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Spurious correlation #1,315 · 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 Andrew and the second variable is Burglaries in Utah.  The chart goes from 1985 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

With fewer Andrews around, there were Andrew-less opportunities for burglar-ly behavior. People just didn't feel as 'drawn' to commit crimes without the 'pop'ularity of the name. It's as if the name Andrew had a, dare I say, 'lock' on crime prevention in Utah!

Model: dalle-3
Prompt: [ A black-and-white newspaper illustration ] of a small-town Utah playground, with a few children playing tag. The name tags of the children are visible, and there are gradually fewer "Andrews" present. As the number of Andrews diminishes, the game becomes more chaotic, with taggers struggling to coordinate their chases amid the decreasing number of participants. 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 situation described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here is a situation: Because the decrease in popularity of the first name Andrew led to fewer people being named Andrew in Utah. With fewer Andrews around, the local burglars lost their main lookout guy, making it harder for them to coordinate their heists.. Given that situation, which of the following image descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand and the tone of the explanation. Please respond with only one of the following potential descriptions: A black-and-white newspaper illustration Surrealism Symbolism Whimsical illustration Vaporwave
ChatGPT: A black-and-white newspaper illustration

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated and the explanation described. Do not reference graphs or charts; describe physical objects.
User prompt: Please describe a visual scene that depicts the following situation. Keep the description simple. Because the decrease in popularity of the first name Andrew led to fewer people being named Andrew in Utah. With fewer Andrews around, the local burglars lost their main lookout guy, making it harder for them to coordinate their heists.
ChatGPT: In a small town in Utah, the playground was less crowded with children playing tag. The children had name tags, and as fewer and fewer Andrews turned up to play, the game became more uncoordinated, with fewer lookouts to keep an eye out for the taggers. The taggers found it harder to coordinate their chases and "heists" without the help of the missing Andrews.

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: [ A black-and-white newspaper illustration ] and depicting this scene: In a small town in Utah, the playground was less crowded with children playing tag. The children had name tags, and as fewer and fewer Andrews turned up to play, the game became more uncoordinated, with fewer lookouts to keep an eye out for the taggers. The taggers found it harder to coordinate their chases and "heists" without the help of the missing Andrews. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ A black-and-white newspaper illustration ] of a small-town Utah playground, with a few children playing tag. The name tags of the children are visible, and there are gradually fewer "Andrews" present. As the number of Andrews diminishes, the game becomes more chaotic, with taggers struggling to coordinate their chases amid the decreasing number of participants.

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

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

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

AI academic paper

(Because p < 0.01)
Breaking and Entering the Name Game: A Burglarious Connection Between Andrew and Utah

Journal of Nameology

Jan 2024

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




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

Please draft the title and abstract of an academic research paper presenting the findings of the connection between Popularity of the first name Andrew and Burglaries in Utah. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

Make the title punny if you can come up with clever pun. If not, just make it sound clever.

Your research team used data from US Social Security Administration and FBI Criminal Justice Information Services to assess this nagging question. You found a correlation coefficient of 0.9671460 and p < 0.01 for 1985 to 2022.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
Breaking and Entering the Name Game: A Burglarious Connection Between Andrew and Utah

[[ABSTRACT]]
This study aims to illuminate the potentially peculiar correlation between the popularity of the given name "Andrew" and burglary incidents in the state of Utah. Leveraging data from the US Social Security Administration and the FBI Criminal Justice Information Services, we employed rigorous statistical analyses to scrutinize this seemingly whimsical link. Our findings unveil a surprisingly robust correlation coefficient of 0.9671460, with a p-value less than 0.01, across the years 1985 to 2022. While the underlying mechanisms of this correlation remain enigmatic, the implications of these findings warrant further investigation and perhaps a lighthearted reflection on the possible influence of nomenclature on criminal propensities. This study not only sheds light on the intersection of nomenclature and criminal behavior but also provides a contemplative repartee to the age-old question, "Does one’s name influentially predispose them to thievery?"


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

Please make up the introduction section of an academic research paper presenting the findings of the connection between Popularity of the first name Andrew and Burglaries in Utah. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
Breaking and Entering the Name Game: A Burglarious Connection Between Andrew and Utah

[[ABSTRACT]]
This study aims to illuminate the potentially peculiar correlation between the popularity of the given name "Andrew" and burglary incidents in the state of Utah. Leveraging data from the US Social Security Administration and the FBI Criminal Justice Information Services, we employed rigorous statistical analyses to scrutinize this seemingly whimsical link. Our findings unveil a surprisingly robust correlation coefficient of 0.9671460, with a p-value less than 0.01, across the years 1985 to 2022. While the underlying mechanisms of this correlation remain enigmatic, the implications of these findings warrant further investigation and perhaps a lighthearted reflection on the possible influence of nomenclature on criminal propensities. This study not only sheds light on the intersection of nomenclature and criminal behavior but also provides a contemplative repartee to the age-old question, "Does one’s name influentially predispose them to thievery?"

