Spurious correlation #2,723 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Robberies in Alaska and the second variable is Professor salaries in the US. The chart goes from 2009 to 2021, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Robberies in Alaska and the second variable is Professor salaries in the US. The chart goes from 2009 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As robberies decreased in Alaska, the demand for security systems also decreased, leading to a surplus of security devices. This surplus put pressure on the manufacturing industry, causing companies to cut costs. Since many of these companies also happened to be major university donors, they had less funds available to contribute to professor salaries, ultimately leading to a nationwide decrease in pay for educators. This just goes to show that even the most unexpected trends can have a ripple effect on our economy and day-to-day lives. Remember, a safer Alaska could mean a lighter wallet for your favorite professor!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image combining the style of a vintage magazine cover with the scene of a school professor counting his salary in a dimly lit faculty office in a quiet Alaskan town, while outside, a group of robbers lurk in the shadows, eyeing the town's main bank for their next heist. Try focusing on the contrast between the cozy, academic setting and the imminent danger lurking outside. The lighting should create a moody atmosphere to reflect the tense situation. 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: Robberies in Alaska and Professor salaries in the US. 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: Cyberpunk Scalar art Futuristic A Discovery magazine cover image inspired by bauhaus
ChatGPT: A Discovery magazine cover 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 Robberies in Alaska and Professor salaries in the US together. Keep the description simple.
ChatGPT: In a quiet town in Alaska, a school professor carefully counts his salary at his desk in the dimly lit faculty office. Outside, a group of robbers lurk in the shadows, eyeing the town's main bank for their next heist.

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 Discovery magazine cover image ] and depicting this scene: In a quiet town in Alaska, a school professor carefully counts his salary at his desk in the dimly lit faculty office. Outside, a group of robbers lurk in the shadows, eyeing the town's main bank for their next heist. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image combining the style of a vintage magazine cover with the scene of a school professor counting his salary in a dimly lit faculty office in a quiet Alaskan town, while outside, a group of robbers lurk in the shadows, eyeing the town's main bank for their next heist. Try focusing on the contrast between the cozy, academic setting and the imminent danger lurking outside. The lighting should create a moody atmosphere to reflect the tense situation.

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

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

AI academic paper

(Because p < 0.01)

The Great Alaska Robbery: A Causative Correlation with Professorial Paychecks?

Journal of Mirthful Economics

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Robberies in Alaska and Professor salaries in the US. 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 Great Alaska Robbery: A Causative Correlation with Professorial Paychecks?

[[ABSTRACT]]
The link between the prevalence of robberies in Alaska and the salaries of professors across the United States has long been an enigma. In this study, utilizing data from the FBI Criminal Justice Information Services and the National Center for Education Statistics, we sought to unravel this puzzling connection. Through meticulous statistical analysis, we calculated a correlation coefficient of 0.9223600 (p < 0.01) for the period from 2009 to 2021, providing robust evidence of a striking association between these seemingly unrelated phenomena. Our findings not only shed light on this curious relationship but also underscore the importance of considering unexpected factors in socioeconomic dynamics. This novel insight prompts further investigation into the underlying mechanisms governing the interplay between regional crime rates and national academic remuneration.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The curious case of the Great Alaska Robbery and its potential causative correlation with professorial paychecks across the United States has perplexed researchers and economists alike. The notion of connecting the rugged wilderness of Alaska with the ivory tower of academia may seem far-fetched, but as the data will reveal, truth is often stranger than fiction!
The allure of Alaska, with its breathtaking landscapes and bountiful wildlife, has captivated the imagination of adventurers and researchers alike. Yet, beneath its stunning exterior lies a statistical anomaly that has eluded explanation for years. On the other hand, the world of academia, with its lecture halls and towering stacks of research papers, seems a world apart from the raw, wild nature of Alaska. However, as we delve into the data, we will find that these seemingly disparate worlds intersect in an unexpected and fascinating manner.
From a research standpoint, this investigation provides a unique opportunity to explore the intersection of criminology and economics, where the depth of qualitative analysis meets the breadth of quantitative inquiry. We aim to navigate the labyrinth of statistics and unravel the mystery that lies at the confluence of criminal activity in the Last Frontier and the remuneration of esteemed educators across the nation.
The traditional image of a professor engrossed in scholarly pursuits, juxtaposed with the brazen deeds of robbers in the untamed North, may seem incongruous at first glance. However, as we embark on our analytical journey, we will uncover the unexpected commonalities and divergences that underlie these apparently unconnected spheres. We shall embark upon the proverbial sled dogs of data, traversing the frozen tundra of uncertainty in pursuit of empirical evidence and statistical enlightenment.
As we proceed in unraveling this enigmatic connection, we cannot help but ponder the striking juxtaposition of these variables. The wild, frontier spirit of Alaska confronts the hallowed halls of academia in a collision of unconventional forces, as though the statistical dice of fate were cast by a mischievous cosmic gambler. Indeed, the serendipitous convergence of these disparate factors invites us to explore the interplay of chance and causation, where empirical breadcrumbs and analytical acumen may lead us to unexpected revelations.
In this quest for understanding, we are reminded of the maxim that "correlation does not imply causation." However, as we tease apart the tangled web of data and delve into the minutiae of statistical relationships, we may uncover a coherence that challenges conventional wisdom and defies facile assumptions. Like intrepid explorers of a statistical frontier, we must navigate the terrain of outliers and outliers, seeking the elusive threads that bind these distinct phenomena.
With a wink at the caprice of fate and a nod to the whims of statistical significance, we delve into the heart of this empirical enigma, eager to shed light on the unexpected interplay of Alaska's criminal undercurrents and the remuneration of erudite professionals in the wider academic fabric of the United States. It is in this spirit of intellectual curiosity and statistical quirkiness that we present the results of our investigation, with all due humility and a touch of whimsy.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In the study by Smith et al., the authors find a significant positive correlation between the incidence of robberies in Alaska and the average salaries of professors in the United States. These findings challenge conventional notions of causality and illuminate the unexpected interplay between regional crime rates and national academic remuneration. Furthermore, Doe's research provides compelling evidence supporting this remarkable correlation, further emphasizing the need for a deeper understanding of the intricate web that ties these seemingly disparate phenomena.

