Download png, svg
AI explanation
As the name Lewis gained popularity, more and more people were subconsciously reminded of the iconic duo, Lewis and Regeneron (you know, like Lewis and Clark, but with lab coats). This led to an inexplicable surge in support for all things related to scientific discovery and pharmaceutical advancements. Essentially, it's as if the name Lewis became a catalyst for investor enthusiasm, creating a lewis acid-like reaction in the stock market, with REGN stock riding the positive wave. Who would've thought that a simple first name could have such a dose of influence on biotech stocks? It's like the market just couldn't keep its REGN under control!Model: dalle-3
Prompt: Generate an image of a cozy nursery with pastel-colored walls, filled with plush toys and a row of tiny, personalized baby blankets with the name "Lewis" embroidered on them hanging on a clothesline. Connected to this nursery is a sleek stock market office, where traders excitedly discuss the soaring stock price of Regeneron Pharmaceuticals. They are pointing at a large, illuminated stock ticker displaying the company's climbing numbers. The nursery and the stock market office are connected by a pulsating neon arrow, symbolizing the unexpected link between the popular name Lewis and the rise in Regeneron stock price. 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 situation described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here is a situation: "Scientists Uncover Surprising Link Between Popular Name Lewis and Rise in Regeneron Stock Price: A recent study has revealed that the meteoric rise in popularity of the name Lewis has coincided with a significant increase in the stock price of Regeneron Pharmaceuticals. Experts speculate that individuals named Lewis are unknowingly contributing to the demand for Regeneron's products, causing a spike in the company's stock value. Market analysts are now keeping a close eye on baby name trends to predict future stock market movements.". Given that situation, which of the following image descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand and the tone of the explanation. Please respond with only one of the following potential descriptions: Concept art High-tech Steampunk Low poly Voxel art
ChatGPT: High-tech
Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated and the explanation described. Do not reference graphs or charts; describe physical objects.
User prompt: Please describe a visual scene that depicts the following situation. Keep the description simple. "Scientists Uncover Surprising Link Between Popular Name Lewis and Rise in Regeneron Stock Price: A recent study has revealed that the meteoric rise in popularity of the name Lewis has coincided with a significant increase in the stock price of Regeneron Pharmaceuticals. Experts speculate that individuals named Lewis are unknowingly contributing to the demand for Regeneron's products, causing a spike in the company's stock value. Market analysts are now keeping a close eye on baby name trends to predict future stock market movements."
ChatGPT: In a cozy nursery adorned with pastel-colored walls and plush toys, a row of tiny, personalized baby blankets with the name "Lewis" embroidered on them hangs on a clothesline. Meanwhile, in a sleek stock market office, traders excitedly discuss the soaring stock price of Regeneron Pharmaceuticals, pointing at a large, illuminated stock ticker displaying the company's climbing numbers. The nursery and the stock market office are connected by a pulsating neon arrow, symbolizing the unexpected link between the popular name Lewis and the rise in Regeneron stock price.
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: [ High-tech ] and depicting this scene: In a cozy nursery adorned with pastel-colored walls and plush toys, a row of tiny, personalized baby blankets with the name "Lewis" embroidered on them hangs on a clothesline. Meanwhile, in a sleek stock market office, traders excitedly discuss the soaring stock price of Regeneron Pharmaceuticals, pointing at a large, illuminated stock ticker displaying the company's climbing numbers. The nursery and the stock market office are connected by a pulsating neon arrow, symbolizing the unexpected link between the popular name Lewis and the rise in Regeneron stock price. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a cozy nursery with pastel-colored walls, filled with plush toys and a row of tiny, personalized baby blankets with the name "Lewis" embroidered on them hanging on a clothesline. Connected to this nursery is a sleek stock market office, where traders excitedly discuss the soaring stock price of Regeneron Pharmaceuticals. They are pointing at a large, illuminated stock ticker displaying the company's climbing numbers. The nursery and the stock market office are connected by a pulsating neon arrow, symbolizing the unexpected link between the popular name Lewis and the rise in Regeneron stock price.
*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 Popularity of the first name Lewis caused Regeneron Pharmaceuticals' stock price (REGN) to increase. Include one good pun.
AI academic paper
The Lewis Effect on Regeneron: A Statistical Examination of the Impact of the First Name Lewis on Stock Prices The Journal of Quirky Quandaries in Economic Research Jan 2024 Reminder: This paper is AI-generated. Not real! |
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You write titles and abstracts of goofy academic research papers.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, and add unexpected twists in your writing.
Please draft the title and abstract of an academic research paper presenting the findings of the connection between Popularity of the first name Lewis and Regeneron Pharmaceuticals' stock price. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.
Rhyme words in the title.
Your research team used data from US Social Security Administration and LSEG Analytics (Refinitiv) to assess this nagging question. You found a correlation coefficient of 0.9709784 and p < 0.01 for 2002 to 2022.
Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)
[[TITLE]]
Lorem ipsum dolor sit
[[ABSTRACT]]
Lorem ipsum dolor sit
ChatGPT:
[[TITLE]]
The Lewis Effect on Regeneron: A Statistical Examination of the Impact of the First Name "Lewis" on Stock Prices
[[ABSTRACT]]
This paper aims to unravel the perplexing correlation between the popularity of the first name Lewis and the performance of Regeneron Pharmaceuticals' stock. Through a meticulous examination of US Social Security Administration data and LSEG Analytics (Refinitiv) information over the period 2002 to 2022, we unearth an astonishingly high correlation coefficient of 0.9709784 and a statistically significant p-value of less than 0.01. Our research delves into the quirky world of naming trends and financial markets, shedding light on the peculiar influence - be it serendipitous or utterly nonsensical - that monikers can have on the ever-fluctuating landscape of stock prices. This study serves as a lighthearted exploration of the unexpected realms where the whims of personal nomenclature intersect with the staid world of economic analysis.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the introduction section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the introduction section of an academic research paper presenting the findings of the connection between Popularity of the first name Lewis and Regeneron Pharmaceuticals' stock price. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.
Here is the title and abstract of the paper:
[[TITLE]]
The Lewis Effect on Regeneron: A Statistical Examination of the Impact of the First Name "Lewis" on Stock Prices
[[ABSTRACT]]
This paper aims to unravel the perplexing correlation between the popularity of the first name Lewis and the performance of Regeneron Pharmaceuticals' stock. Through a meticulous examination of US Social Security Administration data and LSEG Analytics (Refinitiv) information over the period 2002 to 2022, we unearth an astonishingly high correlation coefficient of 0.9709784 and a statistically significant p-value of less than 0.01. Our research delves into the quirky world of naming trends and financial markets, shedding light on the peculiar influence - be it serendipitous or utterly nonsensical - that monikers can have on the ever-fluctuating landscape of stock prices. This study serves as a lighthearted exploration of the unexpected realms where the whims of personal nomenclature intersect with the staid world of economic analysis.
-------
Your response should start like this:
[[INTRODUCTION]]
ChatGPT:
[[INTRODUCTION]]
There's an old saying that a rose by any other name might smell as sweet, but what if that name happened to be "Lewis" and its aroma was the sweet scent of stock market success? In this paradoxical pursuit of peculiar patterns, we delve into the enigmatic world where the unconventional realms of human nomenclature intersect with the often opaque domain of financial markets.
The influence of personal names on one's destiny has long been a subject of fascination, folklore, and, at times, frivolity. From astrological musings to literary references, the power of nomenclature has captivated the human imagination. But what about its impact on the decidedly less whimsical world of stock prices? Can the popularity of a specific first name really sway the fortunes of a pharmaceutical giant like Regeneron, or is it merely an amusing anecdote in the annals of statistical quirks?
Our quest for answers begins with a seemingly arbitrary inquiry: What if there existed a discernible connection between the ebb and flow of the stock market and the prevalence of a particular forename? What if the name "Lewis" held the key to unlocking the mystifying machinations of stock price trends? Could it be an uncanny coincidence, an obscure quirk, or sheer happenstance that brings together the realms of personal nomenclature and financial analysis?
Amidst the labyrinthine data sets, jargon-laden reports, and the solemnity of economic analysis, we embark on a light-hearted exploration. Our endeavor seeks to unravel the perplexing puzzle of the Lewis effect on Regeneron, amid the often buttoned-up world of high finance. As we navigate the statistical seas and unearth correlations, let us not forget to sprinkle a dash of levity into this curious confluence of monetary matters and monikers.
So, dear reader, fasten your seatbelts, for we are about to embark on an academic journey that may just shed light on the whimsical whims of the stock market and the surprisingly sprightly influence of a name like "Lewis."
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a literature review section of an academic research paper presenting the findings of the connection between Popularity of the first name Lewis and Regeneron Pharmaceuticals' stock price. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.
Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.
Make up the lorem and ipsum part, but make it sound related to the topic at hand.
Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then name a couple popular internet memes that are related to one of the topics.
Here is the title and abstract of the paper:
[[TITLE]]
The Lewis Effect on Regeneron: A Statistical Examination of the Impact of the First Name "Lewis" on Stock Prices
[[ABSTRACT]]
This paper aims to unravel the perplexing correlation between the popularity of the first name Lewis and the performance of Regeneron Pharmaceuticals' stock. Through a meticulous examination of US Social Security Administration data and LSEG Analytics (Refinitiv) information over the period 2002 to 2022, we unearth an astonishingly high correlation coefficient of 0.9709784 and a statistically significant p-value of less than 0.01. Our research delves into the quirky world of naming trends and financial markets, shedding light on the peculiar influence - be it serendipitous or utterly nonsensical - that monikers can have on the ever-fluctuating landscape of stock prices. This study serves as a lighthearted exploration of the unexpected realms where the whims of personal nomenclature intersect with the staid world of economic analysis.
-------
And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
There's an old saying that a rose by any other name might smell as sweet, but what if that name happened to be "Lewis" and its aroma was the sweet scent of stock market success? In this paradoxical pursuit of peculiar patterns, we delve into the enigmatic world where the unconventional realms of human nomenclature intersect with the often opaque domain of financial markets.
The influence of personal names on one's destiny has long been a subject of fascination, folklore, and, at times, frivolity. From astrological musings to literary references, the power of nomenclature has captivated the human imagination. But what about its impact on the decidedly less whimsical world of stock prices? Can the popularity of a specific first name really sway the fortunes of a pharmaceutical giant like Regeneron, or is it merely an amusing anecdote in the annals of statistical quirks?
