intrigue, encompassing both linguistic and sociocultural dimensions. Within the realm of statistical analysis, the investigation of names in relation to various phenomena has ventured into territory as diverse as the names themselves. In this vein, the present study seeks to unravel the enigmatic correlation between the prevalence of the first name "Shaun" and the incidence of arson in the state of Arizona. Despite its seemingly whimsical nature, one cannot help but ponder the potential impact of nomenclature on criminal proclivity. Are there hidden sparks within the cultural fabric that ignite the flames of unlawful behavior, or is the connection merely a statistical anomaly flickering in the winds of chance?
Fueled by the burgeoning availability of data and the passion for uncovering unexpected associations, our research team embarked on a quest to decipher the tangled web of nomenclature and delinquency. Leveraging information from the US Social Security Administration and the FBI Criminal Justice Information Services, we undertook a meticulous analysis spanning nearly four decades. The resulting revelations, laced with statistical significance and phenomenological peculiarity, set ablaze the notion that a name is merely an innocuous label.
As we delve into the labyrinthine world of statistical analysis, it is impossible to overlook the sparks of curiosity that ignite the flames of investigation. Our quest for understanding leads us to question not only the peculiar connection between the name "Shaun" and arson, but also the broader implications for our understanding of criminal behavior. How might the embers of nomenclature kindle the fires of deviance, and what unforeseen variables lurk amidst the smoke and mirrors of statistical inference? With these questions smoldering at the periphery of empirical inquiry, we cast our wide net of analysis into the vast expanse of data, seeking to shed light on this curious conflagration of nomenclature and criminality.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The analysis of the data spanning 1985 to 2022 revealed a striking correlation between the prevalence of the first name "Shaun" and the incidence of arson in the state of Arizona. The correlation coefficient of 0.9189290, combined with an r-squared value of 0.8444306, solidifies the robust relationship between these seemingly disparate variables. With a p-value of less than 0.01, the statistical significance of this association blazes like a bonfire in the realm of empirical inquiry.

Fig. 1 presents a scatterplot illustrating the compelling link between the popularity of the name "Shaun" and the incidence of arson in Arizona. The plot paints a vivid picture of the confluence of these variables, leaving no doubt about the intensity of their relationship. One cannot help but warm up to the idea that there might be a fiery connection between nomenclature and incendiary acts, igniting both intrigue and amusement within the scientific community.

These findings kindle a fervent interest in the underlying mechanisms governing the Shaun-arson connection, stoking the flames of curiosity within the scientific community. The notion that a simple name could kindle the flames of criminal behavior serves as a testament to the intricate interplay of human behavior and nomenclature. As we sift through the ashes of this remarkable correlation, it becomes increasingly apparent that the world of statistical analysis is not devoid of surprises, and that even the most unlikely variables may fuel the fires of empirical discovery.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Popularity of the first name Shaun and Arson in Arizona. 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]]
Playing with Fire: The Shaun-arson Connection in Arizona

[[ABSTRACT]]
This study aims to investigate the potential relationship between the popularity of the first name "Shaun" and the incidence of arson in the state of Arizona. Drawing from data provided by the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted a thorough analysis covering the years 1985 to 2022. Our findings revealed a remarkably high correlation coefficient of 0.9189290, with statistical significance at p < 0.01, suggesting a strong association between the prevalence of the name "Shaun" and arson occurrences in the state. While the exact mechanisms underlying this association remain elusive, the results impart a newfound appreciation for the impact of nomenclature on delinquent behavior. Our study underscores the importance of considering unconventional factors in the investigation of criminal activities and sparks further scholarly inquiry into the peculiar interplay between nomenclature and unlawful conduct.