As we journey deeper into this curious correlation, it becomes evident that the intersection of criminology and economics unveils a tapestry of statistical anomalies and unexpected connections. The enigmatic nature of this association prompts us to consider unconventional factors that may influence the financial landscape of academia, akin to an academic version of the Wild West.

Shifting our focus to the realm of literature, "Into the Wild" by Jon Krakauer and "Educated: A Memoir" by Tara Westover offer intriguing parallels to our exploration. The untamed frontier spirit of Alaska mirrored in the trials and tribulations of brave adventurers and scholars challenges the age-old adage that "truth is stranger than fiction." These literary works exemplify the boundless human spirit and the pursuit of knowledge, seemingly disparate yet inexplicably entwined themes that echo the unexpected correlation we have uncovered in our research.

In a delightful twist, the fictional worlds of "The Da Vinci Code" by Dan Brown and "Gone Girl" by Gillian Flynn present uncanny reflections of our statistical journey. The symbiotic relationship between hidden clues and unexpected revelations in these novels mirrors the serendipitous convergence of crime rates in Alaska and professorial salaries, evoking a sense of comedic irony that permeates the fabric of our empirical investigation.

Moreover, popular internet memes such as the "Distracted Boyfriend" meme, with its juxtaposition of attention-grabbing stimuli, amusingly parallels the intriguing juxtaposition of Alaskan robberies and national academic remuneration. This seemingly lighthearted meme inadvertently captures the essence of our research, reminding us of the unexpected correlations that can emerge from the most unlikely of combinations.

In closing, the profound insights garnered from our investigation not only challenge traditional paradigms but also invite further exploration into the whimsical realms of statistical correlations. The intertwining landscapes of rugged Alaskan terrains and the hallowed halls of academia beckon us to unravel their enigmatic connectivity, with a playful quirkiness that exemplifies the captivating essence of empirical inquiry.

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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Robberies in Alaska and Professor salaries in the US. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from FBI Criminal Justice Information Services and National Center for Education Statistics . You used data from 2009 to 2021

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
The Great Alaska Robbery: A Causative Correlation with Professorial Paychecks?

[[ABSTRACT]]
The link between the prevalence of robberies in Alaska and the salaries of professors across the United States has long been an enigma. In this study, utilizing data from the FBI Criminal Justice Information Services and the National Center for Education Statistics, we sought to unravel this puzzling connection. Through meticulous statistical analysis, we calculated a correlation coefficient of 0.9223600 (p < 0.01) for the period from 2009 to 2021, providing robust evidence of a striking association between these seemingly unrelated phenomena. Our findings not only shed light on this curious relationship but also underscore the importance of considering unexpected factors in socioeconomic dynamics. This novel insight prompts further investigation into the underlying mechanisms governing the interplay between regional crime rates and national academic remuneration.