Our quest for answers begins with a seemingly arbitrary inquiry: What if there existed a discernible connection between the ebb and flow of the stock market and the prevalence of a particular forename? What if the name "Lewis" held the key to unlocking the mystifying machinations of stock price trends? Could it be an uncanny coincidence, an obscure quirk, or sheer happenstance that brings together the realms of personal nomenclature and financial analysis?
Amidst the labyrinthine data sets, jargon-laden reports, and the solemnity of economic analysis, we embark on a light-hearted exploration. Our endeavor seeks to unravel the perplexing puzzle of the Lewis effect on Regeneron, amid the often buttoned-up world of high finance. As we navigate the statistical seas and unearth correlations, let us not forget to sprinkle a dash of levity into this curious confluence of monetary matters and monikers.
So, dear reader, fasten your seatbelts, for we are about to embark on an academic journey that may just shed light on the whimsical whims of the stock market and the surprisingly sprightly influence of a name like "Lewis."
-------
Your response should start like this:
[[LITERATURE REVIEW]]
ChatGPT:
[[LITERATURE REVIEW]]
The perplexing relationship between nomenclature and financial performance has spurred a plethora of inquiries and investigations. Smith (2015) postulates on the potential impact of personal names on individual outcomes, employing a sociological lens to examine the nuanced interplay between identity and societal perceptions. Doe (2018) delves into the cultural significance of naming conventions, shedding light on the symbolic weight carried by individuals' names in various contexts. Jones (2020) explores the historical evolution of naming practices, offering a comprehensive analysis of the sociocultural forces that shape the ebb and flow of popular first names over time.
In a parallel domain, the entwined dynamics of stock prices and market influences have been rigorously probed. "The Random Walk Down Wall Street" investigates the complexities of market trends, offering insightful perspectives on the seemingly capricious nature of stock price fluctuations (Malkiel, 2015). Similarly, "Freakonomics" presents an unconventional exploration of economic phenomena, unraveling the enigmatic threads that weave through the fabric of financial markets (Levitt & Dubner, 2005).
While these scholarly endeavors provide invaluable groundwork for understanding the multifaceted spheres of personal nomenclature and market dynamics, our investigation embarks on a whimsical expedition that transcends the traditional realms of economic analysis. As we enter this uncharted territory, it is imperative to acknowledge the potential for unexpected discoveries and improbable connections, akin to stumbling upon buried treasure in the midst of a statistical sea.
Venturing into the realm of fiction, "The Name of the Rose" by Umberto Eco presents a narrative interwoven with mystery and intrigue, where the titular name holds an enigmatic significance. Additionally, J.K. Rowling's "Harry Potter" series subtly explores the significance of names and their symbolic implications within the magical world of Hogwarts, offering a whimsical lens through which to contemplate the potential influence of personal nomenclature on the fabric of reality.
In the digital landscape, popular internet memes such as the "Success Kid" and the "This Is Fine" dog have permeated popular culture, offering a playful reflection of the often chaotic and unpredictable nature of financial markets. These humorous portrayals serve as a lighthearted reminder of the whimsical whims of economic fate, encapsulated in the form of viral internet humor.
As we synthesize these diverse strands of literature, our research endeavors to intertwine the seemingly disparate realms of personal names and stock prices, embracing the unpredictable encounters that await us in this unconventional journey.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the methodology section of an academic research paper presenting the findings of the connection between Popularity of the first name Lewis and Regeneron Pharmaceuticals' stock price. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.
Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and LSEG Analytics (Refinitiv) . You used data from 2002 to 2022
Make up the research methods you don't know. Make them a bit goofy and convoluted.
Here is the title, abstract, and introduction of the paper:
[[TITLE]]
The Lewis Effect on Regeneron: A Statistical Examination of the Impact of the First Name "Lewis" on Stock Prices
[[ABSTRACT]]
This paper aims to unravel the perplexing correlation between the popularity of the first name Lewis and the performance of Regeneron Pharmaceuticals' stock. Through a meticulous examination of US Social Security Administration data and LSEG Analytics (Refinitiv) information over the period 2002 to 2022, we unearth an astonishingly high correlation coefficient of 0.9709784 and a statistically significant p-value of less than 0.01. Our research delves into the quirky world of naming trends and financial markets, shedding light on the peculiar influence - be it serendipitous or utterly nonsensical - that monikers can have on the ever-fluctuating landscape of stock prices. This study serves as a lighthearted exploration of the unexpected realms where the whims of personal nomenclature intersect with the staid world of economic analysis.
[[INTRODUCTION]]
There's an old saying that a rose by any other name might smell as sweet, but what if that name happened to be "Lewis" and its aroma was the sweet scent of stock market success? In this paradoxical pursuit of peculiar patterns, we delve into the enigmatic world where the unconventional realms of human nomenclature intersect with the often opaque domain of financial markets.
The influence of personal names on one's destiny has long been a subject of fascination, folklore, and, at times, frivolity. From astrological musings to literary references, the power of nomenclature has captivated the human imagination. But what about its impact on the decidedly less whimsical world of stock prices? Can the popularity of a specific first name really sway the fortunes of a pharmaceutical giant like Regeneron, or is it merely an amusing anecdote in the annals of statistical quirks?
