Spurious correlation #2,131 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Master's degrees awarded in literature and the second variable is Cenovus Energy's stock price (CVE). The chart goes from 2012 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 Master's degrees awarded in literature and the second variable is Cenovus Energy's stock price (CVE). The chart goes from 2012 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the number of Master's degrees awarded in English language and literature/letters decreases, so does the ability to write compelling and persuasive content. This leads to a decline in the quality of Cenovus Energy's marketing materials and communication with investors. As a result, investor confidence wanes, leading to a decrease in demand for the company's stock and ultimately causing Cenovus Energy's stock price (CVE) to decrease. Remember, behind every successful stock is a team of English majors crafting the perfect narrative!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a serene library setting with shelves of ancient tomes and a group of students in elegant graduation gowns, their jubilant faces illuminated by the warm glow of brass reading lamps. The scene is focused on the students receiving their Master's degrees in English language and literature/letters. Adjacent to them, a digital screen displays the Cenovus Energy stock price graph, conveying a steady upward trend symbolizing the company's positive growth. Capture the contrast between the scholarly celebration and the modern financial indicator with a sense of depth and tranquility. 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: Master's degrees awarded in English language and literature/letters and Cenovus Energy's stock price. 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: A scene from Skyrim A scene from Skyrim Cutsy art illustration Cybernetic art Hyper-realistic
ChatGPT: A scene from Skyrim

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 Master's degrees awarded in English language and literature/letters and Cenovus Energy's stock price together. Keep the description simple.
ChatGPT: In a quiet library, a group of students in graduation gowns celebrate as they receive their Master's degrees in English language and literature/letters. Meanwhile, on a nearby screen, the Cenovus Energy stock price graph shows a steady upward trend, indicating positive growth in the company's value.

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 scene from Skyrim ] and depicting this scene: In a quiet library, a group of students in graduation gowns celebrate as they receive their Master's degrees in English language and literature/letters. Meanwhile, on a nearby screen, the Cenovus Energy stock price graph shows a steady upward trend, indicating positive growth in the company's value. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a serene library setting with shelves of ancient tomes and a group of students in elegant graduation gowns, their jubilant faces illuminated by the warm glow of brass reading lamps. The scene is focused on the students receiving their Master's degrees in English language and literature/letters. Adjacent to them, a digital screen displays the Cenovus Energy stock price graph, conveying a steady upward trend symbolizing the company's positive growth. Capture the contrast between the scholarly celebration and the modern financial indicator with a sense of depth and tranquility.

*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 Master's degrees awarded in English language and literature/letters caused Cenovus Energy's stock price (CVE) to decrease.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)

Masters in Metaphors and Markets: Exploring the Elysian Link between English Masters Degrees and Cenovus Energy Stock Prices

The Journal of Interdisciplinary Linguistic and Economic Phenomena

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 goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Master's degrees awarded in English language and literature/letters and Cenovus Energy's stock price (CVE). 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 cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
Masters in Metaphors and Markets: Exploring the Elysian Link between English Masters Degrees and Cenovus Energy Stock Prices

[[ABSTRACT]]
In this study, we delve into the whimsically unexpected connection between the abundance of Master's degrees in English language and literature/letters and the fluctuating stock price of Cenovus Energy (CVE). Leveraging data from the National Center for Education Statistics and LSEG Analytics (Refinitiv), we embarked on an odyssey to unravel the enigmatic correlation between these seemingly disparate domains. Remarkably, our analysis yielded a correlation coefficient of 0.9609507, with a p-value of less than 0.01 for the years 2012 to 2021. Our findings, though sardonically surprising, may offer unforeseen insights into the esoteric interplay between linguistic acumen and energy market dynamics. This scholarly pursuit not only tickles the intelligence but also illuminates the preconceived notions by shedding light on the revealing link between the realm of rhetoric and the world of financial exchanges.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Introduction
In pondering the intricate and often unpredictable machinations of the financial world, one might not immediately associate the movements of Cenovus Energy's stock price with the confounding complexities of English language and literature. However, as we peer through the looking glass of academic research, we find ourselves on an expedition to uncover the enchanting connection between Master's degrees in English and the capricious fluctuations of Cenovus Energy's stock price.
The notion of a relationship between these two seemingly incongruous domains may initially evoke a skeptical furrow of the brow, but we assure you, dear reader, that our investigation has unearthed a correlation so compelling, it would make even the Bard himself cock an eyebrow in surprise. As we dive headfirst into the abyss of statistical analysis and esoteric ponderings, we invite you to join us on this quirky quest to unravel the enigmatic threads that weave together the realms of literary mastery and financial prowess.
Before we embark on this intrepid journey, let us first elucidate the backdrop against which our scholarly escapade unfolded. The surge in Master's degrees awarded in English language and literature/letters over the past decade has been nothing short of remarkable. While some may surmise that the proliferation of such degrees is merely an ode to the enduring appeal of Shakespearean sonnets, we cannot dismiss the possibility that there may be a larger, more clandestine force at play – one that tugs at the heartstrings of stock prices and bids Wordsworth's verses to waltz with the whims of Wall Street.
As we delve into the annals of academic inquiry, armed with data from the National Center for Education Statistics and LSEG Analytics (Refinitiv), we seek to unveil the enigmatic correlation that has eluded conventional wisdom. Drawing upon the seductive power of regression analysis and the tantalizing allure of p-values, we aim to demonstrate that the tangled web of numbers and narratives holds within it a secret so compelling, it would make even the most erudite scholar raise an eyebrow in astonishment.
So, strap in, dear reader, for our scholarly rollercoaster ride promises to be anything but mundane. As we navigate through the labyrinthine corridors of linguistic expertise and financial fortitude, we shall not only illuminate the unexpected intersections of these domains but also sprinkle a touch of whimsy and wonder upon the often staid landscape of academic inquiry. Our findings, though perhaps mirthfully bemusing at first glance, may very well offer a fresh perspective on the synergies between the realms of rhetoric and the world of financial exchanges.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "The Art of Stock-Broiling: Linguistic Leverage in Financial Markets," Smith et al. embark on a linguistic expedition, aiming to unveil the surreal nexus between language prowess and stock market maneuvers. Their analysis, though initially met with raised eyebrows from the finance community, presents a compelling case for the profound impact of linguistic finesse on market dynamics.

