Spurious correlation #2,090 · 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 Delaware 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 Delaware 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

As arson rates decreased in Delaware, there were fewer instances of fiery passion, leading to a reduction in the number of hot and heavy pregnancies, ultimately lowering the likelihood of triplets or more being conceived. This is due to the fact that less burnt out buildings meant less burnt out love lives, resulting in decreased instances of spontaneous combustion of fertility, and ultimately leading to a smoldering reduction in the delivery of three or more bundles of joy.

^{Show image generation prompt} Model: dalle-3
Prompt: Create an image of contrasts between chaos and peace in a suburban setting. Show a serene neighborhood in Delaware with a small house engulfed in flames, billowing out smoke from the windows. Meanwhile, at the local hospital, depict three sets of triplets being born simultaneously, bringing unexpected joy and a flurry of newborns into the world. The juxtaposition of these scenes should emphasize the stark contrast between the calamity and celebration in a peaceful environment. The focus should be on the emotions stirred by these opposing events. 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 Delaware 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: Steampunk Glitch art Cubism Data cyber art Scalar art
ChatGPT: Data cyber art

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 Delaware and US birth rates of triplets or more together. Keep the description simple.
ChatGPT: In a peaceful neighborhood in Delaware, a small house is on fire, with smoke billowing from the windows. Meanwhile, at the local hospital, three sets of triplets are born at the same time, bringing joy and an unexpected number of newborns into the world.

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: [ Data cyber art ] and depicting this scene: In a peaceful neighborhood in Delaware, a small house is on fire, with smoke billowing from the windows. Meanwhile, at the local hospital, three sets of triplets are born at the same time, bringing joy and an unexpected number of newborns into the world. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of contrasts between chaos and peace in a suburban setting. Show a serene neighborhood in Delaware with a small house engulfed in flames, billowing out smoke from the windows. Meanwhile, at the local hospital, depict three sets of triplets being born simultaneously, bringing unexpected joy and a flurry of newborns into the world. The juxtaposition of these scenes should emphasize the stark contrast between the calamity and celebration in a peaceful environment. The focus should be on the emotions stirred by these opposing events.

*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 Delaware caused US birth rates of triplets or more to decrease.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)

Playing with Fire: Exploring the Incendiary Connection Between Arson Rates in Delaware and the Uncommon Incidence of Triplet Births in the United States

Journal of Pyrokinetic Epidemiology

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 Delaware 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. Perhaps you also got inspiration from some board games that are vaugely related.

Here is the title and abstract of the paper:
[[TITLE]]
Playing with Fire: Exploring the Incendiary Connection Between Arson Rates in Delaware and the Uncommon Incidence of Triplet Births in the United States

[[ABSTRACT]]
This comprehensive research paper delves into the seldom-explored link between arson rates in the state of Delaware and the prevalence of triplets or more births across the United States. Utilizing meticulous data analysis sourced from the FBI Criminal Justice Information Services and the Centers for Disease Control and Prevention, our research team has uncovered a striking correlation coefficient of 0.9512290 (p < 0.01) for the years spanning 2002 to 2021.

The analysis not only highlights the statistically significant relationship between these seemingly disparate phenomena but also sheds light on the "hot" nature of the connection. This paper aims to ignite serious academic discourse regarding the unexpected implications of incendiary incidents on birth rates, sparking a blaze of interest in this niche intersection of criminology and reproductive demography.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The relationship between arson and birth rates of triplets or more may sound like the plot of an improbable crime thriller or a far-fetched conspiracy theory. However, our research endeavors to uncover the fiery truth behind this seemingly unlikely connection.
Arson, defined as the criminal act of deliberately setting fire to property, has long been a topic of interest for criminologists and law enforcement agencies. On the other hand, the occurrence of triplet births, while undoubtedly a cause for celebration for the families involved, has not often been juxtaposed with criminal activities. Nevertheless, our study aims to unravel the intricate web of connections between these two disparate phenomena.
Delaware, the second smallest state in the United States, is known for its rich history and scenic beauty. It is also unfortunately known for its disproportionately high arson rates, providing the perfect backdrop for our investigation. In contrast, the prevalence of triplet or higher-order multiple births across the entire United States presents an enigmatic puzzle, enticing us to explore whether there exists a hidden spark linking these occurrences.
To pursue this ambitious endeavor, we pored over years of meticulously collated data from the FBI Criminal Justice Information Services and the Centers for Disease Control and Prevention. The dataset provided an extensive canvas for our analysis, allowing us to discern patterns, correlations, and perhaps even the occasional red herring.
In this paper, we aim to not only present the empirical findings but also to kindle the flames of curiosity within the academic community. Through our research, we hope to shed light on this uncharted territory, beckoning scholars to join us in exploring the intriguing relationship between arson in Delaware and the birth rates of triplets or more in the United States. After all, when it comes to understanding these phenomena, the more, the merrier – or should we say, the "tripletier."

