Spurious correlation #3,634 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Orlando and the second variable is Burglaries in West Virginia. The chart goes from 1985 to 2022, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Orlando and the second variable is Burglaries in West Virginia. The chart goes from 1985 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

Fewer parents were naming their kids after the city in Florida, leading to a decrease in subconscious desires to visit sunny, crime-free locations. As a result, the overall burglary rates in West Virginia decreased, because, let's face it, nobody wants to steal West Virginia's thunder.

^{Show image generation prompt} Model: dalle-3
Prompt: An image that looks like it is a scene from 'Star Wars', depicting a chart showing the decreasing popularity of the first name Orlando with a line graph gently declining. Below it, imagine a map of West Virginia with a diminishing number of burglar icons scattered across the state, signaling a decrease in burglaries. In the middle, picture a group of burglars sitting around, looking gloomy and deflated as if they've lost their motivation. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Popularity of the first name Orlando and Burglaries in West Virginia. 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: Whimsical illustration Psychedelic Cubism An image that looks like it is a scene from 'Star Wars' Steampunk
ChatGPT: An image that looks like it is a scene from 'Star Wars'

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Popularity of the first name Orlando and Burglaries in West Virginia, in the following situation: The decrease in popularity of the first name Orlando caused burglaries in West Virginia to decrease because the burglars were so upset about the decline in Orlandos that they decided to take a break and reevaluate their career choices.. Keep the description simple.
ChatGPT: Picture a chart showing the decreasing popularity of the first name Orlando, with a line graph gently declining. Below it, imagine a map of West Virginia with a diminishing number of burglar icons scattered across the state, signaling a decrease in burglaries. In the middle, picture a group of burglars sitting around, looking gloomy and deflated, as if they've lost their motivation.

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 'Star Wars' ] and depicting this scene: Picture a chart showing the decreasing popularity of the first name Orlando, with a line graph gently declining. Below it, imagine a map of West Virginia with a diminishing number of burglar icons scattered across the state, signaling a decrease in burglaries. In the middle, picture a group of burglars sitting around, looking gloomy and deflated, as if they've lost their motivation. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: An image that looks like it is a scene from 'Star Wars', depicting a chart showing the decreasing popularity of the first name Orlando with a line graph gently declining. Below it, imagine a map of West Virginia with a diminishing number of burglar icons scattered across the state, signaling a decrease in burglaries. In the middle, picture a group of burglars sitting around, looking gloomy and deflated as if they've lost their motivation.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how a decrease in Popularity of the first name Orlando caused Burglaries in West Virginia to decrease.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)

Orlando's Popularity and West Virginia's Criminality: A Correlational Study

The Journal of Quirky Social Science

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Popularity of the first name Orlando and Burglaries in West Virginia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading CVS receipts.

Here is the title and abstract of the paper:
[[TITLE]]
Orlando's Popularity and West Virginia's Criminality: A Correlational Study

[[ABSTRACT]]
The correlation between the popularity of the first name Orlando and the incidence of burglaries in West Virginia was examined in this research. Utilizing data from the US Social Security Administration and the FBI Criminal Justice Information Services, a thorough analysis was conducted covering the years 1985 to 2022. The results revealed a striking correlation coefficient of 0.8525528 and a statistically significant p-value of less than 0.01. It seems that there may be more to the name Orlando than meets the eye, as it appears to exhibit an unexpected association with criminal activity in the mountain state.

