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Spurious correlation #3,268 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Stevie and the second variable is Netflix's stock price (NFLX).  The chart goes from 2003 to 2022, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

The soothing sound of the name Stevie resulted in a nation-wide decrease in stress levels, leading to more people unwinding with Netflix, and therefore driving up the stock price. Plus, there's a rumor that Stevie Wonder's secret side gig is writing Netflix original series, and everyone's loving them.

Model: dalle-3
Prompt: Generate an image of a brutalist-style city street filled with bustling energy. A towering billboard for Netflix stands prominently at the center, adorned with a classic rock documentary featuring the iconic Stevie Nicks. Surrounding the billboard, a group of excited individuals, some of whom are named Stevie, are absorbed in streaming content on their phones. High above the scene, a stock ticker steadily displays the rising stock price of Netflix (NFLX). Capture the dynamic atmosphere and futuristic implications of technology and entertainment. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.
This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Popularity of the first name Stevie and Netflix's stock price (NFLX). 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: Whimsical illustration Cybernetic art Brutalism a meme Brutalism
ChatGPT: Brutalism

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Popularity of the first name Stevie and Netflix's stock price (NFLX), in the following situation: Because the increase in popularity of the first name Stevie led to a surge in demand for classic rock music, which in turn resulted in a spike in viewership of documentaries about legendary musicians like Stevie Nicks. This increased viewership boosted Netflix's subscription numbers, leading to higher revenue and ultimately causing a rise in the stock price. It seems that the name Stevie wasn't just a "landslide" in terms of popularity, but also had a "dreams"worthy impact on Netflix's bottom line.. Keep the description simple.
ChatGPT: Imagine a bustling city street with a prominent billboard for Netflix featuring a classic rock documentary with Stevie Nicks. The billboard is surrounded by excited people, some of whom are named Stevie, and they are all streaming content on their phones. Above the scene, a stock ticker shows Netflix's stock price (NFLX) rising steadily.

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: [ Brutalism ] and depicting this scene: Imagine a bustling city street with a prominent billboard for Netflix featuring a classic rock documentary with Stevie Nicks. The billboard is surrounded by excited people, some of whom are named Stevie, and they are all streaming content on their phones. Above the scene, a stock ticker shows Netflix's stock price (NFLX) rising steadily. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a brutalist-style city street filled with bustling energy. A towering billboard for Netflix stands prominently at the center, adorned with a classic rock documentary featuring the iconic Stevie Nicks. Surrounding the billboard, a group of excited individuals, some of whom are named Stevie, are absorbed in streaming content on their phones. High above the scene, a stock ticker steadily displays the rising stock price of Netflix (NFLX). Capture the dynamic atmosphere and futuristic implications of technology and entertainment.

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

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.

Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Popularity of the first name Stevie caused Netflix's stock price (NFLX) to increase.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)
Stevie's Stock Surprises: The Silly Saga of Netflix's NFLX

The Journal of Unpredictable Economics

Jan 2024

Reminder: This paper is AI-generated. Not real!
Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.




Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You 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 Stevie and Netflix's stock price (NFLX). Make lots of jokes, goofy observations, and puns.

Make the title an alliteration.

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 0.9963501 and p < 0.01 for 2003 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]]
Stevie's Stock Surprises: The Silly Saga of Netflix's NFLX

[[ABSTRACT]]
This study examines the peculiar path of Netflix's stock price (NFLX) in correlation with the popularity of the given name "Stevie" in the United States. Utilizing data from the US Social Security Administration and LSEG Analytics (Refinitiv), we conducted a rigorous analysis covering the period from 2003 to 2022. The remarkable correlation coefficient of 0.9963501 and p < 0.01 suggests a strong, albeit puzzling, connection between the two seemingly unrelated variables. Our findings serve as a stark reminder that in the whimsical world of stock markets, even the most unexpected factors may hold sway. This paper seeks to untangle the entwined strands of Stevie's stardom and Netflix's stock swings, shedding light on the inexplicable and the absurd in the world of financial analysis.


Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the 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 Stevie and Netflix's stock price (NFLX). Make lots of jokes, goofy observations, and puns.

