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AI explanation
As the wreckage of ships increased, more and more sea creatures sought refuge and entertainment in the sunken vessels, leading to a surge in underwater electricity usage. This unexpected demand for power from the depths of the ocean boosted the stock price of Cia Paranaense De Energia Copel as they became the leading provider of marine-mains electricity. Remember, it's all about making waves in the stock market!Model: dalle-3
Prompt: [Concept art] Generate an image of a stormy sea with dark, ominous clouds swirling above, casting eerie shadows over the tumultuous waves. Several shipwrecks are scattered across the surface, their masts jutting out at odd angles. Beneath the waves, a blurred vision of marine debris collects on the ocean floor, hinting at the hidden turmoil of the deep. The water's surface is disrupted by the sharp rise and fall of the waves, reflecting the turbulent nature of the sea. Above this dramatic scene, overlay a stock price chart of Cia Paranaense De Energia Copel (ELP) depicting a steady upward trend. The chart should be seamlessly integrated into the image, symbolizing the surge in demand for marine energy and the resulting increase in the company's profitability. The juxtaposition of the stormy sea and the positive stock trend creates a visually compelling narrative of the intersection between natural forces and financial markets. 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: Global shipwrecks and Cia Paranaense De Energia Copel's stock price (ELP). 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 comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s Cutsy graphics Pop art Concept art Cute cartoon
ChatGPT: Concept art
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 Global shipwrecks and Cia Paranaense De Energia Copel's stock price (ELP), in the following situation: Because as the number of shipwrecks increases, more underwater debris accumulates, causing a surge in demand for energy generated from marine sources, leading to higher profits for Cia Paranaense De Energia Copel and subsequently driving up their stock price.. Keep the description simple.
ChatGPT: A stormy sea with multiple shipwrecks scattered across the surface. Beneath the waves, a blurred image of marine debris accumulating on the ocean floor. Above the water, a stock price chart of Cia Paranaense De Energia Copel (ELP) showing a steady upward trend, reflecting the surge in demand for marine energy and the subsequent increase in the company's profits.
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: [ Concept art ] and depicting this scene: A stormy sea with multiple shipwrecks scattered across the surface. Beneath the waves, a blurred image of marine debris accumulating on the ocean floor. Above the water, a stock price chart of Cia Paranaense De Energia Copel (ELP) showing a steady upward trend, reflecting the surge in demand for marine energy and the subsequent increase in the company's profits. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [Concept art] Generate an image of a stormy sea with dark, ominous clouds swirling above, casting eerie shadows over the tumultuous waves. Several shipwrecks are scattered across the surface, their masts jutting out at odd angles. Beneath the waves, a blurred vision of marine debris collects on the ocean floor, hinting at the hidden turmoil of the deep. The water's surface is disrupted by the sharp rise and fall of the waves, reflecting the turbulent nature of the sea. Above this dramatic scene, overlay a stock price chart of Cia Paranaense De Energia Copel (ELP) depicting a steady upward trend. The chart should be seamlessly integrated into the image, symbolizing the surge in demand for marine energy and the resulting increase in the company's profitability. The juxtaposition of the stormy sea and the positive stock trend creates a visually compelling narrative of the intersection between natural forces and financial markets.
*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.
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 an increase in Global shipwrecks caused Cia Paranaense De Energia Copel's stock price (ELP) to increase.
AI academic paper
Navigating the Seas of Stock Market: A Shipwrecking Analysis of Cia Paranaense De Energia Copel's (ELP) Stock Price The Journal of Financial Frivolity Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between Global shipwrecks and Cia Paranaense De Energia Copel's stock price (ELP). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Make the title a clever pun.
Your research team used data from Wikipedia and LSEG Analytics (Refinitiv) to assess this nagging question. You found a correlation coefficient of 0.9058292 and p < 0.01 for 2002 to 2014.
Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)
[[TITLE]]
Lorem ipsum dolor sit
[[ABSTRACT]]
Lorem ipsum dolor sit
ChatGPT:
[[TITLE]]
Navigating the Seas of Stock Market: A Shipwrecking Analysis of Cia Paranaense De Energia Copel's (ELP) Stock Price
[[ABSTRACT]]
Ahoy, fellow researchers and financiers! In this paper, we embark on a humorous yet enlightening journey to explore the intriguing correlation between global shipwrecks and Cia Paranaense De Energia Copel's (ELP) stock price. Using data extracted from the treasure chest of Wikipedia and the compass of LSEG Analytics (Refinitiv), we charted a course to untangle this mysterious relationship.
With a twinkle in our eyes and a hearty chuckle, we reveal a correlation coefficient of 0.9058292 and a p-value less than 0.01 for the period of 2002 to 2014. It seems that the waves of shipwrecks and ELP's stock price have been dancing a merry jig in unison, much like a pirate's parrot and its sea shanty. As we traverse the rough waters of statistical analysis, we also encountered some unexpected humor – after all, what do you call a ship captain’s sword that tells dad jokes? A pun-dulum!
So, come aboard our scholarly ship, and let's hoist the anchor of financial curiosity as we navigate these uncharted waters of shipwrecks and stock prices. Just remember, in the world of finance, sometimes the best treasure lies beneath the surface... or at the bottom of the sea!
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the introduction section of an academic research paper presenting the findings of the connection between Global shipwrecks and Cia Paranaense De Energia Copel's stock price (ELP). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Here is the title and abstract of the paper:
[[TITLE]]
Navigating the Seas of Stock Market: A Shipwrecking Analysis of Cia Paranaense De Energia Copel's (ELP) Stock Price
[[ABSTRACT]]
Ahoy, fellow researchers and financiers! In this paper, we embark on a humorous yet enlightening journey to explore the intriguing correlation between global shipwrecks and Cia Paranaense De Energia Copel's (ELP) stock price. Using data extracted from the treasure chest of Wikipedia and the compass of LSEG Analytics (Refinitiv), we charted a course to untangle this mysterious relationship.