Doe's "Wordsmiths and Stock Shifts: A Tale of Linguistic Prowess" further enriches our understanding of the interplay between language mastery and stock price fluctuations. With an eloquence that rivals the prose of literary giants, Doe deftly navigates through the labyrinth of market jargon, shedding light on the uncanny parallels between linguistic dexterity and stock market resilience.

Jones and colleagues, in "The Language of Numbers, The Numbers of Language: An Unconventional Exploration," chart a course through the enigmatic waters of linguistic numerology. Their findings, though cloaked in the statistical garb of academic rigor, whisper a tantalizing tale of linguistic prowess deftly influencing market trends, much like a masterfully spun literary yarn captivating eager readers.

Moving from the scholarly to the literary domain, "The Decline and Fall of Stock Prices: A Linguistic Odyssey" by Ernest Hemingway offers a fictitious yet thought-provoking narrative that seemingly tangos with the whims of Wall Street. Hemingway's prose, while evoking a world far removed from financial markets, resonates with a subtle undercurrent that beckons the imagination to ponder the allure of linguistic mastery on stock price tides.

"Sonnets and Stocks: A Comparative Analysis" by William Shakespeare, a timeless classic in literature circles, may seem a far cry from the pulsating beat of stock market transactions. However, a closer examination reveals the subtle cadence of linguistic elegance mirroring the tempo of market fluctuations, akin to the rhythmic rise and fall of Shakespeare's sonnets.

Venturing into the digital realm, a tweet by @FinancialLinguist tantalizingly suggests, "Unleash the power of metaphor, and watch your stocks soar. #LanguageLeverage #FinancialFluency." While social media may seem an unlikely source of empirical evidence, it offers a curious peek into the zeitgeist of linguistic intrigue intertwining with the ebbs and flows of stock prices.

Perhaps, amidst this charming medley of academic treatises, literary masterpieces, and social musings, the esoteric bond between Master's degrees in English language and literature/letters and Cenovus Energy's stock prices begins to unfurl like the plot of an intriguing novel - one that seamlessly binds the realms of linguistic panache and financial ebullience in a captivating dance of intellect and intrigue.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Master's degrees awarded in English language and literature/letters and Cenovus Energy's stock price (CVE). Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from National Center for Education Statistics and LSEG Analytics (Refinitiv) . You used data from 2012 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]]
Masters in Metaphors and Markets: Exploring the Elysian Link between English Masters Degrees and Cenovus Energy Stock Prices

[[ABSTRACT]]
In this study, we delve into the whimsically unexpected connection between the abundance of Master's degrees in English language and literature/letters and the fluctuating stock price of Cenovus Energy (CVE). Leveraging data from the National Center for Education Statistics and LSEG Analytics (Refinitiv), we embarked on an odyssey to unravel the enigmatic correlation between these seemingly disparate domains. Remarkably, our analysis yielded a correlation coefficient of 0.9609507, with a p-value of less than 0.01 for the years 2012 to 2021. Our findings, though sardonically surprising, may offer unforeseen insights into the esoteric interplay between linguistic acumen and energy market dynamics. This scholarly pursuit not only tickles the intelligence but also illuminates the preconceived notions by shedding light on the revealing link between the realm of rhetoric and the world of financial exchanges.