Here is the title and abstract of the paper:
[[TITLE]]
Stevie's Stock Surprises: The Silly Saga of Netflix's NFLX

[[ABSTRACT]]
This study examines the peculiar path of Netflix's stock price (NFLX) in correlation with the popularity of the given name "Stevie" in the United States. Utilizing data from the US Social Security Administration and LSEG Analytics (Refinitiv), we conducted a rigorous analysis covering the period from 2003 to 2022. The remarkable correlation coefficient of 0.9963501 and p < 0.01 suggests a strong, albeit puzzling, connection between the two seemingly unrelated variables. Our findings serve as a stark reminder that in the whimsical world of stock markets, even the most unexpected factors may hold sway. This paper seeks to untangle the entwined strands of Stevie's stardom and Netflix's stock swings, shedding light on the inexplicable and the absurd in the world of financial analysis.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The intersection of finance and nomenclature has long been an area of curiosity, especially when it comes to the peculiar predilections of stock prices. In this vein, the seemingly absurd correlation between the popularity of the given name "Stevie" and the stock price of Netflix (NFLX) has raised eyebrows and prompted many a wry smile in the world of financial analysis.

As the popular streaming service navigated the tumultuous tides of the stock market, the notion that the ebb and flow of its fortunes might somehow be intertwined with the ebb and flow of individuals bestowing the name "Stevie" upon their offspring became a source of both amusement and bemusement. How could the rise and fall of a stock price be influenced by a moniker with such varied connotations, from rock legends to whimsical characters in children's literature?

While the idea might seem like a stretch, the statistical evidence certainly gives one pause for thought. The correlation coefficient of 0.9963501, with a minuscule p-value less than 0.01, paints a picture of a remarkably strong relationship between the popularity of the name "Stevie" and the trajectory of Netflix's stock price. It is a reminder that in the labyrinthine landscape of financial markets, the most unexpected variables may hold surprising sway.

In this paper, we embark on a quest to disentangle the whimsical web of Stevie's stardom and Netflix's stock swings. By delving into the data and applying rigorous analysis, we aim to shine a light on this wacky correlation and offer a glimpse into the capricious and confounding nature of financial analysis. So, fasten your seatbelts and get ready to journey through the nonsensical nexus of nomenclature and Netflix, as we untangle the curious case of Stevie's Stock Surprises.


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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Popularity of the first name Stevie and Netflix's stock price (NFLX). Make lots of jokes, goofy observations, and puns.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
Stevie's Stock Surprises: The Silly Saga of Netflix's NFLX

[[ABSTRACT]]
This study examines the peculiar path of Netflix's stock price (NFLX) in correlation with the popularity of the given name "Stevie" in the United States. Utilizing data from the US Social Security Administration and LSEG Analytics (Refinitiv), we conducted a rigorous analysis covering the period from 2003 to 2022. The remarkable correlation coefficient of 0.9963501 and p < 0.01 suggests a strong, albeit puzzling, connection between the two seemingly unrelated variables. Our findings serve as a stark reminder that in the whimsical world of stock markets, even the most unexpected factors may hold sway. This paper seeks to untangle the entwined strands of Stevie's stardom and Netflix's stock swings, shedding light on the inexplicable and the absurd in the world of financial analysis.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intersection of finance and nomenclature has long been an area of curiosity, especially when it comes to the peculiar predilections of stock prices. In this vein, the seemingly absurd correlation between the popularity of the given name "Stevie" and the stock price of Netflix (NFLX) has raised eyebrows and prompted many a wry smile in the world of financial analysis.
As the popular streaming service navigated the tumultuous tides of the stock market, the notion that the ebb and flow of its fortunes might somehow be intertwined with the ebb and flow of individuals bestowing the name "Stevie" upon their offspring became a source of both amusement and bemusement. How could the rise and fall of a stock price be influenced by a moniker with such varied connotations, from rock legends to whimsical characters in children's literature?
While the idea might seem like a stretch, the statistical evidence certainly gives one pause for thought. The correlation coefficient of 0.9963501, with a minuscule p-value less than 0.01, paints a picture of a remarkably strong relationship between the popularity of the name "Stevie" and the trajectory of Netflix's stock price. It is a reminder that in the labyrinthine landscape of financial markets, the most unexpected variables may hold surprising sway.
In this paper, we embark on a quest to disentangle the whimsical web of Stevie's stardom and Netflix's stock swings. By delving into the data and applying rigorous analysis, we aim to shine a light on this wacky correlation and offer a glimpse into the capricious and confounding nature of financial analysis. So, fasten your seatbelts and get ready to journey through the nonsensical nexus of nomenclature and Netflix, as we untangle the curious case of Stevie's Stock Surprises.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

Numerous studies have delved into the enthralling realm of name popularity and its potential influence on various facets of human behavior. Smith (2015) observed a correlation between popular given names and career success, suggesting that individuals with certain monikers may be predisposed to professional achievement. Similarly, Doe (2017) examined the impact of name popularity on social interactions, positing that individuals with common names may encounter distinct societal experiences compared to their counterparts with more unique appellations. Additionally, Jones (2020) conducted a study on the relationship between name popularity and consumer preferences, revealing intriguing patterns in product choices based on the prevalence of specific names.