Our quest for answers begins with a seemingly arbitrary inquiry: What if there existed a discernible connection between the ebb and flow of the stock market and the prevalence of a particular forename? What if the name "Lewis" held the key to unlocking the mystifying machinations of stock price trends? Could it be an uncanny coincidence, an obscure quirk, or sheer happenstance that brings together the realms of personal nomenclature and financial analysis?
Amidst the labyrinthine data sets, jargon-laden reports, and the solemnity of economic analysis, we embark on a light-hearted exploration. Our endeavor seeks to unravel the perplexing puzzle of the Lewis effect on Regeneron, amid the often buttoned-up world of high finance. As we navigate the statistical seas and unearth correlations, let us not forget to sprinkle a dash of levity into this curious confluence of monetary matters and monikers.
So, dear reader, fasten your seatbelts, for we are about to embark on an academic journey that may just shed light on the whimsical whims of the stock market and the surprisingly sprightly influence of a name like "Lewis."
-------
Your response should start like this:
[[METHODOLOGY]]
ChatGPT:
[[METHODOLOGY]]
To disentangle the enigmatic connection between the popularity of the first name "Lewis" and the stock performance of Regeneron Pharmaceuticals, a multi-faceted approach was employed. Our research team combed through vast swathes of data sourced primarily from the US Social Security Administration and LSEG Analytics (Refinitiv) to construct an expansive dataset spanning the years 2002 to 2022.
First, to trace the prevalence of the name "Lewis", we utilized the Social Security Administration's records, which provided succinct insights into the historical popularity of first names in the United States. This involved wading through a sea of nomenclature, each name a veritable treasure trove of whimsy and wonder. The climb to the peak of naming trends was, dare I say, quite an uphill struggle, akin to navigating the labyrinth of stock market fluctuations.
Simultaneously, financial data from LSEG Analytics (Refinitiv) formed the cornerstone of our analysis. The daily stock prices of Regeneron Pharmaceuticals were meticulously scrutinized, with particular attention paid to any aberrations coinciding with fluctuations in the popularity of the name "Lewis". We dove deep into these swirling seas of stock prices, riding the waves of market variations with a zest for discovery, aiming to uncover the improbable interplay between nomenclature and financial futures.
Furthermore, we employed various statistical techniques, including correlation analysis and regression modeling, to elucidate the seemingly improbable relationship between the prevalence of the name "Lewis" and the performance of Regeneron Pharmaceuticals' stock. This methodological medley allowed us to unearth insights that quirkily connected these disparate realms, casting the spotlight on the delightful dance of names and numbers within the stock market milieu.
In summary, our methodology, while teasing the boundaries of traditional economic analysis with the eccentricity of our research question, provided a robust foundation for exploring the Lewis effect on Regeneron Pharmaceuticals' stock performance. It was a journey through the offbeat nexus of nomenclature and market dynamics, an expedition where the data-driven met the whimsically whimsical, painting a picture of intrigue and amusement.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the results section of an academic research paper. You speak in the past tense (you found...).
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the results section of an academic research paper presenting the findings of the connection between Popularity of the first name Lewis and Regeneron Pharmaceuticals' stock price. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, jokes, goofy observations, and puns.
Your research team collected data from all across the internet, but mostly just used information from US Social Security Administration and LSEG Analytics (Refinitiv) .
For the time period 2002 to 2022, you found a correlation 0.9709784, r-squared of 0.9427991, and p < 0.01.
One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.
Here is the title and abstract of the paper:
[[TITLE]]
The Lewis Effect on Regeneron: A Statistical Examination of the Impact of the First Name "Lewis" on Stock Prices
[[ABSTRACT]]
This paper aims to unravel the perplexing correlation between the popularity of the first name Lewis and the performance of Regeneron Pharmaceuticals' stock. Through a meticulous examination of US Social Security Administration data and LSEG Analytics (Refinitiv) information over the period 2002 to 2022, we unearth an astonishingly high correlation coefficient of 0.9709784 and a statistically significant p-value of less than 0.01. Our research delves into the quirky world of naming trends and financial markets, shedding light on the peculiar influence - be it serendipitous or utterly nonsensical - that monikers can have on the ever-fluctuating landscape of stock prices. This study serves as a lighthearted exploration of the unexpected realms where the whims of personal nomenclature intersect with the staid world of economic analysis.
-------
And here is the methodology section that led to this result:
[[METHODOLOGY]]
There's an old saying that a rose by any other name might smell as sweet, but what if that name happened to be "Lewis" and its aroma was the sweet scent of stock market success? In this paradoxical pursuit of peculiar patterns, we delve into the enigmatic world where the unconventional realms of human nomenclature intersect with the often opaque domain of financial markets.
The influence of personal names on one's destiny has long been a subject of fascination, folklore, and, at times, frivolity. From astrological musings to literary references, the power of nomenclature has captivated the human imagination. But what about its impact on the decidedly less whimsical world of stock prices? Can the popularity of a specific first name really sway the fortunes of a pharmaceutical giant like Regeneron, or is it merely an amusing anecdote in the annals of statistical quirks?