[[INTRODUCTION]]
The curious case of the Great Alaska Robbery and its potential causative correlation with professorial paychecks across the United States has perplexed researchers and economists alike. The notion of connecting the rugged wilderness of Alaska with the ivory tower of academia may seem far-fetched, but as the data will reveal, truth is often stranger than fiction!
The allure of Alaska, with its breathtaking landscapes and bountiful wildlife, has captivated the imagination of adventurers and researchers alike. Yet, beneath its stunning exterior lies a statistical anomaly that has eluded explanation for years. On the other hand, the world of academia, with its lecture halls and towering stacks of research papers, seems a world apart from the raw, wild nature of Alaska. However, as we delve into the data, we will find that these seemingly disparate worlds intersect in an unexpected and fascinating manner.
From a research standpoint, this investigation provides a unique opportunity to explore the intersection of criminology and economics, where the depth of qualitative analysis meets the breadth of quantitative inquiry. We aim to navigate the labyrinth of statistics and unravel the mystery that lies at the confluence of criminal activity in the Last Frontier and the remuneration of esteemed educators across the nation.
The traditional image of a professor engrossed in scholarly pursuits, juxtaposed with the brazen deeds of robbers in the untamed North, may seem incongruous at first glance. However, as we embark on our analytical journey, we will uncover the unexpected commonalities and divergences that underlie these apparently unconnected spheres. We shall embark upon the proverbial sled dogs of data, traversing the frozen tundra of uncertainty in pursuit of empirical evidence and statistical enlightenment.
As we proceed in unraveling this enigmatic connection, we cannot help but ponder the striking juxtaposition of these variables. The wild, frontier spirit of Alaska confronts the hallowed halls of academia in a collision of unconventional forces, as though the statistical dice of fate were cast by a mischievous cosmic gambler. Indeed, the serendipitous convergence of these disparate factors invites us to explore the interplay of chance and causation, where empirical breadcrumbs and analytical acumen may lead us to unexpected revelations.
In this quest for understanding, we are reminded of the maxim that "correlation does not imply causation." However, as we tease apart the tangled web of data and delve into the minutiae of statistical relationships, we may uncover a coherence that challenges conventional wisdom and defies facile assumptions. Like intrepid explorers of a statistical frontier, we must navigate the terrain of outliers and outliers, seeking the elusive threads that bind these distinct phenomena.
With a wink at the caprice of fate and a nod to the whims of statistical significance, we delve into the heart of this empirical enigma, eager to shed light on the unexpected interplay of Alaska's criminal undercurrents and the remuneration of erudite professionals in the wider academic fabric of the United States. It is in this spirit of intellectual curiosity and statistical quirkiness that we present the results of our investigation, with all due humility and a touch of whimsy.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

Data Collection
The foundations of our inquiry rested upon data gleaned from the FBI Criminal Justice Information Services and the National Center for Education Statistics. Our intrepid research team combed through digital archives, traversing the virtual wilderness of the internet, in search of the elusive strands of evidence. Like explorers of old charting uncharted territories, we scoured the electronic realm for nuggets of statistical gold that would illuminate the connection between Alaskan robberies and professorial salaries.

The FBI Crime Data Explorer served as our compass in navigating the landscape of criminal statistics, providing granular insights into the frequency and nature of robberies in the vast wilderness of Alaska. Simultaneously, the National Center for Education Statistics bestowed upon us a trove of invaluable information regarding the salaries of esteemed educators across the United States. By marrying these disparate datasets, we endeavored to forge a bridge between the wild frontiers of criminal activity and the lofty heights of academic compensation.

Methodological Framework
Our statistical odyssey commenced with the identification of relevant variables that would serve as companions on our analytical expedition. The incidence of robberies in Alaska stood as our stalwart sentinel, representing the untamed undercurrent of criminal activity amid the snow-capped peaks and icy fjords. Meanwhile, the median salaries of full-time professors in the United States assumed the role of our erudite academic luminary, casting its scholarly glow across the socioeconomic landscape.

Employing a methodological kaleidoscope of regression analysis, time-series modeling, and cluster analysis, we sought to distill the essence of the intricate relationship between these seemingly incongruous variables. Through the statistical alchemy of ordinary least squares and robust standard errors, we endeavored to unveil the hidden patterns and causal links that underpinned the enigmatic bond between Alaskan robberies and professorial remuneration.

Statistical Analysis
The empirical journey traversed the temporal expanse from 2009 to 2021, a span of years that witnessed the ebb and flow of criminal activity and academic emolument. Adopting a Bayesian approach to statistical inference, we delved into the quantitative hinterlands with the tenacity of a sled dog team forging through Arctic blizzards. The correlation coefficient emerged as our guiding star, illuminating the path toward understanding the robust association between Alaskan robberies and professorial paychecks.

We rejoiced in the revelation of a correlation coefficient of 0.9223600 (p < 0.01), a resounding testament to the formidable bond that we had uncovered. The statistical heavens had smiled upon our endeavor, bestowing upon us a p-value that resoundingly rejected the null hypothesis and affirmed the existence of a compelling relationship between these unassuming variables.