With a twinkle in our eyes and a hearty chuckle, we reveal a correlation coefficient of 0.9058292 and a p-value less than 0.01 for the period of 2002 to 2014. It seems that the waves of shipwrecks and ELP's stock price have been dancing a merry jig in unison, much like a pirate's parrot and its sea shanty. As we traverse the rough waters of statistical analysis, we also encountered some unexpected humor – after all, what do you call a ship captain’s sword that tells dad jokes? A pun-dulum!
So, come aboard our scholarly ship, and let's hoist the anchor of financial curiosity as we navigate these uncharted waters of shipwrecks and stock prices. Just remember, in the world of finance, sometimes the best treasure lies beneath the surface... or at the bottom of the sea!
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
Ahoy there, fellow scholars and investors! In this seafaring study, we set sail on a voyage to uncover the curious correlation between global shipwrecks and the stock price of Cia Paranaense De Energia Copel (ELP). As we navigate the choppy waters of financial data and maritime mishaps, we will delve into the depths of statistical analysis to unravel this mysterious relationship. But before we dive in, let me tell you a joke: Why did the sailor become a musician? Because he had perfect pitch! Just like a sailor navigating through stormy seas, we aim to steer through the turbulent financial waters with precision and a healthy dose of humor.
The maritime industry has long captivated our curiosity, sparking tales of adventure, peril, and occasionally, unexpected connections to the world of finance. Our research sets out to shed light on this captivating intersection, all while keeping in mind the old adage: What did the ocean say to the sailboat? Nothing, it just waved.
In recent years, the fascination with stock market movements has drawn parallels to the unpredictable nature of the open sea. It's as if the stock market is the financial equivalent of a high-stakes game of battleship – you never quite know where the next hit will land. Our investigation aims to uncover the extent to which shipwrecks, with their tumultuous history and potential for hidden treasures, are intertwined with the stock price of ELP. A quick, yet relevant joke – What did the ocean say to the pirate? Nothing, it just waved – and similarly, we shall explore the waves of data to uncover any hidden treasure troves of knowledge.
As we embark on this expedition, we anticipate encountering waves of empirical evidence and statistical analyses that will help us navigate through the complexities of this intriguing relationship. Our research seeks to shed light on the interplay between historical shipwrecks and the stock price movements of ELP, offering insights that may surprise even the most seasoned of financial seafarers. And now, a seafaring joke to keep us afloat: How much does it cost for a pirate to pierce his ears? About a buck an earrrrrr!
So, batten down the hatches and ready the sails as we embark on this exhilarating journey through the turbulent waters of finance and nautical history. We invite you to join us on this thrilling expedition and raise the anchor of financial knowledge as we aim to uncover the hidden treasures submerged in the depths of global shipwrecks and stock price movements. After all, in the world of data analysis, there's always room for a good shipwreck pun – but for now, let's dive deeper into the depths of our investigation.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a literature review section of an academic research paper presenting the findings of the connection between Global shipwrecks and Cia Paranaense De Energia Copel's stock price (ELP). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
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]]
Navigating the Seas of Stock Market: A Shipwrecking Analysis of Cia Paranaense De Energia Copel's (ELP) Stock Price
[[ABSTRACT]]
Ahoy, fellow researchers and financiers! In this paper, we embark on a humorous yet enlightening journey to explore the intriguing correlation between global shipwrecks and Cia Paranaense De Energia Copel's (ELP) stock price. Using data extracted from the treasure chest of Wikipedia and the compass of LSEG Analytics (Refinitiv), we charted a course to untangle this mysterious relationship.
With a twinkle in our eyes and a hearty chuckle, we reveal a correlation coefficient of 0.9058292 and a p-value less than 0.01 for the period of 2002 to 2014. It seems that the waves of shipwrecks and ELP's stock price have been dancing a merry jig in unison, much like a pirate's parrot and its sea shanty. As we traverse the rough waters of statistical analysis, we also encountered some unexpected humor – after all, what do you call a ship captain’s sword that tells dad jokes? A pun-dulum!
So, come aboard our scholarly ship, and let's hoist the anchor of financial curiosity as we navigate these uncharted waters of shipwrecks and stock prices. Just remember, in the world of finance, sometimes the best treasure lies beneath the surface... or at the bottom of the sea!
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Ahoy there, fellow scholars and investors! In this seafaring study, we set sail on a voyage to uncover the curious correlation between global shipwrecks and the stock price of Cia Paranaense De Energia Copel (ELP). As we navigate the choppy waters of financial data and maritime mishaps, we will delve into the depths of statistical analysis to unravel this mysterious relationship. But before we dive in, let me tell you a joke: Why did the sailor become a musician? Because he had perfect pitch! Just like a sailor navigating through stormy seas, we aim to steer through the turbulent financial waters with precision and a healthy dose of humor.
The maritime industry has long captivated our curiosity, sparking tales of adventure, peril, and occasionally, unexpected connections to the world of finance. Our research sets out to shed light on this captivating intersection, all while keeping in mind the old adage: What did the ocean say to the sailboat? Nothing, it just waved.
In recent years, the fascination with stock market movements has drawn parallels to the unpredictable nature of the open sea. It's as if the stock market is the financial equivalent of a high-stakes game of battleship – you never quite know where the next hit will land. Our investigation aims to uncover the extent to which shipwrecks, with their tumultuous history and potential for hidden treasures, are intertwined with the stock price of ELP. A quick, yet relevant joke – What did the ocean say to the pirate? Nothing, it just waved – and similarly, we shall explore the waves of data to uncover any hidden treasure troves of knowledge.
