about · email me · subscribe
Spurious correlation #4,049 · 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 Katharine and the second variable is Robberies in Colorado.  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

As the name Katharine fell out of favor, so did the trendy activity of committing robberies in Colorado. It seems that Katharine just couldn't catch a break, but the good citizens of Colorado certainly did!

Model: dalle-3
Prompt: An image that looks like it is a scene from a Pixar movie: In a bustling Colorado town, a traditional wooden sign proudly marked "Welcome to Katharine Street" hangs against a backdrop of charming brick buildings. The warm sun creates a soft glow, casting a lively atmosphere over the scene. Nearby, a group of children play in a vibrant park filled with colorful flowers and towering trees. The name "Katharine" adorns the sign, slowly fading into the background as it becomes less popular among parents. Meanwhile, a news headline flashes "Robberies in Colorado Reach Record Low" on a nearby screen, highlighting the diminishing influence of the once-infamous bank robber Kitty Katharine, her notoriety fading into obscurity. 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 Katharine and Robberies in Colorado. 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: Glitch art Cutsy graphics An image that looks like it is a scene from a Pixar movie Cute cartoon Woodblock painting
ChatGPT: An image that looks like it is a scene from a Pixar movie

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Popularity of the first name Katharine and Robberies in Colorado, in the following situation: Because as the popularity of the name Katharine decreased, fewer people were naming their daughters after the infamous bank robber Kitty Katharine, which led to a decrease in robberies in Colorado as her notoriety dwindled.. Keep the description simple.
ChatGPT: In a bustling Colorado town, a traditional wooden sign marked "Welcome to Katharine Street" hung proudly in the warm sun. Nearby, a group of children played in a vibrant park as the name Katharine became less popular among parents. Meanwhile, a news headline flashed "Robberies in Colorado Reach Record Low" as the once-infamous bank robber Kitty Katharine slipped into obscurity, greatly diminishing her influence.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ An image that looks like it is a scene from a Pixar movie ] and depicting this scene: In a bustling Colorado town, a traditional wooden sign marked "Welcome to Katharine Street" hung proudly in the warm sun. Nearby, a group of children played in a vibrant park as the name Katharine became less popular among parents. Meanwhile, a news headline flashed "Robberies in Colorado Reach Record Low" as the once-infamous bank robber Kitty Katharine slipped into obscurity, greatly diminishing her influence. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: An image that looks like it is a scene from a Pixar movie: In a bustling Colorado town, a traditional wooden sign proudly marked "Welcome to Katharine Street" hangs against a backdrop of charming brick buildings. The warm sun creates a soft glow, casting a lively atmosphere over the scene. Nearby, a group of children play in a vibrant park filled with colorful flowers and towering trees. The name "Katharine" adorns the sign, slowly fading into the background as it becomes less popular among parents. Meanwhile, a news headline flashes "Robberies in Colorado Reach Record Low" on a nearby screen, highlighting the diminishing influence of the once-infamous bank robber Kitty Katharine, her notoriety fading into obscurity.

*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 Katharine caused Robberies in Colorado to decrease.

AI academic paper

(Because p < 0.01)
The Katharine Crime Connection: Colorado's Curious Crime Correlation

The Journal of Quirky Criminology

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 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 Katharine and Robberies in Colorado. Make lots of jokes, goofy observations, and puns.

Make the title an alliteration.

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 0.9200450 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 Katharine Crime Connection: Colorado's Curious Crime Correlation

[[ABSTRACT]]
In this study, we delved into the peculiar connection between the popularity of the first name Katharine and the incidence of robberies in the state of Colorado. Utilizing data extracted from the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted an extensive analysis spanning the years 1985 to 2022. The results revealed a striking correlation coefficient of 0.9200450 and statistically significant p-value of less than 0.01, suggesting a robust association between the frequency of the name Katharine and the occurrence of theft-related offenses within the Colorado region.

The findings of our study raise intriguing questions regarding the potential influence of nomenclature on criminal behavior, prompting contemplation on the role of moniker trends in shaping societal dynamics. While causation cannot be definitively inferred from our correlational analysis, the "Katharine Crime Connection" presents an engrossing avenue for further exploration, offering a whimsical twist on the intersections of nomenclature and nefarious activities.


Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Katharine and Robberies in Colorado. Make lots of 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 Katharine Crime Connection: Colorado's Curious Crime Correlation

[[ABSTRACT]]
In this study, we delved into the peculiar connection between the popularity of the first name Katharine and the incidence of robberies in the state of Colorado. Utilizing data extracted from the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted an extensive analysis spanning the years 1985 to 2022. The results revealed a striking correlation coefficient of 0.9200450 and statistically significant p-value of less than 0.01, suggesting a robust association between the frequency of the name Katharine and the occurrence of theft-related offenses within the Colorado region.

The findings of our study raise intriguing questions regarding the potential influence of nomenclature on criminal behavior, prompting contemplation on the role of moniker trends in shaping societal dynamics. While causation cannot be definitively inferred from our correlational analysis, the "Katharine Crime Connection" presents an engrossing avenue for further exploration, offering a whimsical twist on the intersections of nomenclature and nefarious activities.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
INTRODUCTION

The intersection of nomenclature and nefarious activities has long captured the collective imagination, invoking images of dastardly individuals bearing monikers laden with foreboding connotations. From the notorious John Dillinger to the enigmatic Bonnie and Clyde, the allure of names intertwined with criminal lore has persisted throughout history. However, our study embarks on a more peculiar inquiry, delving into the seemingly whimsical association between the popularity of the first name Katharine and the incidence of robberies within the picturesque state of Colorado.

While the correlation between nomenclature and criminal behavior may seem to belong to the realm of frivolous musings, our investigation sheds light on a curious relationship that extends beyond the confines of mere happenstance. With a correlation coefficient that not only raises eyebrows but also prompts a wary glance over one's shoulder, the "Katharine Crime Connection" adds an unexpected twist to the conventional understanding of societal dynamics.

Join us in unraveling this enigmatic correlation, as we embark on a journey that traverses the realms of statistical analysis, nomenclature trends, and the caprices of criminal proclivities. Let us peel back the layers of this perplexing phenomenon and explore the whimsical interplay between the popularity of the name Katharine and the perpetration of robberies in the scenic expanse of Colorado. As we embark on this expedition, we invite you to prepare for a riveting odyssey into the unforeseen junctures of nomenclature and criminal activities, where the unexpected reigns supreme and the conventional gives way to the captivatingly peculiar.


Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Katharine and Robberies in Colorado. Make lots of 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 couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
The Katharine Crime Connection: Colorado's Curious Crime Correlation

[[ABSTRACT]]
In this study, we delved into the peculiar connection between the popularity of the first name Katharine and the incidence of robberies in the state of Colorado. Utilizing data extracted from the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted an extensive analysis spanning the years 1985 to 2022. The results revealed a striking correlation coefficient of 0.9200450 and statistically significant p-value of less than 0.01, suggesting a robust association between the frequency of the name Katharine and the occurrence of theft-related offenses within the Colorado region.

The findings of our study raise intriguing questions regarding the potential influence of nomenclature on criminal behavior, prompting contemplation on the role of moniker trends in shaping societal dynamics. While causation cannot be definitively inferred from our correlational analysis, the "Katharine Crime Connection" presents an engrossing avenue for further exploration, offering a whimsical twist on the intersections of nomenclature and nefarious activities.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
The intersection of nomenclature and nefarious activities has long captured the collective imagination, invoking images of dastardly individuals bearing monikers laden with foreboding connotations. From the notorious John Dillinger to the enigmatic Bonnie and Clyde, the allure of names intertwined with criminal lore has persisted throughout history. However, our study embarks on a more peculiar inquiry, delving into the seemingly whimsical association between the popularity of the first name Katharine and the incidence of robberies within the picturesque state of Colorado.
While the correlation between nomenclature and criminal behavior may seem to belong to the realm of frivolous musings, our investigation sheds light on a curious relationship that extends beyond the confines of mere happenstance. With a correlation coefficient that not only raises eyebrows but also prompts a wary glance over one's shoulder, the "Katharine Crime Connection" adds an unexpected twist to the conventional understanding of societal dynamics.
Join us in unraveling this enigmatic correlation, as we embark on a journey that traverses the realms of statistical analysis, nomenclature trends, and the caprices of criminal proclivities. Let us peel back the layers of this perplexing phenomenon and explore the whimsical interplay between the popularity of the name Katharine and the perpetration of robberies in the scenic expanse of Colorado. As we embark on this expedition, we invite you to prepare for a riveting odyssey into the unforeseen junctures of nomenclature and criminal activities, where the unexpected reigns supreme and the conventional gives way to the captivatingly peculiar.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

The intersection of nomenclature and criminal behavior is a topic that has piqued the interest of researchers and enthusiasts alike. Smith et al. (2010) conducted a comprehensive study on the influence of names on behavioral outcomes, drawing attention to the potential ramifications of nomenclature trends on societal dynamics. Building on this foundation, Doe and Jones (2015) further explored the psychological implications of nomenclature, highlighting the subtle but profound impact of names on individual identities and societal perceptions.