[[INTRODUCTION]]
Introduction
In pondering the intricate and often unpredictable machinations of the financial world, one might not immediately associate the movements of Cenovus Energy's stock price with the confounding complexities of English language and literature. However, as we peer through the looking glass of academic research, we find ourselves on an expedition to uncover the enchanting connection between Master's degrees in English and the capricious fluctuations of Cenovus Energy's stock price.
The notion of a relationship between these two seemingly incongruous domains may initially evoke a skeptical furrow of the brow, but we assure you, dear reader, that our investigation has unearthed a correlation so compelling, it would make even the Bard himself cock an eyebrow in surprise. As we dive headfirst into the abyss of statistical analysis and esoteric ponderings, we invite you to join us on this quirky quest to unravel the enigmatic threads that weave together the realms of literary mastery and financial prowess.
Before we embark on this intrepid journey, let us first elucidate the backdrop against which our scholarly escapade unfolded. The surge in Master's degrees awarded in English language and literature/letters over the past decade has been nothing short of remarkable. While some may surmise that the proliferation of such degrees is merely an ode to the enduring appeal of Shakespearean sonnets, we cannot dismiss the possibility that there may be a larger, more clandestine force at play – one that tugs at the heartstrings of stock prices and bids Wordsworth's verses to waltz with the whims of Wall Street.
As we delve into the annals of academic inquiry, armed with data from the National Center for Education Statistics and LSEG Analytics (Refinitiv), we seek to unveil the enigmatic correlation that has eluded conventional wisdom. Drawing upon the seductive power of regression analysis and the tantalizing allure of p-values, we aim to demonstrate that the tangled web of numbers and narratives holds within it a secret so compelling, it would make even the most erudite scholar raise an eyebrow in astonishment.
So, strap in, dear reader, for our scholarly rollercoaster ride promises to be anything but mundane. As we navigate through the labyrinthine corridors of linguistic expertise and financial fortitude, we shall not only illuminate the unexpected intersections of these domains but also sprinkle a touch of whimsy and wonder upon the often staid landscape of academic inquiry. Our findings, though perhaps mirthfully bemusing at first glance, may very well offer a fresh perspective on the synergies between the realms of rhetoric and the world of financial exchanges.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

In our endeavor to untangle the peculiar correlation between Master's degrees in English language and literature/letters and Cenovus Energy's stock price, we employed a methodological concoction that could rival the whimsical wizardry of a Shakespearean potion. Our data collection, akin to traversing through the dense forest of academia, involved a seemingly mystical fusion of digital spelunking and statistical alchemy.

To begin with, we summoned the spirits of the National Center for Education Statistics and LSEG Analytics (Refinitiv) to lay bare the numerical tapestries that lay hidden within the labyrinthine corridors of their databases. Our first incantation involved harvesting data on the annual number of Master's degrees awarded in English language and literature/letters from 2012 to 2021, conjuring forth the figures that would serve as the beating heart of our analysis.

The mystic art of data manipulation then took center stage as we harnessed the powers of spreadsheet sorcery to cleanse and fortify our dataset, ensuring that no mischievous outliers or malignant errors could cast aspersions upon the sanctity of our inquiry. With the data polished to a lustrous sheen, we then summoned the genie of statistical software to conjure up regression analyses, correlation coefficients, and p-values that would elucidate the elusive relationship between linguistic erudition and financial machinations.

As we peered through the kaleidoscopic lens of our statistical incantations, we cast our calculations across the temporal tapestry of the past decade, seeking to discern patterns and anomalies that might offer a glimpse into the hidden covenants that bind the worlds of literature and stock prices. Our method was not merely textbook – it was a symphony of scholarly symposium and whimsical wizardry, an enchanting dalliance between conventional precision and scholarly serendipity.

With our analytical spells firmly in place, we advanced to perform robustness checks and sensitivity analyses, ensuring that our findings resonated across diverse scenarios and did not succumb to the caprices of statistical chicanery. The safeguards we erected were as meticulous as a doting guardian watching over a prized collection of rare manuscripts, ensuring that no spurious conclusion could creep into the edifice of our scholarly endeavor.

Ultimately, our methodology, much like a mischievous imp cloaked in the garb of erudition, was designed to unravel the enigmatic correlation between Master's degrees in English language and literature/letters and Cenovus Energy's stock price, while infusing a dose of levity and mirth into the often sobering realm of academic research.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Master's degrees awarded in English language and literature/letters and Cenovus Energy's stock price (CVE). Make lots of jokes, goofy observations, and puns.

Your research team collected data from all across the internet, but mostly just used information from National Center for Education Statistics and LSEG Analytics (Refinitiv) .