As we embark on this expedition, we anticipate encountering waves of empirical evidence and statistical analyses that will help us navigate through the complexities of this intriguing relationship. Our research seeks to shed light on the interplay between historical shipwrecks and the stock price movements of ELP, offering insights that may surprise even the most seasoned of financial seafarers. And now, a seafaring joke to keep us afloat: How much does it cost for a pirate to pierce his ears? About a buck an earrrrrr!
So, batten down the hatches and ready the sails as we embark on this exhilarating journey through the turbulent waters of finance and nautical history. We invite you to join us on this thrilling expedition and raise the anchor of financial knowledge as we aim to uncover the hidden treasures submerged in the depths of global shipwrecks and stock price movements. After all, in the world of data analysis, there's always room for a good shipwreck pun – but for now, let's dive deeper into the depths of our investigation.
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
Turning our attention to the existing body of literature on the subject of shipwrecks and stock market correlations, we first encounter the work of Smith et al. In "Navigating the Depths of Financial Data," the authors find a compelling link between historical maritime disasters and stock price variability, sparking intrigue and raising questions as to the underlying mechanisms at play. However, let's not "ship-sink" the relevance of other studies, such as Doe's "Anchors Aweigh: Exploring the Interconnectedness of Shipwrecks and Financial Markets," which further illuminates the potential impact of global shipwrecks on stock market dynamics.
But, hold on to your lifebuoys, because we're about to take a detour into unexpected waters. Consider, for instance, the book "Treasure Island" by Robert Louis Stevenson, which, while a work of fiction, offers a captivating narrative that resonates with the themes of buried wealth and maritime lore. As we navigate the figurative seas of scholarly inquiry, we cannot overlook the thought-provoking insights found in Clive Cussler's "Shipwreck" series, which, while not academic in nature, serves as a reminder of the enduring fascination with maritime mishaps and their potential ramifications.
And now, for a light-hearted deviation into internet culture, cast your mind back to the "This is Fine" meme. While typically symbolizing a comically chaotic situation, it ironically captures the precarious nature of financial markets and the unexpected entanglements that can arise, much like a ship caught in a tempest. Similarly, the "Distracted Boyfriend" meme lends a sardonic yet relevant commentary on the ever-changing allegiances and surprising connections within complex systems – a notion not entirely dissimilar to the enigmatic relationship between shipwrecks and stock prices.
In essence, our foray into the existing literature yields a rich tapestry of insights, both serious and whimsical, illustrating the multifaceted nature of this captivating subject. With our proverbial sails at full mast, we set a course to chart new territory and uncover the hidden treasures that lie beneath the turbulent waters of global shipwrecks and stock price movements. After all, what do you call a pirate's favorite data visualization tool? A barrrrrr chart! Now, let us navigate the tides of empirical analysis and statistical scrutiny with a hearty sense of academic curiosity and a touch of seafaring humor.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the methodology section of an academic research paper presenting the findings of the connection between Global shipwrecks and Cia Paranaense De Energia Copel's stock price (ELP). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Your research team collected data from all across the internet, but mostly just used information from Wikipedia and LSEG Analytics (Refinitiv) . You used data from 2002 to 2014
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]]
Navigating the Seas of Stock Market: A Shipwrecking Analysis of Cia Paranaense De Energia Copel's (ELP) Stock Price
[[ABSTRACT]]
Ahoy, fellow researchers and financiers! In this paper, we embark on a humorous yet enlightening journey to explore the intriguing correlation between global shipwrecks and Cia Paranaense De Energia Copel's (ELP) stock price. Using data extracted from the treasure chest of Wikipedia and the compass of LSEG Analytics (Refinitiv), we charted a course to untangle this mysterious relationship.
With a twinkle in our eyes and a hearty chuckle, we reveal a correlation coefficient of 0.9058292 and a p-value less than 0.01 for the period of 2002 to 2014. It seems that the waves of shipwrecks and ELP's stock price have been dancing a merry jig in unison, much like a pirate's parrot and its sea shanty. As we traverse the rough waters of statistical analysis, we also encountered some unexpected humor – after all, what do you call a ship captain’s sword that tells dad jokes? A pun-dulum!
So, come aboard our scholarly ship, and let's hoist the anchor of financial curiosity as we navigate these uncharted waters of shipwrecks and stock prices. Just remember, in the world of finance, sometimes the best treasure lies beneath the surface... or at the bottom of the sea!
[[INTRODUCTION]]
Ahoy there, fellow scholars and investors! In this seafaring study, we set sail on a voyage to uncover the curious correlation between global shipwrecks and the stock price of Cia Paranaense De Energia Copel (ELP). As we navigate the choppy waters of financial data and maritime mishaps, we will delve into the depths of statistical analysis to unravel this mysterious relationship. But before we dive in, let me tell you a joke: Why did the sailor become a musician? Because he had perfect pitch! Just like a sailor navigating through stormy seas, we aim to steer through the turbulent financial waters with precision and a healthy dose of humor.
The maritime industry has long captivated our curiosity, sparking tales of adventure, peril, and occasionally, unexpected connections to the world of finance. Our research sets out to shed light on this captivating intersection, all while keeping in mind the old adage: What did the ocean say to the sailboat? Nothing, it just waved.
In recent years, the fascination with stock market movements has drawn parallels to the unpredictable nature of the open sea. It's as if the stock market is the financial equivalent of a high-stakes game of battleship – you never quite know where the next hit will land. Our investigation aims to uncover the extent to which shipwrecks, with their tumultuous history and potential for hidden treasures, are intertwined with the stock price of ELP. A quick, yet relevant joke – What did the ocean say to the pirate? Nothing, it just waved – and similarly, we shall explore the waves of data to uncover any hidden treasure troves of knowledge.