In "The Name Game: The Power of Labels in Shaping Society" (2008), Brown delves into the multifaceted dimensions of nomenclature, unraveling the complex interplay between names and societal constructs. Similarly, in "Beyond the Name: Unraveling the Mysteries of Monikers" (2012), Johnson offers an engaging exploration of the intrinsic connections between names and human behavior, inviting readers to contemplate the far-reaching implications of nomenclature patterns.

Venturing into the realms of fiction, the works of Agatha Christie, renowned for her astute portrayal of criminal investigations, provide a tangential yet intriguing perspective. In "Murder on the Orient Express" (1934), Christie weaves a captivating narrative that underscores the enigmatic nature of human motivations and actions, leading readers through a labyrinth of intrigue and misdirection.

Amidst the labyrinth of internet memes, the "Hide the Pain Harold" meme offers a lighthearted yet relevant depiction of concealing distress beneath a façade of composure, mirroring the potential discrepancy between nomenclature trends and underlying behavioral tendencies.

As we delve into the whimsical realm of the "Katharine Crime Connection," the fusion of empirical investigations, literary musings, and cultural phenomena coalesce to offer an unconventional exploration of the correlation between the popularity of the name Katharine and the prevalence of robberies in the scenic landscapes of Colorado. With an air of playful curiosity and a penchant for unexpected discoveries, our journey unfolds into the uncharted territories where nomenclature and criminal proclivities converge, beckoning us to embrace the inexplicable and revel in the enigmatic.


Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Katharine and Robberies in Colorado. Make lots of 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 Katharine Crime Connection: Colorado's Curious Crime Correlation

[[ABSTRACT]]
In this study, we delved into the peculiar connection between the popularity of the first name Katharine and the incidence of robberies in the state of Colorado. Utilizing data extracted from the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted an extensive analysis spanning the years 1985 to 2022. The results revealed a striking correlation coefficient of 0.9200450 and statistically significant p-value of less than 0.01, suggesting a robust association between the frequency of the name Katharine and the occurrence of theft-related offenses within the Colorado region.

The findings of our study raise intriguing questions regarding the potential influence of nomenclature on criminal behavior, prompting contemplation on the role of moniker trends in shaping societal dynamics. While causation cannot be definitively inferred from our correlational analysis, the "Katharine Crime Connection" presents an engrossing avenue for further exploration, offering a whimsical twist on the intersections of nomenclature and nefarious activities.

[[INTRODUCTION]]
INTRODUCTION
The intersection of nomenclature and nefarious activities has long captured the collective imagination, invoking images of dastardly individuals bearing monikers laden with foreboding connotations. From the notorious John Dillinger to the enigmatic Bonnie and Clyde, the allure of names intertwined with criminal lore has persisted throughout history. However, our study embarks on a more peculiar inquiry, delving into the seemingly whimsical association between the popularity of the first name Katharine and the incidence of robberies within the picturesque state of Colorado.
While the correlation between nomenclature and criminal behavior may seem to belong to the realm of frivolous musings, our investigation sheds light on a curious relationship that extends beyond the confines of mere happenstance. With a correlation coefficient that not only raises eyebrows but also prompts a wary glance over one's shoulder, the "Katharine Crime Connection" adds an unexpected twist to the conventional understanding of societal dynamics.
Join us in unraveling this enigmatic correlation, as we embark on a journey that traverses the realms of statistical analysis, nomenclature trends, and the caprices of criminal proclivities. Let us peel back the layers of this perplexing phenomenon and explore the whimsical interplay between the popularity of the name Katharine and the perpetration of robberies in the scenic expanse of Colorado. As we embark on this expedition, we invite you to prepare for a riveting odyssey into the unforeseen junctures of nomenclature and criminal activities, where the unexpected reigns supreme and the conventional gives way to the captivatingly peculiar.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

**METHODOLOGY**

**Data Collection**

Ah, the thrill of delving into data! We began our foray into the Katharine Crime Connection by gathering a myriad of information from the US Social Security Administration (SSA) and the FBI Criminal Justice Information Services (CJIS). Armed with our metaphorical magnifying glasses and statistical swords, we combed through datasets spanning the years 1985 to 2022 in search of the elusive relationship between the popularity of the first name Katharine and the prevalence of robberies in the alluring terrain of Colorado.

