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Spurious correlation #2,092 · 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 Daniel and the second variable is Robberies in Michigan.  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

Fewer individuals were using the name Daniel as their moniker of choice. This led to a decrease in the overall population of Daniels. With fewer Daniels around, there were less likely to be dastardly deeds being carried out. It seems that as the popularity of the name Daniel wanes, so does the proclivity for pilfering in the state of Michigan. It's as if the name itself had some sort of bizarre influence on criminal behavior. Maybe it's a case of Dan-iel-mentary psychology at play here. Or perhaps the real mastermind behind the drop in thefts has been Dan all along. It's a puzzling conundrum, but one thing's for sure: the Dan effect on crime rates is nothing short of astounding!

Model: dalle-3
Prompt: Create an image of a schoolyard in Michigan where a lively group of children are engrossed in a joyous game. One distinctive boy, named Daniel, is at the heart of the action, surrounded by his exuberant friends who are engaged in conversation and laughter. In the background, a photo-realistic police car with flashing lights speeds towards a distant robbery scene, with officers hustling to respond. Capture the contrasting scenes of innocence and real-life urgency in a visually compelling manner. 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 Daniel and Robberies in Michigan. 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: Scalar art A photo-realistic image Surrealism A photo-realistic image Symbolism
ChatGPT: A photo-realistic image

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 Daniel and Robberies in Michigan together. Keep the description simple.
ChatGPT: In a schoolyard in Michigan, a group of children are playing a game together. One boy, named Daniel, is surrounded by his friends, laughing and chatting. In the background, a police car is responding to a robbery nearby, with officers rushing to the scene.

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 photo-realistic image ] and depicting this scene: In a schoolyard in Michigan, a group of children are playing a game together. One boy, named Daniel, is surrounded by his friends, laughing and chatting. In the background, a police car is responding to a robbery nearby, with officers rushing to the scene. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Create an image of a schoolyard in Michigan where a lively group of children are engrossed in a joyous game. One distinctive boy, named Daniel, is at the heart of the action, surrounded by his exuberant friends who are engaged in conversation and laughter. In the background, a photo-realistic police car with flashing lights speeds towards a distant robbery scene, with officers hustling to respond. Capture the contrasting scenes of innocence and real-life urgency in a visually compelling manner.

*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 Daniel caused Robberies in Michigan to decrease.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)
The Stealing Hearts: A Robbing Robber's Romp with Daniel in Michigan Study

The Journal of Criminal Cognition and Deviant Behavior

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

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

Include a pun in the title.

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 0.9755136 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]]
The "Stealing Hearts: A Robbing Robber's Romp with Daniel in Michigan" Study

[[ABSTRACT]]
The quest to apprehend the enigmatic relationship between the popularity of the first name Daniel and the frequency of robberies in the state of Michigan has been a dashing pursuit. Our research team embarked on a riveting investigation, delving deeply into the troves of data from the US Social Security Administration and the FBI Criminal Justice Information Services. Analyzing the time span from 1985 to 2022, we uncovered a remarkably robust correlation coefficient of 0.9755136 and a p-value of less than 0.01, adding a dash of statistical intrigue to the mix.

Whether vagabonds are drawn to the name Daniel like a moth to a flame, or perhaps it is merely a case of serendipitous alignment, our findings are sure to spark lively conversations among researchers and enthusiasts alike. While the true causative factor behind this peculiar correlation remains elusive, one cannot help but marvel at the whimsical twists and turns the world of statistical analysis unveils. This study serves as a gentle reminder that even in the rigorous realm of academic inquiry, one can still find shades of whimsy and wonder.


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

Please make up the introduction section of an academic research paper presenting the findings of the connection between Popularity of the first name Daniel and Robberies in Michigan. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Here is the title and abstract of the paper:
[[TITLE]]
The "Stealing Hearts: A Robbing Robber's Romp with Daniel in Michigan" Study

[[ABSTRACT]]
The quest to apprehend the enigmatic relationship between the popularity of the first name Daniel and the frequency of robberies in the state of Michigan has been a dashing pursuit. Our research team embarked on a riveting investigation, delving deeply into the troves of data from the US Social Security Administration and the FBI Criminal Justice Information Services. Analyzing the time span from 1985 to 2022, we uncovered a remarkably robust correlation coefficient of 0.9755136 and a p-value of less than 0.01, adding a dash of statistical intrigue to the mix.

Whether vagabonds are drawn to the name Daniel like a moth to a flame, or perhaps it is merely a case of serendipitous alignment, our findings are sure to spark lively conversations among researchers and enthusiasts alike. While the true causative factor behind this peculiar correlation remains elusive, one cannot help but marvel at the whimsical twists and turns the world of statistical analysis unveils. This study serves as a gentle reminder that even in the rigorous realm of academic inquiry, one can still find shades of whimsy and wonder.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The captivating intersection of nomenclature and criminality has long intrigued scholars and the general public alike. Our investigation into the interplay between the popularity of the first name Daniel and the frequency of robberies in Michigan unfolds like a gripping mystery novel, with unexpected twists and turns at every corner. Much like Sherlock Holmes on the trail of a perplexing case, we embarked on this compelling study armed with datasets from the US Social Security Administration and the FBI Criminal Justice Information Services spanning the years 1985 to 2022.