While the popular saying goes that "Orlando steals your heart," our research suggests that it may also be associated with a higher likelihood of theft in certain regions. However, the causal mechanism underlying this correlation remains an intriguing area for future exploration. This study sheds light on the curious relationship between naming trends and criminal behavior, offering a fresh perspective on the factors influencing regional crime rates.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The relationship between personal names and various aspects of life has been a topic of fascination for researchers and humorists alike. From the classic "Knock, knock. Who's there? Olive. Olive who? Olive(live) next door to you!" to the more serious inquiries into the socio-economic implications of names, there is no denying the impact of nomenclature on our perceptions and experiences.
In this vein, the curious case of the name Orlando and its potential connection to the incidence of burglaries in West Virginia has piqued our interest. It seems that beyond its association with theme parks and literary characters, the name Orlando may carry an unexpected statistic significance.
Much like a lock without a key, the correlation between the popularity of the name Orlando and the occurrence of burglaries in West Virginia appears to be a conundrum begging for exploration. As we delve into this enigma, we will inevitably encounter statistical complexities, methodological mysteries, and perhaps a pun or two along the way.
The interplay between seemingly unrelated variables such as names and crime rates invites us to ponder the intricacies of societal influences. It prompts us to question whether there is more than meets the eye in the dance of data and demographics.
With curiosity as our compass and a healthy dose of statistical skepticism as our guiding star, we embark on the journey to unravel the tangled web of Orlando's popularity and West Virginia's criminality. As we navigate through the labyrinth of correlation and causation, we remain mindful of the potential for serendipitous discoveries and unexpected revelations, much like finding a hidden treasure in a field of data.
Thus, we begin our quest to shed light on the curious relationship between the eponymous and the criminal, armed with graphs, charts, and a dash of whimsy. For as the research gods say, "May your p-values be small and your confidence intervals be tight."

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The theoretical framework for linking the popularity of a first name to criminal behavior finds its roots in sociological and psychological research. Smith et al. (2010) illuminate the influence of self-fulfilling prophecies and stereotype threat in shaping individuals' behavioral tendencies, suggesting that the social connotations of a given name may inadvertently influence one's actions. Additionally, Doe (2015) highlights the role of societal expectations and name-based biases in shaping individuals' self-perception and subsequent behavior, further underpinning the plausibility of a connection between nomenclature and criminality.

It appears that the name "Orlando" may have the potential to open doors - but perhaps not in the conventional sense. This unexpected association between a seemingly innocuous name and criminal activity prompts a re-examination of the societal influences that shape human behavior. It invites us to question whether the pattern in the data is a mere coincidence or a meaningful reflection of underlying psychological or sociological dynamics. While the divine "may your p-values be small and your confidence intervals be tight" provides a guiding light in our statistical endeavors, it cannot illuminate the humorous intricacies of potential causative mechanisms.

In "The Geography of Names" by M. H. DeMille, the exploration of regional naming trends intersects with the terrain of criminal behavior, offering a tantalizing glimpse into the unexpected interplay of geographic nomenclature and illicit activities. This intersection hints at the possibility of a hidden correlation between the eponymous and the criminal, echoing the very essence of our inquiry.

Moreover, in the fictional realm, works such as "The Burglar on the Name Trail" and "Orlando's Odyssey: A Crime Story" by Agatha Detective present narratives where the eponymous protagonist finds himself embroiled in criminal escapades, providing a whimsical parallel to our empirical exploration. The fictional representation of Orlando's entanglement in criminal mysteries serves as a lighthearted reflection of the unexpected correlation unearthed in our empirical investigation, compelling us to ponder the intricate layers of reality and fiction.

In a departure from conventional academic sources, an unconventional approach to literature review was necessitated. The exhaustive examination of the connection between the popularity of the first name Orlando and burglaries in West Virginia extended to the unlikely domains of cultural artifacts, including but not limited to, the obscure musings on CVS receipts. While this pursuit elicited quizzical looks and raised eyebrows from the research community, it yielded no discernible insights into the perplexing connection at hand, serving as a gentle reminder that not all paths lead to empirical enlightenment.

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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Popularity of the first name Orlando and Burglaries in West Virginia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and FBI Criminal Justice Information Services . You used data from 1985 to 2022

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Orlando's Popularity and West Virginia's Criminality: A Correlational Study

[[ABSTRACT]]
The correlation between the popularity of the first name Orlando and the incidence of burglaries in West Virginia was examined in this research. Utilizing data from the US Social Security Administration and the FBI Criminal Justice Information Services, a thorough analysis was conducted covering the years 1985 to 2022. The results revealed a striking correlation coefficient of 0.8525528 and a statistically significant p-value of less than 0.01. It seems that there may be more to the name Orlando than meets the eye, as it appears to exhibit an unexpected association with criminal activity in the mountain state.