Voyaging through the digital sea of nomenclature statistics and crime figures, we navigated the tumultuous waves of internet archives, encountering mountains of numerical treasure that held the key to unlocking the perplexing correlation we sought. While the process may not have involved grappling with pirate ships or deciphering cryptic map engravings, the pursuit of this unique association surely felt like a swashbuckling escapade through the virtual realms of data.

**Data Analysis**

With our treasure trove of data secured, we harnessed the formidable powers of statistical analysis to unravel the enigmatic link between the name Katharine and the capers of thievery that unfolded within the boundaries of Colorado. Wielding the mighty swords of correlation and regression analyses, we set forth on a quest to unearth the hidden patterns that lay beneath the surface of numerical landscapes.

Employing robust statistical software and invoking the ancient incantations of p-values and correlation coefficients, we channeled our inner explorers to navigate the uncharted territories of data visualization and hypothesis testing. Armed with our trusty calculators and fervent determination, we braved the labyrinthine pathways of statistical significance, charting a course through the tumultuous seas of variability and association.

**Modeling and Interpretation**

As we emerged triumphantly from the statistical wilderness, the contours of our findings materialized before our eyes, unveiling a striking correlation coefficient of 0.9200450 and a notably significant p-value of less than 0.01. The robustness of this association left us at the edge of our seats, contemplating the whimsical interplay between the trends of nomenclature and the web of criminal activities that enshrouded the state of Colorado.

While the correlation does not lay claim to causation, the resonance of the "Katharine Crime Connection" resonates with an undeniable vigour, beckoning us to explore the unforeseen junctures of nomenclature and criminal dynamics. With our findings in hand, we invite scholarly cohorts and curious minds alike to embark on this thrilling expedition traversing the intriguing terrain where the improbable intersects with the plausible, and where the captivatingly peculiar reigns supreme.


Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Katharine and Robberies in Colorado. Make lots of 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 0.9200450, r-squared of 0.8464828, 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 Katharine Crime Connection: Colorado's Curious Crime Correlation

[[ABSTRACT]]
In this study, we delved into the peculiar connection between the popularity of the first name Katharine and the incidence of robberies in the state of Colorado. Utilizing data extracted from the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted an extensive analysis spanning the years 1985 to 2022. The results revealed a striking correlation coefficient of 0.9200450 and statistically significant p-value of less than 0.01, suggesting a robust association between the frequency of the name Katharine and the occurrence of theft-related offenses within the Colorado region.

The findings of our study raise intriguing questions regarding the potential influence of nomenclature on criminal behavior, prompting contemplation on the role of moniker trends in shaping societal dynamics. While causation cannot be definitively inferred from our correlational analysis, the "Katharine Crime Connection" presents an engrossing avenue for further exploration, offering a whimsical twist on the intersections of nomenclature and nefarious activities.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
INTRODUCTION
The intersection of nomenclature and nefarious activities has long captured the collective imagination, invoking images of dastardly individuals bearing monikers laden with foreboding connotations. From the notorious John Dillinger to the enigmatic Bonnie and Clyde, the allure of names intertwined with criminal lore has persisted throughout history. However, our study embarks on a more peculiar inquiry, delving into the seemingly whimsical association between the popularity of the first name Katharine and the incidence of robberies within the picturesque state of Colorado.
While the correlation between nomenclature and criminal behavior may seem to belong to the realm of frivolous musings, our investigation sheds light on a curious relationship that extends beyond the confines of mere happenstance. With a correlation coefficient that not only raises eyebrows but also prompts a wary glance over one's shoulder, the "Katharine Crime Connection" adds an unexpected twist to the conventional understanding of societal dynamics.
Join us in unraveling this enigmatic correlation, as we embark on a journey that traverses the realms of statistical analysis, nomenclature trends, and the caprices of criminal proclivities. Let us peel back the layers of this perplexing phenomenon and explore the whimsical interplay between the popularity of the name Katharine and the perpetration of robberies in the scenic expanse of Colorado. As we embark on this expedition, we invite you to prepare for a riveting odyssey into the unforeseen junctures of nomenclature and criminal activities, where the unexpected reigns supreme and the conventional gives way to the captivatingly peculiar.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The results of our analysis unveiled a remarkable correlation between the popularity of the first name Katharine and the incidence of robberies in the state of Colorado. Over the period spanning from 1985 to 2022, our investigation yielded a correlation coefficient of 0.9200450, indicating a substantial positive correlation between the frequency of the name Katharine and the occurrence of theft-related offenses in the Colorado region. This correlation was further substantiated by a robust r-squared value of 0.8464828, denoting that approximately 84.6% of the variability in the occurrence of robberies in Colorado can be attributed to the popularity of the name Katharine.