[[LITERATURE REVIEW]]
Our investigation into the relationship between the prevalence of the first name "Shaun" and the incidence of arson in Arizona was ignited by a series of scholarly works that sought to illuminate the influence of names on societal phenomena. Smith, in "The Namesake's Impact: Uncovering Hidden Connections," delved into the nexus of nomenclature and behavior, presenting compelling theories that kindle curiosity about the potential impact of names on individual life paths. Meanwhile, Doe, in "Monikers and Misdeeds: A Statistical Inquiry," embarked on a meticulous exploration of the association between names and criminal activities, albeit stopping short of igniting any definite conclusions.
The literary blaze of our inquiry was further fueled by Jones, whose work "Title TBD" kindled our curiosity with a wide-ranging investigation into the idiosyncrasies of names and their resonance within societal trends.
Venturing beyond the academic realm, our curiosity was piqued by the non-fiction works "The Fire Within: Understanding Pyromania" by John Blaze and "Red, Hot, and Blue: The Psychology of Arsonists" by B. A. Burn. These scorching texts provided invaluable insights into the psychological underpinnings of incendiary behavior, albeit from a perspective not directly correlated with nomenclature.
In the realm of fiction, we found ourselves drawn to "The Arsonist's Apprentice" by Lucy Combustion and "Kindling Hearts: A Love Story Set Ablaze" by Blaze Kindle. While these works did not directly address the Shaun-arson connection, they certainly stoked the flames of our imagination.
Our literature review then took an unexpected turn as we stumbled into the whimsical world of cartoons and children's shows. The fiery escapades of "The Adventures of Shaun the Sheep" and "Shaun the Firefighter" provided lighthearted entertainment, albeit with no substantial insights into the perplexing Shaun-arson correlation. However, the suggestive nature of the titles could not be overlooked, leaving a lingering ember of curiosity in our analytical pursuits.

[[RESULTS]]
The analysis of the data spanning 1985 to 2022 revealed a striking correlation between the prevalence of the first name "Shaun" and the incidence of arson in the state of Arizona. The correlation coefficient of 0.9189290, combined with an r-squared value of 0.8444306, solidifies the robust relationship between these seemingly disparate variables. With a p-value of less than 0.01, the statistical significance of this association blazes like a bonfire in the realm of empirical inquiry.
Fig. 1 presents a scatterplot illustrating the compelling link between the popularity of the name "Shaun" and the incidence of arson in Arizona. The plot paints a vivid picture of the confluence of these variables, leaving no doubt about the intensity of their relationship. One cannot help but warm up to the idea that there might be a fiery connection between nomenclature and incendiary acts, igniting both intrigue and amusement within the scientific community.
These findings kindle a fervent interest in the underlying mechanisms governing the Shaun-arson connection, stoking the flames of curiosity within the scientific community. The notion that a simple name could kindle the flames of criminal behavior serves as a testament to the intricate interplay of human behavior and nomenclature. As we sift through the ashes of this remarkable correlation, it becomes increasingly apparent that the world of statistical analysis is not devoid of surprises, and that even the most unlikely variables may fuel the fires of empirical discovery.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The scorching findings of our study have set the stage for an animated discussion of the Shaun-arson connection, igniting a fervor for further inquiry. Our results, which resonated with previous scholarly works and illuminated a clear link between the prevalence of the first name "Shaun" and arson occurrences in Arizona, add fuel to the fire of the ongoing debate on the impact of nomenclature on delinquent behavior.

Venturing into the realm of statistical analysis, we found ourselves in the midst of a heated debate, as the sizzling correlation coefficient of 0.9189290 and the r-squared value of 0.8444306 illuminated the potent relationship between these seemingly unrelated variables. The statistical significance at p < 0.01 is akin to a blazing inferno in the domain of empirical inquiry, leaving little room for doubt about the robustness of the Shaun-arson association.

Our findings rejuvenate the discussions sparked by prior research, drawing particular inspiration from the literary inferno that is Smith's "The Namesake's Impact" and the incendiary exploration of Doe, both of which shed light on the intriguing nexus of nomenclature and behavior. It is both amusing and intriguing that the puzzling Shaun-arson correlation, once a whimsical ember of curiosity stoked by Jones' wide-ranging investigation, has now erupted into a conflagration of empirical evidence.

As we sift through the ashes of this remarkable correlation, it becomes increasingly apparent that the world of statistical analysis is not devoid of surprises, and that even the most unlikely variables may fuel the fires of empirical discovery. The suggestion that a simple name could kindle the flames of criminal behavior serves as a testament to the intricate interplay of human behavior and nomenclature. Our findings underscore the importance of embracing unconventional factors in the investigation of criminal activities, thereby enkindling a newfound appreciation for the impact of nomenclature on deviant conduct.

In conclusion, the blistering implications of our research embolden researchers to delve deeper into the enigmatic interplay between nomenclature and unlawful conduct, catalyzing a fiery passion for unconventional avenues of scholarly exploration. As the flames of curiosity continue to spread, the prevailing insight from our study remains ablaze: the Shaun-arson connection sheds light on the sizzling potential of unorthodox factors in shaping societal phenomena.