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The quest to unravel the perplexing correlation between arson rates in the state of Delaware and the incidence of triplet or higher-order multiple births in the United States has enticed researchers from diverse fields. While traditionally disparate in their subject matter, the exploration of potential links between phenomena of this nature has generated both curiosity and skepticism within the academic community.

Smith et al. (2015) provide an insightful analysis of the socioeconomic factors contributing to arson occurrences, shedding light on the societal undercurrents that may fuel such criminal behavior. Meanwhile, Doe and Jones (2018) delve into the complexities of multiple gestations, outlining the physiological and epidemiological aspects of triplet and higher-order birth rates in the United States.

In "Flames and Fertility: An Unlikely Tale of Two Phenomena," the authors illuminate the intersection between criminal psychology and reproductive demography, prompting readers to rethink the boundaries of interdisciplinary studies. However, it is important to note that the literature on this specific connection is still in its embryonic stages, leaving ample room for exploration and conjecture – much like the development of triplets in the womb.

Turning to non-fiction sources, "The Arsonist's Handbook" by John Smith and "The Triplet Mystery: An In-Depth Analysis" by Jane Doe provide valuable insights from their respective domains. While the former focuses on the modus operandi and psychological profiles of arsonists, the latter delves into the intricacies of multiple births, bringing forth a wealth of information that intertwines criminal behavior and reproductive anomalies.

On the more creative front, fictional works such as "Playing with Fire" by Sarah Jones and "Triple Trouble: A Suspenseful Tale" by Michael Smith offer tantalizing narratives that, while not grounded in empirical evidence, may provide sparks of inspiration for researchers navigating this uncharted territory. Additionally, the popular board game "Fire & Fertility" – although not an academic source – has sparked casual conversations around the potential synergies between arson and multiple births, serving as a quirky reminder of the diverse avenues through which this connection can be explored.

While these sources serve as preliminary guides, it is evident that a comprehensive understanding of the arson-triplets connection demands an interdisciplinary approach, fusing elements of criminology, demography, and perhaps a touch of speculative curiosity. As we venture into this uncharted terrain, it becomes increasingly clear that unraveling the complex tapestry of fire and fertility will require not only scholarly rigor but also a spark of imagination.

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 Delaware 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.

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]]
Playing with Fire: Exploring the Incendiary Connection Between Arson Rates in Delaware and the Uncommon Incidence of Triplet Births in the United States

[[ABSTRACT]]
This comprehensive research paper delves into the seldom-explored link between arson rates in the state of Delaware and the prevalence of triplets or more births across the United States. Utilizing meticulous data analysis sourced from the FBI Criminal Justice Information Services and the Centers for Disease Control and Prevention, our research team has uncovered a striking correlation coefficient of 0.9512290 (p < 0.01) for the years spanning 2002 to 2021.

The analysis not only highlights the statistically significant relationship between these seemingly disparate phenomena but also sheds light on the "hot" nature of the connection. This paper aims to ignite serious academic discourse regarding the unexpected implications of incendiary incidents on birth rates, sparking a blaze of interest in this niche intersection of criminology and reproductive demography.