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

In the realm of statistical exploration, researchers often find themselves venturing into unforeseen territories, discovering unexpected relationships that challenge conventional wisdom. Our study delves into the fascinating intersection of nomenclature and criminal behavior, with a focus on the distinctive connection between the popularity of the given name "Andrew" and burglary incidents in the captivating state of Utah. While one might initially view this as an offbeat and whimsical pursuit, the robust statistical analyses conducted in this study prod us to consider the possibility of a meaningful correlation lurking behind the seemingly arbitrary pairing of a popular name and the perpetration of property crimes.

The allure of this study lies not only in its unorthodox premise but also in its keen utilization of empirical data to unveil a correlation that is undeniably... arresting. Leveraging a diverse pool of information from the US Social Security Administration and the FBI Criminal Justice Information Services, we embarked on a meticulous quest to discern if there exists any discernible relationship between the eponymous popularity of "Andrew" and the occurrence of unlawful entries into premises in the illustrious state of Utah.

As our analysis unfolds, we invite the reader to join us in this divergent exploration, where we shall unravel the enigmatic statistical patterns that hint at a provocative link between nomenclature and larcenous leanings. Through the lens of rigorous statistical methodologies, we aim to embrace the unexpected and render a compelling narrative that not only enriches the academic literature but also injects an element of whimsy into the staid domain of statistical inquiry. After all, who knew that the teasing tagline "What's in a name?" would lead us down this peculiar path of statistical scrutiny and sociological musing?


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 Andrew and Burglaries in Utah. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

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

Here is the title and abstract of the paper:
[[TITLE]]
Breaking and Entering the Name Game: A Burglarious Connection Between Andrew and Utah

[[ABSTRACT]]
This study aims to illuminate the potentially peculiar correlation between the popularity of the given name "Andrew" and burglary incidents in the state of Utah. Leveraging data from the US Social Security Administration and the FBI Criminal Justice Information Services, we employed rigorous statistical analyses to scrutinize this seemingly whimsical link. Our findings unveil a surprisingly robust correlation coefficient of 0.9671460, with a p-value less than 0.01, across the years 1985 to 2022. While the underlying mechanisms of this correlation remain enigmatic, the implications of these findings warrant further investigation and perhaps a lighthearted reflection on the possible influence of nomenclature on criminal propensities. This study not only sheds light on the intersection of nomenclature and criminal behavior but also provides a contemplative repartee to the age-old question, "Does one’s name influentially predispose them to thievery?"

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
In the realm of statistical exploration, researchers often find themselves venturing into unforeseen territories, discovering unexpected relationships that challenge conventional wisdom. Our study delves into the fascinating intersection of nomenclature and criminal behavior, with a focus on the distinctive connection between the popularity of the given name "Andrew" and burglary incidents in the captivating state of Utah. While one might initially view this as an offbeat and whimsical pursuit, the robust statistical analyses conducted in this study prod us to consider the possibility of a meaningful correlation lurking behind the seemingly arbitrary pairing of a popular name and the perpetration of property crimes.
The allure of this study lies not only in its unorthodox premise but also in its keen utilization of empirical data to unveil a correlation that is undeniably... arresting. Leveraging a diverse pool of information from the US Social Security Administration and the FBI Criminal Justice Information Services, we embarked on a meticulous quest to discern if there exists any discernible relationship between the eponymous popularity of "Andrew" and the occurrence of unlawful entries into premises in the illustrious state of Utah.
As our analysis unfolds, we invite the reader to join us in this divergent exploration, where we shall unravel the enigmatic statistical patterns that hint at a provocative link between nomenclature and larcenous leanings. Through the lens of rigorous statistical methodologies, we aim to embrace the unexpected and render a compelling narrative that not only enriches the academic literature but also injects an element of whimsy into the staid domain of statistical inquiry. After all, who knew that the teasing tagline "What's in a name?" would lead us down this peculiar path of statistical scrutiny and sociological musing?

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The literature on the relationship between personal nomenclature and criminal tendencies is scarce, with only a handful of studies delving into this eccentric realm. Smith (2007) explored the potential influence of given names on criminal behavior and found intriguing associations in a sample of individuals named John, Paul, George, and Ringo. However, the relevance of these findings to the current study on the correlation between the popularity of the name "Andrew" and burglary incidents in Utah remains speculative at best.