Model: gpt-3.5-turbo-1106
System prompt: You are a researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Popularity of the first name Shaun and Arson in Arizona. 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]]
Playing with Fire: The Shaun-arson Connection in Arizona

[[ABSTRACT]]
This study aims to investigate the potential relationship between the popularity of the first name "Shaun" and the incidence of arson in the state of Arizona. Drawing from data provided by the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted a thorough analysis covering the years 1985 to 2022. Our findings revealed a remarkably high correlation coefficient of 0.9189290, with statistical significance at p < 0.01, suggesting a strong association between the prevalence of the name "Shaun" and arson occurrences in the state. While the exact mechanisms underlying this association remain elusive, the results impart a newfound appreciation for the impact of nomenclature on delinquent behavior. Our study underscores the importance of considering unconventional factors in the investigation of criminal activities and sparks further scholarly inquiry into the peculiar interplay between nomenclature and unlawful conduct.

[[INTRDUCTION]]
The etymology of names has long been a subject of intrigue, encompassing both linguistic and sociocultural dimensions. Within the realm of statistical analysis, the investigation of names in relation to various phenomena has ventured into territory as diverse as the names themselves. In this vein, the present study seeks to unravel the enigmatic correlation between the prevalence of the first name "Shaun" and the incidence of arson in the state of Arizona. Despite its seemingly whimsical nature, one cannot help but ponder the potential impact of nomenclature on criminal proclivity. Are there hidden sparks within the cultural fabric that ignite the flames of unlawful behavior, or is the connection merely a statistical anomaly flickering in the winds of chance?
Fueled by the burgeoning availability of data and the passion for uncovering unexpected associations, our research team embarked on a quest to decipher the tangled web of nomenclature and delinquency. Leveraging information from the US Social Security Administration and the FBI Criminal Justice Information Services, we undertook a meticulous analysis spanning nearly four decades. The resulting revelations, laced with statistical significance and phenomenological peculiarity, set ablaze the notion that a name is merely an innocuous label.
As we delve into the labyrinthine world of statistical analysis, it is impossible to overlook the sparks of curiosity that ignite the flames of investigation. Our quest for understanding leads us to question not only the peculiar connection between the name "Shaun" and arson, but also the broader implications for our understanding of criminal behavior. How might the embers of nomenclature kindle the fires of deviance, and what unforeseen variables lurk amidst the smoke and mirrors of statistical inference? With these questions smoldering at the periphery of empirical inquiry, we cast our wide net of analysis into the vast expanse of data, seeking to shed light on this curious conflagration of nomenclature and criminality.

[[RESULTS]]
The analysis of the data spanning 1985 to 2022 revealed a striking correlation between the prevalence of the first name "Shaun" and the incidence of arson in the state of Arizona. The correlation coefficient of 0.9189290, combined with an r-squared value of 0.8444306, solidifies the robust relationship between these seemingly disparate variables. With a p-value of less than 0.01, the statistical significance of this association blazes like a bonfire in the realm of empirical inquiry.
Fig. 1 presents a scatterplot illustrating the compelling link between the popularity of the name "Shaun" and the incidence of arson in Arizona. The plot paints a vivid picture of the confluence of these variables, leaving no doubt about the intensity of their relationship. One cannot help but warm up to the idea that there might be a fiery connection between nomenclature and incendiary acts, igniting both intrigue and amusement within the scientific community.
These findings kindle a fervent interest in the underlying mechanisms governing the Shaun-arson connection, stoking the flames of curiosity within the scientific community. The notion that a simple name could kindle the flames of criminal behavior serves as a testament to the intricate interplay of human behavior and nomenclature. As we sift through the ashes of this remarkable correlation, it becomes increasingly apparent that the world of statistical analysis is not devoid of surprises, and that even the most unlikely variables may fuel the fires of empirical discovery.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, the scorching correlation between the popularity of the name "Shaun" and the incidence of arson in Arizona is nothing short of a statistical wildfire, igniting both curiosity and bemusement among researchers. While we may be tempted to extinguish any conclusions with a dose of skepticism, the sizzling correlation coefficient of 0.9189290 and the fiery statistical significance at p < 0.01 leave little room for doubt. This inferno of a relationship fuels the flames of inquiry into the uncharted territory of nomenclature and its incendiary effects.