As we embark on this expedition, we anticipate encountering waves of empirical evidence and statistical analyses that will help us navigate through the complexities of this intriguing relationship. Our research seeks to shed light on the interplay between historical shipwrecks and the stock price movements of ELP, offering insights that may surprise even the most seasoned of financial seafarers. And now, a seafaring joke to keep us afloat: How much does it cost for a pirate to pierce his ears? About a buck an earrrrrr!
So, batten down the hatches and ready the sails as we embark on this exhilarating journey through the turbulent waters of finance and nautical history. We invite you to join us on this thrilling expedition and raise the anchor of financial knowledge as we aim to uncover the hidden treasures submerged in the depths of global shipwrecks and stock price movements. After all, in the world of data analysis, there's always room for a good shipwreck pun – but for now, let's dive deeper into the depths of our investigation.
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
(This section is where the rubber meets the road, or should we say, the ship meets the sea! But don't worry, we won't leave you high and dry with flimsy methods. We'll steer through the methodology with the precision of an experienced sea captain – or at least with the enthusiasm of a dad telling one more maritime pun.)
Our research embarked on a daring voyage across the vast and wild oceans of data collection, seeking to gather the necessary information to navigate the swirling currents of statistical analysis. With a hearty "Aye, aye!" and a trusty compass in hand, we set sail through the treacherous waters of digital archives, primarily utilizing data from the trustworthy repositories of Wikipedia and LSEG Analytics (Refinitiv).
With the keen eye of a sailor scanning the horizon for distant land, we carefully selected the period from 2002 to 2014 to guide our research voyage. This timeframe provided a sturdy anchor for our analysis, allowing us to capture the ebbs and flows of both global shipwrecks and the stock price of Cia Paranaense De Energia Copel (ELP) with the precision of a seasoned mariner - or at least as precise as a sailor's compass in a magnetic storm.
To navigate the murky depths of our data, we employed a variety of statistical methods, including correlation analysis, time series modeling, and regression techniques fit for a sea monster of a dataset. As we combed through the waves of data, we kept a keen eye out for any hidden treasures of insight that might surface. Like a skilled sailor adept at unraveling knotted ropes, we diligently untangled the complexities of our dataset to unearth meaningful patterns and relationships, all while keeping an eye out for the occasional statistical sea monster lurking beneath the surface.
Now, just like an unexpected gust of wind catching the sails, we encountered a few unexpected quirks and challenges during our voyage. But fear not! We weathered the statistical tempest with the tenacity of a seasoned seafarer, adjusting our course and charting a new path to ensure the integrity of our analysis remained as steady as a ship in a calm harbor - or at least steady enough to crack a few more sea-themed puns.
Our data analysis journey was not without its fair share of maritime mishaps and statistical squalls, but armed with determination and a willingness to navigate the choppy waters, we emerged victorious, ready to present our findings with the gusto of a pirate declaring newfound treasure. So, join us as we hoist the flag of statistical rigor high and set sail towards the treasure trove of empirical findings with the spirit of adventure and a splash of dad humor. After all, what do you get when you cross a pirate with a pedant? A grammar seafarer! Now, with the storm behind us, let's dive into the depths of our research findings.
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the results section of an academic research paper presenting the findings of the connection between Global shipwrecks and Cia Paranaense De Energia Copel's stock price (ELP). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
Your research team collected data from all across the internet, but mostly just used information from Wikipedia and LSEG Analytics (Refinitiv) .
For the time period 2002 to 2014, you found a correlation 0.9058292, r-squared of 0.8205265, 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]]
Navigating the Seas of Stock Market: A Shipwrecking Analysis of Cia Paranaense De Energia Copel's (ELP) Stock Price
[[ABSTRACT]]
Ahoy, fellow researchers and financiers! In this paper, we embark on a humorous yet enlightening journey to explore the intriguing correlation between global shipwrecks and Cia Paranaense De Energia Copel's (ELP) stock price. Using data extracted from the treasure chest of Wikipedia and the compass of LSEG Analytics (Refinitiv), we charted a course to untangle this mysterious relationship.
With a twinkle in our eyes and a hearty chuckle, we reveal a correlation coefficient of 0.9058292 and a p-value less than 0.01 for the period of 2002 to 2014. It seems that the waves of shipwrecks and ELP's stock price have been dancing a merry jig in unison, much like a pirate's parrot and its sea shanty. As we traverse the rough waters of statistical analysis, we also encountered some unexpected humor – after all, what do you call a ship captain’s sword that tells dad jokes? A pun-dulum!
So, come aboard our scholarly ship, and let's hoist the anchor of financial curiosity as we navigate these uncharted waters of shipwrecks and stock prices. Just remember, in the world of finance, sometimes the best treasure lies beneath the surface... or at the bottom of the sea!
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
Ahoy there, fellow scholars and investors! In this seafaring study, we set sail on a voyage to uncover the curious correlation between global shipwrecks and the stock price of Cia Paranaense De Energia Copel (ELP). As we navigate the choppy waters of financial data and maritime mishaps, we will delve into the depths of statistical analysis to unravel this mysterious relationship. But before we dive in, let me tell you a joke: Why did the sailor become a musician? Because he had perfect pitch! Just like a sailor navigating through stormy seas, we aim to steer through the turbulent financial waters with precision and a healthy dose of humor.
The maritime industry has long captivated our curiosity, sparking tales of adventure, peril, and occasionally, unexpected connections to the world of finance. Our research sets out to shed light on this captivating intersection, all while keeping in mind the old adage: What did the ocean say to the sailboat? Nothing, it just waved.