The statistical significance of this correlation was underscored by a p-value of less than 0.01, solidifying the strength of the association and rendering it highly improbable that this relationship occurred by mere chance. From a statistical standpoint, the evidence of a strong association between the prevalence of the name Katharine and the frequency of robberies in Colorado is as compelling as, dare I say, an open safe in a heist movie.

In Figure 1, the scatterplot depicts the conspicuous clustering of data points, portraying a clear and coherent pattern that exemplifies the robust correlation observed between the two variables. As one navigates through the scatterplot, it becomes evident that the frequency of the name Katharine and the incidence of robberies in Colorado move in tandem, signaling a seemingly inexplicable yet intriguing relationship that beckons further scrutiny.

Contrary to popular belief, it appears that in this case, the name Katharine is not just a mere "Katharine of Aragon" in the annals of nomenclature; rather, it stands as a pivotal player in the symphony of criminal activities within the confines of Colorado. While we refrain from leaping to causative conclusions, the prodigious correlation unveiled through our analysis does warrant contemplation on the potential influence of nomenclature trends on societal phenomena, particularly in the realm of illicit behavior. Our findings invite a whimsical reconsideration of the impact of names on nefarious inclinations, offering a delightful detour into the realms of both statistical analysis and speculative whimsy.


Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Katharine and Robberies in Colorado. Make lots of 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 Katharine Crime Connection: Colorado's Curious Crime Correlation

[[ABSTRACT]]
In this study, we delved into the peculiar connection between the popularity of the first name Katharine and the incidence of robberies in the state of Colorado. Utilizing data extracted from the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted an extensive analysis spanning the years 1985 to 2022. The results revealed a striking correlation coefficient of 0.9200450 and statistically significant p-value of less than 0.01, suggesting a robust association between the frequency of the name Katharine and the occurrence of theft-related offenses within the Colorado region.

The findings of our study raise intriguing questions regarding the potential influence of nomenclature on criminal behavior, prompting contemplation on the role of moniker trends in shaping societal dynamics. While causation cannot be definitively inferred from our correlational analysis, the "Katharine Crime Connection" presents an engrossing avenue for further exploration, offering a whimsical twist on the intersections of nomenclature and nefarious activities.

[[LITERATURE REVIEW]]
The intersection of nomenclature and criminal behavior is a topic that has piqued the interest of researchers and enthusiasts alike. Smith et al. (2010) conducted a comprehensive study on the influence of names on behavioral outcomes, drawing attention to the potential ramifications of nomenclature trends on societal dynamics. Building on this foundation, Doe and Jones (2015) further explored the psychological implications of nomenclature, highlighting the subtle but profound impact of names on individual identities and societal perceptions.
In "The Name Game: The Power of Labels in Shaping Society" (2008), Brown delves into the multifaceted dimensions of nomenclature, unraveling the complex interplay between names and societal constructs. Similarly, in "Beyond the Name: Unraveling the Mysteries of Monikers" (2012), Johnson offers an engaging exploration of the intrinsic connections between names and human behavior, inviting readers to contemplate the far-reaching implications of nomenclature patterns.
Venturing into the realms of fiction, the works of Agatha Christie, renowned for her astute portrayal of criminal investigations, provide a tangential yet intriguing perspective. In "Murder on the Orient Express" (1934), Christie weaves a captivating narrative that underscores the enigmatic nature of human motivations and actions, leading readers through a labyrinth of intrigue and misdirection.
Amidst the labyrinth of internet memes, the "Hide the Pain Harold" meme offers a lighthearted yet relevant depiction of concealing distress beneath a façade of composure, mirroring the potential discrepancy between nomenclature trends and underlying behavioral tendencies.
As we delve into the whimsical realm of the "Katharine Crime Connection," the fusion of empirical investigations, literary musings, and cultural phenomena coalesce to offer an unconventional exploration of the correlation between the popularity of the name Katharine and the prevalence of robberies in the scenic landscapes of Colorado. With an air of playful curiosity and a penchant for unexpected discoveries, our journey unfolds into the uncharted territories where nomenclature and criminal proclivities converge, beckoning us to embrace the inexplicable and revel in the enigmatic.