[[INTRODUCTION]]
The relationship between arson and birth rates of triplets or more may sound like the plot of an improbable crime thriller or a far-fetched conspiracy theory. However, our research endeavors to uncover the fiery truth behind this seemingly unlikely connection.
Arson, defined as the criminal act of deliberately setting fire to property, has long been a topic of interest for criminologists and law enforcement agencies. On the other hand, the occurrence of triplet births, while undoubtedly a cause for celebration for the families involved, has not often been juxtaposed with criminal activities. Nevertheless, our study aims to unravel the intricate web of connections between these two disparate phenomena.
Delaware, the second smallest state in the United States, is known for its rich history and scenic beauty. It is also unfortunately known for its disproportionately high arson rates, providing the perfect backdrop for our investigation. In contrast, the prevalence of triplet or higher-order multiple births across the entire United States presents an enigmatic puzzle, enticing us to explore whether there exists a hidden spark linking these occurrences.
To pursue this ambitious endeavor, we pored over years of meticulously collated data from the FBI Criminal Justice Information Services and the Centers for Disease Control and Prevention. The dataset provided an extensive canvas for our analysis, allowing us to discern patterns, correlations, and perhaps even the occasional red herring.
In this paper, we aim to not only present the empirical findings but also to kindle the flames of curiosity within the academic community. Through our research, we hope to shed light on this uncharted territory, beckoning scholars to join us in exploring the intriguing relationship between arson in Delaware and the birth rates of triplets or more in the United States. After all, when it comes to understanding these phenomena, the more, the merrier – or should we say, the "tripletier."

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To unravel this enigmatic connection, our research team employed a multifaceted approach that involved both quantitative and qualitative analyses. Our initial step involved combing through the extensive database of the FBI Criminal Justice Information Services for comprehensive arson incident reports in the state of Delaware. We meticulously cataloged the time, location, and nature of each incendiary event, ensuring that no arsonist’s fiery deed went unnoticed or unrecorded. We then layered this data with historical weather patterns, local economic indicators, and the proximity of marshmallow and graham cracker suppliers in the vicinity, to account for potential s’more-related motivation.

Simultaneously, our team ventured into the realm of reproductive demography by delving into the troves of birth records maintained by the Centers for Disease Control and Prevention. We meticulously identified births of triplets or more across the United States during the same time period, meticulously cross-referencing them with any reported sightings of storks, delivering not only bundles of joy but also an unexpected statistical anomaly.

The qualitative aspect of our methodology involved extensive interviews with firefighters, obstetricians, and perhaps even the occasional mythological fire-breathing creature to gain insights into the symbolic, allegorical, and potentially metaphysical associations between arson and the birthing of multiple offspring.

To ensure the robustness of our findings, we conducted a series of statistical analyses, including correlation coefficients, regression models, and an unanticipated but invariably exciting round of interpretive dance. Our peer debaters, uh, reviewers, later joined our interpretive dance session to offer cogent comments and raised eyebrows, further bolstering the trustworthiness of our conclusions.

Lastly, as a measure of due diligence, we consulted with experts in the fields of pyromania, fertility treatments, and the physics of spontaneous combustion, to account for any unforeseen confounding variables. And, in good academic tradition, we also crossed our T's and dotted our I's, ensuring that no statistical stone was left unturned, and not a single statistical birth of triplets or more was miscounted.

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 Delaware 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.

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: Exploring the Incendiary Connection Between Arson Rates in Delaware and the Uncommon Incidence of Triplet Births in the United States

[[ABSTRACT]]
This comprehensive research paper delves into the seldom-explored link between arson rates in the state of Delaware and the prevalence of triplets or more births across the United States. Utilizing meticulous data analysis sourced from the FBI Criminal Justice Information Services and the Centers for Disease Control and Prevention, our research team has uncovered a striking correlation coefficient of 0.9512290 (p < 0.01) for the years spanning 2002 to 2021.

The analysis not only highlights the statistically significant relationship between these seemingly disparate phenomena but also sheds light on the "hot" nature of the connection. This paper aims to ignite serious academic discourse regarding the unexpected implications of incendiary incidents on birth rates, sparking a blaze of interest in this niche intersection of criminology and reproductive demography.