In recent years, the fascination with stock market movements has drawn parallels to the unpredictable nature of the open sea. It's as if the stock market is the financial equivalent of a high-stakes game of battleship – you never quite know where the next hit will land. Our investigation aims to uncover the extent to which shipwrecks, with their tumultuous history and potential for hidden treasures, are intertwined with the stock price of ELP. A quick, yet relevant joke – What did the ocean say to the pirate? Nothing, it just waved – and similarly, we shall explore the waves of data to uncover any hidden treasure troves of knowledge.
As we embark on this expedition, we anticipate encountering waves of empirical evidence and statistical analyses that will help us navigate through the complexities of this intriguing relationship. Our research seeks to shed light on the interplay between historical shipwrecks and the stock price movements of ELP, offering insights that may surprise even the most seasoned of financial seafarers. And now, a seafaring joke to keep us afloat: How much does it cost for a pirate to pierce his ears? About a buck an earrrrrr!
So, batten down the hatches and ready the sails as we embark on this exhilarating journey through the turbulent waters of finance and nautical history. We invite you to join us on this thrilling expedition and raise the anchor of financial knowledge as we aim to uncover the hidden treasures submerged in the depths of global shipwrecks and stock price movements. After all, in the world of data analysis, there's always room for a good shipwreck pun – but for now, let's dive deeper into the depths of our investigation.
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The results of our analysis reveal a strong and significant correlation between global shipwrecks and the stock price of Cia Paranaense De Energia Copel (ELP) for the period of 2002 to 2014. The correlation coefficient of 0.9058292 indicates a robust positive relationship between these two variables, suggesting that as the number of global shipwrecks increases, so does the stock price of ELP. It's almost as if the stock price is riding the waves of shipwrecks like a seasoned pirate aboard the Black Pearl!
Furthermore, the high R-squared value of 0.8205265 demonstrates that a substantial proportion of the variability in ELP's stock price can be explained by the fluctuations in global shipwrecks. It's as if the shipwrecks are charting the course for the stock price, much like a compass guiding a ship through treacherous waters. One might even say that the shipwrecks act as the first mate to ELP's stock price, steering it through the choppy seas of financial markets.
The p-value being less than 0.01 adds to the confidence in the strength of this relationship, providing statistical support for the notion that the occurrence of global shipwrecks is indeed associated with movements in ELP's stock price. It's as if the relationship between the two is as solid as a ship's hull, weathering the storm of statistical scrutiny and emerging unscathed.
Fig. 1 portrays the correlation between global shipwrecks and ELP's stock price with a scatterplot, further illustrating the synchronous dance of these two variables. The figure shows the tight clustering of data points, akin to a fleet of ships navigating the vast expanse of the stock market, all guided by the winds of shipwrecks.
In conclusion, our findings not only unveil a strong statistical association between global shipwrecks and ELP's stock price but also shed light on the captivating interplay between maritime mishaps and financial movements. It's as if the waves of shipwrecks are whispering secrets to the stock market, revealing hidden treasures beneath the surface – just like a deep-sea dive for buried riches. As we wrap up this section, here's a fitting joke: What do you call a pirate who has lost his ship? A ... a ... 'matey'!
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the discussion section of an academic research paper presenting the findings of the connection between Global shipwrecks and Cia Paranaense De Energia Copel's stock price (ELP). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
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]]
Navigating the Seas of Stock Market: A Shipwrecking Analysis of Cia Paranaense De Energia Copel's (ELP) Stock Price
[[ABSTRACT]]
Ahoy, fellow researchers and financiers! In this paper, we embark on a humorous yet enlightening journey to explore the intriguing correlation between global shipwrecks and Cia Paranaense De Energia Copel's (ELP) stock price. Using data extracted from the treasure chest of Wikipedia and the compass of LSEG Analytics (Refinitiv), we charted a course to untangle this mysterious relationship.
With a twinkle in our eyes and a hearty chuckle, we reveal a correlation coefficient of 0.9058292 and a p-value less than 0.01 for the period of 2002 to 2014. It seems that the waves of shipwrecks and ELP's stock price have been dancing a merry jig in unison, much like a pirate's parrot and its sea shanty. As we traverse the rough waters of statistical analysis, we also encountered some unexpected humor – after all, what do you call a ship captain’s sword that tells dad jokes? A pun-dulum!
So, come aboard our scholarly ship, and let's hoist the anchor of financial curiosity as we navigate these uncharted waters of shipwrecks and stock prices. Just remember, in the world of finance, sometimes the best treasure lies beneath the surface... or at the bottom of the sea!
[[LITERATURE REVIEW]]
Turning our attention to the existing body of literature on the subject of shipwrecks and stock market correlations, we first encounter the work of Smith et al. In "Navigating the Depths of Financial Data," the authors find a compelling link between historical maritime disasters and stock price variability, sparking intrigue and raising questions as to the underlying mechanisms at play. However, let's not "ship-sink" the relevance of other studies, such as Doe's "Anchors Aweigh: Exploring the Interconnectedness of Shipwrecks and Financial Markets," which further illuminates the potential impact of global shipwrecks on stock market dynamics.
But, hold on to your lifebuoys, because we're about to take a detour into unexpected waters. Consider, for instance, the book "Treasure Island" by Robert Louis Stevenson, which, while a work of fiction, offers a captivating narrative that resonates with the themes of buried wealth and maritime lore. As we navigate the figurative seas of scholarly inquiry, we cannot overlook the thought-provoking insights found in Clive Cussler's "Shipwreck" series, which, while not academic in nature, serves as a reminder of the enduring fascination with maritime mishaps and their potential ramifications.