Similarly, Doe (2014) conducted a comprehensive analysis of the interplay between moniker popularity and white-collar crimes, revealing curious dynamics among individuals bearing the name "Richard." While the findings added a layer of complexity to the inquiry, they remained tangential to the present investigation.

Jones (2018) examined the impact of names associated with literary figures on illicit activities, embarking on a whimsical journey that scrutinized the potential influence of monikers such as "Hannibal," "Lolita," and "Gatsby." Although the study unleashed a flood of entertaining conjectures, its applicability to the specific correlation between the name "Andrew" and burglaries in Utah remains, regrettably, inconclusive.

Turning our attention to literature that indirectly touches upon the theme of nomenclature and its potential ramifications, the work of "Freakonomics" (Levitt & Dubner, 2005) provides a nuanced view of unconventional societal phenomena, prompting us to ponder the unanticipated pathways through which names may shape human behavior. While not directly addressing our inquiry, this engaging work amplifies our contemplation of the intricate interweaving of names and actions.

In a departure from the world of non-fiction, the fictional landscape offers an assortment of titles that tangentially echo the theme of our investigation. In "The Art of Racing in the Rain" (Stein, 2008), the protagonist's name, Enzo, becomes emblematic of a canine persona grappling with existential complexities, hinting at the potential metaphorical significance of names in navigating the labyrinth of human conduct.

Likewise, in the whimsical world of children's literature and animated entertainment, the adventures of "Arthur" (Brown, 1976) and "Andi Mack" (Minsky & Tesich, 2017) beckon us to contemplate the diversity of experiences encapsulated within distinct names. While these cultural touchstones offer a delightful distraction, they also infuse a spirit of irreverent curiosity into our scholarly pursuit.

In summary, the existing scholarly and entertainment literature offers fragmented insights into the intersection of nomenclature and behavioral proclivities. As we navigate this uncharted terrain of statistical scrutiny and sociological whimsy, we are reminded that research, much like a treasure hunt, often leads us through unexpected alleyways and hidden passages, unraveling enigmatic connections that both confound and captivate our scholarly sensibilities.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 Andrew and Burglaries in Utah. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Breaking and Entering the Name Game: A Burglarious Connection Between Andrew and Utah

[[ABSTRACT]]
This study aims to illuminate the potentially peculiar correlation between the popularity of the given name "Andrew" and burglary incidents in the state of Utah. Leveraging data from the US Social Security Administration and the FBI Criminal Justice Information Services, we employed rigorous statistical analyses to scrutinize this seemingly whimsical link. Our findings unveil a surprisingly robust correlation coefficient of 0.9671460, with a p-value less than 0.01, across the years 1985 to 2022. While the underlying mechanisms of this correlation remain enigmatic, the implications of these findings warrant further investigation and perhaps a lighthearted reflection on the possible influence of nomenclature on criminal propensities. This study not only sheds light on the intersection of nomenclature and criminal behavior but also provides a contemplative repartee to the age-old question, "Does one’s name influentially predispose them to thievery?"

[[INTRODUCTION]]
In the realm of statistical exploration, researchers often find themselves venturing into unforeseen territories, discovering unexpected relationships that challenge conventional wisdom. Our study delves into the fascinating intersection of nomenclature and criminal behavior, with a focus on the distinctive connection between the popularity of the given name "Andrew" and burglary incidents in the captivating state of Utah. While one might initially view this as an offbeat and whimsical pursuit, the robust statistical analyses conducted in this study prod us to consider the possibility of a meaningful correlation lurking behind the seemingly arbitrary pairing of a popular name and the perpetration of property crimes.
The allure of this study lies not only in its unorthodox premise but also in its keen utilization of empirical data to unveil a correlation that is undeniably... arresting. Leveraging a diverse pool of information from the US Social Security Administration and the FBI Criminal Justice Information Services, we embarked on a meticulous quest to discern if there exists any discernible relationship between the eponymous popularity of "Andrew" and the occurrence of unlawful entries into premises in the illustrious state of Utah.
As our analysis unfolds, we invite the reader to join us in this divergent exploration, where we shall unravel the enigmatic statistical patterns that hint at a provocative link between nomenclature and larcenous leanings. Through the lens of rigorous statistical methodologies, we aim to embrace the unexpected and render a compelling narrative that not only enriches the academic literature but also injects an element of whimsy into the staid domain of statistical inquiry. After all, who knew that the teasing tagline "What's in a name?" would lead us down this peculiar path of statistical scrutiny and sociological musing?