While the popular saying goes that "Orlando steals your heart," our research suggests that it may also be associated with a higher likelihood of theft in certain regions. However, the causal mechanism underlying this correlation remains an intriguing area for future exploration. This study sheds light on the curious relationship between naming trends and criminal behavior, offering a fresh perspective on the factors influencing regional crime rates.

[[INTRODUCTION]]
The relationship between personal names and various aspects of life has been a topic of fascination for researchers and humorists alike. From the classic "Knock, knock. Who's there? Olive. Olive who? Olive(live) next door to you!" to the more serious inquiries into the socio-economic implications of names, there is no denying the impact of nomenclature on our perceptions and experiences.
In this vein, the curious case of the name Orlando and its potential connection to the incidence of burglaries in West Virginia has piqued our interest. It seems that beyond its association with theme parks and literary characters, the name Orlando may carry an unexpected statistic significance.
Much like a lock without a key, the correlation between the popularity of the name Orlando and the occurrence of burglaries in West Virginia appears to be a conundrum begging for exploration. As we delve into this enigma, we will inevitably encounter statistical complexities, methodological mysteries, and perhaps a pun or two along the way.
The interplay between seemingly unrelated variables such as names and crime rates invites us to ponder the intricacies of societal influences. It prompts us to question whether there is more than meets the eye in the dance of data and demographics.
With curiosity as our compass and a healthy dose of statistical skepticism as our guiding star, we embark on the journey to unravel the tangled web of Orlando's popularity and West Virginia's criminality. As we navigate through the labyrinth of correlation and causation, we remain mindful of the potential for serendipitous discoveries and unexpected revelations, much like finding a hidden treasure in a field of data.
Thus, we begin our quest to shed light on the curious relationship between the eponymous and the criminal, armed with graphs, charts, and a dash of whimsy. For as the research gods say, "May your p-values be small and your confidence intervals be tight."

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

Data Collection:

The first step in unraveling the mystery of Orlando's name and its possible correlation with burglaries in West Virginia involved the collection of extensive data spanning the years 1985 to 2022. The US Social Security Administration and the FBI's Criminal Justice Information Services were the primary sources of information, providing a treasure trove of statistical gems to be mined in pursuit of our research objectives. Like prospectors panning for gold in a digital creek, our team meticulously gathered the nuggets of data necessary to illuminate the relationship between nomenclature and nefarious deeds.

Variable Selection:

With data in hand, the next task was to identify the pertinent variables for our analysis. The frequency of the first name Orlando within the population of West Virginia served as our measure of nomenclatural prominence. Concurrently, the incidence of burglaries in the state over the aforementioned time period constituted our indicator of criminal activity. This selection process brought to mind the timeless question: "Which comes first, the burglary or the Orlando?"

Statistical Analysis:

Employing robust statistical methods, we set out to scrutinize the relationship between the popularity of the name Orlando and the occurrence of burglaries in West Virginia. A correlation analysis was conducted to ascertain the strength and direction of the association, akin to investigating the pull of two celestial bodies in the vast universe of data. The correlation coefficient emerged as the celestial compass guiding our exploration, revealing the degree of alignment between Orlando's allure and the allure of illicit activities in the Mountain State.

Furthermore, a regression analysis was employed to ascertain the predictive power of the name Orlando on burglary rates, allowing us to peek into the crystal ball of statistical forecasting. Finally, a time-series analysis was conducted to discern any temporal patterns in the fluctuating fortunes of Orlando's popularity and the ebb and flow of the criminal tide in West Virginia. This endeavor was akin to deciphering the whims of an enigmatic oracle, hoping to glean insight into the curious dance of variables across the temporal landscape.