Turning to the world of finance, the influence of seemingly unrelated external factors on stock prices has been a subject of perennial fascination. However, the specific connection between the prevalence of the name "Stevie" and the fluctuations of Netflix's stock price (NFLX) has garnered remarkably scant scholarly attention. This paper seeks to bridge this gap and contribute to the understanding of this idiosyncratic correlation.

In the domain of non-fiction literature, works such as "Freakonomics" by Steven D. Levitt and Stephen J. Dubner have explored unconventional factors that shape human behavior and societal phenomena, offering a lens through which to contemplate the unexpected interplay of seemingly disparate variables. Similarly, "Blink: The Power of Thinking Without Thinking" by Malcolm Gladwell delves into the subconscious influences that guide decision-making processes, providing insight into the enigmatic forces that may underpin the curious connection between name popularity and financial dynamics.

Shifting to the realm of fiction, the whimsical world of Roald Dahl's "Charlie and the Chocolate Factory" presents a fanciful exploration of unlikely occurrences and improbable juxtapositions, mirroring the improbable combination under scrutiny in this analysis. Furthermore, the comedic chaos of Douglas Adams' "The Hitchhiker's Guide to the Galaxy" offers a fitting backdrop for contemplating the outlandish correlation between the popularity of "Stevie" and the undulating trajectory of Netflix's stock price.

In traversing the landscape of social media, anecdotal evidence gleaned from platforms such as Twitter and Reddit has provided amusing musings on the potential link between the nomenclature of "Stevie" and the financial fate of Netflix. User posts such as "Stevie's rise is lifting Netflix's stock higher than a helium balloon" and "Netflix's stock is paralleling the ascent of Stevie's popularity faster than a shooting star" underscore the lighthearted speculation surrounding this curious phenomenon.

In the following sections, a detailed analysis of the empirical evidence pertaining to the connection between the popularity of the name "Stevie" and Netflix's stock price will be presented, encapsulating the intersection of the whimsical and the wacky in the realm of financial analysis.


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

Please make up the methodology section of an academic research paper presenting the findings of the connection between Popularity of the first name Stevie and Netflix's stock price (NFLX). Make lots of 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 2003 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]]
Stevie's Stock Surprises: The Silly Saga of Netflix's NFLX

[[ABSTRACT]]
This study examines the peculiar path of Netflix's stock price (NFLX) in correlation with the popularity of the given name "Stevie" in the United States. Utilizing data from the US Social Security Administration and LSEG Analytics (Refinitiv), we conducted a rigorous analysis covering the period from 2003 to 2022. The remarkable correlation coefficient of 0.9963501 and p < 0.01 suggests a strong, albeit puzzling, connection between the two seemingly unrelated variables. Our findings serve as a stark reminder that in the whimsical world of stock markets, even the most unexpected factors may hold sway. This paper seeks to untangle the entwined strands of Stevie's stardom and Netflix's stock swings, shedding light on the inexplicable and the absurd in the world of financial analysis.

[[INTRODUCTION]]
The intersection of finance and nomenclature has long been an area of curiosity, especially when it comes to the peculiar predilections of stock prices. In this vein, the seemingly absurd correlation between the popularity of the given name "Stevie" and the stock price of Netflix (NFLX) has raised eyebrows and prompted many a wry smile in the world of financial analysis.
As the popular streaming service navigated the tumultuous tides of the stock market, the notion that the ebb and flow of its fortunes might somehow be intertwined with the ebb and flow of individuals bestowing the name "Stevie" upon their offspring became a source of both amusement and bemusement. How could the rise and fall of a stock price be influenced by a moniker with such varied connotations, from rock legends to whimsical characters in children's literature?
While the idea might seem like a stretch, the statistical evidence certainly gives one pause for thought. The correlation coefficient of 0.9963501, with a minuscule p-value less than 0.01, paints a picture of a remarkably strong relationship between the popularity of the name "Stevie" and the trajectory of Netflix's stock price. It is a reminder that in the labyrinthine landscape of financial markets, the most unexpected variables may hold surprising sway.
In this paper, we embark on a quest to disentangle the whimsical web of Stevie's stardom and Netflix's stock swings. By delving into the data and applying rigorous analysis, we aim to shine a light on this wacky correlation and offer a glimpse into the capricious and confounding nature of financial analysis. So, fasten your seatbelts and get ready to journey through the nonsensical nexus of nomenclature and Netflix, as we untangle the curious case of Stevie's Stock Surprises.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To investigate the unexpected correlation between the popularity of the first name "Stevie" and Netflix's stock price (NFLX), we employed a multifaceted methodology that combined data collection, statistical analysis, and a touch of whimsical wonder.