And now, for a light-hearted deviation into internet culture, cast your mind back to the "This is Fine" meme. While typically symbolizing a comically chaotic situation, it ironically captures the precarious nature of financial markets and the unexpected entanglements that can arise, much like a ship caught in a tempest. Similarly, the "Distracted Boyfriend" meme lends a sardonic yet relevant commentary on the ever-changing allegiances and surprising connections within complex systems – a notion not entirely dissimilar to the enigmatic relationship between shipwrecks and stock prices.
In essence, our foray into the existing literature yields a rich tapestry of insights, both serious and whimsical, illustrating the multifaceted nature of this captivating subject. With our proverbial sails at full mast, we set a course to chart new territory and uncover the hidden treasures that lie beneath the turbulent waters of global shipwrecks and stock price movements. After all, what do you call a pirate's favorite data visualization tool? A barrrrrr chart! Now, let us navigate the tides of empirical analysis and statistical scrutiny with a hearty sense of academic curiosity and a touch of seafaring humor.
[[RESULTS]]
The results of our analysis reveal a strong and significant correlation between global shipwrecks and the stock price of Cia Paranaense De Energia Copel (ELP) for the period of 2002 to 2014. The correlation coefficient of 0.9058292 indicates a robust positive relationship between these two variables, suggesting that as the number of global shipwrecks increases, so does the stock price of ELP. It's almost as if the stock price is riding the waves of shipwrecks like a seasoned pirate aboard the Black Pearl!
Furthermore, the high R-squared value of 0.8205265 demonstrates that a substantial proportion of the variability in ELP's stock price can be explained by the fluctuations in global shipwrecks. It's as if the shipwrecks are charting the course for the stock price, much like a compass guiding a ship through treacherous waters. One might even say that the shipwrecks act as the first mate to ELP's stock price, steering it through the choppy seas of financial markets.
The p-value being less than 0.01 adds to the confidence in the strength of this relationship, providing statistical support for the notion that the occurrence of global shipwrecks is indeed associated with movements in ELP's stock price. It's as if the relationship between the two is as solid as a ship's hull, weathering the storm of statistical scrutiny and emerging unscathed.
Fig. 1 portrays the correlation between global shipwrecks and ELP's stock price with a scatterplot, further illustrating the synchronous dance of these two variables. The figure shows the tight clustering of data points, akin to a fleet of ships navigating the vast expanse of the stock market, all guided by the winds of shipwrecks.
In conclusion, our findings not only unveil a strong statistical association between global shipwrecks and ELP's stock price but also shed light on the captivating interplay between maritime mishaps and financial movements. It's as if the waves of shipwrecks are whispering secrets to the stock market, revealing hidden treasures beneath the surface – just like a deep-sea dive for buried riches. As we wrap up this section, here's a fitting joke: What do you call a pirate who has lost his ship? A ... a ... 'matey'!
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
Our results provide robust support for the prior research that posited a link between global shipwrecks and the stock price of Cia Paranaense De Energia Copel (ELP). Smith et al.'s findings on the correlation between historical maritime disasters and stock price variability are echoed in our study, as we uncovered a strong positive relationship between these two variables. The magnitude of the correlation coefficient further strengthens the case for a significant association, akin to the sturdy frame of a well-constructed ship. It seems that the waves of shipwrecks and ELP's stock price have indeed been dancing in harmony, much like a perfectly synchronized crew on a pirate ship performing a lively sea shanty. Ahoy, matey, these findings are no mere flotsam and jetsam – they provide concrete evidence of a substantial connection between global shipwrecks and stock market dynamics.
Likewise, Doe's exploration of the interconnectedness of shipwrecks and financial markets finds resonance in our study's results. Our analysis revealed a high R-squared value, signifying that a large proportion of the variance in ELP's stock price can be explained by fluctuations in global shipwrecks. It's as if the shipwrecks are not merely adrift at sea but rather serving as guiding lights for the stock price, akin to the steadfast beacon of a lighthouse guiding sailors through tumultuous waters. One might jest that the shipwrecks are the true financial seafarers, charting the course for ELP's stock price through the unpredictable waves of market dynamics.
Furthermore, our statistical significance, as evidenced by the p-value being less than 0.01, adds weight to the empirical support for the relationship between global shipwrecks and ELP's stock price. This is akin to an anchor firmly securing a ship amidst a turbulent storm, underscoring the substantial and tangible nature of this association. It's as if the statistical scrutiny has unraveled a treasure trove of evidence, akin to the bountiful spoils revealed by an intrepid crew upon discovering a long-lost shipwreck.
In essence, our findings not only confirm but also build upon the existing literature, adding a weighty cargo of empirical evidence to the intriguing narrative of oceanic disasters and financial markets. They invite us to explore further, as if beckoning us to sail into uncharted waters and uncover the buried riches of knowledge that lie beneath the surface. It's almost as if the research journey itself mirrors the intrepid spirit of a daring sea voyage, replete with unexpected discoveries and precious insights waiting to be unearthed – just like a treasure map leading to untold academic wealth!
And, as a fitting jest to honor our research findings, here’s a pun: Why don't pirates shower before they walk the plank? Because they'll just wash up on shore later!
Model: gpt-3.5-turbo-1106
System prompt: You are a witty academic researcher. Your writing sounds like it belongs in a statistics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a short conclusion of an academic research paper presenting the findings of the connection between Global shipwrecks and Cia Paranaense De Energia Copel's stock price (ELP). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.
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]]
Navigating the Seas of Stock Market: A Shipwrecking Analysis of Cia Paranaense De Energia Copel's (ELP) Stock Price
[[ABSTRACT]]
Ahoy, fellow researchers and financiers! In this paper, we embark on a humorous yet enlightening journey to explore the intriguing correlation between global shipwrecks and Cia Paranaense De Energia Copel's (ELP) stock price. Using data extracted from the treasure chest of Wikipedia and the compass of LSEG Analytics (Refinitiv), we charted a course to untangle this mysterious relationship.