For the time period 2012 to 2021, you found a correlation 0.9609507, r-squared of 0.9234262, 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]]
Masters in Metaphors and Markets: Exploring the Elysian Link between English Masters Degrees and Cenovus Energy Stock Prices

[[ABSTRACT]]
In this study, we delve into the whimsically unexpected connection between the abundance of Master's degrees in English language and literature/letters and the fluctuating stock price of Cenovus Energy (CVE). Leveraging data from the National Center for Education Statistics and LSEG Analytics (Refinitiv), we embarked on an odyssey to unravel the enigmatic correlation between these seemingly disparate domains. Remarkably, our analysis yielded a correlation coefficient of 0.9609507, with a p-value of less than 0.01 for the years 2012 to 2021. Our findings, though sardonically surprising, may offer unforeseen insights into the esoteric interplay between linguistic acumen and energy market dynamics. This scholarly pursuit not only tickles the intelligence but also illuminates the preconceived notions by shedding light on the revealing link between the realm of rhetoric and the world of financial exchanges.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
Introduction
In pondering the intricate and often unpredictable machinations of the financial world, one might not immediately associate the movements of Cenovus Energy's stock price with the confounding complexities of English language and literature. However, as we peer through the looking glass of academic research, we find ourselves on an expedition to uncover the enchanting connection between Master's degrees in English and the capricious fluctuations of Cenovus Energy's stock price.
The notion of a relationship between these two seemingly incongruous domains may initially evoke a skeptical furrow of the brow, but we assure you, dear reader, that our investigation has unearthed a correlation so compelling, it would make even the Bard himself cock an eyebrow in surprise. As we dive headfirst into the abyss of statistical analysis and esoteric ponderings, we invite you to join us on this quirky quest to unravel the enigmatic threads that weave together the realms of literary mastery and financial prowess.
Before we embark on this intrepid journey, let us first elucidate the backdrop against which our scholarly escapade unfolded. The surge in Master's degrees awarded in English language and literature/letters over the past decade has been nothing short of remarkable. While some may surmise that the proliferation of such degrees is merely an ode to the enduring appeal of Shakespearean sonnets, we cannot dismiss the possibility that there may be a larger, more clandestine force at play – one that tugs at the heartstrings of stock prices and bids Wordsworth's verses to waltz with the whims of Wall Street.
As we delve into the annals of academic inquiry, armed with data from the National Center for Education Statistics and LSEG Analytics (Refinitiv), we seek to unveil the enigmatic correlation that has eluded conventional wisdom. Drawing upon the seductive power of regression analysis and the tantalizing allure of p-values, we aim to demonstrate that the tangled web of numbers and narratives holds within it a secret so compelling, it would make even the most erudite scholar raise an eyebrow in astonishment.
So, strap in, dear reader, for our scholarly rollercoaster ride promises to be anything but mundane. As we navigate through the labyrinthine corridors of linguistic expertise and financial fortitude, we shall not only illuminate the unexpected intersections of these domains but also sprinkle a touch of whimsy and wonder upon the often staid landscape of academic inquiry. Our findings, though perhaps mirthfully bemusing at first glance, may very well offer a fresh perspective on the synergies between the realms of rhetoric and the world of financial exchanges.

-------

Your response should start like this:

[[RESULTS]]

ChatGPT:

[[RESULTS]]

The results of our whimsical investigation reveal a remarkably robust correlation between the number of Master's degrees awarded in English language and literature/letters and the stock price of Cenovus Energy (CVE) from 2012 to 2021. Our analysis uncovered a correlation coefficient of 0.9609507, indicating a stunningly strong positive relationship between these seemingly incongruous variables. This finding sheds light on an unexpected connection that transcends the boundaries of traditional academic discourse and dabbles in the mystical realms of linguistic prowess and financial wizardry.

In addition to the correlation coefficient, our analysis also yielded an r-squared value of 0.9234262. This high r-squared value suggests that a substantial proportion of the variance in Cenovus Energy's stock price can be explained by the abundance of Master's degrees in English language and literature/letters. It appears that the pen may indeed be mightier than the sword, at least in the realm of stock market fluctuations.

Furthermore, the p-value of less than 0.01 provides compelling evidence against the null hypothesis, indicating that the observed correlation is statistically significant. In other words, the likelihood of such a strong relationship occurring due to random chance is exceedingly remote, leading us to ponder the intriguing notion that perhaps the eloquence of literary scholars exerts a palpable influence on the ebbs and flows of stock market dynamics.

To visually encapsulate the compelling relationship unearthed by our study, we present Figure 1, a scatterplot that vividly illustrates the robust correlation between the number of Master's degrees in English language and literature/letters and Cenovus Energy's stock price. This figure serves not only as a testament to the arcane connection between these two domains but also as a whimsical ode to the unsuspected harmonies that reverberate through the intellectual tapestry of our scholarly discourse.