Data Collection:
We gathered data on the popularity of the name "Stevie" from the US Social Security Administration, which maintains records of names given to newborns in the United States. This dataset provided us with the annual frequency of occurrences of the name "Stevie" from 2003 to 2022. Concurrently, we obtained historical stock price data for Netflix (NFLX) from LSEG Analytics (Refinitiv), spanning the same time period. By integrating these disparate datasets, we sought to discern any potential connections between the popularity of the name "Stevie" and the fluctuation of Netflix's stock price.

Statistical Analysis:
To unravel the enigmatic relationship between the chosen name and the stock market performance, we employed rigorous statistical techniques. Firstly, we calculated the correlation coefficient between the frequency of the name "Stevie" and Netflix's stock price, utilizing advanced econometric modeling. The astonishingly high correlation coefficient of 0.9963501 left us both astounded and amused. Furthermore, we conducted hypothesis testing to evaluate the significance of this correlation, yielding a p-value less than 0.01. Despite our initial incredulity, the statistical evidence compelled us to delve further into this peculiar pairing.

Optional Goofy Approach:
In a lighthearted departure from convention, we indulged in a bit of imaginative exploration to probe the unorthodox connection between a popular name and a stock price. Our team engaged in a friendly debate about the potential influence of fictional characters named Stevie in popular culture on investor sentiment, though we concede that this line of inquiry may not be scientifically rigorous.

The combination of these methodological approaches allowed us to dissect the seemingly nonsensical nexus of nomenclature and Netflix, illuminating the curious case of Stevie's Stock Surprises.


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

Please make up the results section of an academic research paper presenting the findings of the connection between Popularity of the first name Stevie and Netflix's stock price (NFLX). Make lots of 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 2003 to 2022, you found a correlation 0.9963501, r-squared of 0.9927136, 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]]
Stevie's Stock Surprises: The Silly Saga of Netflix's NFLX

[[ABSTRACT]]
This study examines the peculiar path of Netflix's stock price (NFLX) in correlation with the popularity of the given name "Stevie" in the United States. Utilizing data from the US Social Security Administration and LSEG Analytics (Refinitiv), we conducted a rigorous analysis covering the period from 2003 to 2022. The remarkable correlation coefficient of 0.9963501 and p < 0.01 suggests a strong, albeit puzzling, connection between the two seemingly unrelated variables. Our findings serve as a stark reminder that in the whimsical world of stock markets, even the most unexpected factors may hold sway. This paper seeks to untangle the entwined strands of Stevie's stardom and Netflix's stock swings, shedding light on the inexplicable and the absurd in the world of financial analysis.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The intersection of finance and nomenclature has long been an area of curiosity, especially when it comes to the peculiar predilections of stock prices. In this vein, the seemingly absurd correlation between the popularity of the given name "Stevie" and the stock price of Netflix (NFLX) has raised eyebrows and prompted many a wry smile in the world of financial analysis.
As the popular streaming service navigated the tumultuous tides of the stock market, the notion that the ebb and flow of its fortunes might somehow be intertwined with the ebb and flow of individuals bestowing the name "Stevie" upon their offspring became a source of both amusement and bemusement. How could the rise and fall of a stock price be influenced by a moniker with such varied connotations, from rock legends to whimsical characters in children's literature?
While the idea might seem like a stretch, the statistical evidence certainly gives one pause for thought. The correlation coefficient of 0.9963501, with a minuscule p-value less than 0.01, paints a picture of a remarkably strong relationship between the popularity of the name "Stevie" and the trajectory of Netflix's stock price. It is a reminder that in the labyrinthine landscape of financial markets, the most unexpected variables may hold surprising sway.
In this paper, we embark on a quest to disentangle the whimsical web of Stevie's stardom and Netflix's stock swings. By delving into the data and applying rigorous analysis, we aim to shine a light on this wacky correlation and offer a glimpse into the capricious and confounding nature of financial analysis. So, fasten your seatbelts and get ready to journey through the nonsensical nexus of nomenclature and Netflix, as we untangle the curious case of Stevie's Stock Surprises.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The analysis of the data collected from the US Social Security Administration and LSEG Analytics (Refinitiv) revealed a staggering correlation coefficient of 0.9963501 between the popularity of the first name "Stevie" and Netflix's stock price (NFLX) from 2003 to 2022. This near-perfect correlation indicates an eerily synchronized dance between the fluctuating fortunes of the streaming giant and the waxing and waning popularity of the moniker "Stevie."

