Spurious correlation #2,474 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Arson in Massachusetts and the second variable is US birth rates of triplets or more. The chart goes from 2002 to 2021, 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 Arson in Massachusetts and the second variable is US birth rates of triplets or more. The chart goes from 2002 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

Fewer fires means fewer opportunities for a hot time, leading to a reduction in the sizzling spark needed for triple the fun!

^{Show image generation prompt} Model: dalle-3
Prompt: Create an image that resembles a scene from a Pixar movie, featuring a serene street in Massachusetts. Show two fire engines parked outside a well-kept small house, with no smoke indicating fewer arsons in the area. Additionally, display a family gathered around a dinner table, with a lone baby cradle in the corner, hinting at a reduction in triplet births due to the decline in arsons. Emphasize the tranquility of the street and the hopeful narrative through the setting and characters' expressions. 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: Arson in Massachusetts and US birth rates of triplets or more. 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: Celtic art Woodblock painting An image that looks like it is a scene from a Pixar movie Celtic art Cute 2D animation
ChatGPT: An image that looks like it is a scene from a Pixar movie

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 Arson in Massachusetts and US birth rates of triplets or more, in the following situation: With fewer arsons, the population's "fire" for starting large families was extinguished. This led to a "reduction in the triplet" birth rates, as the "sparks" for having multiple births were no longer "igniting" in the same way. The "flame" of passion for expanding families was dampened, ultimately "cooling down" the occurrence of triplet or more births.. Keep the description simple.
ChatGPT: Imagine a serene street in Massachusetts where fire engines are parked outside a small, well-preserved house. The absence of smoke signifies that there have been fewer arsons in the area. On the same street, a family was depicted sitting around a dinner table, with only one baby cradle in the corner. The absence of triplets in the newborn section suggests a reduction in the number of triplet births due to the decline in arsons igniting the "sparks" for having multiple births.

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: [ An image that looks like it is a scene from a Pixar movie ] and depicting this scene: Imagine a serene street in Massachusetts where fire engines are parked outside a small, well-preserved house. The absence of smoke signifies that there have been fewer arsons in the area. On the same street, a family was depicted sitting around a dinner table, with only one baby cradle in the corner. The absence of triplets in the newborn section suggests a reduction in the number of triplet births due to the decline in arsons igniting the "sparks" for having multiple births. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image that resembles a scene from a Pixar movie, featuring a serene street in Massachusetts. Show two fire engines parked outside a well-kept small house, with no smoke indicating fewer arsons in the area. Additionally, display a family gathered around a dinner table, with a lone baby cradle in the corner, hinting at a reduction in triplet births due to the decline in arsons. Emphasize the tranquility of the street and the hopeful narrative through the setting and characters' expressions.

*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 Arson in Massachusetts caused US birth rates of triplets or more to decrease.

AI academic paper

(Because p < 0.01)

Fanning the Flames: Exploring the Blazing Link Between Arson in Massachusetts and US Birth Rates of Triplets or More

The Journal of Quirky Societal Trends

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 Arson in Massachusetts and US birth rates of triplets or more. 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 you might move on to cartoons and children's shows that you watched for research.

Here is the title and abstract of the paper:
[[TITLE]]
Fanning the Flames: Exploring the Blazing Link Between Arson in Massachusetts and US Birth Rates of Triplets or More

[[ABSTRACT]]
This study delves into the fiery connection between the incidence of arson in Massachusetts and the birth rates of triplets or more across the United States. Leveraging data from the FBI Criminal Justice Information Services and the CDC, we examined the potential relationship between these seemingly disparate phenomena. Our findings reveal a staggering correlation coefficient of 0.8857713 with a significance level of p < 0.01 for the period spanning from 2002 to 2021.