Data Verification and Validation:

To ensure the trustworthiness of our findings, extensive cross-validation and sensitivity analyses were performed, akin to a meticulous examination of a time-traveling apparatus to ascertain its reliability and consistency. This validation process sought to affirm the robustness of our results and mitigate the risk of spurious correlations masquerading as empirical truths. In the words of a timeless sage: "Trust, but verify."

Ethical Considerations:

As custodians of data and guardians of truth, ethical principles guided every phase of our research endeavor. Respect for privacy and confidentiality underscored our approach to handling sensitive personal information, akin to caretakers safeguarding the sanctity of individuals' statistical identities. In our pursuit of knowledge, we remained mindful of the imperative to uphold the dignity of those whose numerical footprints shaped our investigation, and thus proceeded with the utmost ethical mindfulness.

Limitations:

Although our analyses yielded intriguing insights, it is essential to acknowledge the limitations inherent in correlational research. Causation cannot be inferred from correlation alone, and lurking variables may yet reveal themselves like undercover agents in a statistical spy thriller, casting a shadow of uncertainty over our findings. Furthermore, regional and temporal variations in naming trends and criminal behavior may introduce complexities requiring further exploration, much like untangling a Gordian knot of statistical conundrums.

In summation, through a blend of diligent data collection, rigorous statistical analyses, and unwavering ethical adherence, our research seeks to shed light on the curious link between the popularity of the name Orlando and the incidence of burglaries in West Virginia. As we venture further into the statistical wilderness, guided by the twin torches of methodological rigor and statistical slyness, we remain poised to uncover hidden truths and unexpected revelations, armed with nothing but our wits and an unyielding dedication to unraveling the enigmatic web of correlation and causation.

As the saying goes, "May your data be clean and your correlations be meaningful."

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Popularity of the first name Orlando and Burglaries in West Virginia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Orlando's Popularity and West Virginia's Criminality: A Correlational Study

[[ABSTRACT]]
The correlation between the popularity of the first name Orlando and the incidence of burglaries in West Virginia was examined in this research. Utilizing data from the US Social Security Administration and the FBI Criminal Justice Information Services, a thorough analysis was conducted covering the years 1985 to 2022. The results revealed a striking correlation coefficient of 0.8525528 and a statistically significant p-value of less than 0.01. It seems that there may be more to the name Orlando than meets the eye, as it appears to exhibit an unexpected association with criminal activity in the mountain state.

While the popular saying goes that "Orlando steals your heart," our research suggests that it may also be associated with a higher likelihood of theft in certain regions. However, the causal mechanism underlying this correlation remains an intriguing area for future exploration. This study sheds light on the curious relationship between naming trends and criminal behavior, offering a fresh perspective on the factors influencing regional crime rates.

[[LITERATURE REVIEW]]
The theoretical framework for linking the popularity of a first name to criminal behavior finds its roots in sociological and psychological research. Smith et al. (2010) illuminate the influence of self-fulfilling prophecies and stereotype threat in shaping individuals' behavioral tendencies, suggesting that the social connotations of a given name may inadvertently influence one's actions. Additionally, Doe (2015) highlights the role of societal expectations and name-based biases in shaping individuals' self-perception and subsequent behavior, further underpinning the plausibility of a connection between nomenclature and criminality.
It appears that the name "Orlando" may have the potential to open doors - but perhaps not in the conventional sense. This unexpected association between a seemingly innocuous name and criminal activity prompts a re-examination of the societal influences that shape human behavior. It invites us to question whether the pattern in the data is a mere coincidence or a meaningful reflection of underlying psychological or sociological dynamics. While the divine "may your p-values be small and your confidence intervals be tight" provides a guiding light in our statistical endeavors, it cannot illuminate the humorous intricacies of potential causative mechanisms.
In "The Geography of Names" by M. H. DeMille, the exploration of regional naming trends intersects with the terrain of criminal behavior, offering a tantalizing glimpse into the unexpected interplay of geographic nomenclature and illicit activities. This intersection hints at the possibility of a hidden correlation between the eponymous and the criminal, echoing the very essence of our inquiry.
Moreover, in the fictional realm, works such as "The Burglar on the Name Trail" and "Orlando's Odyssey: A Crime Story" by Agatha Detective present narratives where the eponymous protagonist finds himself embroiled in criminal escapades, providing a whimsical parallel to our empirical exploration. The fictional representation of Orlando's entanglement in criminal mysteries serves as a lighthearted reflection of the unexpected correlation unearthed in our empirical investigation, compelling us to ponder the intricate layers of reality and fiction.
In a departure from conventional academic sources, an unconventional approach to literature review was necessitated. The exhaustive examination of the connection between the popularity of the first name Orlando and burglaries in West Virginia extended to the unlikely domains of cultural artifacts, including but not limited to, the obscure musings on CVS receipts. While this pursuit elicited quizzical looks and raised eyebrows from the research community, it yielded no discernible insights into the perplexing connection at hand, serving as a gentle reminder that not all paths lead to empirical enlightenment.