As we meticulously sifted through the troves of data, we could not help but appreciate the delightful quirkiness of our subject matter. The idea that the name "Daniel" could wield such mysterious influence over criminal behavior is a notion as charming as it is confounding. Pondering the possibility of a felonious affinity for this particular appellation, we set out to unravel the enigma, armed with statistical tools and a touch of scholarly humor.

The scintillating correlation coefficient of 0.9755136 and a p-value of less than 0.01 that emerged from our analysis added an exhilarating twist to our pursuit. It appeared that the connection between the popularity of the name "Daniel" and the incidence of robberies in the state of Michigan was far from arbitrary. Whether this correlation signals a murky fascination with the name or merely reflects a serendipitous alignment of trends, the unexpectedness of our findings left us gleefully astounded, much like finding a rare gem in a trove of data.

So, dear colleagues and esteemed readers, fasten your seatbelts and prepare for an academic adventure that is as intellectually stimulating as it is delightfully whimsical. The journey ahead promises to shed light on the curious connection between a seemingly innocuous name and the clandestine world of larceny. Indeed, as in the tale of Robin Hood, where an unexpected hero emerges from the shadows, we anticipate that our findings will unveil an unexpected protagonist in this perplexing saga of Daniel and robberies in the state of Michigan.


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Popularity of the first name Daniel and Robberies in Michigan. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a few real TV shows that sound like they might be relevant to the topic that you watched as research.

Here is the title and abstract of the paper:
[[TITLE]]
The "Stealing Hearts: A Robbing Robber's Romp with Daniel in Michigan" Study

[[ABSTRACT]]
The quest to apprehend the enigmatic relationship between the popularity of the first name Daniel and the frequency of robberies in the state of Michigan has been a dashing pursuit. Our research team embarked on a riveting investigation, delving deeply into the troves of data from the US Social Security Administration and the FBI Criminal Justice Information Services. Analyzing the time span from 1985 to 2022, we uncovered a remarkably robust correlation coefficient of 0.9755136 and a p-value of less than 0.01, adding a dash of statistical intrigue to the mix.

Whether vagabonds are drawn to the name Daniel like a moth to a flame, or perhaps it is merely a case of serendipitous alignment, our findings are sure to spark lively conversations among researchers and enthusiasts alike. While the true causative factor behind this peculiar correlation remains elusive, one cannot help but marvel at the whimsical twists and turns the world of statistical analysis unveils. This study serves as a gentle reminder that even in the rigorous realm of academic inquiry, one can still find shades of whimsy and wonder.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The captivating intersection of nomenclature and criminality has long intrigued scholars and the general public alike. Our investigation into the interplay between the popularity of the first name Daniel and the frequency of robberies in Michigan unfolds like a gripping mystery novel, with unexpected twists and turns at every corner. Much like Sherlock Holmes on the trail of a perplexing case, we embarked on this compelling study armed with datasets from the US Social Security Administration and the FBI Criminal Justice Information Services spanning the years 1985 to 2022.
As we meticulously sifted through the troves of data, we could not help but appreciate the delightful quirkiness of our subject matter. The idea that the name "Daniel" could wield such mysterious influence over criminal behavior is a notion as charming as it is confounding. Pondering the possibility of a felonious affinity for this particular appellation, we set out to unravel the enigma, armed with statistical tools and a touch of scholarly humor.
The scintillating correlation coefficient of 0.9755136 and a p-value of less than 0.01 that emerged from our analysis added an exhilarating twist to our pursuit. It appeared that the connection between the popularity of the name "Daniel" and the incidence of robberies in the state of Michigan was far from arbitrary. Whether this correlation signals a murky fascination with the name or merely reflects a serendipitous alignment of trends, the unexpectedness of our findings left us gleefully astounded, much like finding a rare gem in a trove of data.
So, dear colleagues and esteemed readers, fasten your seatbelts and prepare for an academic adventure that is as intellectually stimulating as it is delightfully whimsical. The journey ahead promises to shed light on the curious connection between a seemingly innocuous name and the clandestine world of larceny. Indeed, as in the tale of Robin Hood, where an unexpected hero emerges from the shadows, we anticipate that our findings will unveil an unexpected protagonist in this perplexing saga of Daniel and robberies in the state of Michigan.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The correlation between individual names and societal behaviors has been a subject of interest in various academic disciplines, spanning from psychology to sociology. Smith et al. (2010) delved into the psychological effects of nomenclature, outlining the potential influence of a person's name on their behavior and identity. Similarly, Doe and Jones (2015) explored the social implications of names, highlighting the intricate relationship between nomenclature and cultural perceptions. This body of literature sets the stage for our investigation into the curious correlation between the prevalence of the first name Daniel and the occurrence of robberies in the state of Michigan.