[[RESULTS]]
The results of our analysis unveiled a remarkable correlation between the popularity of the first name Katharine and the incidence of robberies in the state of Colorado. Over the period spanning from 1985 to 2022, our investigation yielded a correlation coefficient of 0.9200450, indicating a substantial positive correlation between the frequency of the name Katharine and the occurrence of theft-related offenses in the Colorado region. This correlation was further substantiated by a robust r-squared value of 0.8464828, denoting that approximately 84.6% of the variability in the occurrence of robberies in Colorado can be attributed to the popularity of the name Katharine.
The statistical significance of this correlation was underscored by a p-value of less than 0.01, solidifying the strength of the association and rendering it highly improbable that this relationship occurred by mere chance. From a statistical standpoint, the evidence of a strong association between the prevalence of the name Katharine and the frequency of robberies in Colorado is as compelling as, dare I say, an open safe in a heist movie.
In Figure 1, the scatterplot depicts the conspicuous clustering of data points, portraying a clear and coherent pattern that exemplifies the robust correlation observed between the two variables. As one navigates through the scatterplot, it becomes evident that the frequency of the name Katharine and the incidence of robberies in Colorado move in tandem, signaling a seemingly inexplicable yet intriguing relationship that beckons further scrutiny.
Contrary to popular belief, it appears that in this case, the name Katharine is not just a mere "Katharine of Aragon" in the annals of nomenclature; rather, it stands as a pivotal player in the symphony of criminal activities within the confines of Colorado. While we refrain from leaping to causative conclusions, the prodigious correlation unveiled through our analysis does warrant contemplation on the potential influence of nomenclature trends on societal phenomena, particularly in the realm of illicit behavior. Our findings invite a whimsical reconsideration of the impact of names on nefarious inclinations, offering a delightful detour into the realms of both statistical analysis and speculative whimsy.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The "Katharine Crime Connection" unravels a curious conundrum that may leave both seasoned criminologists and language enthusiasts scratching their heads in bemusement. Borne out of our statistical analysis, the robust correlation coefficient of 0.9200450 presents a significant nod to the potential interplay between the popularity of the name Katharine and the incidence of robberies in the picturesque land of Colorado. But what could possibly underpin this seemingly enigmatic correlation? Are there subtle psychological mechanisms at play, akin to a sophisticated heist unfolding under the cover of darkness?

Building on the foundations laid by prior research, our study not only substantiates the previous literature's insights but also serves as a quirky testament to the potential influence of nomenclature trends on deviant conduct. The works of Smith et al. (2010) and Doe and Jones (2015), though not explicitly delving into the whimsical dimensions of moniker trends vis-à-vis criminal proclivities, have indirectly laid the groundwork for our unanticipated foray into the idiosyncratic terrain of the "Katharine Crime Connection." As we traverse the unconventional paths of academia, it is essential to recognize the serendipitous intersections of seemingly disparate scholarly pursuits, evoking whimsical contemplations reminiscent of Agatha Christie's enigmatic narratives.

In the realm of statistical rigor, our results reverberate with the resonance of a concealed safe being cracked open, revealing the engrossing storyline woven through the scatterplot. The substantial r-squared value of 0.8464828 alludes to the overwhelming influence exerted by the frequency of the name Katharine on the occurrence of robberies in Colorado, akin to an artful play in the domain of data visualization. Furthermore, the p-value of less than 0.01 unequivocally underscores the strength of this association, albeit in a manner more reminiscent of a carefully orchestrated heist than a traditional statistical inference.

This thought-provoking correlation not only enriches the oftentimes staid landscape of criminological research but also injects a delightful dose of whimsy and wonder into the scholarly discourse, much like the unexpected twist in a beloved mystery novel. As we ponder the implications of the "Katharine Crime Connection," we are beckoned to embrace the inexplicable with open minds and compelled to revel in the enigmatic, mirroring the lively capacity for unexpected discoveries within the realm of academia.


Model: gpt-3.5-turbo-1106
System prompt: You are a 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 Katharine and Robberies in Colorado. Make lots of 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 Katharine Crime Connection: Colorado's Curious Crime Correlation

[[ABSTRACT]]
In this study, we delved into the peculiar connection between the popularity of the first name Katharine and the incidence of robberies in the state of Colorado. Utilizing data extracted from the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted an extensive analysis spanning the years 1985 to 2022. The results revealed a striking correlation coefficient of 0.9200450 and statistically significant p-value of less than 0.01, suggesting a robust association between the frequency of the name Katharine and the occurrence of theft-related offenses within the Colorado region.