In conclusion, our findings defy conventional expectations and beckon us to ponder the symbiotic dance between the eloquence of language and the tumultuous symphony of financial markets. This investigation not only tickles the intellect but also invites us to marvel at the serendipitous alignments that lie beneath the surface of seemingly disparate realms. As we gaze into the horizon of future research endeavors, we are left with the tantalizing prospect of further unraveling the intriguing interplay between linguistic acumen and market dynamics, for the saga of Master's in Metaphors and Markets continues to unfold with beguiling curiosity and scholarly merriment.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Master's degrees awarded in English language and literature/letters and Cenovus Energy's stock price (CVE). Make lots of jokes, goofy observations, and puns.

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]]
Masters in Metaphors and Markets: Exploring the Elysian Link between English Masters Degrees and Cenovus Energy Stock Prices

[[ABSTRACT]]
In this study, we delve into the whimsically unexpected connection between the abundance of Master's degrees in English language and literature/letters and the fluctuating stock price of Cenovus Energy (CVE). Leveraging data from the National Center for Education Statistics and LSEG Analytics (Refinitiv), we embarked on an odyssey to unravel the enigmatic correlation between these seemingly disparate domains. Remarkably, our analysis yielded a correlation coefficient of 0.9609507, with a p-value of less than 0.01 for the years 2012 to 2021. Our findings, though sardonically surprising, may offer unforeseen insights into the esoteric interplay between linguistic acumen and energy market dynamics. This scholarly pursuit not only tickles the intelligence but also illuminates the preconceived notions by shedding light on the revealing link between the realm of rhetoric and the world of financial exchanges.

[[LITERATURE REVIEW]]
In "The Art of Stock-Broiling: Linguistic Leverage in Financial Markets," Smith et al. embark on a linguistic expedition, aiming to unveil the surreal nexus between language prowess and stock market maneuvers. Their analysis, though initially met with raised eyebrows from the finance community, presents a compelling case for the profound impact of linguistic finesse on market dynamics.
Doe's "Wordsmiths and Stock Shifts: A Tale of Linguistic Prowess" further enriches our understanding of the interplay between language mastery and stock price fluctuations. With an eloquence that rivals the prose of literary giants, Doe deftly navigates through the labyrinth of market jargon, shedding light on the uncanny parallels between linguistic dexterity and stock market resilience.
Jones and colleagues, in "The Language of Numbers, The Numbers of Language: An Unconventional Exploration," chart a course through the enigmatic waters of linguistic numerology. Their findings, though cloaked in the statistical garb of academic rigor, whisper a tantalizing tale of linguistic prowess deftly influencing market trends, much like a masterfully spun literary yarn captivating eager readers.
Moving from the scholarly to the literary domain, "The Decline and Fall of Stock Prices: A Linguistic Odyssey" by Ernest Hemingway offers a fictitious yet thought-provoking narrative that seemingly tangos with the whims of Wall Street. Hemingway's prose, while evoking a world far removed from financial markets, resonates with a subtle undercurrent that beckons the imagination to ponder the allure of linguistic mastery on stock price tides.
"Sonnets and Stocks: A Comparative Analysis" by William Shakespeare, a timeless classic in literature circles, may seem a far cry from the pulsating beat of stock market transactions. However, a closer examination reveals the subtle cadence of linguistic elegance mirroring the tempo of market fluctuations, akin to the rhythmic rise and fall of Shakespeare's sonnets.
Venturing into the digital realm, a tweet by @FinancialLinguist tantalizingly suggests, "Unleash the power of metaphor, and watch your stocks soar. #LanguageLeverage #FinancialFluency." While social media may seem an unlikely source of empirical evidence, it offers a curious peek into the zeitgeist of linguistic intrigue intertwining with the ebbs and flows of stock prices.
Perhaps, amidst this charming medley of academic treatises, literary masterpieces, and social musings, the esoteric bond between Master's degrees in English language and literature/letters and Cenovus Energy's stock prices begins to unfurl like the plot of an intriguing novel - one that seamlessly binds the realms of linguistic panache and financial ebullience in a captivating dance of intellect and intrigue.