The r-squared value of 0.9927136 further confirms that a whopping 99.27% of the variability in NFLX stock price can be explained by the popularity of the name "Stevie." It appears that the whims of Wall Street are not immune to the whimsy of nomenclature.

The p-value of less than 0.01 serves as a resounding exclamation point, signaling the statistical significance of this correlation. One could say that the relationship between Stevie's popularity and Netflix's stock price is as clear as... well, Stevie Nicks' crystal visions.

As shown in Figure 1, the scatterplot graphically illustrates the tight clustering of data points, unequivocally demonstrating the remarkably strong correlation between these seemingly disparate variables. It seems that as the name "Stevie" rises in popularity, so does the stock price of Netflix, mirroring each other with an almost eerie precision.

In conclusion, our findings provide compelling evidence of an inexplicable and, dare we say, whimsical association between the popularity of the first name "Stevie" and the stock price of Netflix. This study serves as a quirky reminder that in the enigmatic realm of financial markets, even the most outlandish and unexpected factors can exert considerable influence.


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

Please make up the discussion section of an academic research paper presenting the findings of the connection between Popularity of the first name Stevie and Netflix's stock price (NFLX). Make lots of jokes, goofy observations, and puns.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Stevie's Stock Surprises: The Silly Saga of Netflix's NFLX

[[ABSTRACT]]
This study examines the peculiar path of Netflix's stock price (NFLX) in correlation with the popularity of the given name "Stevie" in the United States. Utilizing data from the US Social Security Administration and LSEG Analytics (Refinitiv), we conducted a rigorous analysis covering the period from 2003 to 2022. The remarkable correlation coefficient of 0.9963501 and p < 0.01 suggests a strong, albeit puzzling, connection between the two seemingly unrelated variables. Our findings serve as a stark reminder that in the whimsical world of stock markets, even the most unexpected factors may hold sway. This paper seeks to untangle the entwined strands of Stevie's stardom and Netflix's stock swings, shedding light on the inexplicable and the absurd in the world of financial analysis.

[[LITERATURE REVIEW]]
Numerous studies have delved into the enthralling realm of name popularity and its potential influence on various facets of human behavior. Smith (2015) observed a correlation between popular given names and career success, suggesting that individuals with certain monikers may be predisposed to professional achievement. Similarly, Doe (2017) examined the impact of name popularity on social interactions, positing that individuals with common names may encounter distinct societal experiences compared to their counterparts with more unique appellations. Additionally, Jones (2020) conducted a study on the relationship between name popularity and consumer preferences, revealing intriguing patterns in product choices based on the prevalence of specific names.
Turning to the world of finance, the influence of seemingly unrelated external factors on stock prices has been a subject of perennial fascination. However, the specific connection between the prevalence of the name "Stevie" and the fluctuations of Netflix's stock price (NFLX) has garnered remarkably scant scholarly attention. This paper seeks to bridge this gap and contribute to the understanding of this idiosyncratic correlation.
In the domain of non-fiction literature, works such as "Freakonomics" by Steven D. Levitt and Stephen J. Dubner have explored unconventional factors that shape human behavior and societal phenomena, offering a lens through which to contemplate the unexpected interplay of seemingly disparate variables. Similarly, "Blink: The Power of Thinking Without Thinking" by Malcolm Gladwell delves into the subconscious influences that guide decision-making processes, providing insight into the enigmatic forces that may underpin the curious connection between name popularity and financial dynamics.
Shifting to the realm of fiction, the whimsical world of Roald Dahl's "Charlie and the Chocolate Factory" presents a fanciful exploration of unlikely occurrences and improbable juxtapositions, mirroring the improbable combination under scrutiny in this analysis. Furthermore, the comedic chaos of Douglas Adams' "The Hitchhiker's Guide to the Galaxy" offers a fitting backdrop for contemplating the outlandish correlation between the popularity of "Stevie" and the undulating trajectory of Netflix's stock price.
In traversing the landscape of social media, anecdotal evidence gleaned from platforms such as Twitter and Reddit has provided amusing musings on the potential link between the nomenclature of "Stevie" and the financial fate of Netflix. User posts such as "Stevie's rise is lifting Netflix's stock higher than a helium balloon" and "Netflix's stock is paralleling the ascent of Stevie's popularity faster than a shooting star" underscore the lighthearted speculation surrounding this curious phenomenon.
In the following sections, a detailed analysis of the empirical evidence pertaining to the connection between the popularity of the name "Stevie" and Netflix's stock price will be presented, encapsulating the intersection of the whimsical and the wacky in the realm of financial analysis.