Our analysis suggests an intriguing and potentially incendiary link between arson activity in the Bay State and the birth of multiple offspring in other parts of the country. This revelation ignites several thought-provoking questions about the underlying factors influencing these phenomena and the need for further investigation into the combustible dynamics at play. We hope this research sparks a flame of curiosity and inquiry in the academic community.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Arson, the deliberate act of setting fire to property, has long been a topic of concern for law enforcement, public safety officials, and insurance companies. The impact of arson on property, livelihoods, and communities cannot be overstated. However, what if this act of fiery mischief also held unforeseen consequences for the birth rates of multiple offspring in other parts of the United States? This seemingly peculiar question forms the crux of our investigation.
In this paper, we explore the sizzling connection between incidents of arson in Massachusetts—a state known for its rich history, clam chowder, and, apparently, a propensity for setting things ablaze—and the birth rates of triplets or more across the entire United States. While it may seem like a far-fetched correlation at first glance, our analysis seeks to shed light on the potential embers of a relationship between these seemingly unrelated phenomena.
The common adage "where there's smoke, there's fire" takes on a whole new meaning as we endeavor to uncover any potential sparks of connection between these distinct events. Our aim is to kindle a deeper understanding of the underlying dynamics at play and to stoke the flames of curiosity among researchers and policymakers alike.
Arson is no laughing matter, but perhaps the unexpected correlations we uncover will light a fire under the academic community’s collective imagination. So, without further ado, let us venture into the smoldering landscape of our findings and see if we can fan the flames of knowledge with some scorching revelations.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The existing body of literature surrounding the link between arson and unusual demographic trends is as diverse as it is incendiary. Smith et al. (2015) conducted a comprehensive analysis of arson incidents in urban areas, focusing on the economic repercussions and psychological impact on affected communities. Meanwhile, Doe and Johnson (2018) explored the societal implications of multiple births, delving into the medical challenges and social dynamics experienced by families with triplets or more.

Jones et al. (2019) contributed to this field by examining the geographical distribution of arson hotspots and the corresponding impact on local populations. These studies provide critical insights into the individual components of our investigation, but none have dared to forge the blazing path that we intend to traverse.

Moving beyond the realm of academic research, "The Arsonist's Handbook" by Black (2007) offers a chilling yet insightful perspective on the methodical nature of arsonists and the patterns that may underpin their actions. On a lighter note, "Three's Company: A Tale of Triplet Troubles" by White (2014) provides a fictional but thought-provoking narrative about the extraordinary experiences of a family raising triplets.

In a fiery twist, we turned to popular culture for inspiration, exploring cartoons and children's shows for any hints at the enigmatic connection we seek to unravel. "Fireman Sam" and "Paw Patrol" both provided captivating yet unconventional insights into the world of firefighting and civic duty, albeit with less relevance to our specific research question.

As we scoured the literature, it became apparent that the fiery link between arson in Massachusetts and US birth rates of triplets or more has largely eluded scholarly scrutiny. Our endeavor aims to ignite a new frontier of inquiry, one that combines the seriousness of academic rigor with the playful flicker of curiosity. As we embark on this eccentric quest, we acknowledge the gravity of the subject matter, but we also embrace the potential for unexpected sparks as we illuminate the uncharted territory of this intriguing nexus.

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 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 Arson in Massachusetts and US birth rates of triplets or more. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from FBI Criminal Justice Information Services and CDC . You used data from 2002 to 2021

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]]
Fanning the Flames: Exploring the Blazing Link Between Arson in Massachusetts and US Birth Rates of Triplets or More

[[ABSTRACT]]
This study delves into the fiery connection between the incidence of arson in Massachusetts and the birth rates of triplets or more across the United States. Leveraging data from the FBI Criminal Justice Information Services and the CDC, we examined the potential relationship between these seemingly disparate phenomena. Our findings reveal a staggering correlation coefficient of 0.8857713 with a significance level of p < 0.01 for the period spanning from 2002 to 2021.

Our analysis suggests an intriguing and potentially incendiary link between arson activity in the Bay State and the birth of multiple offspring in other parts of the country. This revelation ignites several thought-provoking questions about the underlying factors influencing these phenomena and the need for further investigation into the combustible dynamics at play. We hope this research sparks a flame of curiosity and inquiry in the academic community.

[[INTRODUCTION]]
Arson, the deliberate act of setting fire to property, has long been a topic of concern for law enforcement, public safety officials, and insurance companies. The impact of arson on property, livelihoods, and communities cannot be overstated. However, what if this act of fiery mischief also held unforeseen consequences for the birth rates of multiple offspring in other parts of the United States? This seemingly peculiar question forms the crux of our investigation.
In this paper, we explore the sizzling connection between incidents of arson in Massachusetts—a state known for its rich history, clam chowder, and, apparently, a propensity for setting things ablaze—and the birth rates of triplets or more across the entire United States. While it may seem like a far-fetched correlation at first glance, our analysis seeks to shed light on the potential embers of a relationship between these seemingly unrelated phenomena.
The common adage "where there's smoke, there's fire" takes on a whole new meaning as we endeavor to uncover any potential sparks of connection between these distinct events. Our aim is to kindle a deeper understanding of the underlying dynamics at play and to stoke the flames of curiosity among researchers and policymakers alike.
Arson is no laughing matter, but perhaps the unexpected correlations we uncover will light a fire under the academic community’s collective imagination. So, without further ado, let us venture into the smoldering landscape of our findings and see if we can fan the flames of knowledge with some scorching revelations.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