Limitations and Future Directions
As with any scholarly quest, our odyssey was not without its vicissitudes and shadows. The limitations inherent in our study beckon forth as pathways for future expedition. The temporal scope of our analysis, while expansive, remains but a snapshot in the continuum of socioeconomic dynamics. Further exploration across broader temporal horizons, as well as the inclusion of additional covariates, beckon as promising avenues for future research. Additionally, the specificity of our geographical focus on Alaska, while pivotal to our investigation, prompts contemplation of similar inquiries across diverse regional landscapes.

In the spirit of scientific inquiry, we anticipate that our findings will serve as a springboard for further explorations into the tapestry of unexpected causative linkages. The interplay of climate, demographic shifts, and institutional dynamics presents a fertile ground for the cultivation of future research endeavors. As the statistical torchbearers of this singular inquiry, we encourage fellow scholars to embark on their own analytical adventures, poised to unearth the captivating complexities of socioeconomic phenomena.

Conclusion
With meticulous methodology and statistical rigor as our faithful companions, we embarked upon this scholarly odyssey with a spirit of inquiry and whimsical determination. Our findings unveil a profound connection between the roaring undercurrents of Alaskan crime and the academic bounties bestowed upon educators across the United States. The unexpected convergence of these seemingly disparate realms imparts to us a poignant reminder of the capricious interplay of chance and causation in the socioeconomic landscape.

It is in this spirit of scholarly mirth and statistical revelation that we humbly present the results of our expedition, trusting that our foray into the enigmatic union of Alaskan robberies and professorial paychecks will inspire further elucidation and spark the flame of curiosity in the hearts of fellow researchers.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the 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 Robberies in Alaska and Professor salaries in the US. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from FBI Criminal Justice Information Services and National Center for Education Statistics .

For the time period 2009 to 2021, you found a correlation 0.9223600, r-squared of 0.8507480, 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 Great Alaska Robbery: A Causative Correlation with Professorial Paychecks?

[[ABSTRACT]]
The link between the prevalence of robberies in Alaska and the salaries of professors across the United States has long been an enigma. In this study, utilizing data from the FBI Criminal Justice Information Services and the National Center for Education Statistics, we sought to unravel this puzzling connection. Through meticulous statistical analysis, we calculated a correlation coefficient of 0.9223600 (p < 0.01) for the period from 2009 to 2021, providing robust evidence of a striking association between these seemingly unrelated phenomena. Our findings not only shed light on this curious relationship but also underscore the importance of considering unexpected factors in socioeconomic dynamics. This novel insight prompts further investigation into the underlying mechanisms governing the interplay between regional crime rates and national academic remuneration.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The curious case of the Great Alaska Robbery and its potential causative correlation with professorial paychecks across the United States has perplexed researchers and economists alike. The notion of connecting the rugged wilderness of Alaska with the ivory tower of academia may seem far-fetched, but as the data will reveal, truth is often stranger than fiction!
The allure of Alaska, with its breathtaking landscapes and bountiful wildlife, has captivated the imagination of adventurers and researchers alike. Yet, beneath its stunning exterior lies a statistical anomaly that has eluded explanation for years. On the other hand, the world of academia, with its lecture halls and towering stacks of research papers, seems a world apart from the raw, wild nature of Alaska. However, as we delve into the data, we will find that these seemingly disparate worlds intersect in an unexpected and fascinating manner.
From a research standpoint, this investigation provides a unique opportunity to explore the intersection of criminology and economics, where the depth of qualitative analysis meets the breadth of quantitative inquiry. We aim to navigate the labyrinth of statistics and unravel the mystery that lies at the confluence of criminal activity in the Last Frontier and the remuneration of esteemed educators across the nation.
The traditional image of a professor engrossed in scholarly pursuits, juxtaposed with the brazen deeds of robbers in the untamed North, may seem incongruous at first glance. However, as we embark on our analytical journey, we will uncover the unexpected commonalities and divergences that underlie these apparently unconnected spheres. We shall embark upon the proverbial sled dogs of data, traversing the frozen tundra of uncertainty in pursuit of empirical evidence and statistical enlightenment.
As we proceed in unraveling this enigmatic connection, we cannot help but ponder the striking juxtaposition of these variables. The wild, frontier spirit of Alaska confronts the hallowed halls of academia in a collision of unconventional forces, as though the statistical dice of fate were cast by a mischievous cosmic gambler. Indeed, the serendipitous convergence of these disparate factors invites us to explore the interplay of chance and causation, where empirical breadcrumbs and analytical acumen may lead us to unexpected revelations.
In this quest for understanding, we are reminded of the maxim that "correlation does not imply causation." However, as we tease apart the tangled web of data and delve into the minutiae of statistical relationships, we may uncover a coherence that challenges conventional wisdom and defies facile assumptions. Like intrepid explorers of a statistical frontier, we must navigate the terrain of outliers and outliers, seeking the elusive threads that bind these distinct phenomena.
With a wink at the caprice of fate and a nod to the whims of statistical significance, we delve into the heart of this empirical enigma, eager to shed light on the unexpected interplay of Alaska's criminal undercurrents and the remuneration of erudite professionals in the wider academic fabric of the United States. It is in this spirit of intellectual curiosity and statistical quirkiness that we present the results of our investigation, with all due humility and a touch of whimsy.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The numerical analysis revealed a striking correlation coefficient of 0.9223600 (p < 0.01) between the prevalence of robberies in Alaska and the salaries of professors across the United States from 2009 to 2021. This eyebrow-raising correlation indicates a robust statistical association that commands attention, much like an unexpected guest appearance by an outlier in a regression model.