Beyond the academic realm, works like "The Power of Names" by Adams (2018) and "The Name Game: Exploring the Art and Science of Naming" by Smith (2017) provide insightful perspectives on the significance of names in shaping human experiences and societal dynamics. These sources offer a broader context for understanding the potential impact of a name, such as Daniel, on behavioral patterns within a given population.

In the realm of fiction, novels such as "The Robber of Sherwood" by Merryweather (2019) and "Daniel and the Caper Chronicles" by Johnson (2016) offer imaginative portrayals of crime and derring-do, albeit in fictional settings. Although these works are not empirical studies, they underscore the enduring allure of narratives surrounding theft and the enigmatic allure of names in storytelling.

Furthermore, our investigation was informed by popular television shows with criminal themes, including "Breaking Bad" and "Sherlock," as well as light-hearted comedies like "Brooklyn Nine-Nine," which provided both entertainment and potential insights into criminal behavior and its depiction in popular media. While these sources may not directly address the correlation between the name Daniel and robberies in Michigan, they undoubtedly contributed to a multidimensional understanding of the broader cultural context in which our study is situated.

As we plunge into the enchanting nexus of nomenclature and criminal activities, we acknowledge the serendipitous charm of our pursuit and the unexpected avenues it has led us down. The scholarly exploration of this curiously peculiar correlation promises to unveil the delightful whimsy that underpins the intricate fabric of our world, beckoning us to embrace the dashing romp between the name Daniel and the realm of larceny in the state of Michigan.


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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Popularity of the first name Daniel and Robberies in Michigan. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Your research team collected data from all across the internet, but mostly just used information from 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]]
The "Stealing Hearts: A Robbing Robber's Romp with Daniel in Michigan" Study

[[ABSTRACT]]
The quest to apprehend the enigmatic relationship between the popularity of the first name Daniel and the frequency of robberies in the state of Michigan has been a dashing pursuit. Our research team embarked on a riveting investigation, delving deeply into the troves of data from the US Social Security Administration and the FBI Criminal Justice Information Services. Analyzing the time span from 1985 to 2022, we uncovered a remarkably robust correlation coefficient of 0.9755136 and a p-value of less than 0.01, adding a dash of statistical intrigue to the mix.

Whether vagabonds are drawn to the name Daniel like a moth to a flame, or perhaps it is merely a case of serendipitous alignment, our findings are sure to spark lively conversations among researchers and enthusiasts alike. While the true causative factor behind this peculiar correlation remains elusive, one cannot help but marvel at the whimsical twists and turns the world of statistical analysis unveils. This study serves as a gentle reminder that even in the rigorous realm of academic inquiry, one can still find shades of whimsy and wonder.

[[INTRODUCTION]]
The captivating intersection of nomenclature and criminality has long intrigued scholars and the general public alike. Our investigation into the interplay between the popularity of the first name Daniel and the frequency of robberies in Michigan unfolds like a gripping mystery novel, with unexpected twists and turns at every corner. Much like Sherlock Holmes on the trail of a perplexing case, we embarked on this compelling study armed with datasets from the US Social Security Administration and the FBI Criminal Justice Information Services spanning the years 1985 to 2022.
As we meticulously sifted through the troves of data, we could not help but appreciate the delightful quirkiness of our subject matter. The idea that the name "Daniel" could wield such mysterious influence over criminal behavior is a notion as charming as it is confounding. Pondering the possibility of a felonious affinity for this particular appellation, we set out to unravel the enigma, armed with statistical tools and a touch of scholarly humor.
The scintillating correlation coefficient of 0.9755136 and a p-value of less than 0.01 that emerged from our analysis added an exhilarating twist to our pursuit. It appeared that the connection between the popularity of the name "Daniel" and the incidence of robberies in the state of Michigan was far from arbitrary. Whether this correlation signals a murky fascination with the name or merely reflects a serendipitous alignment of trends, the unexpectedness of our findings left us gleefully astounded, much like finding a rare gem in a trove of data.
So, dear colleagues and esteemed readers, fasten your seatbelts and prepare for an academic adventure that is as intellectually stimulating as it is delightfully whimsical. The journey ahead promises to shed light on the curious connection between a seemingly innocuous name and the clandestine world of larceny. Indeed, as in the tale of Robin Hood, where an unexpected hero emerges from the shadows, we anticipate that our findings will unveil an unexpected protagonist in this perplexing saga of Daniel and robberies in the state of Michigan.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To embark on this riveting academic escapade, our research team employed a mixture of traditional and innovative methodologies—equally reminiscent of Holmes' astute deductive reasoning and Q's ingenious gadgets from the James Bond series. Our primary data sources encompassed the US Social Security Administration and the FBI Criminal Justice Information Services, which served as the treasure troves for our quest.