With a twinkle in our eyes and a hearty chuckle, we reveal a correlation coefficient of 0.9058292 and a p-value less than 0.01 for the period of 2002 to 2014. It seems that the waves of shipwrecks and ELP's stock price have been dancing a merry jig in unison, much like a pirate's parrot and its sea shanty. As we traverse the rough waters of statistical analysis, we also encountered some unexpected humor – after all, what do you call a ship captain’s sword that tells dad jokes? A pun-dulum!
So, come aboard our scholarly ship, and let's hoist the anchor of financial curiosity as we navigate these uncharted waters of shipwrecks and stock prices. Just remember, in the world of finance, sometimes the best treasure lies beneath the surface... or at the bottom of the sea!
[[INTRDUCTION]]
Ahoy there, fellow scholars and investors! In this seafaring study, we set sail on a voyage to uncover the curious correlation between global shipwrecks and the stock price of Cia Paranaense De Energia Copel (ELP). As we navigate the choppy waters of financial data and maritime mishaps, we will delve into the depths of statistical analysis to unravel this mysterious relationship. But before we dive in, let me tell you a joke: Why did the sailor become a musician? Because he had perfect pitch! Just like a sailor navigating through stormy seas, we aim to steer through the turbulent financial waters with precision and a healthy dose of humor.
The maritime industry has long captivated our curiosity, sparking tales of adventure, peril, and occasionally, unexpected connections to the world of finance. Our research sets out to shed light on this captivating intersection, all while keeping in mind the old adage: What did the ocean say to the sailboat? Nothing, it just waved.
In recent years, the fascination with stock market movements has drawn parallels to the unpredictable nature of the open sea. It's as if the stock market is the financial equivalent of a high-stakes game of battleship – you never quite know where the next hit will land. Our investigation aims to uncover the extent to which shipwrecks, with their tumultuous history and potential for hidden treasures, are intertwined with the stock price of ELP. A quick, yet relevant joke – What did the ocean say to the pirate? Nothing, it just waved – and similarly, we shall explore the waves of data to uncover any hidden treasure troves of knowledge.
As we embark on this expedition, we anticipate encountering waves of empirical evidence and statistical analyses that will help us navigate through the complexities of this intriguing relationship. Our research seeks to shed light on the interplay between historical shipwrecks and the stock price movements of ELP, offering insights that may surprise even the most seasoned of financial seafarers. And now, a seafaring joke to keep us afloat: How much does it cost for a pirate to pierce his ears? About a buck an earrrrrr!
So, batten down the hatches and ready the sails as we embark on this exhilarating journey through the turbulent waters of finance and nautical history. We invite you to join us on this thrilling expedition and raise the anchor of financial knowledge as we aim to uncover the hidden treasures submerged in the depths of global shipwrecks and stock price movements. After all, in the world of data analysis, there's always room for a good shipwreck pun – but for now, let's dive deeper into the depths of our investigation.
[[RESULTS]]
The results of our analysis reveal a strong and significant correlation between global shipwrecks and the stock price of Cia Paranaense De Energia Copel (ELP) for the period of 2002 to 2014. The correlation coefficient of 0.9058292 indicates a robust positive relationship between these two variables, suggesting that as the number of global shipwrecks increases, so does the stock price of ELP. It's almost as if the stock price is riding the waves of shipwrecks like a seasoned pirate aboard the Black Pearl!
Furthermore, the high R-squared value of 0.8205265 demonstrates that a substantial proportion of the variability in ELP's stock price can be explained by the fluctuations in global shipwrecks. It's as if the shipwrecks are charting the course for the stock price, much like a compass guiding a ship through treacherous waters. One might even say that the shipwrecks act as the first mate to ELP's stock price, steering it through the choppy seas of financial markets.
The p-value being less than 0.01 adds to the confidence in the strength of this relationship, providing statistical support for the notion that the occurrence of global shipwrecks is indeed associated with movements in ELP's stock price. It's as if the relationship between the two is as solid as a ship's hull, weathering the storm of statistical scrutiny and emerging unscathed.
Fig. 1 portrays the correlation between global shipwrecks and ELP's stock price with a scatterplot, further illustrating the synchronous dance of these two variables. The figure shows the tight clustering of data points, akin to a fleet of ships navigating the vast expanse of the stock market, all guided by the winds of shipwrecks.
In conclusion, our findings not only unveil a strong statistical association between global shipwrecks and ELP's stock price but also shed light on the captivating interplay between maritime mishaps and financial movements. It's as if the waves of shipwrecks are whispering secrets to the stock market, revealing hidden treasures beneath the surface – just like a deep-sea dive for buried riches. As we wrap up this section, here's a fitting joke: What do you call a pirate who has lost his ship? A ... a ... 'matey'!
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
To plunge into the depths of this research, we have unearthed a compelling relationship between global shipwrecks and the stock price of Cia Paranaense De Energia Copel (ELP). The robust correlation coefficient of 0.9058292 and a p-value less than 0.01 affirm that these two seemingly disparate entities have been sailing in tandem, much like two ships navigating the same course. It's almost as if the stock price has found its first mate in the world of shipwrecks, sailing alongside with unwavering determination.
The high R-squared value further demonstrates the profound impact of global shipwrecks on ELP's stock price, as if the shipwrecks are casting a net and reeling in the movements of the stock price like a seasoned fisherman. It truly showcases the interconnectedness of these two domains, much like the intricate web of the ocean's ecosystem.