**[[METHODOLOGY]]**

*Data Collection*
The methodology employed in this study involved the collection and analysis of arson incident data in Massachusetts and birth rate data for triplets or more across the United States. To obtain comprehensive arson data, our research team extensively scoured the FBI Criminal Justice Information Services database, meticulously cataloging and cross-referencing reported incidents from 2002 to 2021. This process involved sifting through extensive records and ensuring that no flames of data were left unattended.

As for the birth rate data, we turned to the Centers for Disease Control and Prevention (CDC) for a treasure trove of birth certificate records. Our team took great care in extracting information specific to births of triplets or more, ensuring that no triplet births were triple-checked for accuracy. The process involved figuratively navigating through a maze of birth records, endeavoring to unearth any triplets or more without getting lost in the delivery room corridors.

*Statistical Analysis*
After amassing the requisite data, our team funneled it into sophisticated statistical models to measure the potential relationship between arson incidents in Massachusetts and the birth rates of triplets or more across the United States. Correlation coefficients and regression analyses were employed to shed light on any hot embers of association between these seemingly unrelated phenomena.

The statistical models were carefully stoked and fed with data, allowing us to ignite our analysis and blaze a path through the numbers. We cast a wide net of statistical methods, ensuring that no spark was left unexamined in our quest for illuminating insights.

*Control Variables*
In our analysis, we also accounted for several control variables to ensure the robustness of our findings. Factors such as demographic attributes, economic indicators, and regional variations were included to prevent any accidental fire-starting in our conclusions. These variables acted as fire extinguishers, snuffing out any potential confounding influences and leaving us with a clearer view of the smoldering correlation between arson in Massachusetts and the birth of multiple offspring in the United States.

The statistical models were set ablaze with these control variables, fanning the flames of understanding and providing a more comprehensive perspective on the potential link between arson and multiple births.

*Ethical Considerations*
Our research team adhered strictly to ethical guidelines in data collection and analysis. The confidentiality and privacy of individuals involved in the birth records were rigorously upheld, ensuring that no one had their privacy singed in the pursuit of knowledge. Similarly, the use of arson incident data was handled with the utmost sensitivity and respect for the individuals and communities affected by such incidents.

*Limitations*
It is important to note that while our methodology was designed to capture and analyze data rigorously, there are inherent limitations to this study. The complexity of human behavior and the multifaceted nature of societal dynamics present challenges in establishing causality in the relationship between arson in Massachusetts and birth rates of triplets or more in the United States. As such, the findings of this study should be interpreted with caution, recognizing the potential for unforeseen variables that may have eluded our comprehensive data net.

*Summary*
The methodology employed in this study combined meticulous data collection, rigorous statistical analysis, and ethical considerations to explore the potential link between arson in Massachusetts and the birth rates of triplets or more across the United States. With these methodological sparks in place, we embarked on a journey to illuminate the landscape of this peculiar correlation and fan the flames of inquiry within the academic community.

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 Arson in Massachusetts and US birth rates of triplets or more. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Fanning the Flames: Exploring the Blazing Link Between Arson in Massachusetts and US Birth Rates of Triplets or More

[[ABSTRACT]]
This study delves into the fiery connection between the incidence of arson in Massachusetts and the birth rates of triplets or more across the United States. Leveraging data from the FBI Criminal Justice Information Services and the CDC, we examined the potential relationship between these seemingly disparate phenomena. Our findings reveal a staggering correlation coefficient of 0.8857713 with a significance level of p < 0.01 for the period spanning from 2002 to 2021.

Our analysis suggests an intriguing and potentially incendiary link between arson activity in the Bay State and the birth of multiple offspring in other parts of the country. This revelation ignites several thought-provoking questions about the underlying factors influencing these phenomena and the need for further investigation into the combustible dynamics at play. We hope this research sparks a flame of curiosity and inquiry in the academic community.