The analysis methodology combined a splendid blend of quantitative techniques, jaw-dropping statistical acrobatics, and a touch of old-fashioned gumshoe investigation. We began by meticulously gathering the historical data concerning the popularity of the first name "Daniel" from the US Social Security Administration. This involved wading through countless records, akin to Sherlock Holmes scrutinizing minute details in the throes of solving a mysterious case—an endeavor that proved to be both exhilarating and, at times, as tedious as counting every grain of sand on a beach.

Simultaneously, we ventured into the figurative labyrinth of FBI Criminal Justice Information Services' archives to extract the pivotal statistics on the frequency of robberies in the state of Michigan. This digital quest was akin to a technological treasure hunt, with every keystroke leading us closer to the elusive truth. The data, much like a cryptic riddle, held the promise of unveiling the hidden connection between the popularity of the name Daniel and the incidence of robberies, whispering tantalizing secrets and ushering us into a world of suspense and intrigue.

With these datasets in hand, we unleashed the full force of statistical analysis, equipping ourselves with powerful software akin to the proverbial Excalibur, to uncover any shred of a connection between the popularity of the name "Daniel" and the anomalies in the frequency of robberies in the state of Michigan. Our statistical maneuvers encompassed the deployment of correlation analyses, regression models, and a gaggle of exploratory techniques, all designed to extract every last drop of insight from the labyrinthine web of data.

Furthermore, we dabbled in the arcane art of time-series analyses to capture the dynamics of temporal changes in both the popularity of the name "Daniel" and the frequency of robberies in Michigan. We delved into the time-traveling realm of historical data, scrutinizing trends and patterns with the gusto of an intrepid explorer charting uncharted territories.

While our odyssey encountered many challenges and whimsical surprises along the way, our approach fused elements of meticulous inquiry with a playful spirit, elevating the often-dry domain of academic research to a realm of intellectual adventure. At every turn, we remained ever vigilant for unexpected insights, recognizing that often, it is in the unlikeliest of places that one uncovers the most remarkable treasures.


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

Please make up the results section of an academic research paper presenting the findings of the connection between Popularity of the first name Daniel and Robberies in Michigan. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

For the time period 1985 to 2022, you found a correlation 0.9755136, r-squared of 0.9516269, 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]]
The "Stealing Hearts: A Robbing Robber's Romp with Daniel in Michigan" Study

[[ABSTRACT]]
The quest to apprehend the enigmatic relationship between the popularity of the first name Daniel and the frequency of robberies in the state of Michigan has been a dashing pursuit. Our research team embarked on a riveting investigation, delving deeply into the troves of data from the US Social Security Administration and the FBI Criminal Justice Information Services. Analyzing the time span from 1985 to 2022, we uncovered a remarkably robust correlation coefficient of 0.9755136 and a p-value of less than 0.01, adding a dash of statistical intrigue to the mix.

Whether vagabonds are drawn to the name Daniel like a moth to a flame, or perhaps it is merely a case of serendipitous alignment, our findings are sure to spark lively conversations among researchers and enthusiasts alike. While the true causative factor behind this peculiar correlation remains elusive, one cannot help but marvel at the whimsical twists and turns the world of statistical analysis unveils. This study serves as a gentle reminder that even in the rigorous realm of academic inquiry, one can still find shades of whimsy and wonder.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The captivating intersection of nomenclature and criminality has long intrigued scholars and the general public alike. Our investigation into the interplay between the popularity of the first name Daniel and the frequency of robberies in Michigan unfolds like a gripping mystery novel, with unexpected twists and turns at every corner. Much like Sherlock Holmes on the trail of a perplexing case, we embarked on this compelling study armed with datasets from the US Social Security Administration and the FBI Criminal Justice Information Services spanning the years 1985 to 2022.
As we meticulously sifted through the troves of data, we could not help but appreciate the delightful quirkiness of our subject matter. The idea that the name "Daniel" could wield such mysterious influence over criminal behavior is a notion as charming as it is confounding. Pondering the possibility of a felonious affinity for this particular appellation, we set out to unravel the enigma, armed with statistical tools and a touch of scholarly humor.
The scintillating correlation coefficient of 0.9755136 and a p-value of less than 0.01 that emerged from our analysis added an exhilarating twist to our pursuit. It appeared that the connection between the popularity of the name "Daniel" and the incidence of robberies in the state of Michigan was far from arbitrary. Whether this correlation signals a murky fascination with the name or merely reflects a serendipitous alignment of trends, the unexpectedness of our findings left us gleefully astounded, much like finding a rare gem in a trove of data.
So, dear colleagues and esteemed readers, fasten your seatbelts and prepare for an academic adventure that is as intellectually stimulating as it is delightfully whimsical. The journey ahead promises to shed light on the curious connection between a seemingly innocuous name and the clandestine world of larceny. Indeed, as in the tale of Robin Hood, where an unexpected hero emerges from the shadows, we anticipate that our findings will unveil an unexpected protagonist in this perplexing saga of Daniel and robberies in the state of Michigan.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The analysis of the data extracted from the US Social Security Administration and the FBI Criminal Justice Information Services revealed a remarkably robust correlation between the popularity of the first name Daniel and the occurrences of robberies in the state of Michigan. Our findings unveiled a correlation coefficient of 0.9755136, indicating a strong positive relationship between the two variables. The coefficient of determination (r-squared) was calculated to be 0.9516269, suggesting that approximately 95.2% of the variability in the frequency of robberies in Michigan can be explained by the popularity of the name Daniel. Utilizing rigorous statistical tests, we obtained a p-value of less than 0.01, signifying a highly significant relationship between the variables.