[[RESULTS]]
The analysis of the data spanning from 1985 to 2022 revealed a robust and intriguing correlation between the popularity of the first name Orlando and the incidence of burglaries in West Virginia. The correlation coefficient, calculated to be 0.8525528, demonstrates a remarkably strong positive relationship between these variables. This finding suggests that as the popularity of the name Orlando increased, so did the frequency of burglaries in the mountain state.
It seems that the name Orlando may not only be associated with magical adventures in theme parks, but also with a statistical quirk in the realm of criminal activity. Perhaps the phrase should be updated to "Orlando steals your heart and possibly your TV too."
The r-squared value of 0.7268463 further elucidates the strength of the association, indicating that approximately 72.7% of the variability in the incidence of burglaries in West Virginia can be explained by the popularity of the name Orlando. This indicates a high degree of predictability in the relationship, akin to being able to predict the likelihood of a good dad joke at a family gathering.
Furthermore, the p-value of less than 0.01 underscores the statistical significance of the correlation, providing strong evidence against the null hypothesis. In other words, the likelihood of observing such a strong relationship between the popularity of the name Orlando and burglaries in West Virginia due to chance alone is exceedingly small, much like finding a needle in a haystack, or a burglar in a dark alley.
Figure 1 presents a scatterplot illustrating the compelling correlation between the popularity of the name Orlando and the incidence of burglaries in West Virginia. The data points form a distinct positive trend, visually reinforcing the strong statistical relationship observed in our analysis. This figure serves as a poignant reminder that sometimes, truth is indeed stranger than fiction, much like realizing that correlation does not necessarily imply causation, but it sure makes for an interesting conversation starter.
Overall, these results offer a thought-provoking insight into the interplay between naming trends and criminal behavior, prompting further contemplation of the intricate factors shaping regional crime rates. And as we unravel the mysteries of data with our trusty statistical toolkit, we cannot help but wonder, what's in a name? In the case of Orlando, apparently more than we might think.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of the present study provide compelling support for the previously posited theoretical and empirical link between the popularity of the first name Orlando and the incidence of burglaries in West Virginia. The robust correlation coefficient of 0.8525528 aligns with the conceptual groundwork laid by Smith et al. (2010) and Doe (2015), suggesting that societal expectations and name-based biases may indeed shape behavioral tendencies, and in this case, potentially contribute to criminal activity. It seems that the name Orlando, known for its associations with adventure and charisma, might harbor a darker side, akin to a character in a suspenseful novel who turns out to have a hidden agenda – or should we say "hidden moniker"?

These findings also echo the unexpected parallels observed in works such as "The Burglar on the Name Trail," where the eponymous protagonist becomes ensnared in criminal escapades, offering a nod to the peculiar correlation uncovered in our investigation. The statistical robustness of the correlation further reinforces the plausibility of a meaningful connection, leaving us to ponder whether the rise in popularity of the name Orlando coincided with a surge in illicit escapades, perhaps hinting at a mysterious influence at play, much akin to a skilled illusionist who can make statistics dance to a lively tune.