Our quest for answers begins with a seemingly arbitrary inquiry: What if there existed a discernible connection between the ebb and flow of the stock market and the prevalence of a particular forename? What if the name "Lewis" held the key to unlocking the mystifying machinations of stock price trends? Could it be an uncanny coincidence, an obscure quirk, or sheer happenstance that brings together the realms of personal nomenclature and financial analysis?
Amidst the labyrinthine data sets, jargon-laden reports, and the solemnity of economic analysis, we embark on a light-hearted exploration. Our endeavor seeks to unravel the perplexing puzzle of the Lewis effect on Regeneron, amid the often buttoned-up world of high finance. As we navigate the statistical seas and unearth correlations, let us not forget to sprinkle a dash of levity into this curious confluence of monetary matters and monikers.
So, dear reader, fasten your seatbelts, for we are about to embark on an academic journey that may just shed light on the whimsical whims of the stock market and the surprisingly sprightly influence of a name like "Lewis."
-------
Your response should start like this:
[[RESULTS]]
ChatGPT:
[[RESULTS]]
The results of our analysis have unveiled a striking correlation between the popularity of the first name "Lewis" and the stock price of Regeneron Pharmaceuticals. Over the span of 2002 to 2022, we found a remarkably high correlation coefficient of 0.9709784, indicating a strong positive relationship between the two variables. In addition, the r-squared value of 0.9427991 suggests that an impressive 94.28% of the variability in Regeneron's stock price can be explained by the prevalence of the name "Lewis." Furthermore, the p-value of less than 0.01 provides solid evidence to reject the null hypothesis and accept the alternative hypothesis that there is indeed a significant association between the popularity of the name "Lewis" and the fluctuations in Regeneron's stock price.
Our findings are succinctly encapsulated in Figure 1, which displays a compelling scatterplot illustrating the robust correlation between the prevalence of the name "Lewis" and the stock price of Regeneron Pharmaceuticals. This visual representation underscores the strength of the relationship we have uncovered, demonstrating a clear trend of co-movement between the two variables.
The implications of these results are both intriguing and, some might say, delightfully whimsical. While our analysis may appear to tread the unconventional path of intertwining personal nomenclature with financial market dynamics, the statistical evidence we have amassed cannot be ignored. It seems that the mischievous hand of fate, or perhaps the whimsical wink of chance, has woven an unexpected connection between the name "Lewis" and the performance of Regeneron's stock. Thus, our study stands as a testament to the serendipitous synergies that evade the traditional confines of economic analysis, showcasing the unforeseen influence of a name on the soaring heights and plunging depths of stock prices.
In conclusion, the Lewis Effect on Regeneron emerges as a compelling, albeit lighthearted, avenue of exploration in the symbiotic relationship between personal nomenclature and financial markets. This discovery invites further contemplation and inquiry into the esoteric interplay of names and numbers, urging us to embrace the whimsy intertwined with empirical rigor as we navigate the captivating crossroads of monetary matters and monikers.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up the discussion section of an academic research paper presenting the findings of the connection between Popularity of the first name Lewis and Regeneron Pharmaceuticals' stock price. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
The Lewis Effect on Regeneron: A Statistical Examination of the Impact of the First Name "Lewis" on Stock Prices
[[ABSTRACT]]
This paper aims to unravel the perplexing correlation between the popularity of the first name Lewis and the performance of Regeneron Pharmaceuticals' stock. Through a meticulous examination of US Social Security Administration data and LSEG Analytics (Refinitiv) information over the period 2002 to 2022, we unearth an astonishingly high correlation coefficient of 0.9709784 and a statistically significant p-value of less than 0.01. Our research delves into the quirky world of naming trends and financial markets, shedding light on the peculiar influence - be it serendipitous or utterly nonsensical - that monikers can have on the ever-fluctuating landscape of stock prices. This study serves as a lighthearted exploration of the unexpected realms where the whims of personal nomenclature intersect with the staid world of economic analysis.
[[LITERATURE REVIEW]]
The perplexing relationship between nomenclature and financial performance has spurred a plethora of inquiries and investigations. Smith (2015) postulates on the potential impact of personal names on individual outcomes, employing a sociological lens to examine the nuanced interplay between identity and societal perceptions. Doe (2018) delves into the cultural significance of naming conventions, shedding light on the symbolic weight carried by individuals' names in various contexts. Jones (2020) explores the historical evolution of naming practices, offering a comprehensive analysis of the sociocultural forces that shape the ebb and flow of popular first names over time.
In a parallel domain, the entwined dynamics of stock prices and market influences have been rigorously probed. "The Random Walk Down Wall Street" investigates the complexities of market trends, offering insightful perspectives on the seemingly capricious nature of stock price fluctuations (Malkiel, 2015). Similarly, "Freakonomics" presents an unconventional exploration of economic phenomena, unraveling the enigmatic threads that weave through the fabric of financial markets (Levitt & Dubner, 2005).
While these scholarly endeavors provide invaluable groundwork for understanding the multifaceted spheres of personal nomenclature and market dynamics, our investigation embarks on a whimsical expedition that transcends the traditional realms of economic analysis. As we enter this uncharted territory, it is imperative to acknowledge the potential for unexpected discoveries and improbable connections, akin to stumbling upon buried treasure in the midst of a statistical sea.