Our results are depicted in Fig. 1, showcasing a scatterplot that vividly portrays the robust correlation observed between the popularity of the first name Daniel and the occurrence of robberies. This visually compelling representation serves as a testament to the striking relationship elucidated by our analysis.

The sheer strength of the correlation prompts contemplation of intriguing possibilities. Could it be that the name "Daniel" exerts a magnetic pull on individuals with criminal inclinations, or does it simply share an inexplicably intertwined fate with the clandestine world of larceny in Michigan? While we are unable to ascertain the causative mechanisms underlying this correlation, the intriguing nature of our findings undoubtedly adds a refreshing dash of intrigue to the realm of statistical inquiry.

These results beckon a deeper understanding of the mysterious dance between nomenclature and criminal behavior, inviting further scholarly investigation and contemplation. The enigma of the connection between the popularity of the first name Daniel and the frequency of robberies in Michigan infuses the scholarly pursuit with a sense of wonder, underlining the boundless potential for unexpected revelations in the world of academic inquiry.


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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Popularity of the first name Daniel and Robberies in Michigan. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

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

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

[[TITLE]]
The "Stealing Hearts: A Robbing Robber's Romp with Daniel in Michigan" Study

[[ABSTRACT]]
The quest to apprehend the enigmatic relationship between the popularity of the first name Daniel and the frequency of robberies in the state of Michigan has been a dashing pursuit. Our research team embarked on a riveting investigation, delving deeply into the troves of data from the US Social Security Administration and the FBI Criminal Justice Information Services. Analyzing the time span from 1985 to 2022, we uncovered a remarkably robust correlation coefficient of 0.9755136 and a p-value of less than 0.01, adding a dash of statistical intrigue to the mix.

Whether vagabonds are drawn to the name Daniel like a moth to a flame, or perhaps it is merely a case of serendipitous alignment, our findings are sure to spark lively conversations among researchers and enthusiasts alike. While the true causative factor behind this peculiar correlation remains elusive, one cannot help but marvel at the whimsical twists and turns the world of statistical analysis unveils. This study serves as a gentle reminder that even in the rigorous realm of academic inquiry, one can still find shades of whimsy and wonder.

[[LITERATURE REVIEW]]
The correlation between individual names and societal behaviors has been a subject of interest in various academic disciplines, spanning from psychology to sociology. Smith et al. (2010) delved into the psychological effects of nomenclature, outlining the potential influence of a person's name on their behavior and identity. Similarly, Doe and Jones (2015) explored the social implications of names, highlighting the intricate relationship between nomenclature and cultural perceptions. This body of literature sets the stage for our investigation into the curious correlation between the prevalence of the first name Daniel and the occurrence of robberies in the state of Michigan.
Beyond the academic realm, works like "The Power of Names" by Adams (2018) and "The Name Game: Exploring the Art and Science of Naming" by Smith (2017) provide insightful perspectives on the significance of names in shaping human experiences and societal dynamics. These sources offer a broader context for understanding the potential impact of a name, such as Daniel, on behavioral patterns within a given population.
In the realm of fiction, novels such as "The Robber of Sherwood" by Merryweather (2019) and "Daniel and the Caper Chronicles" by Johnson (2016) offer imaginative portrayals of crime and derring-do, albeit in fictional settings. Although these works are not empirical studies, they underscore the enduring allure of narratives surrounding theft and the enigmatic allure of names in storytelling.
Furthermore, our investigation was informed by popular television shows with criminal themes, including "Breaking Bad" and "Sherlock," as well as light-hearted comedies like "Brooklyn Nine-Nine," which provided both entertainment and potential insights into criminal behavior and its depiction in popular media. While these sources may not directly address the correlation between the name Daniel and robberies in Michigan, they undoubtedly contributed to a multidimensional understanding of the broader cultural context in which our study is situated.
As we plunge into the enchanting nexus of nomenclature and criminal activities, we acknowledge the serendipitous charm of our pursuit and the unexpected avenues it has led us down. The scholarly exploration of this curiously peculiar correlation promises to unveil the delightful whimsy that underpins the intricate fabric of our world, beckoning us to embrace the dashing romp between the name Daniel and the realm of larceny in the state of Michigan.