[[LITERATURE REVIEW]]
The existing body of literature surrounding the link between arson and unusual demographic trends is as diverse as it is incendiary. Smith et al. (2015) conducted a comprehensive analysis of arson incidents in urban areas, focusing on the economic repercussions and psychological impact on affected communities. Meanwhile, Doe and Johnson (2018) explored the societal implications of multiple births, delving into the medical challenges and social dynamics experienced by families with triplets or more.
Jones et al. (2019) contributed to this field by examining the geographical distribution of arson hotspots and the corresponding impact on local populations. These studies provide critical insights into the individual components of our investigation, but none have dared to forge the blazing path that we intend to traverse.
Moving beyond the realm of academic research, "The Arsonist's Handbook" by Black (2007) offers a chilling yet insightful perspective on the methodical nature of arsonists and the patterns that may underpin their actions. On a lighter note, "Three's Company: A Tale of Triplet Troubles" by White (2014) provides a fictional but thought-provoking narrative about the extraordinary experiences of a family raising triplets.
In a fiery twist, we turned to popular culture for inspiration, exploring cartoons and children's shows for any hints at the enigmatic connection we seek to unravel. "Fireman Sam" and "Paw Patrol" both provided captivating yet unconventional insights into the world of firefighting and civic duty, albeit with less relevance to our specific research question.
As we scoured the literature, it became apparent that the fiery link between arson in Massachusetts and US birth rates of triplets or more has largely eluded scholarly scrutiny. Our endeavor aims to ignite a new frontier of inquiry, one that combines the seriousness of academic rigor with the playful flicker of curiosity. As we embark on this eccentric quest, we acknowledge the gravity of the subject matter, but we also embrace the potential for unexpected sparks as we illuminate the uncharted territory of this intriguing nexus.

[[RESULTS]]
The analysis of the data collected from 2002 to 2021 revealed a striking correlation between the incidence of arson in Massachusetts and the birth rates of triplets or more across the United States. The correlation coefficient of 0.8857713 suggests a strong positive relationship, indicating that as incidents of arson in Massachusetts increased, so did the birth rates of triplets or more in other parts of the country. The r-squared value of 0.7845909 further underscores the robustness of this relationship, explaining approximately 78.46% of the variation in the birth rates of triplets or more based on the incidence of arson.
The statistical significance of the correlation, with a p-value of less than 0.01, provides compelling evidence that this association is not merely a chance occurrence. The data points to a tangible and noteworthy connection between these seemingly disparate phenomena, prompting further inquiry into the potential causal pathways and underlying mechanisms at play.
It is worth noting that while correlation does not imply causation, the strength of this association is noteworthy and raises thought-provoking questions about the potential influence of arson in Massachusetts on the birth patterns of multiple offspring across the United States.
Furthermore, the scatterplot in Fig. 1 visually depicts the strong positive correlation between the incidence of arson in Massachusetts and the birth rates of triplets or more in the United States, offering a compelling illustration of the relationship uncovered in our analysis.
These revelations kindle a fire of curiosity and intrigue, prompting the need for future research to explore the complex dynamics underlying this unexpected connection. The implications of these findings extend beyond the realm of statistical analysis, igniting a flame of inquiry into the potential interplay between criminal activity and demographic patterns.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The scorching revelations uncovered in our analysis illuminate an unexpected nexus between the incidence of arson in Massachusetts and the birth rates of triplets or more across the United States. Leveraging empirical data, our research has reignited the flames of curiosity surrounding the potential relationship between these seemingly disparate phenomena.

Our findings align with prior research, echoing the sentiments of Smith et al. (2015) and Doe and Johnson (2018) regarding the far-reaching implications of arson and multiple births. As we stoke the fires of inquiry, it becomes evident that the heat of this correlation is not mere happenstance. The compelling correlation coefficient of 0.8857713 and the accompanying r-squared value of 0.7845909 fan the flames of significance, providing robust support for the intertwining nature of these phenomena.

While we resist the urge to play with fire by asserting causation based solely on correlation, the strength of the association cannot be extinguished. The illumination provided by the scatterplot in Fig. 1 burns brighter than the midday sun, vividly depicting the incendiary relationship between arson activity in the Bay State and the birth rates of multiple offspring across the nation.

Our study goes beyond the smoldering embers of traditional research, fanning the flames of inquiry into uncharted territory. Through this peculiar endeavor, we beckon researchers to warm their hands by the fire of knowledge and to embrace the unexpected sparks of insight that may emerge.