The r-squared value of 0.8507480 further underlines the strong linear relationship between these seemingly incongruous variables. This coefficient signifies that approximately 85.07% of the variability in professorial salaries can be explained by the fluctuating incidence of robberies in the rugged terrain of Alaska. It seems that the financial fates of scholars nationwide are surprisingly entwined with the mischievous activities occurring in the icy backdrop of the 49th state.

Fig. 1, the scatterplot presenting this enthralling correlation, provides a visual depiction of the unexpectedly close bond between these disparate factors. The graph exhibits a clear pattern resembling the points of a constellation connected by an invisible statistical thread, weaving a narrative that defies conventional expectations and tickles the scientific imagination.

In conclusion, the findings of our study unravel a compelling relationship between the incidence of robberies in Alaska and the remuneration of professors across the United States. This unexpected association challenges traditional conceptual boundaries and beckons further investigation into the intricate web of socioeconomic interactions. The interplay of chance and causation in these statistical phenomena offers a tantalizing prospect for deeper exploration, fueling the fervor of statistical curiosities and raising new questions that demand rigorous scientific inquiry.

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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Robberies in Alaska and Professor salaries in the US. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Limit your response to 500 tokens.

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

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

[[TITLE]]
The Great Alaska Robbery: A Causative Correlation with Professorial Paychecks?

[[ABSTRACT]]
The link between the prevalence of robberies in Alaska and the salaries of professors across the United States has long been an enigma. In this study, utilizing data from the FBI Criminal Justice Information Services and the National Center for Education Statistics, we sought to unravel this puzzling connection. Through meticulous statistical analysis, we calculated a correlation coefficient of 0.9223600 (p < 0.01) for the period from 2009 to 2021, providing robust evidence of a striking association between these seemingly unrelated phenomena. Our findings not only shed light on this curious relationship but also underscore the importance of considering unexpected factors in socioeconomic dynamics. This novel insight prompts further investigation into the underlying mechanisms governing the interplay between regional crime rates and national academic remuneration.

[[LITERATURE REVIEW]]
In the study by Smith et al., the authors find a significant positive correlation between the incidence of robberies in Alaska and the average salaries of professors in the United States. These findings challenge conventional notions of causality and illuminate the unexpected interplay between regional crime rates and national academic remuneration. Furthermore, Doe's research provides compelling evidence supporting this remarkable correlation, further emphasizing the need for a deeper understanding of the intricate web that ties these seemingly disparate phenomena.
As we journey deeper into this curious correlation, it becomes evident that the intersection of criminology and economics unveils a tapestry of statistical anomalies and unexpected connections. The enigmatic nature of this association prompts us to consider unconventional factors that may influence the financial landscape of academia, akin to an academic version of the Wild West.
Shifting our focus to the realm of literature, "Into the Wild" by Jon Krakauer and "Educated: A Memoir" by Tara Westover offer intriguing parallels to our exploration. The untamed frontier spirit of Alaska mirrored in the trials and tribulations of brave adventurers and scholars challenges the age-old adage that "truth is stranger than fiction." These literary works exemplify the boundless human spirit and the pursuit of knowledge, seemingly disparate yet inexplicably entwined themes that echo the unexpected correlation we have uncovered in our research.
In a delightful twist, the fictional worlds of "The Da Vinci Code" by Dan Brown and "Gone Girl" by Gillian Flynn present uncanny reflections of our statistical journey. The symbiotic relationship between hidden clues and unexpected revelations in these novels mirrors the serendipitous convergence of crime rates in Alaska and professorial salaries, evoking a sense of comedic irony that permeates the fabric of our empirical investigation.
Moreover, popular internet memes such as the "Distracted Boyfriend" meme, with its juxtaposition of attention-grabbing stimuli, amusingly parallels the intriguing juxtaposition of Alaskan robberies and national academic remuneration. This seemingly lighthearted meme inadvertently captures the essence of our research, reminding us of the unexpected correlations that can emerge from the most unlikely of combinations.
In closing, the profound insights garnered from our investigation not only challenge traditional paradigms but also invite further exploration into the whimsical realms of statistical correlations. The intertwining landscapes of rugged Alaskan terrains and the hallowed halls of academia beckon us to unravel their enigmatic connectivity, with a playful quirkiness that exemplifies the captivating essence of empirical inquiry.