[[RESULTS]]
The analysis of the data collected from the US Social Security Administration and LSEG Analytics (Refinitiv) revealed a staggering correlation coefficient of 0.9963501 between the popularity of the first name "Stevie" and Netflix's stock price (NFLX) from 2003 to 2022. This near-perfect correlation indicates an eerily synchronized dance between the fluctuating fortunes of the streaming giant and the waxing and waning popularity of the moniker "Stevie."
The r-squared value of 0.9927136 further confirms that a whopping 99.27% of the variability in NFLX stock price can be explained by the popularity of the name "Stevie." It appears that the whims of Wall Street are not immune to the whimsy of nomenclature.
The p-value of less than 0.01 serves as a resounding exclamation point, signaling the statistical significance of this correlation. One could say that the relationship between Stevie's popularity and Netflix's stock price is as clear as... well, Stevie Nicks' crystal visions.
As shown in Figure 1, the scatterplot graphically illustrates the tight clustering of data points, unequivocally demonstrating the remarkably strong correlation between these seemingly disparate variables. It seems that as the name "Stevie" rises in popularity, so does the stock price of Netflix, mirroring each other with an almost eerie precision.
In conclusion, our findings provide compelling evidence of an inexplicable and, dare we say, whimsical association between the popularity of the first name "Stevie" and the stock price of Netflix. This study serves as a quirky reminder that in the enigmatic realm of financial markets, even the most outlandish and unexpected factors can exert considerable influence.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

Our findings offer a fascinating foray into the unpredictable terrain of stock market correlations, shedding light on the improbable yet captivating link between the popularity of the name "Stevie" and Netflix's stock price (NFLX). The spectacularly high correlation coefficient of 0.9963501 underscores the uncanny synchronicity between these ostensibly unrelated variables, affirming the adage that truth can indeed be stranger than fiction.

The strong correlation observed in our analysis is in line with prior research on the influence of name popularity on diverse facets of human behavior. As Smith (2015) proposed, individuals bearing certain names may be predisposed to particular career achievements, suggesting that the prominent presence of "Stevie" in the public consciousness could resonate with favorable perceptions of Netflix's offerings, thereby bolstering its stock price. Moreover, the correlation aligns with Jones's (2020) examination of the relationship between name popularity and consumer preferences, indicating that the pervasive appeal of "Stevie" could sway investor sentiment toward Netflix, driving its stock price in tandem with the name's popularity trajectory.

The significant correlation coefficient and r-squared value in our study are reminiscent of the inquisitive inquiries into name-based phenomena by Doe (2017). Just as Doe elucidated the potential impact of name popularity on social interactions, our findings illuminate the curious interplay between the ubiquity of "Stevie" and the market dynamics of Netflix. This resonance underscores the intricate web of influences shaping consumer behavior, investor sentiment, and the idiosyncratic fluctuations of stock prices.

In navigating the whimsical world of stock market analysis, our study contributes to the dialogue sparked by Levitt and Dubner's "Freakonomics" and Gladwell's "Blink", showcasing that seemingly whimsical variables can indeed exert unforeseen sway over financial outcomes. The unexpected correlation unearthed here, reminiscent of the improbable coincidences in Roald Dahl's whimsical tales and the chaotic wit of Douglas Adams, highlights the playful unpredictability inherent in financial markets.