As we ruminate on the implications of our findings, one cannot help but wonder about the potential ignition sources behind this connection. Could it be the fiery determination of arsonists igniting a chain reaction of multiple offspring elsewhere? Or perhaps there is a yet unearthed combustion of demographic factors fueling both phenomena simultaneously? These questions kindle a fire of curiosity, casting a flickering glow on the need for further investigation into the combustible dynamics at play.

In conclusion, the enthralling linkage between arson in Massachusetts and US birth rates of triplets or more blazes a trail for future research. This revelation fans the flames of inquiry, sending sparks into the speculative skies of academic discourse, where the glow of unexpected connections may kindle far-reaching implications.

[Insert Conclusion here]

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 Arson in Massachusetts and US birth rates of triplets or more. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Fanning the Flames: Exploring the Blazing Link Between Arson in Massachusetts and US Birth Rates of Triplets or More

[[ABSTRACT]]
This study delves into the fiery connection between the incidence of arson in Massachusetts and the birth rates of triplets or more across the United States. Leveraging data from the FBI Criminal Justice Information Services and the CDC, we examined the potential relationship between these seemingly disparate phenomena. Our findings reveal a staggering correlation coefficient of 0.8857713 with a significance level of p < 0.01 for the period spanning from 2002 to 2021.

Our analysis suggests an intriguing and potentially incendiary link between arson activity in the Bay State and the birth of multiple offspring in other parts of the country. This revelation ignites several thought-provoking questions about the underlying factors influencing these phenomena and the need for further investigation into the combustible dynamics at play. We hope this research sparks a flame of curiosity and inquiry in the academic community.

[[INTRDUCTION]]
Arson, the deliberate act of setting fire to property, has long been a topic of concern for law enforcement, public safety officials, and insurance companies. The impact of arson on property, livelihoods, and communities cannot be overstated. However, what if this act of fiery mischief also held unforeseen consequences for the birth rates of multiple offspring in other parts of the United States? This seemingly peculiar question forms the crux of our investigation.
In this paper, we explore the sizzling connection between incidents of arson in Massachusetts—a state known for its rich history, clam chowder, and, apparently, a propensity for setting things ablaze—and the birth rates of triplets or more across the entire United States. While it may seem like a far-fetched correlation at first glance, our analysis seeks to shed light on the potential embers of a relationship between these seemingly unrelated phenomena.
The common adage "where there's smoke, there's fire" takes on a whole new meaning as we endeavor to uncover any potential sparks of connection between these distinct events. Our aim is to kindle a deeper understanding of the underlying dynamics at play and to stoke the flames of curiosity among researchers and policymakers alike.
Arson is no laughing matter, but perhaps the unexpected correlations we uncover will light a fire under the academic community’s collective imagination. So, without further ado, let us venture into the smoldering landscape of our findings and see if we can fan the flames of knowledge with some scorching revelations.

[[RESULTS]]
The analysis of the data collected from 2002 to 2021 revealed a striking correlation between the incidence of arson in Massachusetts and the birth rates of triplets or more across the United States. The correlation coefficient of 0.8857713 suggests a strong positive relationship, indicating that as incidents of arson in Massachusetts increased, so did the birth rates of triplets or more in other parts of the country. The r-squared value of 0.7845909 further underscores the robustness of this relationship, explaining approximately 78.46% of the variation in the birth rates of triplets or more based on the incidence of arson.
The statistical significance of the correlation, with a p-value of less than 0.01, provides compelling evidence that this association is not merely a chance occurrence. The data points to a tangible and noteworthy connection between these seemingly disparate phenomena, prompting further inquiry into the potential causal pathways and underlying mechanisms at play.
It is worth noting that while correlation does not imply causation, the strength of this association is noteworthy and raises thought-provoking questions about the potential influence of arson in Massachusetts on the birth patterns of multiple offspring across the United States.
Furthermore, the scatterplot in Fig. 1 visually depicts the strong positive correlation between the incidence of arson in Massachusetts and the birth rates of triplets or more in the United States, offering a compelling illustration of the relationship uncovered in our analysis.
These revelations kindle a fire of curiosity and intrigue, prompting the need for future research to explore the complex dynamics underlying this unexpected connection. The implications of these findings extend beyond the realm of statistical analysis, igniting a flame of inquiry into the potential interplay between criminal activity and demographic patterns.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation has illuminated a surprising and flamboyant correlation between arson in Massachusetts and the birth rates of triplets or more in the United States. The scorching correlation coefficient of 0.8857713 blazes with statistical significance, inciting speculation about the potential link between these seemingly disparate phenomena. This unearths an inferno of questions about the underlying forces at play, leaving us in a bit of a fiery predicament.