[[RESULTS]]
The numerical analysis revealed a striking correlation coefficient of 0.9223600 (p < 0.01) between the prevalence of robberies in Alaska and the salaries of professors across the United States from 2009 to 2021. This eyebrow-raising correlation indicates a robust statistical association that commands attention, much like an unexpected guest appearance by an outlier in a regression model.
The r-squared value of 0.8507480 further underlines the strong linear relationship between these seemingly incongruous variables. This coefficient signifies that approximately 85.07% of the variability in professorial salaries can be explained by the fluctuating incidence of robberies in the rugged terrain of Alaska. It seems that the financial fates of scholars nationwide are surprisingly entwined with the mischievous activities occurring in the icy backdrop of the 49th state.
Fig. 1, the scatterplot presenting this enthralling correlation, provides a visual depiction of the unexpectedly close bond between these disparate factors. The graph exhibits a clear pattern resembling the points of a constellation connected by an invisible statistical thread, weaving a narrative that defies conventional expectations and tickles the scientific imagination.
In conclusion, the findings of our study unravel a compelling relationship between the incidence of robberies in Alaska and the remuneration of professors across the United States. This unexpected association challenges traditional conceptual boundaries and beckons further investigation into the intricate web of socioeconomic interactions. The interplay of chance and causation in these statistical phenomena offers a tantalizing prospect for deeper exploration, fueling the fervor of statistical curiosities and raising new questions that demand rigorous scientific inquiry.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The peculiar correlation uncovered in our investigation between the prevalence of robberies in Alaska and the salaries of professors across the United States from 2009 to 2021 has flung open the doors of statistical revelation with the force of an unexpected gust of Arctic wind. Our results resoundingly support prior research by Smith et al. and Doe, affirming the striking positive correlation that defies conventional expectations and delights the statistical maverick within us. Much like the sudden appearance of a statistically significant p-value, this correlation gallops forth with the irrefutable confidence of an outlier in a regression model, demanding our attention and undeniably influencing the financial fates of scholars nationwide.

The robust correlation coefficient of 0.9223600 (p < 0.01) we derived serves as a beacon illuminating the intriguing association between these seemingly incongruous variables, akin to a statistical lighthouse guiding us through the tumultuous seas of unexpected connections. The r-squared value of 0.8507480 further solidifies this captivating relationship, highlighting the substantial explanatory power of the fluctuating incidence of theft in the frigid embrace of Alaska over the salaries of erudite educators across the nation.

Our findings mirror the dramatic twists and turns of a statistical thriller, portraying a visual narrative reminiscent of the points of a constellation connected by an invisible statistical thread in the scatterplot presented in Fig. 1. The unmistakable pattern woven by this enthralling correlation challenges traditional conceptual boundaries and beckons further investigation, much like the unsolved enigma of a cryptic statistical anomaly that tantalizes the scientific imagination.

As we consider the implications of our unprecedented revelation, it is imperative to heed the unexpected messages embedded within the statistical tapestry we have unraveled. The whimsical whims of economic fate and the mischievous antics of criminal activity intertwine in a dance of statistical serendipity, reminding us of the capricious nature of empirical inquiry and the enduring allure of statistical curiosities. Just as the ripples of a statistical anomaly can reverberate through the hallowed halls of academia, our findings underscore the potent influence of unanticipated factors in the labyrinthine web of socioeconomic interactions, inviting further exploration with a hint of statistical quirkiness that encapsulates the captivating essence of empirical investigation.

In conclusion, the uncanny relationship we have unearthed between the incidence of robberies in Alaska and the remuneration of professors across the United States offers an invigorating vista for future empirical inquiry, echoing the unbridled fervor of a statistical quest for truth amidst the wild wilderness of data analysis and scientific exploration.

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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Robberies in Alaska and Professor salaries in the US. Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
The Great Alaska Robbery: A Causative Correlation with Professorial Paychecks?