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

In order to unfurl the flagrant correlation between the popularity of the moniker "Andrew" and the spate of burglaries in the state of Utah, we embarked on an odyssey of number-crunching and statistical jiggery-pokery. Our data, sourced from the US Social Security Administration and the FBI Criminal Justice Information Services, provided the bedrock for our analysis. With records spanning from the year 1985 to 2022, we amassed an impressive array of information on Andrew's popularity and the incidence of unauthorized domicile entry throughout this period.

For the veritable statistical feast that lay before us, we employed a multifaceted approach sprinkled with a dash of mirth to dissect the potential connection betwixt nomenclature and mischief-making. Our first foray involved the calculation of the popularity of the name "Andrew" in Utah over this timespan, utilizing a keen combination of census data and whimsical extrapolations. This served as the fertile soil from which our investigation could spring forth into the fertile fields of correlation analysis.

Next, we applied rigorous statistical techniques, including but not limited to the prodigious Pearson correlation coefficient, to scrutinize the association between the frequency of the name "Andrew" and the prevalence of burglary occurrences. This elegant dance of numbers led us to the precipice of an immensely striking correlation coefficient of 0.9671460, accompanied by a p-value that gleefully skipped under the 0.01 threshold, much to the surprise of our statistician who had bet against such fortuitous odds.

Additionally, our analysis incorporated a time-series analysis to apprehend any temporal trends in these purportedly peculiar patterns. The dexterous deployment of autoregressive integrated moving average (ARIMA) models and other such sundry statistical forecasts illuminated the nuances of this correlation across the decades. Our journey through this intricate statistical landscape revealed that the connection between Andrew's popularity and burglary incidents was not a mere fleeting fancy, but a curiously constant companion throughout the years, with neither name nor larceny showing signs of abating.

Having navigated this statistical labyrinth, we also indulged in regression analyses to ascertain other potential factors that might confound or elucidate the Andrew-burglary link. With covariates carefully selected to tickle the fancies of our models, we sought to probe deeper into this capricious relationship. The quixotic nature of this investigation left us with no choice but to embrace the unexpected and whimsically wander through the statistical overgrowth, forgoing the well-trodden paths of conventional analyses in favor of a more adventurous quest.

In conclusion, our methodology, while undeniably imbued with a touch of levity, stood as a testament to the dedication and ingenuity with which we sought to untangle this confounding correlation. Through the union of meticulous data collection, calculated statistical analyses, and the occasional sprinkle of statistical fairy dust, we endeavored to shed light on the mysterious dance between nomenclature and nefarious deeds. Our results, as you shall see, present a compelling tableau of statistical harmonies and offbeat synchronies that opens a window into the unexpected joys of statistical exploration.

Our journey continues in the subsequent section, where the findings of our analysis await your perusal.


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

Please make up the results section of an academic research paper presenting the findings of the connection between Popularity of the first name Andrew and Burglaries in Utah. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

For the time period 1985 to 2022, you found a correlation 0.9671460, r-squared of 0.9353713, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
Breaking and Entering the Name Game: A Burglarious Connection Between Andrew and Utah

[[ABSTRACT]]
This study aims to illuminate the potentially peculiar correlation between the popularity of the given name "Andrew" and burglary incidents in the state of Utah. Leveraging data from the US Social Security Administration and the FBI Criminal Justice Information Services, we employed rigorous statistical analyses to scrutinize this seemingly whimsical link. Our findings unveil a surprisingly robust correlation coefficient of 0.9671460, with a p-value less than 0.01, across the years 1985 to 2022. While the underlying mechanisms of this correlation remain enigmatic, the implications of these findings warrant further investigation and perhaps a lighthearted reflection on the possible influence of nomenclature on criminal propensities. This study not only sheds light on the intersection of nomenclature and criminal behavior but also provides a contemplative repartee to the age-old question, "Does one’s name influentially predispose them to thievery?"

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
In the realm of statistical exploration, researchers often find themselves venturing into unforeseen territories, discovering unexpected relationships that challenge conventional wisdom. Our study delves into the fascinating intersection of nomenclature and criminal behavior, with a focus on the distinctive connection between the popularity of the given name "Andrew" and burglary incidents in the captivating state of Utah. While one might initially view this as an offbeat and whimsical pursuit, the robust statistical analyses conducted in this study prod us to consider the possibility of a meaningful correlation lurking behind the seemingly arbitrary pairing of a popular name and the perpetration of property crimes.
The allure of this study lies not only in its unorthodox premise but also in its keen utilization of empirical data to unveil a correlation that is undeniably... arresting. Leveraging a diverse pool of information from the US Social Security Administration and the FBI Criminal Justice Information Services, we embarked on a meticulous quest to discern if there exists any discernible relationship between the eponymous popularity of "Andrew" and the occurrence of unlawful entries into premises in the illustrious state of Utah.
As our analysis unfolds, we invite the reader to join us in this divergent exploration, where we shall unravel the enigmatic statistical patterns that hint at a provocative link between nomenclature and larcenous leanings. Through the lens of rigorous statistical methodologies, we aim to embrace the unexpected and render a compelling narrative that not only enriches the academic literature but also injects an element of whimsy into the staid domain of statistical inquiry. After all, who knew that the teasing tagline "What's in a name?" would lead us down this peculiar path of statistical scrutiny and sociological musing?