The strength of the association, as evidenced by the high r-squared value of 0.7268463, illuminates the substantial predictability in the relationship, akin to foreseeing the likelihood of a well-timed dad joke at a family gathering. Additionally, the statistically significant p-value of less than 0.01 unequivocally dismisses the notion of a chance occurrence, highlighting the unmistakable nature of the correlation. It appears that the connection between the popularity of the name Orlando and burglaries in West Virginia is not just a fluke, much like how a sudden downpour during a statistical conference isn't merely a coincidence, but rather a statistical anomaly – or in this case, a "rain of insights".

The scatterplot depicting the relationship between the popularity of the name Orlando and the incidence of burglaries in West Virginia serves as a visual testament to the compelling nature of the correlation, raising intriguing questions about the underlying dynamics at play. It is reminiscent of a puzzling mystery novel that beckons the reader to unravel its enigmatic clues, leaving us to ponder what unforeseen variables may be contributing to this curious relationship, much like sleuths piecing together evidence to uncover a hidden truth amidst the statistical noise.

In summary, this study contributes to the growing body of evidence that suggests a deeper connection between naming trends and criminal behavior. The unexpected correlation between the popularity of the name Orlando and burglaries in West Virginia prompts a reevaluation of the factors influencing regional crime rates and invites further exploration into the nuanced interplay of nomenclature and societal constructs. As we delve deeper into the layers of this peculiar association, we are reminded that sometimes, statistical relationships can hold unexpected revelations and hints of humor – much like a cleverly crafted dad joke that catches one off guard and leaves a lasting impression.

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Popularity of the first name Orlando and Burglaries in West Virginia. You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Orlando's Popularity and West Virginia's Criminality: A Correlational Study

[[ABSTRACT]]
The correlation between the popularity of the first name Orlando and the incidence of burglaries in West Virginia was examined in this research. Utilizing data from the US Social Security Administration and the FBI Criminal Justice Information Services, a thorough analysis was conducted covering the years 1985 to 2022. The results revealed a striking correlation coefficient of 0.8525528 and a statistically significant p-value of less than 0.01. It seems that there may be more to the name Orlando than meets the eye, as it appears to exhibit an unexpected association with criminal activity in the mountain state.

While the popular saying goes that "Orlando steals your heart," our research suggests that it may also be associated with a higher likelihood of theft in certain regions. However, the causal mechanism underlying this correlation remains an intriguing area for future exploration. This study sheds light on the curious relationship between naming trends and criminal behavior, offering a fresh perspective on the factors influencing regional crime rates.

[[INTRDUCTION]]
The relationship between personal names and various aspects of life has been a topic of fascination for researchers and humorists alike. From the classic "Knock, knock. Who's there? Olive. Olive who? Olive(live) next door to you!" to the more serious inquiries into the socio-economic implications of names, there is no denying the impact of nomenclature on our perceptions and experiences.
In this vein, the curious case of the name Orlando and its potential connection to the incidence of burglaries in West Virginia has piqued our interest. It seems that beyond its association with theme parks and literary characters, the name Orlando may carry an unexpected statistic significance.
Much like a lock without a key, the correlation between the popularity of the name Orlando and the occurrence of burglaries in West Virginia appears to be a conundrum begging for exploration. As we delve into this enigma, we will inevitably encounter statistical complexities, methodological mysteries, and perhaps a pun or two along the way.
The interplay between seemingly unrelated variables such as names and crime rates invites us to ponder the intricacies of societal influences. It prompts us to question whether there is more than meets the eye in the dance of data and demographics.
With curiosity as our compass and a healthy dose of statistical skepticism as our guiding star, we embark on the journey to unravel the tangled web of Orlando's popularity and West Virginia's criminality. As we navigate through the labyrinth of correlation and causation, we remain mindful of the potential for serendipitous discoveries and unexpected revelations, much like finding a hidden treasure in a field of data.
Thus, we begin our quest to shed light on the curious relationship between the eponymous and the criminal, armed with graphs, charts, and a dash of whimsy. For as the research gods say, "May your p-values be small and your confidence intervals be tight."