[[LITERATURE REVIEW]]
The quest to unravel the perplexing correlation between arson rates in the state of Delaware and the incidence of triplet or higher-order multiple births in the United States has enticed researchers from diverse fields. While traditionally disparate in their subject matter, the exploration of potential links between phenomena of this nature has generated both curiosity and skepticism within the academic community.
Smith et al. (2015) provide an insightful analysis of the socioeconomic factors contributing to arson occurrences, shedding light on the societal undercurrents that may fuel such criminal behavior. Meanwhile, Doe and Jones (2018) delve into the complexities of multiple gestations, outlining the physiological and epidemiological aspects of triplet and higher-order birth rates in the United States.
In "Flames and Fertility: An Unlikely Tale of Two Phenomena," the authors illuminate the intersection between criminal psychology and reproductive demography, prompting readers to rethink the boundaries of interdisciplinary studies. However, it is important to note that the literature on this specific connection is still in its embryonic stages, leaving ample room for exploration and conjecture – much like the development of triplets in the womb.
Turning to non-fiction sources, "The Arsonist's Handbook" by John Smith and "The Triplet Mystery: An In-Depth Analysis" by Jane Doe provide valuable insights from their respective domains. While the former focuses on the modus operandi and psychological profiles of arsonists, the latter delves into the intricacies of multiple births, bringing forth a wealth of information that intertwines criminal behavior and reproductive anomalies.
On the more creative front, fictional works such as "Playing with Fire" by Sarah Jones and "Triple Trouble: A Suspenseful Tale" by Michael Smith offer tantalizing narratives that, while not grounded in empirical evidence, may provide sparks of inspiration for researchers navigating this uncharted territory. Additionally, the popular board game "Fire & Fertility" – although not an academic source – has sparked casual conversations around the potential synergies between arson and multiple births, serving as a quirky reminder of the diverse avenues through which this connection can be explored.
While these sources serve as preliminary guides, it is evident that a comprehensive understanding of the arson-triplets connection demands an interdisciplinary approach, fusing elements of criminology, demography, and perhaps a touch of speculative curiosity. As we venture into this uncharted terrain, it becomes increasingly clear that unraveling the complex tapestry of fire and fertility will require not only scholarly rigor but also a spark of imagination.

[[RESULTS]]
The analysis of the data spanning the years 2002 to 2021 has yielded a striking correlation coefficient of 0.9512290, with an r-squared value of 0.9048366 and a p-value of less than 0.01. These findings provide compelling evidence for a strong relationship between the incidence of arson in Delaware and the birth rates of triplets or more across the United States.
The visually impactful representation of this relationship is presented in Figure 1, where a scatterplot reveals the unmistakable clustering of data points, reminiscent of sparks flying from a bonfire of statistical significance. This compelling visualization underscores the close association between these seemingly disparate phenomena, emphasizing the need for further investigation into this fiery correlation.
The strength of this correlation calls to mind the phrase, "where there's smoke, there's fire"—a fitting analogy for our robust findings. The high correlation coefficient indicates that as arson rates in Delaware fluctuated, so too did the incidence of triplet or higher-order multiple births across the United States. This intriguing connection, akin to a smoldering mystery, invites scholars to fan the flames of inquiry and illuminate the underlying mechanisms driving this correlation.
While it may seem unconventional to bridge the realms of criminal justice and reproductive demography, our findings unequivocally highlight the incendiary nature of this relationship. Moreover, the statistically significant p-value adds fuel to the fire, reinforcing the credibility of our results and affirming the importance of this unconventional investigation.
In summary, the results of our study clearly demonstrate a compelling correlation between arson rates in Delaware and the occurrence of triplet or more births in the United States. This unexpected connection not only underscores the need for interdisciplinary exploration but also ignites a fervent interest in uncovering the mysterious forces at play.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of our study provide robust support for the previously unexplored connection between arson rates in Delaware and the incidence of triplet or higher-order multiple births across the United States. The statistically significant correlation coefficient of 0.9512290 echoes the musings of earlier researchers who dared to envision the enigmatic link between pyromania and prolific pregnancies.

Our results lend credence to the notion posited in "Flames and Fertility: An Unlikely Tale of Two Phenomena," suggesting that the societal undercurrents contributing to arson occurrences may ripple through to influence the multifaceted dynamics of multiple gestations. Smith et al. (2015) offered insightful analysis of the socioeconomic factors fueling arson, igniting discussions on the channels through which such influences may extend to reproductive demography - a literal case of societal "heat" impacting birth outcomes.

Further delving into our findings, the visual representation in Figure 1 not only illuminates the association between arson rates and triplet birth incidences but also kindles a new appreciation for the fiery synergy between these seemingly unrelated phenomena. This visualization, much like a well-contained bonfire of statistical significance, offers a captivating display of the clustering data points, mirroring the sparks of correlation flying between these distinct realms.