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The analysis of data spanning the years 1985 to 2022 has revealed a striking correlation between the popularity of the first name "Andrew" and the occurrences of burglaries in the state of Utah. The correlation coefficient of 0.9671460 suggests a remarkably strong positive linear relationship between the two variables. This robust correlation is further supported by an r-squared value of 0.9353713, indicating that approximately 93.54% of the variability in burglary incidents in Utah can be explained by the popularity of the name "Andrew." Digging deeper into the statistical underworld, we found that the p-value is less than 0.01, providing strong evidence against the null hypothesis and lending additional credence to the observed association.

Additionally, the scatterplot (Fig. 1) displays a clear and positive trend, visually substantiating the formidable connection between the nomenclatural precedence of "Andrew" and the perpetration of unlawful entries into premises in Utah. While the underlying reasons for this surprising correlation remain shrouded in mystery, it is impossible to overlook the statistically significant relationship that emerges from the analysis.

This unexpected confluence of statistically compelling evidence and the subject matter's inherent whimsy urges us to contemplate the influence of nomenclature on criminal proclivities and presents an intriguing avenue for further investigation. The correlation observed in this study not only raises important questions about the potential impact of a name on one's criminal trajectory but also adds a playful twist to the traditionally serious discourse of statistical inquiry. Indeed, it appears that this research has uncovered a “burglarious” connection that is as statistically intriguing as it is whimsically captivating.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 Andrew and Burglaries in Utah. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Breaking and Entering the Name Game: A Burglarious Connection Between Andrew and Utah

[[ABSTRACT]]
This study aims to illuminate the potentially peculiar correlation between the popularity of the given name "Andrew" and burglary incidents in the state of Utah. Leveraging data from the US Social Security Administration and the FBI Criminal Justice Information Services, we employed rigorous statistical analyses to scrutinize this seemingly whimsical link. Our findings unveil a surprisingly robust correlation coefficient of 0.9671460, with a p-value less than 0.01, across the years 1985 to 2022. While the underlying mechanisms of this correlation remain enigmatic, the implications of these findings warrant further investigation and perhaps a lighthearted reflection on the possible influence of nomenclature on criminal propensities. This study not only sheds light on the intersection of nomenclature and criminal behavior but also provides a contemplative repartee to the age-old question, "Does one’s name influentially predispose them to thievery?"

[[LITERATURE REVIEW]]
The literature on the relationship between personal nomenclature and criminal tendencies is scarce, with only a handful of studies delving into this eccentric realm. Smith (2007) explored the potential influence of given names on criminal behavior and found intriguing associations in a sample of individuals named John, Paul, George, and Ringo. However, the relevance of these findings to the current study on the correlation between the popularity of the name "Andrew" and burglary incidents in Utah remains speculative at best.
Similarly, Doe (2014) conducted a comprehensive analysis of the interplay between moniker popularity and white-collar crimes, revealing curious dynamics among individuals bearing the name "Richard." While the findings added a layer of complexity to the inquiry, they remained tangential to the present investigation.
Jones (2018) examined the impact of names associated with literary figures on illicit activities, embarking on a whimsical journey that scrutinized the potential influence of monikers such as "Hannibal," "Lolita," and "Gatsby." Although the study unleashed a flood of entertaining conjectures, its applicability to the specific correlation between the name "Andrew" and burglaries in Utah remains, regrettably, inconclusive.
Turning our attention to literature that indirectly touches upon the theme of nomenclature and its potential ramifications, the work of "Freakonomics" (Levitt & Dubner, 2005) provides a nuanced view of unconventional societal phenomena, prompting us to ponder the unanticipated pathways through which names may shape human behavior. While not directly addressing our inquiry, this engaging work amplifies our contemplation of the intricate interweaving of names and actions.
In a departure from the world of non-fiction, the fictional landscape offers an assortment of titles that tangentially echo the theme of our investigation. In "The Art of Racing in the Rain" (Stein, 2008), the protagonist's name, Enzo, becomes emblematic of a canine persona grappling with existential complexities, hinting at the potential metaphorical significance of names in navigating the labyrinth of human conduct.
Likewise, in the whimsical world of children's literature and animated entertainment, the adventures of "Arthur" (Brown, 1976) and "Andi Mack" (Minsky & Tesich, 2017) beckon us to contemplate the diversity of experiences encapsulated within distinct names. While these cultural touchstones offer a delightful distraction, they also infuse a spirit of irreverent curiosity into our scholarly pursuit.
In summary, the existing scholarly and entertainment literature offers fragmented insights into the intersection of nomenclature and behavioral proclivities. As we navigate this uncharted terrain of statistical scrutiny and sociological whimsy, we are reminded that research, much like a treasure hunt, often leads us through unexpected alleyways and hidden passages, unraveling enigmatic connections that both confound and captivate our scholarly sensibilities.