In light of these findings, it seems that the world of finance and maritime history are not as far apart as they may seem. Perhaps the stock market can be likened to a treacherous sea, and global shipwrecks serve as lighthouses guiding the movements of stock prices through the tumultuous waters. As we conclude this study, it's only fitting to share a nautical joke: Why don't pirates shower before they walk the plank? Because they'll just wash up onshore later!
In summation, the correlation between global shipwrecks and ELP's stock price has been unveiled with sublime clarity. It is as if the waves of shipwrecks and financial fluctuations are engaged in an orchestrated dance, each influencing the movements of the other. Therefore, we boldly assert that no further research in this area is needed, for this study has thoroughly navigated the intricate waters of this captivating relationship, leaving no 'ship' unturned.
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 Navigating the Seas of Stock Market: A Shipwrecking Analysis of Cia Paranaense De Energia Copel's (ELP) Stock Price. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Financial Frivolity
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 Navigating the Seas of Stock Market: A Shipwrecking Analysis of Cia Paranaense De Energia Copel's (ELP) Stock Price. Respond only with the name of a fictional organization.
ChatGPT:
Institute for Financial Navigation and 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 Navigating the Seas of Stock Market: A Shipwrecking Analysis of Cia Paranaense De Energia Copel's (ELP) Stock Price with an abstract of Ahoy, fellow researchers and financiers! In this paper, we embark on a humorous yet enlightening journey to explore the intriguing correlation between global shipwrecks and Cia Paranaense De Energia Copel's (ELP) stock price. Using data extracted from the treasure chest of Wikipedia and the compass of LSEG Analytics (Refinitiv), we charted a course to untangle this mysterious relationship.
With a twinkle in our eyes and a hearty chuckle, we reveal a correlation coefficient of 0.9058292 and a p-value less than 0.01 for the period of 2002 to 2014. It seems that the waves of shipwrecks and ELP's stock price have been dancing a merry jig in unison, much like a pirate's parrot and its sea shanty. As we traverse the rough waters of statistical analysis, we also encountered some unexpected humor – after all, what do you call a ship captain’s sword that tells dad jokes? A pun-dulum!
So, come aboard our scholarly ship, and let's hoist the anchor of financial curiosity as we navigate these uncharted waters of shipwrecks and stock prices. Just remember, in the world of finance, sometimes the best treasure lies beneath the surface... or at the bottom of the sea!
ChatGPT:
Cia Paranaense De Energia Copel, ELP, stock price, global shipwrecks, correlation analysis, Wikipedia data, LSEG Analytics, Refinitiv, statistical analysis, correlation coefficient, p-value, financial analysis, stock market, maritime disasters, sea shanty, pirate, statistical correlation, finance, treasure, maritime industry
*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.
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Data details
Global shipwrecksDetailed data title: Ships sunk, foundered, grounded, or otherwise lost during the year
Source: Wikipedia
See what else correlates with Global shipwrecks
Cia Paranaense De Energia Copel's stock price (ELP)
Detailed data title: Opening price of Cia Paranaense De Energia Copel (ELP) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: Via Microsoft Excel Stockhistory function
See what else correlates with Cia Paranaense De Energia Copel's stock price (ELP)
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 = 0.8205265 (Coefficient of determination)
This means 82.1% of the change in the one variable (i.e., Cia Paranaense De Energia Copel's stock price (ELP)) is predictable based on the change in the other (i.e., Global shipwrecks ) over the 13 years from 2002 through 2014.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.02E-5. 0.0000201501731292758700000000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.
But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.
Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.91 in 0.00202% of random cases. Said differently, if you correlated 49,627 random variables You don't actually need 49 thousand variables to find a correlation like this one. 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.
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, 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.
[ 0.71, 0.97 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.
This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!
All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.
Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | |
Global shipwrecks (Wrecks) | 16 | 15 | 18 | 6 | 13 | 33 | 31 | 55 | 71 | 123 | 111 | 70 | 52 |
Cia Paranaense De Energia Copel's stock price (ELP) (Stock price) | 3.75 | 1.43 | 2.39 | 2.23 | 4 | 5.99 | 7.54 | 5.27 | 11.02 | 12.62 | 10.36 | 7.83 | 6.44 |
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
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
Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
Try it yourself
You can calculate the values on this page on your own! Try running the Python code to see the calculation results. Step 1: Download and install Python on your computer.Step 2: Open a plaintext editor like Notepad and paste the code below into it.
Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"
Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.
Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.
Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.
Step 7: Run the Python script by typing "python calculate_correlation.py"
If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:
"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."
# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats
# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):
# Calculate Pearson correlation coefficient and p-value
correlation, p_value = stats.pearsonr(array1, array2)
# Calculate R-squared as the square of the correlation coefficient
r_squared = correlation**2
return correlation, r_squared, p_value
# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([16,15,18,6,13,33,31,55,71,123,111,70,52,])
array_2 = np.array([3.75,1.43,2.39,2.23,4,5.99,7.54,5.27,11.02,12.62,10.36,7.83,6.44,])
array_1_name = "Global shipwrecks "
array_2_name = "Cia Paranaense De Energia Copel's stock price (ELP)"
# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)
# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)
Reuseable content
You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.
For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."
When spoken, my last name is pronounced "vegan," like I don't eat meat.
Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.
Download images for these variables:
- High resolution line chart
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 Global shipwrecks
- Line chart for only Cia Paranaense De Energia Copel's stock price (ELP)
- AI-generated correlation image
- The spurious research paper: Navigating the Seas of Stock Market: A Shipwrecking Analysis of Cia Paranaense De Energia Copel's (ELP) Stock Price
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Correlation ID: 2941 · Black Variable ID: 504 · Red Variable ID: 1871