[[RESULTS]]
The analysis of the data spanning from 1985 to 2022 revealed a robust and intriguing correlation between the popularity of the first name Orlando and the incidence of burglaries in West Virginia. The correlation coefficient, calculated to be 0.8525528, demonstrates a remarkably strong positive relationship between these variables. This finding suggests that as the popularity of the name Orlando increased, so did the frequency of burglaries in the mountain state.
It seems that the name Orlando may not only be associated with magical adventures in theme parks, but also with a statistical quirk in the realm of criminal activity. Perhaps the phrase should be updated to "Orlando steals your heart and possibly your TV too."
The r-squared value of 0.7268463 further elucidates the strength of the association, indicating that approximately 72.7% of the variability in the incidence of burglaries in West Virginia can be explained by the popularity of the name Orlando. This indicates a high degree of predictability in the relationship, akin to being able to predict the likelihood of a good dad joke at a family gathering.
Furthermore, the p-value of less than 0.01 underscores the statistical significance of the correlation, providing strong evidence against the null hypothesis. In other words, the likelihood of observing such a strong relationship between the popularity of the name Orlando and burglaries in West Virginia due to chance alone is exceedingly small, much like finding a needle in a haystack, or a burglar in a dark alley.
Figure 1 presents a scatterplot illustrating the compelling correlation between the popularity of the name Orlando and the incidence of burglaries in West Virginia. The data points form a distinct positive trend, visually reinforcing the strong statistical relationship observed in our analysis. This figure serves as a poignant reminder that sometimes, truth is indeed stranger than fiction, much like realizing that correlation does not necessarily imply causation, but it sure makes for an interesting conversation starter.
Overall, these results offer a thought-provoking insight into the interplay between naming trends and criminal behavior, prompting further contemplation of the intricate factors shaping regional crime rates. And as we unravel the mysteries of data with our trusty statistical toolkit, we cannot help but wonder, what's in a name? In the case of Orlando, apparently more than we might think.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, the correlation between the popularity of the first name Orlando and the incidence of burglaries in West Virginia has unveiled a surprising statistical relationship. This finding has illuminated a unique dimension of societal dynamics, reminding us that even the most unexpected variables may be intertwined in the web of statistical association.

Linguistic and criminological scholars may find themselves pondering the implications of this correlation, musing on whether there is, in fact, something truly 'thefty' about the name Orlando. It seems that while "Orlando steals your heart," it may also have a knack for eliciting a statistical 'break-in' in certain contexts, much like the unexpected appearance of a dad joke in a serious conversation.

The statistical robustness of our findings, including the correlation coefficient of 0.8525528 and the p-value of less than 0.01, reinforces the significance of this correlation. This serves as a gentle reminder that even in the world of research, sometimes the most unexpected relationships can be statistically sound, much like stumbling upon a statistical unicorn in a field of data analysis.

As our analysis grapples with the enigma of Orlando's popularity and West Virginia's criminality, it becomes evident that this unexpected correlation has spurred conversations and contemplations worthy of further exploration. This study sets the stage for future investigations into the complex interplay between names, societal perceptions, and behavior. It also reminds us that when it comes to statistical analysis, sometimes the most peculiar correlations can hold surprising insights, akin to finding a nugget of wisdom in a sea of data.

Despite the lighthearted humor that permeates our discussion, the implications of this correlation are not to be dismissed lightly. The potential influence of naming trends on societal phenomena raises thought-provoking questions, and the curious case of Orlando and West Virginia beckons further inquiry into the multifaceted world of statistical associations and societal influences. However, researchers are cautioned not to jump to conclusions, as correlation does not imply causation – although it does make for a captivating tidbit at academic soirées and dinner parties.

In light of these findings, it seems that no more research is needed in this particular area - unless, of course, one wishes to explore the criminal proclivities of other names. In the wise words of a seasoned researcher: "May your samples be representative, and your hypotheses thought-provoking!"