As we sift through the ashes of this research endeavor, one wonders if this correlation is merely a statistical fluke or if there are truly underlying sparks of influence that continue to blaze beneath the surface. Perhaps this association is merely a case of statistical serendipity, a confluence of variables that caught fire in the realm of empirical investigation. Nonetheless, the allure of this fiery nomenclatural conundrum cannot be extinguished, leaving us to ponder on the enigmatic interplay between names and nefarious deeds.

While our findings spark an illuminative curiosity, we assert with confidence that no further research is needed in this particular area. The intensity of this association and its potential implications have been thoroughly kindled. In the realm of statistical inquiry, the Shaun-arson connection stands as a monumental blaze of curiosity that requires no further stoking.


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 Playing with Fire: The Shaun-arson Connection in Arizona. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Pyrological Psychology


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 Playing with Fire: The Shaun-arson Connection in Arizona. Respond only with the name of a fictional organization.

ChatGPT:

Society for the Advancement of Unusual Arson 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 Playing with Fire: The Shaun-arson Connection in Arizona with an abstract of This study aims to investigate the potential relationship between the popularity of the first name "Shaun" and the incidence of arson in the state of Arizona. Drawing from data provided by the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted a thorough analysis covering the years 1985 to 2022. Our findings revealed a remarkably high correlation coefficient of 0.9189290, with statistical significance at p < 0.01, suggesting a strong association between the prevalence of the name "Shaun" and arson occurrences in the state. While the exact mechanisms underlying this association remain elusive, the results impart a newfound appreciation for the impact of nomenclature on delinquent behavior. Our study underscores the importance of considering unconventional factors in the investigation of criminal activities and sparks further scholarly inquiry into the peculiar interplay between nomenclature and unlawful conduct.

ChatGPT:

"Shaun" popularity, arson incidence, Arizona, correlation coefficient, US Social Security Administration, FBI Criminal Justice Information Services, nomenclature impact, criminal activities, delinquent behavior, scholarly inquiry

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



Random correlation

Discover a new correlation

View all correlations

View all research papers

Report an error


Data details

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

Arson in Arizona
Detailed data title: The arson rate per 100,000 residents in Arizona
Source: FBI Criminal Justice Information Services
See what else correlates with Arson in Arizona

Correlation r = 0.9189290 (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 = 0.8444306 (Coefficient of determination)
This means 84.4% of the change in the one variable (i.e., Arson in Arizona) is predictable based on the change in the other (i.e., Popularity of the first name Shaun) over the 38 years from 1985 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 4.07E-16. 0.0000000000000004074222648847
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 0.92 in 4.07E-14% of random cases. Said differently, if you correlated 2,454,455,944,578,774 random variables You don't actually need 2 quadrillion 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 37 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 37 because we have two variables measured over a period of 38 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.85, 0.96 ] 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.
19851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007200820092010201120122013201420152016201720182019202020212022
Popularity of the first name Shaun (Babies born)24012109185416881417138912151020978808738667650714710769666652699679736912786683565554434395335324315249250211192172157128
Arson in Arizona (Arson rate)58.463.452.651.158.94339.231.329.632.636.130.228.226.526.927.42932.52826.627.938.234.938.832.528.52729.926.326.217.516.616.923.912.817.46.111.6




Why this works

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




Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."


# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([2401,2109,1854,1688,1417,1389,1215,1020,978,808,738,667,650,714,710,769,666,652,699,679,736,912,786,683,565,554,434,395,335,324,315,249,250,211,192,172,157,128,])
array_2 = np.array([58.4,63.4,52.6,51.1,58.9,43,39.2,31.3,29.6,32.6,36.1,30.2,28.2,26.5,26.9,27.4,29,32.5,28,26.6,27.9,38.2,34.9,38.8,32.5,28.5,27,29.9,26.3,26.2,17.5,16.6,16.9,23.9,12.8,17.4,6.1,11.6,])
array_1_name = "Popularity of the first name Shaun"
array_2_name = "Arson in Arizona"

# 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.

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:


View another random correlation

How fun was this correlation?

You're the rating guru we've been waiting for!


Correlation ID: 2303 · Black Variable ID: 2726 · Red Variable ID: 20049
about · subscribe · emailme@tylervigen.com · twitter

CC BY 4.0