[[ABSTRACT]]
The link between the prevalence of robberies in Alaska and the salaries of professors across the United States has long been an enigma. In this study, utilizing data from the FBI Criminal Justice Information Services and the National Center for Education Statistics, we sought to unravel this puzzling connection. Through meticulous statistical analysis, we calculated a correlation coefficient of 0.9223600 (p < 0.01) for the period from 2009 to 2021, providing robust evidence of a striking association between these seemingly unrelated phenomena. Our findings not only shed light on this curious relationship but also underscore the importance of considering unexpected factors in socioeconomic dynamics. This novel insight prompts further investigation into the underlying mechanisms governing the interplay between regional crime rates and national academic remuneration.

[[INTRDUCTION]]
The curious case of the Great Alaska Robbery and its potential causative correlation with professorial paychecks across the United States has perplexed researchers and economists alike. The notion of connecting the rugged wilderness of Alaska with the ivory tower of academia may seem far-fetched, but as the data will reveal, truth is often stranger than fiction!
The allure of Alaska, with its breathtaking landscapes and bountiful wildlife, has captivated the imagination of adventurers and researchers alike. Yet, beneath its stunning exterior lies a statistical anomaly that has eluded explanation for years. On the other hand, the world of academia, with its lecture halls and towering stacks of research papers, seems a world apart from the raw, wild nature of Alaska. However, as we delve into the data, we will find that these seemingly disparate worlds intersect in an unexpected and fascinating manner.
From a research standpoint, this investigation provides a unique opportunity to explore the intersection of criminology and economics, where the depth of qualitative analysis meets the breadth of quantitative inquiry. We aim to navigate the labyrinth of statistics and unravel the mystery that lies at the confluence of criminal activity in the Last Frontier and the remuneration of esteemed educators across the nation.
The traditional image of a professor engrossed in scholarly pursuits, juxtaposed with the brazen deeds of robbers in the untamed North, may seem incongruous at first glance. However, as we embark on our analytical journey, we will uncover the unexpected commonalities and divergences that underlie these apparently unconnected spheres. We shall embark upon the proverbial sled dogs of data, traversing the frozen tundra of uncertainty in pursuit of empirical evidence and statistical enlightenment.
As we proceed in unraveling this enigmatic connection, we cannot help but ponder the striking juxtaposition of these variables. The wild, frontier spirit of Alaska confronts the hallowed halls of academia in a collision of unconventional forces, as though the statistical dice of fate were cast by a mischievous cosmic gambler. Indeed, the serendipitous convergence of these disparate factors invites us to explore the interplay of chance and causation, where empirical breadcrumbs and analytical acumen may lead us to unexpected revelations.
In this quest for understanding, we are reminded of the maxim that "correlation does not imply causation." However, as we tease apart the tangled web of data and delve into the minutiae of statistical relationships, we may uncover a coherence that challenges conventional wisdom and defies facile assumptions. Like intrepid explorers of a statistical frontier, we must navigate the terrain of outliers and outliers, seeking the elusive threads that bind these distinct phenomena.
With a wink at the caprice of fate and a nod to the whims of statistical significance, we delve into the heart of this empirical enigma, eager to shed light on the unexpected interplay of Alaska's criminal undercurrents and the remuneration of erudite professionals in the wider academic fabric of the United States. It is in this spirit of intellectual curiosity and statistical quirkiness that we present the results of our investigation, with all due humility and a touch of whimsy.

[[RESULTS]]
The numerical analysis revealed a striking correlation coefficient of 0.9223600 (p < 0.01) between the prevalence of robberies in Alaska and the salaries of professors across the United States from 2009 to 2021. This eyebrow-raising correlation indicates a robust statistical association that commands attention, much like an unexpected guest appearance by an outlier in a regression model.
The r-squared value of 0.8507480 further underlines the strong linear relationship between these seemingly incongruous variables. This coefficient signifies that approximately 85.07% of the variability in professorial salaries can be explained by the fluctuating incidence of robberies in the rugged terrain of Alaska. It seems that the financial fates of scholars nationwide are surprisingly entwined with the mischievous activities occurring in the icy backdrop of the 49th state.
Fig. 1, the scatterplot presenting this enthralling correlation, provides a visual depiction of the unexpectedly close bond between these disparate factors. The graph exhibits a clear pattern resembling the points of a constellation connected by an invisible statistical thread, weaving a narrative that defies conventional expectations and tickles the scientific imagination.
In conclusion, the findings of our study unravel a compelling relationship between the incidence of robberies in Alaska and the remuneration of professors across the United States. This unexpected association challenges traditional conceptual boundaries and beckons further investigation into the intricate web of socioeconomic interactions. The interplay of chance and causation in these statistical phenomena offers a tantalizing prospect for deeper exploration, fueling the fervor of statistical curiosities and raising new questions that demand rigorous scientific inquiry.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, the intriguing linkage between the frequency of robberies in Alaska and the paychecks of professors across the United States has been unveiled with all the flair of a magician revealing a particularly surprising rabbit from a hat. Our statistical analysis has showcased a correlation coefficient so strong, it’s as if these two unrelated phenomena were engaged in a clandestine dance of economic influence under the shimmering Northern Lights.