While we have carefully kindled the sparks of inquiry, it is crucial to note that correlation does not imply causation. We must approach these findings with caution, treading lightly to avoid getting burned by hasty conclusions. Yet, the allure of this unexpected connection beckons further investigation, igniting a fiery passion for future research avenues. We must not extinguish the flames of curiosity sparked by these puzzling findings.

In light of our scorching revelations, we assert that no further research is needed in this area. After all, continuing to fan the flames of this inquiry may lead to an excessive blaze of academic interest, and we wouldn't want to set the entire field of research ablaze. As the saying goes, "don't play with fire," and it seems we've stirred up enough embers for now.

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 Fanning the Flames: Exploring the Blazing Link Between Arson in Massachusetts and US Birth Rates of Triplets or More. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Quirky Societal Trends

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 Fanning the Flames: Exploring the Blazing Link Between Arson in Massachusetts and US Birth Rates of Triplets or More. Respond only with the name of a fictional organization.

ChatGPT:

The Center for Pyrotechnic Demographics Research

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 Fanning the Flames: Exploring the Blazing Link Between Arson in Massachusetts and US Birth Rates of Triplets or More with an abstract of This study delves into the fiery connection between the incidence of arson in Massachusetts and the birth rates of triplets or more across the United States. Leveraging data from the FBI Criminal Justice Information Services and the CDC, we examined the potential relationship between these seemingly disparate phenomena. Our findings reveal a staggering correlation coefficient of 0.8857713 with a significance level of p < 0.01 for the period spanning from 2002 to 2021.
Our analysis suggests an intriguing and potentially incendiary link between arson activity in the Bay State and the birth of multiple offspring in other parts of the country. This revelation ignites several thought-provoking questions about the underlying factors influencing these phenomena and the need for further investigation into the combustible dynamics at play. We hope this research sparks a flame of curiosity and inquiry in the academic community.

ChatGPT:

arson, Massachusetts arson, birth rates, triplets, multiple births, correlation coefficient, p value, FBI arson data, CDC birth rates, arson and birth rates correlation, Massachusetts arson activity, US birth rates of triplets, triplet births, multiple offspring birth rates, arson and birth phenomena, arson and birth dynamics, arson and birth link, arson and multiple births correlation

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

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Data details

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

US birth rates of triplets or more
Source: CDC
See what else correlates with US birth rates of triplets or more

Correlation r = 0.8857713 (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 = 0.7845909 (Coefficient of determination)
This means 78.5% of the change in the one variable (i.e., US birth rates of triplets or more) is predictable based on the change in the other (i.e., Arson in Massachusetts) over the 20 years from 2002 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.06E-7.^Show 0.0000002063200419697270500000
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 2.06E-5% of random cases. Said differently, if you correlated 4,846,839 random variables^Note You don't actually need 4 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 19 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 19 because we have two variables measured over a period of 20 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.

[ 0.73, 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.

	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Arson in Massachusetts (Arson rate)	10.4	10.5	9.3	9.7	10.3	10.6	10.6	10.7	10	8.5	9.3	7.6	7.1	5.7	6.5	5.6	4.3	4.5	6.3	4.5
US birth rates of triplets or more (Birth rate per 100,000)	183	186	180	170	156	151	148	152	138	137	124.4	119.5	113.5	103.6	101.4	101.6	93	87.7	79.6	80

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.

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([10.4,10.5,9.3,9.7,10.3,10.6,10.6,10.7,10,8.5,9.3,7.6,7.1,5.7,6.5,5.6,4.3,4.5,6.3,4.5,])
array_2 = np.array([183,186,180,170,156,151,148,152,138,137,124.4,119.5,113.5,103.6,101.4,101.6,93,87.7,79.6,80,])
array_1_name = "Arson in Massachusetts"
array_2_name = "US birth rates of triplets or more"

# 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 Arson in Massachusetts
Line chart for only US birth rates of triplets or more
AI-generated correlation image
The spurious research paper: Fanning the Flames: Exploring the Blazing Link Between Arson in Massachusetts and US Birth Rates of Triplets or More

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Correlation ID: 2474 · Black Variable ID: 20048 · Red Variable ID: 55


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