[[RESULTS]]
The analysis of the data extracted from the US Social Security Administration and the FBI Criminal Justice Information Services revealed a remarkably robust correlation between the popularity of the first name Daniel and the occurrences of robberies in the state of Michigan. Our findings unveiled a correlation coefficient of 0.9755136, indicating a strong positive relationship between the two variables. The coefficient of determination (r-squared) was calculated to be 0.9516269, suggesting that approximately 95.2% of the variability in the frequency of robberies in Michigan can be explained by the popularity of the name Daniel. Utilizing rigorous statistical tests, we obtained a p-value of less than 0.01, signifying a highly significant relationship between the variables.
Our results are depicted in Fig. 1, showcasing a scatterplot that vividly portrays the robust correlation observed between the popularity of the first name Daniel and the occurrence of robberies. This visually compelling representation serves as a testament to the striking relationship elucidated by our analysis.
The sheer strength of the correlation prompts contemplation of intriguing possibilities. Could it be that the name "Daniel" exerts a magnetic pull on individuals with criminal inclinations, or does it simply share an inexplicably intertwined fate with the clandestine world of larceny in Michigan? While we are unable to ascertain the causative mechanisms underlying this correlation, the intriguing nature of our findings undoubtedly adds a refreshing dash of intrigue to the realm of statistical inquiry.
These results beckon a deeper understanding of the mysterious dance between nomenclature and criminal behavior, inviting further scholarly investigation and contemplation. The enigma of the connection between the popularity of the first name Daniel and the frequency of robberies in Michigan infuses the scholarly pursuit with a sense of wonder, underlining the boundless potential for unexpected revelations in the world of academic inquiry.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The curious correlation between the prevalence of the first name Daniel and the frequency of robberies in Michigan has sparked a captivating intellectual romp, with intriguing implications for both the realm of statistical inquiry and the whimsical world of nomenclature. Our findings align with previous studies that have explored the enthralling interplay between names and societal behaviors. It appears that the name "Daniel" not only evokes heroic narratives in fiction, as evidenced by the works of Merryweather and Johnson, but also seems to interlace with real-world criminal activities, as indicated by the robust correlation uncovered in our analysis.

The notion of a name influencing individual behavior and societal dynamics, as postulated by Smith et al. (2010) and Doe and Jones (2015), finds resonance in our discovery of a striking relationship between the prevalence of the name Daniel and the occurrences of robberies in Michigan. This correlation adds a fascinating layer to the multidimensional significance of names, extending beyond cultural perceptions, as explored by Adams (2018) and Smith (2017), to potential behavioral manifestations within specific populations. The alignment between our results and the scholarly discourse on the power of nomenclature hints at the delightful whimsy that underpins the intricate fabric of our world, beckoning us to embrace the dashing romp between the name Daniel and the realm of larceny in the state of Michigan.

Additionally, the depiction of criminal behavior in popular media, as reflected in television shows such as "Breaking Bad," "Sherlock," and "Brooklyn Nine-Nine," offers a broader cultural context for our investigation. Although these sources may not directly address the correlation between the name Daniel and robberies in Michigan, they contribute to a multidimensional understanding of the thematic allure of theft and the enigmatic resonance of names as portrayed in entertainment. The intersection between our academic inquiry and the realms of fiction and popular media infuses our findings with a delightful sense of whimsy, underscoring the serendipitous charm of our pursuit.

The robust correlation coefficient and the highly significant p-value obtained in our analysis highlight the compelling nature of the relationship between the name Daniel and the frequency of robberies in Michigan. While we acknowledge the limitations of establishing causative mechanisms, the remarkable strength of the correlation prompts contemplation of intriguing possibilities, adding a refreshing dash of intrigue to the realm of statistical inquiry. The enigmatic dance between nomenclature and criminal behavior beckons further scholarly investigation, infusing the pursuit with a sense of wonder and the boundless potential for unexpected revelations.

In essence, our study serves as a compelling reminder that even in the rigorous realm of academic inquiry, the dashing romp between the name Daniel and the world of larceny in Michigan invites us to embrace the whimsical and the unexpected, challenging us to uncover the delightful mysteries that await in the most unsuspecting places.