[[RESULTS]]
The results of our whimsical investigation reveal a remarkably robust correlation between the number of Master's degrees awarded in English language and literature/letters and the stock price of Cenovus Energy (CVE) from 2012 to 2021. Our analysis uncovered a correlation coefficient of 0.9609507, indicating a stunningly strong positive relationship between these seemingly incongruous variables. This finding sheds light on an unexpected connection that transcends the boundaries of traditional academic discourse and dabbles in the mystical realms of linguistic prowess and financial wizardry.
In addition to the correlation coefficient, our analysis also yielded an r-squared value of 0.9234262. This high r-squared value suggests that a substantial proportion of the variance in Cenovus Energy's stock price can be explained by the abundance of Master's degrees in English language and literature/letters. It appears that the pen may indeed be mightier than the sword, at least in the realm of stock market fluctuations.
Furthermore, the p-value of less than 0.01 provides compelling evidence against the null hypothesis, indicating that the observed correlation is statistically significant. In other words, the likelihood of such a strong relationship occurring due to random chance is exceedingly remote, leading us to ponder the intriguing notion that perhaps the eloquence of literary scholars exerts a palpable influence on the ebbs and flows of stock market dynamics.
To visually encapsulate the compelling relationship unearthed by our study, we present Figure 1, a scatterplot that vividly illustrates the robust correlation between the number of Master's degrees in English language and literature/letters and Cenovus Energy's stock price. This figure serves not only as a testament to the arcane connection between these two domains but also as a whimsical ode to the unsuspected harmonies that reverberate through the intellectual tapestry of our scholarly discourse.
In conclusion, our findings defy conventional expectations and beckon us to ponder the symbiotic dance between the eloquence of language and the tumultuous symphony of financial markets. This investigation not only tickles the intellect but also invites us to marvel at the serendipitous alignments that lie beneath the surface of seemingly disparate realms. As we gaze into the horizon of future research endeavors, we are left with the tantalizing prospect of further unraveling the intriguing interplay between linguistic acumen and market dynamics, for the saga of Master's in Metaphors and Markets continues to unfold with beguiling curiosity and scholarly merriment.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our study has spun a literary tapestry woven with the colorful threads of Master's degrees in English language and literature/letters and the stock price of Cenovus Energy (CVE). As we tread through this whimsical landscape of linguistic prowess and financial fecundity, we find ourselves irresistibly drawn to the tantalizing threads that connect these ostensibly incongruent domains.

The correlation coefficient of 0.9609507, a p-value of less than 0.01, and an r-squared value of 0.9234262 gleefully confirm the robust statistical reconciliation of the abundance of Master's degrees in English language and literature/letters with Cenovus Energy's stock price from 2012 to 2021. These findings, though sardonically surprising, align with prior research, as we recall the wistful ponderings of Smith et al. and Doe's resonating eloquence in navigating the labyrinth of linguistic influence on market dynamics. It seems that our study, like a masterful ode, harmonizes with the melodic insights of our literary and scholarly predecessors, painting an immersive portrait of the symbiotic relationship between linguistic acumen and financial trajectories.

The high r-squared value casts a spotlight on the substantial explanatory power of Master's degrees in English language and literature/letters in deciphering the variations in Cenovus Energy's stock price. It appears that the subtle nuances of metaphor and the cadence of literary resonance may indeed impart a discernible influence on the undulating tides of market fortunes, much like the deft strokes of a maestro's baton sculpting the notes of a symphony.

Our results, clad in the statistical garb of academic rigor, beckon us to ponder the age-old conundrum – can the pen, or rather the erudite minds wielding it, sway the fortunes of financial markets? The unlikely companionship of English literature scholars and energy market dynamics unfolds as a beguiling saga, inviting us to ponder the serendipitous harmonies that reverberate through the intellectual tapestry of our scholarly inquiry.

As we navigate the uncharted terrain of linguistic impact on financial markets, our findings fuel the flame of discovery, shedding a shimmering light on the hitherto unexplored interplay between lexicographic elegance and market exuberance. The paradigms of our study expand to embrace the whimsical dance of esoteric connections and beckon us to consider further unraveling the enchanting harmony between linguistic acumen and market tumult. For the saga of Master's in Metaphors and Markets continues to unfold with scholarly merriment, inviting all curious minds to wander in its enchanting domain.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Master's degrees awarded in English language and literature/letters and Cenovus Energy's stock price (CVE). Make lots of jokes, goofy observations, and puns.

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]]
Masters in Metaphors and Markets: Exploring the Elysian Link between English Masters Degrees and Cenovus Energy Stock Prices

[[ABSTRACT]]
In this study, we delve into the whimsically unexpected connection between the abundance of Master's degrees in English language and literature/letters and the fluctuating stock price of Cenovus Energy (CVE). Leveraging data from the National Center for Education Statistics and LSEG Analytics (Refinitiv), we embarked on an odyssey to unravel the enigmatic correlation between these seemingly disparate domains. Remarkably, our analysis yielded a correlation coefficient of 0.9609507, with a p-value of less than 0.01 for the years 2012 to 2021. Our findings, though sardonically surprising, may offer unforeseen insights into the esoteric interplay between linguistic acumen and energy market dynamics. This scholarly pursuit not only tickles the intelligence but also illuminates the preconceived notions by shedding light on the revealing link between the realm of rhetoric and the world of financial exchanges.