While our study provides compelling evidence of a correlation between the popularity of the name "Stevie" and Netflix's stock price, the underlying mechanisms driving this connection remain an enigma. The whimsical confluence of Stevie's stardom and Netflix's stock behavior invites further exploration into the interplay of popular culture, consumer preferences, and financial dynamics. Our findings beckon future research to unravel the whimsical web woven by the fates of names and stock prices, offering a lighthearted yet thought-provoking lens through which we may ponder the improbable and the ineffable in the realm of financial analysis.


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

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Popularity of the first name Stevie and Netflix's stock price (NFLX). Make lots of jokes, goofy observations, and puns.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Stevie's Stock Surprises: The Silly Saga of Netflix's NFLX

[[ABSTRACT]]
This study examines the peculiar path of Netflix's stock price (NFLX) in correlation with the popularity of the given name "Stevie" in the United States. Utilizing data from the US Social Security Administration and LSEG Analytics (Refinitiv), we conducted a rigorous analysis covering the period from 2003 to 2022. The remarkable correlation coefficient of 0.9963501 and p < 0.01 suggests a strong, albeit puzzling, connection between the two seemingly unrelated variables. Our findings serve as a stark reminder that in the whimsical world of stock markets, even the most unexpected factors may hold sway. This paper seeks to untangle the entwined strands of Stevie's stardom and Netflix's stock swings, shedding light on the inexplicable and the absurd in the world of financial analysis.

[[INTRDUCTION]]
The intersection of finance and nomenclature has long been an area of curiosity, especially when it comes to the peculiar predilections of stock prices. In this vein, the seemingly absurd correlation between the popularity of the given name "Stevie" and the stock price of Netflix (NFLX) has raised eyebrows and prompted many a wry smile in the world of financial analysis.
As the popular streaming service navigated the tumultuous tides of the stock market, the notion that the ebb and flow of its fortunes might somehow be intertwined with the ebb and flow of individuals bestowing the name "Stevie" upon their offspring became a source of both amusement and bemusement. How could the rise and fall of a stock price be influenced by a moniker with such varied connotations, from rock legends to whimsical characters in children's literature?
While the idea might seem like a stretch, the statistical evidence certainly gives one pause for thought. The correlation coefficient of 0.9963501, with a minuscule p-value less than 0.01, paints a picture of a remarkably strong relationship between the popularity of the name "Stevie" and the trajectory of Netflix's stock price. It is a reminder that in the labyrinthine landscape of financial markets, the most unexpected variables may hold surprising sway.
In this paper, we embark on a quest to disentangle the whimsical web of Stevie's stardom and Netflix's stock swings. By delving into the data and applying rigorous analysis, we aim to shine a light on this wacky correlation and offer a glimpse into the capricious and confounding nature of financial analysis. So, fasten your seatbelts and get ready to journey through the nonsensical nexus of nomenclature and Netflix, as we untangle the curious case of Stevie's Stock Surprises.

[[RESULTS]]
The analysis of the data collected from the US Social Security Administration and LSEG Analytics (Refinitiv) revealed a staggering correlation coefficient of 0.9963501 between the popularity of the first name "Stevie" and Netflix's stock price (NFLX) from 2003 to 2022. This near-perfect correlation indicates an eerily synchronized dance between the fluctuating fortunes of the streaming giant and the waxing and waning popularity of the moniker "Stevie."
The r-squared value of 0.9927136 further confirms that a whopping 99.27% of the variability in NFLX stock price can be explained by the popularity of the name "Stevie." It appears that the whims of Wall Street are not immune to the whimsy of nomenclature.
The p-value of less than 0.01 serves as a resounding exclamation point, signaling the statistical significance of this correlation. One could say that the relationship between Stevie's popularity and Netflix's stock price is as clear as... well, Stevie Nicks' crystal visions.
As shown in Figure 1, the scatterplot graphically illustrates the tight clustering of data points, unequivocally demonstrating the remarkably strong correlation between these seemingly disparate variables. It seems that as the name "Stevie" rises in popularity, so does the stock price of Netflix, mirroring each other with an almost eerie precision.
In conclusion, our findings provide compelling evidence of an inexplicable and, dare we say, whimsical association between the popularity of the first name "Stevie" and the stock price of Netflix. This study serves as a quirky reminder that in the enigmatic realm of financial markets, even the most outlandish and unexpected factors can exert considerable influence.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, the results of this study paint a rather colorful and, dare we say, whimsical picture of the correlation between the popularity of the first name "Stevie" and Netflix's stock price. It appears that in the world of financial markets, the rise and fall of stock prices may indeed be influenced by something as seemingly unrelated as the ebb and flow of a moniker with such varied connotations.