While our investigation may seem to tread unorthodox paths across disciplinary boundaries, the compelling and significant p-value adds fuel to the flames of academic curiosity, affirming that our study has set the field ablaze with innovative inquiries. Prompting a rethinking of the interdisciplinary possibilities, our work fuels a fervent interest in understanding the underlying mechanisms driving this incendiary correlation, igniting a blaze of academic fervor reminiscent of a thrilling inferno of inquiry.

In essence, our findings, in startling coherence with prior research and theoretical explorations, reinforce the notion that where there's arson, there may indeed be triplet or higher-order multiple births - a sizzling revelation that stokes the fires of interdisciplinary discourse and sparks a renewed fervor for delving into unconventional intersectional studies.

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 Delaware 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.

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: Exploring the Incendiary Connection Between Arson Rates in Delaware and the Uncommon Incidence of Triplet Births in the United States

[[ABSTRACT]]
This comprehensive research paper delves into the seldom-explored link between arson rates in the state of Delaware and the prevalence of triplets or more births across the United States. Utilizing meticulous data analysis sourced from the FBI Criminal Justice Information Services and the Centers for Disease Control and Prevention, our research team has uncovered a striking correlation coefficient of 0.9512290 (p < 0.01) for the years spanning 2002 to 2021.

The analysis not only highlights the statistically significant relationship between these seemingly disparate phenomena but also sheds light on the "hot" nature of the connection. This paper aims to ignite serious academic discourse regarding the unexpected implications of incendiary incidents on birth rates, sparking a blaze of interest in this niche intersection of criminology and reproductive demography.

[[INTRDUCTION]]
The relationship between arson and birth rates of triplets or more may sound like the plot of an improbable crime thriller or a far-fetched conspiracy theory. However, our research endeavors to uncover the fiery truth behind this seemingly unlikely connection.
Arson, defined as the criminal act of deliberately setting fire to property, has long been a topic of interest for criminologists and law enforcement agencies. On the other hand, the occurrence of triplet births, while undoubtedly a cause for celebration for the families involved, has not often been juxtaposed with criminal activities. Nevertheless, our study aims to unravel the intricate web of connections between these two disparate phenomena.
Delaware, the second smallest state in the United States, is known for its rich history and scenic beauty. It is also unfortunately known for its disproportionately high arson rates, providing the perfect backdrop for our investigation. In contrast, the prevalence of triplet or higher-order multiple births across the entire United States presents an enigmatic puzzle, enticing us to explore whether there exists a hidden spark linking these occurrences.
To pursue this ambitious endeavor, we pored over years of meticulously collated data from the FBI Criminal Justice Information Services and the Centers for Disease Control and Prevention. The dataset provided an extensive canvas for our analysis, allowing us to discern patterns, correlations, and perhaps even the occasional red herring.
In this paper, we aim to not only present the empirical findings but also to kindle the flames of curiosity within the academic community. Through our research, we hope to shed light on this uncharted territory, beckoning scholars to join us in exploring the intriguing relationship between arson in Delaware and the birth rates of triplets or more in the United States. After all, when it comes to understanding these phenomena, the more, the merrier – or should we say, the "tripletier."

[[RESULTS]]
The analysis of the data spanning the years 2002 to 2021 has yielded a striking correlation coefficient of 0.9512290, with an r-squared value of 0.9048366 and a p-value of less than 0.01. These findings provide compelling evidence for a strong relationship between the incidence of arson in Delaware and the birth rates of triplets or more across the United States.
The visually impactful representation of this relationship is presented in Figure 1, where a scatterplot reveals the unmistakable clustering of data points, reminiscent of sparks flying from a bonfire of statistical significance. This compelling visualization underscores the close association between these seemingly disparate phenomena, emphasizing the need for further investigation into this fiery correlation.
The strength of this correlation calls to mind the phrase, "where there's smoke, there's fire"—a fitting analogy for our robust findings. The high correlation coefficient indicates that as arson rates in Delaware fluctuated, so too did the incidence of triplet or higher-order multiple births across the United States. This intriguing connection, akin to a smoldering mystery, invites scholars to fan the flames of inquiry and illuminate the underlying mechanisms driving this correlation.
While it may seem unconventional to bridge the realms of criminal justice and reproductive demography, our findings unequivocally highlight the incendiary nature of this relationship. Moreover, the statistically significant p-value adds fuel to the fire, reinforcing the credibility of our results and affirming the importance of this unconventional investigation.
In summary, the results of our study clearly demonstrate a compelling correlation between arson rates in Delaware and the occurrence of triplet or more births in the United States. This unexpected connection not only underscores the need for interdisciplinary exploration but also ignites a fervent interest in uncovering the mysterious forces at play.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, the scorching revelations of our research illuminate the "fire-and-desire" connection between arson rates in Delaware and the birth rates of triplets or more in the United States. Our findings not only set the data ablaze with a scorching correlation coefficient of 0.9512290 (p < 0.01), but also spark a fiery discussion regarding the unexpected synergy between these phenomena.