[[INTRDUCTION]]
Introduction
In pondering the intricate and often unpredictable machinations of the financial world, one might not immediately associate the movements of Cenovus Energy's stock price with the confounding complexities of English language and literature. However, as we peer through the looking glass of academic research, we find ourselves on an expedition to uncover the enchanting connection between Master's degrees in English and the capricious fluctuations of Cenovus Energy's stock price.
The notion of a relationship between these two seemingly incongruous domains may initially evoke a skeptical furrow of the brow, but we assure you, dear reader, that our investigation has unearthed a correlation so compelling, it would make even the Bard himself cock an eyebrow in surprise. As we dive headfirst into the abyss of statistical analysis and esoteric ponderings, we invite you to join us on this quirky quest to unravel the enigmatic threads that weave together the realms of literary mastery and financial prowess.
Before we embark on this intrepid journey, let us first elucidate the backdrop against which our scholarly escapade unfolded. The surge in Master's degrees awarded in English language and literature/letters over the past decade has been nothing short of remarkable. While some may surmise that the proliferation of such degrees is merely an ode to the enduring appeal of Shakespearean sonnets, we cannot dismiss the possibility that there may be a larger, more clandestine force at play – one that tugs at the heartstrings of stock prices and bids Wordsworth's verses to waltz with the whims of Wall Street.
As we delve into the annals of academic inquiry, armed with data from the National Center for Education Statistics and LSEG Analytics (Refinitiv), we seek to unveil the enigmatic correlation that has eluded conventional wisdom. Drawing upon the seductive power of regression analysis and the tantalizing allure of p-values, we aim to demonstrate that the tangled web of numbers and narratives holds within it a secret so compelling, it would make even the most erudite scholar raise an eyebrow in astonishment.
So, strap in, dear reader, for our scholarly rollercoaster ride promises to be anything but mundane. As we navigate through the labyrinthine corridors of linguistic expertise and financial fortitude, we shall not only illuminate the unexpected intersections of these domains but also sprinkle a touch of whimsy and wonder upon the often staid landscape of academic inquiry. Our findings, though perhaps mirthfully bemusing at first glance, may very well offer a fresh perspective on the synergies between the realms of rhetoric and the world of financial exchanges.

[[RESULTS]]
The results of our whimsical investigation reveal a remarkably robust correlation between the number of Master's degrees awarded in English language and literature/letters and the stock price of Cenovus Energy (CVE) from 2012 to 2021. Our analysis uncovered a correlation coefficient of 0.9609507, indicating a stunningly strong positive relationship between these seemingly incongruous variables. This finding sheds light on an unexpected connection that transcends the boundaries of traditional academic discourse and dabbles in the mystical realms of linguistic prowess and financial wizardry.
In addition to the correlation coefficient, our analysis also yielded an r-squared value of 0.9234262. This high r-squared value suggests that a substantial proportion of the variance in Cenovus Energy's stock price can be explained by the abundance of Master's degrees in English language and literature/letters. It appears that the pen may indeed be mightier than the sword, at least in the realm of stock market fluctuations.
Furthermore, the p-value of less than 0.01 provides compelling evidence against the null hypothesis, indicating that the observed correlation is statistically significant. In other words, the likelihood of such a strong relationship occurring due to random chance is exceedingly remote, leading us to ponder the intriguing notion that perhaps the eloquence of literary scholars exerts a palpable influence on the ebbs and flows of stock market dynamics.
To visually encapsulate the compelling relationship unearthed by our study, we present Figure 1, a scatterplot that vividly illustrates the robust correlation between the number of Master's degrees in English language and literature/letters and Cenovus Energy's stock price. This figure serves not only as a testament to the arcane connection between these two domains but also as a whimsical ode to the unsuspected harmonies that reverberate through the intellectual tapestry of our scholarly discourse.
In conclusion, our findings defy conventional expectations and beckon us to ponder the symbiotic dance between the eloquence of language and the tumultuous symphony of financial markets. This investigation not only tickles the intellect but also invites us to marvel at the serendipitous alignments that lie beneath the surface of seemingly disparate realms. As we gaze into the horizon of future research endeavors, we are left with the tantalizing prospect of further unraveling the intriguing interplay between linguistic acumen and market dynamics, for the saga of Master's in Metaphors and Markets continues to unfold with beguiling curiosity and scholarly merriment.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

As we wrap up our quirky quest to uncover the whimsical connection between Master's degrees in English and Cenovus Energy's stock price, we find ourselves in a state of delightful bemusement. Our examination has not only confirmed the eyebrow-raising correlation between the proliferation of poetic prowess and the financial tango of CVE, but it also leaves us pondering the wondrous ways in which language may sway the tempestuous seas of the stock market.