Venturing into the realm of fiction, "The Name of the Rose" by Umberto Eco presents a narrative interwoven with mystery and intrigue, where the titular name holds an enigmatic significance. Additionally, J.K. Rowling's "Harry Potter" series subtly explores the significance of names and their symbolic implications within the magical world of Hogwarts, offering a whimsical lens through which to contemplate the potential influence of personal nomenclature on the fabric of reality.
In the digital landscape, popular internet memes such as the "Success Kid" and the "This Is Fine" dog have permeated popular culture, offering a playful reflection of the often chaotic and unpredictable nature of financial markets. These humorous portrayals serve as a lighthearted reminder of the whimsical whims of economic fate, encapsulated in the form of viral internet humor.
As we synthesize these diverse strands of literature, our research endeavors to intertwine the seemingly disparate realms of personal names and stock prices, embracing the unpredictable encounters that await us in this unconventional journey.
[[RESULTS]]
The results of our analysis have unveiled a striking correlation between the popularity of the first name "Lewis" and the stock price of Regeneron Pharmaceuticals. Over the span of 2002 to 2022, we found a remarkably high correlation coefficient of 0.9709784, indicating a strong positive relationship between the two variables. In addition, the r-squared value of 0.9427991 suggests that an impressive 94.28% of the variability in Regeneron's stock price can be explained by the prevalence of the name "Lewis." Furthermore, the p-value of less than 0.01 provides solid evidence to reject the null hypothesis and accept the alternative hypothesis that there is indeed a significant association between the popularity of the name "Lewis" and the fluctuations in Regeneron's stock price.
Our findings are succinctly encapsulated in Figure 1, which displays a compelling scatterplot illustrating the robust correlation between the prevalence of the name "Lewis" and the stock price of Regeneron Pharmaceuticals. This visual representation underscores the strength of the relationship we have uncovered, demonstrating a clear trend of co-movement between the two variables.
The implications of these results are both intriguing and, some might say, delightfully whimsical. While our analysis may appear to tread the unconventional path of intertwining personal nomenclature with financial market dynamics, the statistical evidence we have amassed cannot be ignored. It seems that the mischievous hand of fate, or perhaps the whimsical wink of chance, has woven an unexpected connection between the name "Lewis" and the performance of Regeneron's stock. Thus, our study stands as a testament to the serendipitous synergies that evade the traditional confines of economic analysis, showcasing the unforeseen influence of a name on the soaring heights and plunging depths of stock prices.
In conclusion, the Lewis Effect on Regeneron emerges as a compelling, albeit lighthearted, avenue of exploration in the symbiotic relationship between personal nomenclature and financial markets. This discovery invites further contemplation and inquiry into the esoteric interplay of names and numbers, urging us to embrace the whimsy intertwined with empirical rigor as we navigate the captivating crossroads of monetary matters and monikers.
-------
Your response should start like this:
[[DISCUSSION]]
ChatGPT:
[[DISCUSSION]]
Our findings bear out the previously proposed hypotheses and, if we may be so bold as to suggest, lead to some truly "Aha!" moments of insight. On a broader level, they align with and extend the conceptual framework put forth by Smith (2015), Doe (2018), and Jones (2020), inviting us to consider the significance of individual names within the context of societal dynamics and unforeseen influences in fluctuating market spaces.
The strikingly high correlation coefficient of 0.9709784 serves as evidence that the enduring popularity of the first name "Lewis" marches in harmonious step with the undulating tides of Regeneron's stock price. It cannot be overlooked that our results admirably support the notion that personal nomenclature may exert an unanticipated sway upon financial oscillations, a concept that Jones (2020) may well find to be a hidden treasure of theoretical import.
The visually compelling scatterplot depicted in Figure 1 not only showcases the robustness of our findings but also nudges us to ponder whether there might lie a whimsical dance of letters and numbers beneath the veneer of statistical analysis. Might a flippant quirk of fate or perhaps a sly jest from the realms of unpredictability have intertwined the fate of "Lewis" with the fortunes of Regeneron? Our results certainly seem to suggest so, peppering our academic endeavors with a delightful pinch of eccentric revelation.
In delving into this seemingly capricious realm, we must acknowledge the irrepressible charm of veering into uncharted waters. Literature, both scholarly and fictitious, offers a whimsical tapestry against which our findings can be woven. As we traverse this unconventional path, we find that the knot that ties "Lewis" to Regeneron's stock price is not merely a mere, coincidental slip but rather a steadfastly cinched connection that demands our attention.
Our decision to incorporate unconventional literary avenues such as "The Name of the Rose" and "Harry Potter" into the scaffold of our literature review was not just a flight of fancy. These quips of cultural appropriation prove to be more than mere softer touches on the fringes of an academic inquiry. They are essential signposts that beckon us towards acknowledging the playful interplay between fictional realms and empirical explorations, where from unexpected discovery, enlightenment may yet arise.
In sum, our study stands as a whimsical testament to the unforeseen, yet statistically robust, relationship between the name "Lewis" and the financial ebbs and flows of Regeneron Pharmaceuticals. Like the curious case of Schrödinger's cat, there lies an undeniable charm in contemplating the enigmatic influences that ripple across the seemingly disparate realms of personal nomenclature and financial markets. And so, with a scholarly twinkle in our eyes, we invite further mirthful musings to unfurl and resonate within the captivating crossroads of names and numbers.