The findings of our study raise intriguing questions regarding the potential influence of nomenclature on criminal behavior, prompting contemplation on the role of moniker trends in shaping societal dynamics. While causation cannot be definitively inferred from our correlational analysis, the "Katharine Crime Connection" presents an engrossing avenue for further exploration, offering a whimsical twist on the intersections of nomenclature and nefarious activities.

[[INTRDUCTION]]
INTRODUCTION
The intersection of nomenclature and nefarious activities has long captured the collective imagination, invoking images of dastardly individuals bearing monikers laden with foreboding connotations. From the notorious John Dillinger to the enigmatic Bonnie and Clyde, the allure of names intertwined with criminal lore has persisted throughout history. However, our study embarks on a more peculiar inquiry, delving into the seemingly whimsical association between the popularity of the first name Katharine and the incidence of robberies within the picturesque state of Colorado.
While the correlation between nomenclature and criminal behavior may seem to belong to the realm of frivolous musings, our investigation sheds light on a curious relationship that extends beyond the confines of mere happenstance. With a correlation coefficient that not only raises eyebrows but also prompts a wary glance over one's shoulder, the "Katharine Crime Connection" adds an unexpected twist to the conventional understanding of societal dynamics.
Join us in unraveling this enigmatic correlation, as we embark on a journey that traverses the realms of statistical analysis, nomenclature trends, and the caprices of criminal proclivities. Let us peel back the layers of this perplexing phenomenon and explore the whimsical interplay between the popularity of the name Katharine and the perpetration of robberies in the scenic expanse of Colorado. As we embark on this expedition, we invite you to prepare for a riveting odyssey into the unforeseen junctures of nomenclature and criminal activities, where the unexpected reigns supreme and the conventional gives way to the captivatingly peculiar.

[[RESULTS]]
The results of our analysis unveiled a remarkable correlation between the popularity of the first name Katharine and the incidence of robberies in the state of Colorado. Over the period spanning from 1985 to 2022, our investigation yielded a correlation coefficient of 0.9200450, indicating a substantial positive correlation between the frequency of the name Katharine and the occurrence of theft-related offenses in the Colorado region. This correlation was further substantiated by a robust r-squared value of 0.8464828, denoting that approximately 84.6% of the variability in the occurrence of robberies in Colorado can be attributed to the popularity of the name Katharine.
The statistical significance of this correlation was underscored by a p-value of less than 0.01, solidifying the strength of the association and rendering it highly improbable that this relationship occurred by mere chance. From a statistical standpoint, the evidence of a strong association between the prevalence of the name Katharine and the frequency of robberies in Colorado is as compelling as, dare I say, an open safe in a heist movie.
In Figure 1, the scatterplot depicts the conspicuous clustering of data points, portraying a clear and coherent pattern that exemplifies the robust correlation observed between the two variables. As one navigates through the scatterplot, it becomes evident that the frequency of the name Katharine and the incidence of robberies in Colorado move in tandem, signaling a seemingly inexplicable yet intriguing relationship that beckons further scrutiny.
Contrary to popular belief, it appears that in this case, the name Katharine is not just a mere "Katharine of Aragon" in the annals of nomenclature; rather, it stands as a pivotal player in the symphony of criminal activities within the confines of Colorado. While we refrain from leaping to causative conclusions, the prodigious correlation unveiled through our analysis does warrant contemplation on the potential influence of nomenclature trends on societal phenomena, particularly in the realm of illicit behavior. Our findings invite a whimsical reconsideration of the impact of names on nefarious inclinations, offering a delightful detour into the realms of both statistical analysis and speculative whimsy.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our study illuminates a compelling correlation between the name Katharine and the frequency of robberies in Colorado, stirring contemplation on the whimsical interplay between nomenclature trends and illicit activities. The robust correlation coefficient and statistically significant p-value defy mere happenstance, painting a picture as vivid as a surreptitious getaway car in a heist film. Our findings unveil a correlation as strong as Fort Knox's security, highlighting the unpredictably quirky dynamics of nomenclature and societal phenomena.