With a correlation coefficient that could rival the chemistry between Elizabeth Bennet and Mr. Darcy, our findings suggest that the eloquence of literary scholars may indeed hold more sway over stock prices than the plot twists of a Jane Austen novel. Furthermore, our high r-squared value implies that a considerable portion of CVE's stock price fluctuations could be ascribed to the enchanting abundance of Master's degrees in English language and literature/letters.

As we bid adieu to this curious expedition, we cannot help but acknowledge the potential implications of our findings. Could Shakespeare's soliloquies secretly serve as market indicators? Might the musings of Milton move the meters of the NASDAQ? Our study tantalizingly teases at the prospect of linguistic ingenuity shaping the very fabric of financial markets.

In conclusion, our research has illuminated a hitherto overlooked intersection of erudition and economic intrigue. However, in the spirit of scholarly jest, we must concede that perhaps we've delved a tad too deeply into the rabbit hole of academic curiosity. It is with a wry smile and a dash of whimsy that we assert, with utmost scholarly confidence, that the saga of Master's in Metaphors and Markets has been unravelled to its most entertaining depths. No further inquiry is needed in this delightfully absurd domain of academic discovery.

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 Masters in Metaphors and Markets: Exploring the Elysian Link between English Masters Degrees and Cenovus Energy Stock Prices. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Interdisciplinary Linguistic and Economic Phenomena

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 Masters in Metaphors and Markets: Exploring the Elysian Link between English Masters Degrees and Cenovus Energy Stock Prices. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Economic Euphemisms and Linguistic Analysis

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Masters in Metaphors and Markets: Exploring the Elysian Link between English Masters Degrees and Cenovus Energy Stock Prices with an abstract of In this study, we delve into the whimsically unexpected connection between the abundance of Master's degrees in English language and literature/letters and the fluctuating stock price of Cenovus Energy (CVE). Leveraging data from the National Center for Education Statistics and LSEG Analytics (Refinitiv), we embarked on an odyssey to unravel the enigmatic correlation between these seemingly disparate domains. Remarkably, our analysis yielded a correlation coefficient of 0.9609507, with a p-value of less than 0.01 for the years 2012 to 2021. Our findings, though sardonically surprising, may offer unforeseen insights into the esoteric interplay between linguistic acumen and energy market dynamics. This scholarly pursuit not only tickles the intelligence but also illuminates the preconceived notions by shedding light on the revealing link between the realm of rhetoric and the world of financial exchanges.

ChatGPT:

Masters in English, literature, letters, Cenovus Energy, stock prices, correlation, National Center for Education Statistics, LSEG Analytics, Refinitiv, energy market dynamics, linguistic acumen, scholarly pursuit, rhetoric, financial exchanges, correlation coefficient, p-value, market analysis.

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

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Data details

Master's degrees awarded in literature
Detailed data title: Master's degrees conferred by postsecondary institutions in English language and literature/letters
Source: National Center for Education Statistics
See what else correlates with Master's degrees awarded in literature

Cenovus Energy's stock price (CVE)
Detailed data title: Opening price of Cenovus Energy (CVE) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: ^{See full details} Via Microsoft Excel Stockhistory function

See what else correlates with Cenovus Energy's stock price (CVE)

Correlation r = 0.9609507 (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 = 0.9234262 (Coefficient of determination)
This means 92.3% of the change in the one variable (i.e., Cenovus Energy's stock price (CVE)) is predictable based on the change in the other (i.e., Master's degrees awarded in literature) over the 10 years from 2012 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 9.7E-6.^Show 0.0000097036505970071300000000
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 0.96 in 0.00097% of random cases. Said differently, if you correlated 103,054 random variables^Note You don't actually need 103 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 9 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 9 because we have two variables measured over a period of 10 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.

[ 0.84, 0.99 ] 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.

	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Master's degrees awarded in literature (Degrees awarded)	9938	9755	9294	8928	8581	8244	8300	8217	7862	7850
Cenovus Energy's stock price (CVE) (Stock price)	33.81	34.17	28.45	20.42	12.53	15.33	9.21	6.87	10.18	6.14

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([9938,9755,9294,8928,8581,8244,8300,8217,7862,7850,])
array_2 = np.array([33.81,34.17,28.45,20.42,12.53,15.33,9.21,6.87,10.18,6.14,])
array_1_name = "Master's degrees awarded in literature"
array_2_name = "Cenovus Energy's stock price (CVE)"

# 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
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Line chart for only Master's degrees awarded in literature
Line chart for only Cenovus Energy's stock price (CVE)
AI-generated correlation image
The spurious research paper: Masters in Metaphors and Markets: Exploring the Elysian Link between English Masters Degrees and Cenovus Energy Stock Prices

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Correlation ID: 2131 · Black Variable ID: 1322 · Red Variable ID: 1781


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