The robustness of our findings, akin to a sturdy statistical safety net, reinforces the unexpected bond between the wild exploits of Alaskan robbers and the scholarly endeavors of professors nationwide. The r-squared value of 0.8507480 tells a story of statistical intrigue so compelling, it could rival any Hollywood thriller.

As we bask in the glow of our revelatory results, it becomes clear that the financial destinies of educators nationwide are astoundingly twined with the shenanigans unfolding amidst the Alaskan tundra. It's as if the unseen hand of statistical fate has woven an invisible tapestry connecting these seemingly unrelated narratives, leaving our jaws dropped in amazement.

Fig. 1, the visual representation of this captivating correlation, resembles a celestial masterpiece, with each point on the scatterplot twinkling like a statistical star in an unexpected constellation. It's enough to make even the most seasoned of data analysts raise an eyebrow in bemusement and admiration.

In light of this, we assert that no further research is required in this curious area, for our findings have illuminated this unlikely connection in a way that could rival the illumination of the Aurora Borealis itself.

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 Great Alaska Robbery: A Causative Correlation with Professorial Paychecks?. Respond only with the name of a fictional academic journal.

ChatGPT:

Journal of Mirthful Economics

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 Great Alaska Robbery: A Causative Correlation with Professorial Paychecks?. Respond only with the name of a fictional organization.

ChatGPT:

The Consortium for Economic Research and Academic Compensation

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 Great Alaska Robbery: A Causative Correlation with Professorial Paychecks? with an abstract of The link between the prevalence of robberies in Alaska and the salaries of professors across the United States has long been an enigma. In this study, utilizing data from the FBI Criminal Justice Information Services and the National Center for Education Statistics, we sought to unravel this puzzling connection. Through meticulous statistical analysis, we calculated a correlation coefficient of 0.9223600 (p < 0.01) for the period from 2009 to 2021, providing robust evidence of a striking association between these seemingly unrelated phenomena. Our findings not only shed light on this curious relationship but also underscore the importance of considering unexpected factors in socioeconomic dynamics. This novel insight prompts further investigation into the underlying mechanisms governing the interplay between regional crime rates and national academic remuneration.

ChatGPT:

Alaska robbery, professorial paychecks correlation, FBI Criminal Justice Information Services, National Center for Education Statistics, correlation coefficient, socioeconomic dynamics, regional crime rates, academic remuneration, robbery prevalence, statistical analysis, unexpected factors

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

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Data details

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

Professor salaries in the US
Detailed data title: Average salary of full-time instructional faculty on 9-month contracts in degree-granting postsecondary institutions, by academic rank of Professor
Source: National Center for Education Statistics
See what else correlates with Professor salaries in the US

Correlation r = 0.9223600 (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 = 0.8507480 (Coefficient of determination)
This means 85.1% of the change in the one variable (i.e., Professor salaries in the US) is predictable based on the change in the other (i.e., Robberies in Alaska) over the 13 years from 2009 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 7.2E-6.^Show 0.0000072001972051813235000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.92 in 0.00072% of random cases. Said differently, if you correlated 138,885 random variables^Note You don't actually need 138 thousand 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 12 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 12 because we have two variables measured over a period of 13 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.

[ 0.76, 0.98 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Robberies in Alaska (Robbery rate)	93.6	83.2	79.6	86.3	84.5	85.3	103.2	114.6	128.7	121.9	112.6	97.4	73.6
Professor salaries in the US (Salary)	134915	133892	132719	131745	132028	134443	136755	138492	138746	138826	139640	136906	130262

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. ^Note Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.

Try it yourself

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

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

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

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

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

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

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

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

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

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

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

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

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

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([93.6,83.2,79.6,86.3,84.5,85.3,103.2,114.6,128.7,121.9,112.6,97.4,73.6,])
array_2 = np.array([134915,133892,132719,131745,132028,134443,136755,138492,138746,138826,139640,136906,130262,])
array_1_name = "Robberies in Alaska"
array_2_name = "Professor salaries in the US"

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

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

Reuseable content

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

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

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

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

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

Download images for these variables:

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

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

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Robberies in Alaska
Line chart for only Professor salaries in the US
AI-generated correlation image
The spurious research paper: The Great Alaska Robbery: A Causative Correlation with Professorial Paychecks?

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Correlation ID: 2723 · Black Variable ID: 20181 · Red Variable ID: 1201


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