Our findings, with a correlation coefficient that nearly kisses 1 and a p-value that says, "Oh, this is definitely a thing," leave little room for doubt that there is indeed a peculiar dance between Stevie's stardom and Netflix's stock swings. It seems that as the name "Stevie" rises in popularity, so does the stock price of Netflix, mirroring each other with an almost eerie precision. This relationship is as clear as... well, Stevie Nicks' crystal visions.

The wacky correlation further serves as a reminder that in the strange and unpredictable world of financial analysis, even the most unexpected variables may hold surprising sway. We have delved into the nonsensical nexus of nomenclature and Netflix, shedding light on the inexplicable and the absurd in the world of financial markets.

But fear not, dear readers, for it is our conclusion that no further research is needed in this area. The tale of Stevie's stock surprises has been told, and it's time to let this quirky correlation take a bow and exit stage left. After all, every good saga must come to an end, and this one certainly has its fair share of twists and turns.


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 Stevie's Stock Surprises: The Silly Saga of Netflix's NFLX. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Unpredictable Economics


Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited Stevie's Stock Surprises: The Silly Saga of Netflix's NFLX. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Chuckle-Worthy Stock Studies


Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled Stevie's Stock Surprises: The Silly Saga of Netflix's NFLX with an abstract of This study examines the peculiar path of Netflix's stock price (NFLX) in correlation with the popularity of the given name "Stevie" in the United States. Utilizing data from the US Social Security Administration and LSEG Analytics (Refinitiv), we conducted a rigorous analysis covering the period from 2003 to 2022. The remarkable correlation coefficient of 0.9963501 and p < 0.01 suggests a strong, albeit puzzling, connection between the two seemingly unrelated variables. Our findings serve as a stark reminder that in the whimsical world of stock markets, even the most unexpected factors may hold sway. This paper seeks to untangle the entwined strands of Stevie's stardom and Netflix's stock swings, shedding light on the inexplicable and the absurd in the world of financial analysis.

ChatGPT:

"Netflix stock price correlation," "Stevie name popularity," "Netflix stock analysis," "US Social Security Administration data," "LSEG Analytics correlation," "Netflix stock swings," "financial analysis," "unexpected factors in stock markets," "correlation coefficient analysis," "stock market whimsical factors"

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



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Data details

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

Netflix's stock price (NFLX)
Detailed data title: Opening price of Netflix (NFLX) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: Via Microsoft Excel Stockhistory function

See what else correlates with Netflix's stock price (NFLX)

Correlation r = 0.9963501 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r2 = 0.9927136 (Coefficient of determination)
This means 99.3% of the change in the one variable (i.e., Netflix's stock price (NFLX)) is predictable based on the change in the other (i.e., Popularity of the first name Stevie) over the 20 years from 2003 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.08E-20. 0.0000000000000000000107728900
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 1 in 1.08E-18% of random cases. Said differently, if you correlated 92,825,602,043,648,458,752 random variables You don't actually need 92 quintillion 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 19 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 19 because we have two variables measured over a period of 20 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.

[ 0.99, 1 ] 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.
20032004200520062007200820092010201120122013201420152016201720182019202020212022
Popularity of the first name Stevie (Babies born)23221521125222921724021022725426031831237944447362980111471217
Netflix's stock price (NFLX) (Stock price)0.854.111.83.873.713.794.227.932510.0413.652.449.15109124.96196.1259.28326.1539605.61




Why this works

  1. Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
  2. Lack of causal connection: There is probably Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
    no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
  3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
    p-value calculation does not take this into account, so mathematically it appears less probable than it really is.




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([232,215,211,252,229,217,240,210,227,254,260,318,312,379,444,473,629,801,1147,1217,])
array_2 = np.array([0.85,4.11,1.8,3.87,3.71,3.79,4.22,7.93,25,10.04,13.6,52.4,49.15,109,124.96,196.1,259.28,326.1,539,605.61,])
array_1_name = "Popularity of the first name Stevie"
array_2_name = "Netflix's stock price (NFLX)"

# 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)



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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.

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Correlation ID: 3268 · Black Variable ID: 3190 · Red Variable ID: 1584
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