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 Orlando's Popularity and West Virginia's Criminality: A Correlational Study. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Quirky Social Science

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 Orlando's Popularity and West Virginia's Criminality: A Correlational Study. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Regional Affinity Research and Analysis

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 Orlando's Popularity and West Virginia's Criminality: A Correlational Study with an abstract of The correlation between the popularity of the first name Orlando and the incidence of burglaries in West Virginia was examined in this research. Utilizing data from the US Social Security Administration and the FBI Criminal Justice Information Services, a thorough analysis was conducted covering the years 1985 to 2022. The results revealed a striking correlation coefficient of 0.8525528 and a statistically significant p-value of less than 0.01. It seems that there may be more to the name Orlando than meets the eye, as it appears to exhibit an unexpected association with criminal activity in the mountain state.
While the popular saying goes that "Orlando steals your heart," our research suggests that it may also be associated with a higher likelihood of theft in certain regions. However, the causal mechanism underlying this correlation remains an intriguing area for future exploration. This study sheds light on the curious relationship between naming trends and criminal behavior, offering a fresh perspective on the factors influencing regional crime rates.

ChatGPT:

Orlando popularity, West Virginia criminality, correlation study, first name popularity, crime rates, naming trends, burglary incidence, US Social Security Administration data, FBI Criminal Justice Information Services, correlation coefficient, statistical significance, regional crime rates, naming trends and criminal behavior, Orlando association with criminal activity

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

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Data details

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

Burglaries in West Virginia
Detailed data title: The burglary rate per 100,000 residents in West Virginia
Source: FBI Criminal Justice Information Services
See what else correlates with Burglaries in West Virginia

Correlation r = 0.8525528 (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 = 0.7268463 (Coefficient of determination)
This means 72.7% of the change in the one variable (i.e., Burglaries in West Virginia) is predictable based on the change in the other (i.e., Popularity of the first name Orlando) over the 38 years from 1985 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.1E-11.^Show 0.0000000000109945850378800340
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 0.85 in 1.1E-9% of random cases. Said differently, if you correlated 90,953,864,703 random variables^Note You don't actually need 90 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 37 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 37 because we have two variables measured over a period of 38 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.73, 0.92 ] 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.

	1985	1986	1987	1988	1989	1990	1991	1992	1993	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Popularity of the first name Orlando (Babies born)	743	826	889	884	847	805	793	669	691	666	665	654	645	629	680	634	731	708	702	779	813	853	860	697	719	633	545	590	471	491	438	430	392	379	336	306	334	307
Burglaries in West Virginia (Burglary rate)	618.4	625.3	603.6	610.9	626.5	657.1	666.8	622.9	599.1	585.8	565	546.5	586.3	613.5	570.2	546.9	533.1	536.2	579.5	606.5	624.8	636.7	597.2	597.4	659.7	581.2	552.3	617.6	534.5	506.7	514.2	499.1	415.9	327.9	294.2	273.3	215	190.2

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.
Confounding variable: 2020 is particularly different from the other years on this graph. Confounding variables (like global pandemics) will cause two variables to look connected when in fact a "sneaky third" variable is influencing both of them behind the scenes.

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([743,826,889,884,847,805,793,669,691,666,665,654,645,629,680,634,731,708,702,779,813,853,860,697,719,633,545,590,471,491,438,430,392,379,336,306,334,307,])
array_2 = np.array([618.4,625.3,603.6,610.9,626.5,657.1,666.8,622.9,599.1,585.8,565,546.5,586.3,613.5,570.2,546.9,533.1,536.2,579.5,606.5,624.8,636.7,597.2,597.4,659.7,581.2,552.3,617.6,534.5,506.7,514.2,499.1,415.9,327.9,294.2,273.3,215,190.2,])
array_1_name = "Popularity of the first name Orlando"
array_2_name = "Burglaries in West Virginia"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

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

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Popularity of the first name Orlando
Line chart for only Burglaries in West Virginia
AI-generated correlation image
The spurious research paper: Orlando's Popularity and West Virginia's Criminality: A Correlational Study

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Correlation ID: 3634 · Black Variable ID: 2735 · Red Variable ID: 20127


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