Model: gpt-3.5-turbo-1106
System prompt: You are a silly researcher writing an academic paper.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.
Please make up a short conclusion of an academic research paper presenting the findings of the connection between Popularity of the first name Lewis and Regeneron Pharmaceuticals' stock price. Make it seem dry like academic research paper, but with lots of subtle hidden offhand remarks, 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]]
The Lewis Effect on Regeneron: A Statistical Examination of the Impact of the First Name "Lewis" on Stock Prices
[[ABSTRACT]]
This paper aims to unravel the perplexing correlation between the popularity of the first name Lewis and the performance of Regeneron Pharmaceuticals' stock. Through a meticulous examination of US Social Security Administration data and LSEG Analytics (Refinitiv) information over the period 2002 to 2022, we unearth an astonishingly high correlation coefficient of 0.9709784 and a statistically significant p-value of less than 0.01. Our research delves into the quirky world of naming trends and financial markets, shedding light on the peculiar influence - be it serendipitous or utterly nonsensical - that monikers can have on the ever-fluctuating landscape of stock prices. This study serves as a lighthearted exploration of the unexpected realms where the whims of personal nomenclature intersect with the staid world of economic analysis.
[[INTRDUCTION]]
There's an old saying that a rose by any other name might smell as sweet, but what if that name happened to be "Lewis" and its aroma was the sweet scent of stock market success? In this paradoxical pursuit of peculiar patterns, we delve into the enigmatic world where the unconventional realms of human nomenclature intersect with the often opaque domain of financial markets.
The influence of personal names on one's destiny has long been a subject of fascination, folklore, and, at times, frivolity. From astrological musings to literary references, the power of nomenclature has captivated the human imagination. But what about its impact on the decidedly less whimsical world of stock prices? Can the popularity of a specific first name really sway the fortunes of a pharmaceutical giant like Regeneron, or is it merely an amusing anecdote in the annals of statistical quirks?
Our quest for answers begins with a seemingly arbitrary inquiry: What if there existed a discernible connection between the ebb and flow of the stock market and the prevalence of a particular forename? What if the name "Lewis" held the key to unlocking the mystifying machinations of stock price trends? Could it be an uncanny coincidence, an obscure quirk, or sheer happenstance that brings together the realms of personal nomenclature and financial analysis?
Amidst the labyrinthine data sets, jargon-laden reports, and the solemnity of economic analysis, we embark on a light-hearted exploration. Our endeavor seeks to unravel the perplexing puzzle of the Lewis effect on Regeneron, amid the often buttoned-up world of high finance. As we navigate the statistical seas and unearth correlations, let us not forget to sprinkle a dash of levity into this curious confluence of monetary matters and monikers.
So, dear reader, fasten your seatbelts, for we are about to embark on an academic journey that may just shed light on the whimsical whims of the stock market and the surprisingly sprightly influence of a name like "Lewis."
[[RESULTS]]
The results of our analysis have unveiled a striking correlation between the popularity of the first name "Lewis" and the stock price of Regeneron Pharmaceuticals. Over the span of 2002 to 2022, we found a remarkably high correlation coefficient of 0.9709784, indicating a strong positive relationship between the two variables. In addition, the r-squared value of 0.9427991 suggests that an impressive 94.28% of the variability in Regeneron's stock price can be explained by the prevalence of the name "Lewis." Furthermore, the p-value of less than 0.01 provides solid evidence to reject the null hypothesis and accept the alternative hypothesis that there is indeed a significant association between the popularity of the name "Lewis" and the fluctuations in Regeneron's stock price.
Our findings are succinctly encapsulated in Figure 1, which displays a compelling scatterplot illustrating the robust correlation between the prevalence of the name "Lewis" and the stock price of Regeneron Pharmaceuticals. This visual representation underscores the strength of the relationship we have uncovered, demonstrating a clear trend of co-movement between the two variables.
The implications of these results are both intriguing and, some might say, delightfully whimsical. While our analysis may appear to tread the unconventional path of intertwining personal nomenclature with financial market dynamics, the statistical evidence we have amassed cannot be ignored. It seems that the mischievous hand of fate, or perhaps the whimsical wink of chance, has woven an unexpected connection between the name "Lewis" and the performance of Regeneron's stock. Thus, our study stands as a testament to the serendipitous synergies that evade the traditional confines of economic analysis, showcasing the unforeseen influence of a name on the soaring heights and plunging depths of stock prices.
In conclusion, the Lewis Effect on Regeneron emerges as a compelling, albeit lighthearted, avenue of exploration in the symbiotic relationship between personal nomenclature and financial markets. This discovery invites further contemplation and inquiry into the esoteric interplay of names and numbers, urging us to embrace the whimsy intertwined with empirical rigor as we navigate the captivating crossroads of monetary matters and monikers.
-------
Your response should start like this:
[[CONCLUSION]]
ChatGPT:
[[CONCLUSION]]
In the whimsical world of statistical quirks and financial curiosities, our exploration of the Lewis Effect on Regeneron Pharmaceuticals' stock has illuminated a serendipitous connection. The robust correlation between the prevalence of the name "Lewis" and the fluctuation in Regeneron's stock price unveils a delightful dance of data, where the influence of nomenclature intertwines with the ebbs and flows of the market. While some may ponder the peculiarity of this uncanny correlation, we must not discount the possibility of a fortuitous fluke or the mischievous hand of fate at play.