While our study reveals a tantalizing correlation, caution is warranted in leaping to causative conclusions. Nonetheless, the "Katharine Crime Connection" presents an intriguing avenue for further exploration, injecting a dose of whimsy into the realms of statistical analysis and speculative contemplation. It's as if Sherlock Holmes and Miss Marple collaborated on a case of criminal nomenclature!

The implications of our findings extend beyond Colorado's state lines, prompting a chuckle and raising eyebrows in equal measure. The enigmatic correlation between the name Katharine and robberies unveils the capricious influence of nomenclature on societal dynamics, offering a delightful diversion from conventional research pursuits. It's as though the name Katharine took on the role of a mischievous bandit, leaving a quirky trail of statistical significance in its wake.

As such, we assert that no further research is needed in this wholly engaging and offbeat area of study. The "Katharine Crime Connection" stands as a testament to the unexpected quirks in the world of scholarly inquiry, and we bid adieu to this whimsical odyssey with the certainty that, like a well-executed prank, this correlation has left an indelible mark on the annals 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 Katharine Crime Connection: Colorado's Curious Crime Correlation. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Quirky Criminology


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 Katharine Crime Connection: Colorado's Curious Crime Correlation. Respond only with the name of a fictional organization.

ChatGPT:

The Center for Rocky Mountain Criminology Studies


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 Katharine Crime Connection: Colorado's Curious Crime Correlation with an abstract of In this study, we delved into the peculiar connection between the popularity of the first name Katharine and the incidence of robberies in the state of Colorado. Utilizing data extracted from the US Social Security Administration and the FBI Criminal Justice Information Services, our research team conducted an extensive analysis spanning the years 1985 to 2022. The results revealed a striking correlation coefficient of 0.9200450 and statistically significant p-value of less than 0.01, suggesting a robust association between the frequency of the name Katharine and the occurrence of theft-related offenses within the Colorado region.
The findings of our study raise intriguing questions regarding the potential influence of nomenclature on criminal behavior, prompting contemplation on the role of moniker trends in shaping societal dynamics. While causation cannot be definitively inferred from our correlational analysis, the "Katharine Crime Connection" presents an engrossing avenue for further exploration, offering a whimsical twist on the intersections of nomenclature and nefarious activities.

ChatGPT:

Katharine, crime, connection, Colorado, correlation, robbery, US Social Security Administration, FBI Criminal Justice Information Services, data analysis, correlation coefficient, statistical significance, nomenclature, criminal behavior, moniker trends, societal dynamics, causation, exploratory research

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



Random correlation

Discover a new correlation

View all correlations

View all research papers

Report an error


Data details

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

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

Correlation r = 0.9200450 (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 = 0.8464828 (Coefficient of determination)
This means 84.6% of the change in the one variable (i.e., Robberies in Colorado) is predictable based on the change in the other (i.e., Popularity of the first name Katharine) over the 38 years from 1985 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 3.2E-16. 0.0000000000000003204348490649
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 0.92 in 3.2E-14% of random cases. Said differently, if you correlated 3,120,759,189,951,474 random variables You don't actually need 3 quadrillion 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.

[ 0.85, 0.96 ] 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 Katharine (Babies born)846907728754628647687708654542465432407453320362334286375323301293256191160127134110109898962735666453141
Robberies in Colorado (Robbery rate)124.2144.8118.898.89090.6107.4120.5116.7106.996.298.283.381.575.370.580.279.582.281.384.780.471.268.967.162.764.565.459.556.760.863.768.966.464.568.374.572.6




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.
  4. Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
    Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.




Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. 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([846,907,728,754,628,647,687,708,654,542,465,432,407,453,320,362,334,286,375,323,301,293,256,191,160,127,134,110,109,89,89,62,73,56,66,45,31,41,])
array_2 = np.array([124.2,144.8,118.8,98.8,90,90.6,107.4,120.5,116.7,106.9,96.2,98.2,83.3,81.5,75.3,70.5,80.2,79.5,82.2,81.3,84.7,80.4,71.2,68.9,67.1,62.7,64.5,65.4,59.5,56.7,60.8,63.7,68.9,66.4,64.5,68.3,74.5,72.6,])
array_1_name = "Popularity of the first name Katharine"
array_2_name = "Robberies in Colorado"

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

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



Reuseable content

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

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

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

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

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

Download images for these variables:


View another random correlation

How fun was this correlation?

Bravo! Your evaluation rocks!


Correlation ID: 4049 · Black Variable ID: 2992 · Red Variable ID: 20227
about · subscribe · emailme@tylervigen.com · twitter

CC BY 4.0