[[RESULTS]]
The analysis of data spanning the years 1985 to 2022 has revealed a striking correlation between the popularity of the first name "Andrew" and the occurrences of burglaries in the state of Utah. The correlation coefficient of 0.9671460 suggests a remarkably strong positive linear relationship between the two variables. This robust correlation is further supported by an r-squared value of 0.9353713, indicating that approximately 93.54% of the variability in burglary incidents in Utah can be explained by the popularity of the name "Andrew." Digging deeper into the statistical underworld, we found that the p-value is less than 0.01, providing strong evidence against the null hypothesis and lending additional credence to the observed association.
Additionally, the scatterplot (Fig. 1) displays a clear and positive trend, visually substantiating the formidable connection between the nomenclatural precedence of "Andrew" and the perpetration of unlawful entries into premises in Utah. While the underlying reasons for this surprising correlation remain shrouded in mystery, it is impossible to overlook the statistically significant relationship that emerges from the analysis.
This unexpected confluence of statistically compelling evidence and the subject matter's inherent whimsy urges us to contemplate the influence of nomenclature on criminal proclivities and presents an intriguing avenue for further investigation. The correlation observed in this study not only raises important questions about the potential impact of a name on one's criminal trajectory but also adds a playful twist to the traditionally serious discourse of statistical inquiry. Indeed, it appears that this research has uncovered a “burglarious” connection that is as statistically intriguing as it is whimsically captivating.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

The results of our investigation reveal a compelling and statistically significant correlation between the prevalence of the name "Andrew" and incidents of burglary in the state of Utah. To our amusement and surprise, this correlation aligns with the whimsical musings found in the literature, beckoning us to ponder whether one's moniker could indeed act as a subtle influence on their inclination toward criminal activities.

The correlation coefficient of 0.9671460, backed by a p-value less than 0.01, offers unequivocal evidence of a robust connection between the popularity of the name "Andrew" and the perpetration of burglaries. Our findings not only support the fundamental importance of nomenclature in shaping human behavior but also inject a dash of levity into the often somber realm of statistical inquiry.

The integration of nomenclature and criminal proclivities has long been a subject of mirth and speculation, with sporadic forays into the potentially lighthearted intersection of names and actions. As elucidated in the literature review, the scholarly landscape has grappled with whimsical studies examining names such as "John," "Paul," "George," and "Ringo," and the curious dynamics they might incite. While these charming investigations might initially evoke a chuckle, our findings lend substantial credence to the fanciful notion that a name might indeed harbor clandestine influences on one's behavioral predilections.

The scatterplot visually underscores the robustness of this correlation, portraying a clear and positive trend that parallels the statistically significant relationship uncovered in our analysis. The scatterplot, much like a mischievous wink from statistical folklore, conveys the harmonious dance between the name "Andrew" and the occurrences of burglaries in Utah, affirming that correlations can emerge from the most unexpected places.

Moreover, our research adds a vibrant thread to the tapestry of lighthearted scholarly pursuit, inviting a contemplative repartee to the age-old question, "Does one’s name influentially predispose them to thievery?" While remaining cognizant of the inherent whimsy of our investigation, we are reminded of the unexpected charm that statistical inquiry can harbor, spinning a tale as surprising and captivating as the unexpected correlation between the name "Andrew" and burglaries in Utah.

In sum, our findings beckon future researchers to embark on a lighthearted but methodologically rigorous exploration of the intriguing interplay between nomenclature and criminal propensities, embracing the unexpected, and at times, whimsical pathways that statistical inquiry may illuminate. As we navigate this uncharted terrain, we are reminded that statistical investigations, much like a whimsical journey through the world of names and actions, can lead us through unexpected alleyways and hidden passages, unraveling enigmatic connections that both confound and captivate our scholarly sensibilities.


Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics 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 Andrew and Burglaries in Utah. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Breaking and Entering the Name Game: A Burglarious Connection Between Andrew and Utah

[[ABSTRACT]]
This study aims to illuminate the potentially peculiar correlation between the popularity of the given name "Andrew" and burglary incidents in the state of Utah. Leveraging data from the US Social Security Administration and the FBI Criminal Justice Information Services, we employed rigorous statistical analyses to scrutinize this seemingly whimsical link. Our findings unveil a surprisingly robust correlation coefficient of 0.9671460, with a p-value less than 0.01, across the years 1985 to 2022. While the underlying mechanisms of this correlation remain enigmatic, the implications of these findings warrant further investigation and perhaps a lighthearted reflection on the possible influence of nomenclature on criminal propensities. This study not only sheds light on the intersection of nomenclature and criminal behavior but also provides a contemplative repartee to the age-old question, "Does one’s name influentially predispose them to thievery?"

[[INTRDUCTION]]
In the realm of statistical exploration, researchers often find themselves venturing into unforeseen territories, discovering unexpected relationships that challenge conventional wisdom. Our study delves into the fascinating intersection of nomenclature and criminal behavior, with a focus on the distinctive connection between the popularity of the given name "Andrew" and burglary incidents in the captivating state of Utah. While one might initially view this as an offbeat and whimsical pursuit, the robust statistical analyses conducted in this study prod us to consider the possibility of a meaningful correlation lurking behind the seemingly arbitrary pairing of a popular name and the perpetration of property crimes.
The allure of this study lies not only in its unorthodox premise but also in its keen utilization of empirical data to unveil a correlation that is undeniably... arresting. Leveraging a diverse pool of information from the US Social Security Administration and the FBI Criminal Justice Information Services, we embarked on a meticulous quest to discern if there exists any discernible relationship between the eponymous popularity of "Andrew" and the occurrence of unlawful entries into premises in the illustrious state of Utah.
As our analysis unfolds, we invite the reader to join us in this divergent exploration, where we shall unravel the enigmatic statistical patterns that hint at a provocative link between nomenclature and larcenous leanings. Through the lens of rigorous statistical methodologies, we aim to embrace the unexpected and render a compelling narrative that not only enriches the academic literature but also injects an element of whimsy into the staid domain of statistical inquiry. After all, who knew that the teasing tagline "What's in a name?" would lead us down this peculiar path of statistical scrutiny and sociological musing?

[[RESULTS]]
The analysis of data spanning the years 1985 to 2022 has revealed a striking correlation between the popularity of the first name "Andrew" and the occurrences of burglaries in the state of Utah. The correlation coefficient of 0.9671460 suggests a remarkably strong positive linear relationship between the two variables. This robust correlation is further supported by an r-squared value of 0.9353713, indicating that approximately 93.54% of the variability in burglary incidents in Utah can be explained by the popularity of the name "Andrew." Digging deeper into the statistical underworld, we found that the p-value is less than 0.01, providing strong evidence against the null hypothesis and lending additional credence to the observed association.
Additionally, the scatterplot (Fig. 1) displays a clear and positive trend, visually substantiating the formidable connection between the nomenclatural precedence of "Andrew" and the perpetration of unlawful entries into premises in Utah. While the underlying reasons for this surprising correlation remain shrouded in mystery, it is impossible to overlook the statistically significant relationship that emerges from the analysis.
This unexpected confluence of statistically compelling evidence and the subject matter's inherent whimsy urges us to contemplate the influence of nomenclature on criminal proclivities and presents an intriguing avenue for further investigation. The correlation observed in this study not only raises important questions about the potential impact of a name on one's criminal trajectory but also adds a playful twist to the traditionally serious discourse of statistical inquiry. Indeed, it appears that this research has uncovered a “burglarious” connection that is as statistically intriguing as it is whimsically captivating.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our research has uncovered a statistically robust and "burglariously" intriguing correlation between the popularity of the first name "Andrew" and the frequency of burglaries in the state of Utah. The remarkable correlation coefficient of 0.9671460 and the compelling r-squared value of 0.9353713 vividly illustrate the uncanny association between nomenclatural prevalence and the perpetration of property crimes. As we stand on the precipice of this revelatory correlation, it is impossible to overlook the whimsicality of our findings, which add a dash of levity to the weighty realm of statistical inquiry.

While our study may have started with a seemingly offbeat premise, the statistical evidence has propelled us into a thought-provoking journey, where we have unraveled a correlation that stands as arresting as it is unexpected. The scatterplot (Fig. 1) serves as a visual testament to this captivating connection, beckoning us to grapple with the enigma of how a name could potentially influence criminal dispositions. Indeed, we must take a moment to muse on the larcenous allure of the name "Andrew" and its peculiar resonance in the realm of unlawful entries into premises.