As we wrap up this lighthearted foray into the unexpected intersection of personal names and financial analysis, it is undeniable that further investigation into the whimsical whims of the stock market and the surprisingly sprightly influence of a name like "Lewis" could yield entertaining insights. However, for now, we assert that no more research is needed in this area. After all, in the realm of statistical oddities, sometimes it's best to leave a bit of mystery to keep things delightfully enigmatic.
Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited The Lewis Effect on Regeneron: A Statistical Examination of the Impact of the First Name Lewis on Stock Prices. Respond only with the name of a fictional academic journal.
ChatGPT:
The Journal of Quirky Quandaries in Economic Research
Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited The Lewis Effect on Regeneron: A Statistical Examination of the Impact of the First Name Lewis on Stock Prices. Respond only with the name of a fictional organization.
ChatGPT:
The Society for Quirky Quantitative 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 The Lewis Effect on Regeneron: A Statistical Examination of the Impact of the First Name Lewis on Stock Prices with an abstract of This paper aims to unravel the perplexing correlation between the popularity of the first name Lewis and the performance of Regeneron Pharmaceuticals' stock. Through a meticulous examination of US Social Security Administration data and LSEG Analytics (Refinitiv) information over the period 2002 to 2022, we unearth an astonishingly high correlation coefficient of 0.9709784 and a statistically significant p-value of less than 0.01. Our research delves into the quirky world of naming trends and financial markets, shedding light on the peculiar influence - be it serendipitous or utterly nonsensical - that monikers can have on the ever-fluctuating landscape of stock prices. This study serves as a lighthearted exploration of the unexpected realms where the whims of personal nomenclature intersect with the staid world of economic analysis.
ChatGPT:
Lewis, Regeneron Pharmaceuticals, stock prices, US Social Security Administration data, LSEG Analytics, naming trends, financial markets, correlation coefficient, statistical analysis, first name influence, stock market, naming trends, economic 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
Popularity of the first name LewisDetailed data title: Babies of all sexes born in the US named Lewis
Source: US Social Security Administration
See what else correlates with Popularity of the first name Lewis
Regeneron Pharmaceuticals' stock price (REGN)
Detailed data title: Opening price of Regeneron Pharmaceuticals (REGN) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: Via Microsoft Excel Stockhistory function
See what else correlates with Regeneron Pharmaceuticals' stock price (REGN)
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 = 0.9427991 (Coefficient of determination)
This means 94.3% of the change in the one variable (i.e., Regeneron Pharmaceuticals' stock price (REGN)) is predictable based on the change in the other (i.e., Popularity of the first name Lewis) over the 21 years from 2002 through 2022.
p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.91E-13. 0.0000000000002908860048835585
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 0.97 in 2.91E-11% of random cases. Said differently, if you correlated 3,437,772,815,507 random variables You don't actually need 3 trillion 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 20 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 20 because we have two variables measured over a period of 21 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.
[ 0.93, 0.99 ] 95% correlation confidence interval (using the Fisher z-transformation)
The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.
This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!
All values for the years included above: If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.
Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.
2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | |
Popularity of the first name Lewis (Babies born) | 352 | 322 | 342 | 328 | 332 | 339 | 385 | 326 | 325 | 371 | 378 | 389 | 463 | 495 | 589 | 521 | 510 | 505 | 587 | 606 | 616 |
Regeneron Pharmaceuticals' stock price (REGN) (Stock price) | 28.04 | 18.55 | 14.81 | 9.36 | 15.8 | 19.93 | 24.02 | 18.42 | 24.24 | 32.69 | 56.51 | 176.42 | 275.77 | 413.9 | 531.76 | 370.84 | 379.48 | 368.15 | 378 | 486.85 | 625 |
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. - Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves.
Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.
Try it yourself
You can calculate the values on this page on your own! Try running the Python code to see the calculation results. Step 1: Download and install Python on your computer.Step 2: Open a plaintext editor like Notepad and paste the code below into it.
Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"
Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.
Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.
Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.
Step 7: Run the Python script by typing "python calculate_correlation.py"
If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:
"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."
# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats
# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):
# Calculate Pearson correlation coefficient and p-value
correlation, p_value = stats.pearsonr(array1, array2)
# Calculate R-squared as the square of the correlation coefficient
r_squared = correlation**2
return correlation, r_squared, p_value
# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([352,322,342,328,332,339,385,326,325,371,378,389,463,495,589,521,510,505,587,606,616,])
array_2 = np.array([28.04,18.55,14.81,9.36,15.8,19.93,24.02,18.42,24.24,32.69,56.51,176.42,275.77,413.9,531.76,370.84,379.48,368.15,378,486.85,625,])
array_1_name = "Popularity of the first name Lewis"
array_2_name = "Regeneron Pharmaceuticals' stock price (REGN)"
# 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 Popularity of the first name Lewis
- Line chart for only Regeneron Pharmaceuticals' stock price (REGN)
- The spurious research paper: The Lewis Effect on Regeneron: A Statistical Examination of the Impact of the First Name Lewis on Stock Prices
Cheers to you for rating this correlation!
Correlation ID: 1098 · Black Variable ID: 2999 · Red Variable ID: 1649