As we extinguish the flames of this investigation, it is vital to highlight the need for further research in this area. This scintillating correlation, akin to a sizzling mystery novel, beckons scholars to stoke the embers of inquiry and explore the underlying mechanisms driving this unexpected link. However, given the incendiary nature of our findings, one might wonder if the fire of curiosity has been sufficiently stoked, or if it's best to let this blaze of interest simmer down.

In the future, it would be "hot" to delve deeper into potential causative factors underlying this fiery correlation and consider how it may manifest in other geographical areas. Perhaps a closer examination of the environmental, social, and cultural contexts could provide additional kindling for our understanding. Nonetheless, our research unequivocally sets the stage for a "fiery" debate within the academic community regarding the unexpected implications of incendiary incidents on birth rates.

In summary, our findings provide compelling evidence of a smoldering relationship between arson in Delaware and the occurrence of triplet or more births in the United States. Therefore, we confidently assert that further research in this area is unnecessary. The inferno of knowledge has been stoked, and we cautiously recommend letting these findings burn brightly in the annals of academic exploration.

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited Playing with Fire: Exploring the Incendiary Connection Between Arson Rates in Delaware and the Uncommon Incidence of Triplet Births in the United States. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Pyrokinetic Epidemiology

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: Exploring the Incendiary Connection Between Arson Rates in Delaware and the Uncommon Incidence of Triplet Births in the United States. Respond only with the name of a fictional organization.

ChatGPT:

The Consortium for Curious Correlations

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: Exploring the Incendiary Connection Between Arson Rates in Delaware and the Uncommon Incidence of Triplet Births in the United States with an abstract of This comprehensive research paper delves into the seldom-explored link between arson rates in the state of Delaware and the prevalence of triplets or more births across the United States. Utilizing meticulous data analysis sourced from the FBI Criminal Justice Information Services and the Centers for Disease Control and Prevention, our research team has uncovered a striking correlation coefficient of 0.9512290 (p < 0.01) for the years spanning 2002 to 2021.
The analysis not only highlights the statistically significant relationship between these seemingly disparate phenomena but also sheds light on the "hot" nature of the connection. This paper aims to ignite serious academic discourse regarding the unexpected implications of incendiary incidents on birth rates, sparking a blaze of interest in this niche intersection of criminology and reproductive demography.

ChatGPT:

arson rates, Delaware, triplet births, United States, crime statistics, birth rates, statistical correlation, FBI Criminal Justice Information Services, Centers for Disease Control and Prevention, criminology, reproductive demography

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

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

Correlation r = 0.9512290 (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 = 0.9048366 (Coefficient of determination)
This means 90.5% 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 Delaware) over the 20 years from 2002 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.2E-10.^Show 0.0000000001241546558162732600
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 0.95 in 1.2E-8% of random cases. Said differently, if you correlated 8,054,470,398 random variables^Note You don't actually need 8 billion 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.

[ 0.88, 0.98 ] 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 Delaware (Arson rate)	42.6	44.6	44.1	45.7	45	36.1	41.5	34.8	33.5	32.2	24.6	18.6	22.9	17.1	19	14.4	14.2	13.1	0	15.5
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.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([42.6,44.6,44.1,45.7,45,36.1,41.5,34.8,33.5,32.2,24.6,18.6,22.9,17.1,19,14.4,14.2,13.1,0,15.5,])
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 Delaware"
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 Delaware
Line chart for only US birth rates of triplets or more
AI-generated correlation image
The spurious research paper: Playing with Fire: Exploring the Incendiary Connection Between Arson Rates in Delaware and the Uncommon Incidence of Triplet Births in the United States

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Correlation ID: 2090 · Black Variable ID: 20079 · Red Variable ID: 55


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