Despite the amusement that the findings may elicit, it is crucial to acknowledge the limitations of our study. The enigmatic nature of this correlation beckons for further investigation, yet we are compelled to ponder the possibility that statistical serendipity has led us to this unique juncture of inquiry. Nevertheless, as we reflect on the unexpectedly poignant connection between nomenclature and criminal behavior, one cannot help but marvel at the enticingly whimsical dimensions of statistical exploration.

In light of our findings, we are emboldened to assert that the statistical connection between the name "Andrew" and burglaries in Utah stands as an illuminating deviation from the ordinary, provoking chuckles as much as contemplation. No more research may be warranted in this peculiar area of study, as our findings have brought us to a delightfully unconventional denouement.


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 Breaking and Entering the Name Game: A Burglarious Connection Between Andrew and Utah. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Nameology


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 Breaking and Entering the Name Game: A Burglarious Connection Between Andrew and Utah. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Eccentric Etymology and Geographical Intrigue


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 Breaking and Entering the Name Game: A Burglarious Connection Between Andrew and Utah with an abstract of This study aims to illuminate the potentially peculiar correlation between the popularity of the given name "Andrew" and burglary incidents in the state of Utah. Leveraging data from the US Social Security Administration and the FBI Criminal Justice Information Services, we employed rigorous statistical analyses to scrutinize this seemingly whimsical link. Our findings unveil a surprisingly robust correlation coefficient of 0.9671460, with a p-value less than 0.01, across the years 1985 to 2022. While the underlying mechanisms of this correlation remain enigmatic, the implications of these findings warrant further investigation and perhaps a lighthearted reflection on the possible influence of nomenclature on criminal propensities. This study not only sheds light on the intersection of nomenclature and criminal behavior but also provides a contemplative repartee to the age-old question, "Does one’s name influentially predispose them to thievery?

ChatGPT:

"Andrew name popularity Utah burglary correlation," "nomenclature criminal behavior correlation study," "Andrew name and crime statistics," "name influence on criminal propensities," "social security administration FBI crime data analysis," "impact of nomenclature on criminal behavior," "name and criminal propensities research," "Andrew name burglary correlation study," "naming and criminal behavior analysis."

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

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

Correlation r = 0.9671460 (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 = 0.9353713 (Coefficient of determination)
This means 93.5% of the change in the one variable (i.e., Burglaries in Utah) is predictable based on the change in the other (i.e., Popularity of the first name Andrew) over the 38 years from 1985 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 5.3E-23. 0.0000000000000000000000527409
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.97 in 5.3E-21% of random cases. Said differently, if you correlated 18,960,616,902,631,545,110,528 random variables You don't actually need 18 sextillion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 37 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 37 because we have two variables measured over a period of 38 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.94, 0.98 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!


All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
19851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007200820092010201120122013201420152016201720182019202020212022
Popularity of the first name Andrew (Babies born)303803407136429359603496133775316353063927394260772591025285252572371423902236992246522062221992181320770197521848416799148931427813302126531169211191101459434829173116809606156055131
Burglaries in Utah (Burglary rate)942.9914.9950.9881897880.6840.2885790.8790.8800.8848.3890.5812.9685.1642.5605.8652.2721.1628.9601.2577.3589.5539.6547.9543.9468458.7472.9395.9421.5425379.6319.6270.3290.6239.2201.7




Why this works

  1. Data dredging: I have 25,213 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 635,695,369 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
  2. Lack of causal connection: There is probably Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
    no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
  3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
    p-value calculation does not take this into account, so mathematically it appears less probable than it really is.




Try it yourself

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

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

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

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

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

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

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

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

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


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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([30380,34071,36429,35960,34961,33775,31635,30639,27394,26077,25910,25285,25257,23714,23902,23699,22465,22062,22199,21813,20770,19752,18484,16799,14893,14278,13302,12653,11692,11191,10145,9434,8291,7311,6809,6061,5605,5131,])
array_2 = np.array([942.9,914.9,950.9,881,897,880.6,840.2,885,790.8,790.8,800.8,848.3,890.5,812.9,685.1,642.5,605.8,652.2,721.1,628.9,601.2,577.3,589.5,539.6,547.9,543.9,468,458.7,472.9,395.9,421.5,425,379.6,319.6,270.3,290.6,239.2,201.7,])
array_1_name = "Popularity of the first name Andrew"
array_2_name = "Burglaries in Utah"

# 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)



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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."

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Correlation ID: 1315 · Black Variable ID: 1982 · Red Variable ID: 20123
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