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Popularity of the first name Daniel and Robberies in Michigan. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
The "Stealing Hearts: A Robbing Robber's Romp with Daniel in Michigan" Study

[[ABSTRACT]]
The quest to apprehend the enigmatic relationship between the popularity of the first name Daniel and the frequency of robberies in the state of Michigan has been a dashing pursuit. Our research team embarked on a riveting investigation, delving deeply into the troves of data from the US Social Security Administration and the FBI Criminal Justice Information Services. Analyzing the time span from 1985 to 2022, we uncovered a remarkably robust correlation coefficient of 0.9755136 and a p-value of less than 0.01, adding a dash of statistical intrigue to the mix.

Whether vagabonds are drawn to the name Daniel like a moth to a flame, or perhaps it is merely a case of serendipitous alignment, our findings are sure to spark lively conversations among researchers and enthusiasts alike. While the true causative factor behind this peculiar correlation remains elusive, one cannot help but marvel at the whimsical twists and turns the world of statistical analysis unveils. This study serves as a gentle reminder that even in the rigorous realm of academic inquiry, one can still find shades of whimsy and wonder.

[[INTRDUCTION]]
The captivating intersection of nomenclature and criminality has long intrigued scholars and the general public alike. Our investigation into the interplay between the popularity of the first name Daniel and the frequency of robberies in Michigan unfolds like a gripping mystery novel, with unexpected twists and turns at every corner. Much like Sherlock Holmes on the trail of a perplexing case, we embarked on this compelling study armed with datasets from the US Social Security Administration and the FBI Criminal Justice Information Services spanning the years 1985 to 2022.
As we meticulously sifted through the troves of data, we could not help but appreciate the delightful quirkiness of our subject matter. The idea that the name "Daniel" could wield such mysterious influence over criminal behavior is a notion as charming as it is confounding. Pondering the possibility of a felonious affinity for this particular appellation, we set out to unravel the enigma, armed with statistical tools and a touch of scholarly humor.
The scintillating correlation coefficient of 0.9755136 and a p-value of less than 0.01 that emerged from our analysis added an exhilarating twist to our pursuit. It appeared that the connection between the popularity of the name "Daniel" and the incidence of robberies in the state of Michigan was far from arbitrary. Whether this correlation signals a murky fascination with the name or merely reflects a serendipitous alignment of trends, the unexpectedness of our findings left us gleefully astounded, much like finding a rare gem in a trove of data.
So, dear colleagues and esteemed readers, fasten your seatbelts and prepare for an academic adventure that is as intellectually stimulating as it is delightfully whimsical. The journey ahead promises to shed light on the curious connection between a seemingly innocuous name and the clandestine world of larceny. Indeed, as in the tale of Robin Hood, where an unexpected hero emerges from the shadows, we anticipate that our findings will unveil an unexpected protagonist in this perplexing saga of Daniel and robberies in the state of Michigan.

[[RESULTS]]
The analysis of the data extracted from the US Social Security Administration and the FBI Criminal Justice Information Services revealed a remarkably robust correlation between the popularity of the first name Daniel and the occurrences of robberies in the state of Michigan. Our findings unveiled a correlation coefficient of 0.9755136, indicating a strong positive relationship between the two variables. The coefficient of determination (r-squared) was calculated to be 0.9516269, suggesting that approximately 95.2% of the variability in the frequency of robberies in Michigan can be explained by the popularity of the name Daniel. Utilizing rigorous statistical tests, we obtained a p-value of less than 0.01, signifying a highly significant relationship between the variables.
Our results are depicted in Fig. 1, showcasing a scatterplot that vividly portrays the robust correlation observed between the popularity of the first name Daniel and the occurrence of robberies. This visually compelling representation serves as a testament to the striking relationship elucidated by our analysis.
The sheer strength of the correlation prompts contemplation of intriguing possibilities. Could it be that the name "Daniel" exerts a magnetic pull on individuals with criminal inclinations, or does it simply share an inexplicably intertwined fate with the clandestine world of larceny in Michigan? While we are unable to ascertain the causative mechanisms underlying this correlation, the intriguing nature of our findings undoubtedly adds a refreshing dash of intrigue to the realm of statistical inquiry.
These results beckon a deeper understanding of the mysterious dance between nomenclature and criminal behavior, inviting further scholarly investigation and contemplation. The enigma of the connection between the popularity of the first name Daniel and the frequency of robberies in Michigan infuses the scholarly pursuit with a sense of wonder, underlining the boundless potential for unexpected revelations in the world of academic inquiry.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our invigorating expedition through the labyrinthine corridors of statistical analysis has illuminated an extraordinary correlation between the widespread usage of the appellation "Daniel" and the incidents of larceny in the state of Michigan. The captivating correlation coefficient of 0.9755136, akin to a compelling protagonist in a gripping novel, intertwines these seemingly disparate elements into an enigmatic dance of statistical significance. The sheer strength of this correlation, reminiscent of a formidable bond between two unlikely allies, beckons further contemplation regarding the underlying mechanisms of this intriguing relationship.

The undeniable allure of this connection prompts whimsical musings on the possibility of an underground society of "Daniels" orchestrating clandestine heists across the state. As we tread the blurry line between scholarly fascination and fanciful speculation, we cannot help but marvel at the serendipitous alignment of trends that has led us to this perplexing juncture. It appears that the name "Daniel" possesses an unexpected magnetic charm, drawing the attention of both statisticians and potential perpetrators alike.

As we bid adieu to this enthralling escapade, we are left with the lingering sense that the world of statistical inquiry holds untold mysteries, much like a treasure trove waiting to be unearthed. Our findings stand as a testament to the enduring enigma of the human experience, an enigmatic riddle that continues to elude our understanding despite the rigors of empirical analysis. In the spirit of academic inquiry, we embrace the wondrous unpredictability of our findings and the delightful quirks that emerge amidst the quest for knowledge.

Therefore, with a curious twinkle in our eyes and a touch of scholarly mischief, we emphatically declare that no further research is needed in this curious domain. As we bid farewell to the captivating saga of Daniel and robberies in Michigan, it is our hope that this study will inspire future researchers to embrace the delightful interplay of whimsy and wonder within the hallowed halls of academic inquiry.


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 The Stealing Hearts: A Robbing Robber's Romp with Daniel in Michigan Study. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Criminal Cognition and Deviant Behavior


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 The Stealing Hearts: A Robbing Robber's Romp with Daniel in Michigan Study. Respond only with the name of a fictional organization.

ChatGPT:

Society for the Study of Quirky Criminal Behavior


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 The Stealing Hearts: A Robbing Robber's Romp with Daniel in Michigan Study with an abstract of The quest to apprehend the enigmatic relationship between the popularity of the first name Daniel and the frequency of robberies in the state of Michigan has been a dashing pursuit. Our research team embarked on a riveting investigation, delving deeply into the troves of data from the US Social Security Administration and the FBI Criminal Justice Information Services. Analyzing the time span from 1985 to 2022, we uncovered a remarkably robust correlation coefficient of 0.9755136 and a p-value of less than 0.01, adding a dash of statistical intrigue to the mix.
Whether vagabonds are drawn to the name Daniel like a moth to a flame, or perhaps it is merely a case of serendipitous alignment, our findings are sure to spark lively conversations among researchers and enthusiasts alike. While the true causative factor behind this peculiar correlation remains elusive, one cannot help but marvel at the whimsical twists and turns the world of statistical analysis unveils. This study serves as a gentle reminder that even in the rigorous realm of academic inquiry, one can still find shades of whimsy and wonder.

ChatGPT:

Daniel popularity, robberies in Michigan, correlation coefficient, US Social Security Administration, FBI Criminal Justice Information Services, statistical analysis, causative factor, academic inquiry

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

Robberies in Michigan
Detailed data title: The robbery rate per 100,000 residents in Michigan
Source: FBI Criminal Justice Information Services
See what else correlates with Robberies in Michigan

Correlation r = 0.9755136 (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 = 0.9516269 (Coefficient of determination)
This means 95.2% of the change in the one variable (i.e., Robberies in Michigan) is predictable based on the change in the other (i.e., Popularity of the first name Daniel) over the 38 years from 1985 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.8E-25. 0.0000000000000000000000002843
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 0.98 in 2.8E-23% of random cases. Said differently, if you correlated 3,517,411,185,367,568,986,669,056 random variables You don't actually need 3 septillion 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.

[ 0.95, 0.99 ] 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 Daniel (Babies born)3885836865361343499635199339753109329303288182819126830251962402823235227662239721072213752111621076202772012320288190681759715886153211431714340139741355213008117521129310587951991319058
Robberies in Michigan (Robbery rate)292.4301.3276.5241.1222.3234243.3221.5238.5228.9187.3176.2152.8155.8143138129.3118111.6112.2132.1140.9132.7132.4124.6116.7103.9105.51028178.871.765.256.553.644.540.236.6




Why this works

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




Try it yourself

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

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

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

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

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

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

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

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

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


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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([38858,36865,36134,34996,35199,33975,31093,29303,28818,28191,26830,25196,24028,23235,22766,22397,21072,21375,21116,21076,20277,20123,20288,19068,17597,15886,15321,14317,14340,13974,13552,13008,11752,11293,10587,9519,9131,9058,])
array_2 = np.array([292.4,301.3,276.5,241.1,222.3,234,243.3,221.5,238.5,228.9,187.3,176.2,152.8,155.8,143,138,129.3,118,111.6,112.2,132.1,140.9,132.7,132.4,124.6,116.7,103.9,105.5,102,81,78.8,71.7,65.2,56.5,53.6,44.5,40.2,36.6,])
array_1_name = "Popularity of the first name Daniel"
array_2_name = "Robberies in Michigan"

# 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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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.

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Correlation ID: 2092 · Black Variable ID: 1983 · Red Variable ID: 20196
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